Influence of biosolid stability, temperature and water potential on nitrogen

Influence of biosolid stability, temperature and water potential on nitrogen

Influence of biosolid stability, temperature and water potential on nitrogen mineralisation in biosolid amended soils by

Laurinda Nobela

Submitted in partial fulfillment of the requirements for the degree

MSc (Agric) Soil Science

In the Faculty of Natural and Agricultural Sciences

University of Pretoria

Supervisor: P.C. de Jager

Co-Supervisor: J.G. Annandale

February 2011

i

© U n i i v e r r s i i t t y o f P r r e t t o r r i i a

DECLARATION

I hereby certify that this thesis I am submitting to the University of Pretoria for the degree, MSc. (Agric) Soil Science, is entirely my own work, except where duly acknowledged. I also certify that this thesis has never been submitted to any other tertiary institution for any degree.

Signature __________________________ Date: ______________________

ii

ACKNOWLEDGMENTS

My sincere acknowledgment goes to the following parties for their supportive role that made it possible to achieve this Master‟s degree:

 To the Almighty Father for His power and goodness in providing guidance, wisdom and courage that made it possible for me to complete this degree;

 To the Ford Foundation-International Fellowship Program (IFP) in particular the Africa

America Institute (AAI- Mozambique) for financial support without which my studies at this level would have remained but a dream. My special thanks to Dra. Célia Diniz for the affectionate support and encouragement. To the kind team of AAI-Mozambique who untiringly knew how to support me when I was in need;

 The IIAM-Instituto de Investigação Agrária de Moçambique management for giving me permission to leave my duties as employee and enroll in a Master‟s programme;

 The Dept. of Plant Production and Soil Science for the important contribution in all aspects from welcoming me to providing facilities and funds for research;

 To Mr. Chris de Jager and Prof. J.G. Annandale for their patient and helpful supervision;

 My gratitude also goes to Professor Andries Claassens and the laboratory assistants for their technical support;

 To my beloved kids Cátia, Tânia and Dionísio for their understanding and accepting deprivation of their mother‟s physical presence. To my fleshly and spiritual family for all their loving encouragement and their time spent looking after my little kids;

 At last, but not least, to my colleagues that have been on my side sharing their experience and encouraging me all the way. iii

DEDICATION

To my Parents Xavier Mundau Nobela and Ellen Thussi in particular my Father‟s

Soul, who saw this walk beginning and was unable to celebrate this moment of joy!

Rest in peace in God‟s hands!

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Summary

Soils with inherently low soil fertility, and nutrient depletion of fertile soils, are the root causes of declining per capita food production in Africa. On the other hand, demand for better water quality and strict environmental laws have led to an increase in biosolid production. Accumulation of this waste poses an increasing environmental pollution risk. Disposal methods like incineration, ocean dumping and land filling are causing enormous environmental and economic problems.

Therefore, municipal authorities have been challenged with the environmental management of biosolids, whilst many farmers are facing a problem of soil fertility decline. Biosolids of

“Exceptional quality class A” contain high organic matter, plant nutrients and have few restrictions on use for land application. Therefore, it is a valuable resource. Beneficiation of sewage sludge through land application is an optional solution to address both soil fertility and environmental problems. Scientific management of sewage sludge utilization must be observed to minimize environmental problems. The study of N release and the rate of nitrification from biosolids is essential to improve nutrient use efficiency, as well as to prevent environmental pollution. Mineralization and nitrification processes are influenced by several factors, for instance, the origin and quality of organic material, and soil environmental conditions, of which moisture and temperature are the most important factors. The study aims to: (i) evaluate biosolid stability, temperature and soil water effects on net N release from municipal and industrial sludge amended soil, and (ii) generate important parameters for modeling N dynamics (rate constants and half life). This dissertation consists of two major experiments: The first experiment was a fifty six day laboratory incubation study to assess N release and nitrification rate constants in a biosolid amended soil, as well as the biosolid‟s half life time. The experiment was conducted using three types of biosolids originated from three different wastewater treatment processes, subjected to three levels of temperature and three of soil water potentials. The second experiment was an investigation on sample handling strategy for accurate nitrate (NO

3

-

) and ammonium

(NH

4

+

) determinations. Different handling procedures: Direct field extraction, Field drying extraction and Laboratory drying extraction were tested on biosolid amended soils. In conclusion, biosolid stability, temperature and soil water interaction significantly influence mineralization and nitrification processes. Unstable sludges had higher N mineralization rate constant and shorter half life times compared to stable sludge, and the Direct field extraction procedure proved to be the most representative sample handling strategy for determination of N speciation in soils and biosolid amended soils to get representative time specific data. v

TABLE OF CONTENTS

DECLARATION…………………………………………………………………………………. ii

ACKNOWLEGMENTS…………………………………………………………………………. iii

DEDICATION ………………………………………………………………………………….. iv

SUMMARY ……………………………………………………………………………………… v

TABLE OF CONTENTS ……………………………………………………………………...... vi

LIST OF TABLES ……………………………………………………………………………...... x

LIST OF FIGURES …………………………………………………………………………....... xi

ABREVIATIONS ……………………………………………………………………………… xii

CHAPTER I: GENERAL INTRODUCTION

1.1 Soil fertility decline ……………………………………………………………………... 1

1.2 Trends in sewage sludge disposal ………………………………………………………. 2

1.2.1 Disposal strategies ……………………………………………………………….. 3

1.2.2 Advantages of sewage sludge land application ………………………………...…3

1.2.3 Disadvantages of sewage sludge land application ……………………………….. 4

1.2.4 Sewage sludge use regulations in South Africa ………..………………………… 4

1.3 Sample handling strategy for N determination in sewage sludge amended soils………… 6

1.4 Objectives of the study ……………………………………………………………………7

CHAPTER II: LITERATURE REVIEW

2.1 Introduction ………………………………………………………………………...…… 8

2.2 Nitrogen dynamics in the ecosystem ……………………………………………………10

2.2.1 The nitrogen cycle ................................................................................................. 11

2.2.2 Mineralisation of organic nitrogen ....................................................................... 12

2.2.3 Inorganic nitrogen losses ...................................................................................... 13

2.3 Occurrence and abundance of nitrogen in soils ............................................................... 14

2.3.1

Forms of nitrogen taken up by plants .................................................................... 14

2.3.2 Role of nitrogen in plants ...................................................................................... 14

2.3.3 Oversupply of nitrogen .......................................................................................... 15

2.3.4 Deficiency of nitrogen ........................................................................................... 15

2.4 Factors influencing nitrogen mineralisation .................................................................. 16

vi

2.4.1 Soil microbe biomass (SMB)................................................................................. 16

2.4.2 Soil water content and potential ............................................................................ 16

2.4.3 Temperature ........................................................................................................... 18

2.4.4 Substrate quality .................................................................................................... 19

2.4.5 Time ....................................................................................................................... 20

2.4.6 Soil pH ................................................................................................................... 21

2.4.7 Soil texture ............................................................................................................. 21

2.5 Net nitrogen mineralized .................................................................................................. 22

2.6 Kinetics of nitrogen mineralisation .................................................................................. 22

2.7 Half life time (t

1/2

) ...……………………………………………………………….…... 24

2.8 Sewage sludges or biosolids ……………………………………………………………. 24

2.9 References ....................................................................................................................... 26

CHAPTER III: SLUDGE STABILITY, TEMPERATURE AND SOILWATER POTENTIAL

EFFECTS ON NET NITROGEN RELEASE

ABSTRACT .................................................................................................................................. 37

3.1 Introduction ...................................................................................................................... 39

3.2 Materials and methods ..................................................................................................... 41

3.2.1 Materials . .............................................................................................................. 41

3.2.2 Methods ................................................................................................................. 42

3.2.3 Treatments ............................................................................................................. 46

3.2.4 Incubation procedure ..………………………………………………………...... 47

3.2.4.1 Establishing water quantities corresponding to selected water potentials .............47

3.2.4.2 Incubation .................................................................................................…….... 47

3.2.4.3 Monitoring water potential and aeration .............................................................. 48

3.2.5 Calculations ......................................................................................................... 49

3.2.5.1 Mass of sludge used to amend the soil ................................................................. 49

3.2.5.2 Extractable and exchangeable NH

4

+

and NO

3

-

plus NO

2

-

determinations ……… 51

3.2.5.3 Net N release from the sludge .............................................................................. 52

3.2.5.4 Potentially available N .......................................................................................... 52

3.2.5.5 Organic N mineralized or potential mineralizable N............................................. 53

3.2.5.6 Partial N mass balance …… ………………………………………………….… 53 vii

3.2.5.7 Mineralization rate constant ..................................................................................55

3.2.5.8 Half life time ….. ................................................................................................... 57

3.3 Results and discussion ..................................................................................................... 58

3.3.1 Net N mineralized after a 56-day incubation …………………………………….58

3.3.2 Vlakplaas amended soil: Effects of temperature and water potential on the mineralization process ....................................................................…………...... 60

3.3.3 Olifantsfontein amended soil: Effects of temperature and water potential on the mineralization process ................................................................................…….. 65

3.3.4 Sasol amended soil: Effects of temperature and water potential on the mineralization process …………...…...………………………………………… 71

3.3.5 Nitrogen mass balance ...........................................................................................76

3.3.6 Mineralization rate constant and half lifetime ...………………………………... 82

3.4 General discussion……………………………………………………………………… 85

3.5 Conclusions and recommendations ................................................................................... 87

3.5.1 Conclusions ……………………………..……………………………………………… 87

3.5.2. Recommendations ……………………………………………………………………… 88

3.6 Limitations ......................................................................................................................... 88

3.7

References …………………………………………………………………………….... 89

CHAPTER IV: SAMPLING HANDLING STRATEGY

Handling of sewage sludge amended soil samples for nitrate and ammonium analysis ……….. 95

ABSTRACT ................................................................................................................................. 95

4.1 Introduction and background ........................................................................................... 96

4.1.1 Objectives ……………………………………………………………………………… 98

4.2 Materials and methods ..................................................................................................... 99

4.2.1 Materials ................................................................................................................ 99

4.2.2 Methods ................................................................................................................. 99

4.3 Results and discussion.................................................................................................... 102

4.3.1 Sample handling effect on N H

4

+

and NO

3

-

content in sludge amended soil ....... 102

4.3.2 Statistical analysis ............................................................................................... 103

viii

4.4 Conclusions and recommendations ................................................................................ 105

4.4.1

Conclusions ………………………………………………………………………...… 105

4.4.2 Recommendations ……………………………………………………………………..105

4.5 References ...................................................................................................................... 106

5 APPENDICES ………………………………………………………………………… 107

A

1

Statistical analysis for temperature and water potential effect on net N release ...……. 108

A

1.1

Stable Vlakplaas sewage sludge amended soil…………...…………………………….. 108

A

1.2

Unstable Olifantsfontein sewage sludge amended soils…...…………………………… 113

A

1.3

Unstable Sasol sludge amended soil …………….…………….……………………… 118

A

2

Statistical analysis of temperature and water potential effects on NH

4

+

and on NO

3

-

.....123

A

2.1

Stable Vlakplaas sewage sludge amended soil ………………………………………....123

A

2.2

Unstable Olifantsfontein sewage sludge amended soil ..…………….………….….......138

A

2.3

Unstable Sasol sludge amended soil ........................……………………………………154

A

3

Incubation time and water potential effects on net N release at T

3

……………………..169

A.

3. 1

Effect of incubation time on NO

3

-

release at T

2

...………...………………….………. 179 ix

LIST OF TABLES

Table 1.1 Sewage sludge classification system …………..……………...………...……………. 5

Table 2.1 Approximate N distribution in the ecosystem ........…………...…………..………….10

Table 3.1 Some chemical characteristics of the sludges used .…………..………………...……42

Table 3.2 Sludge N composition ………………………….. ………………………………….. .43

Table 3.3 The percentage distribution of N in sewage sludge ……….…...…………….........… 44

Table 3.4 Selected soil physical and chemical properties ……………………………………… 45

Table 3.5 Stable Vlakplaas sludge moisture content .......………………………........................ 50

Table 3.6 Sludge N-forms contained in 50g of sludge amended soil ………………….......…... 54

Table 3.7 Equivalent amounts of N-forms contained in 1kg of sludge amended soil ……......... 55

Table 3.8 Levels of significance between temperature and water potential interaction on N

mineralisation for Vlakplaas sludge amended soil ...........…...........……................… 63

Table 3.9 Ranking and treatment mean comparison of NH

4

+

, NO

3

and net N release for

Vlakplaas sludge amended soil ……........................................................................... 65

Table 3.10 Levels of significance between temperature and water potential interaction on N

mineralization for Olifantsfontein sludge amended soil …………...…...............…...69

Table 3.11 Ranking and mean comparison of NH

4

+

, NO

3

and net N release for Olifantsfontein

sludge amended soil…………………………………………………………….…….70

Table 3.12 Levels of significance between temperature and water potential interaction on N

mineralization from Sasol sludge amended soil ………….…………...…..……….. 74

Table 3.13 Ranking and mean comparison of NH

4

+

, NO

3

and net N release for Sasol

sludge amended soil ………………………………………………….………….…. 75

Table 3.14 Partial N mass balance for the 56-day laboratory incubation with Vlakplaas sludge 77

Table 3.15 Partial N mass balance for the 56-day laboratory incubation with Olifantsfontein

sludge ……………………………………………………………………………….. 79

Table 3.16 Partial N mass balance for the 56-day laboratory incubation with Sasol sludge ....... 81

Table 3.17 N mineralization rate constants and half life times of the fast cycling “pool”...…….83

Table 3.18 Estimated sizes of N pools of different types of sludge investigated …………….... 84

Table 3.19 Mineralization rate and temperature coefficient …………………………………… 84

Table 4.1 Levels of significance for sample handling strategies ……. …………...…...............103

Table 4.2 Ranking and treatment mean comparison ………………………………………...... 104 x

LIST OF FIGURES

Figure 2.1 Nitrogen cycle in the ecosystem…………………………………………………..… 11

Figure 2.2 Influence of soil moisture on relative microbial activity ...……………………….... 17

Figure 2.3 Influence of temperature on relative microbial activity …………………………..... 19

Figure 3.1 Schematic representation of treatments …………………………………………...... 46

Figure 3.2 Net N mineralization compared to net N release........................................................ 58

Figure 3.3 Net N release from stable Vlakplaas sewage sludge amended soil ……….………... 62

Figure 3.4 Net N release from unstable Olifantsfontein sewage sludge amended soil …........... 68

Figure 3.5 Net N release from unstable Sasol sludge amended soil …………………................ 73

Figure 3.6 The natural logarithm of organic N decay and estimated rate constants (slope of graphs) for Sasol and Olifantsfontein sludge (a) compared to that of Vlakplaas (b) ........82

Figure 4.1 Concentration of NH

4

+

and NO

3

-

versus sample handling procedures ………….....103 xi

Abbreviations

CIAT- Centro Internacional para Agricultura Tropical/ International Centre for Tropical

Agriculture

DEAT- Department of Environmental Affairs and Tourism

DEF- Direct Field Extraction

DoA- Department of Agriculture

DoH- Department of Health

DWAF- Department of Water Affairs and Forestry

EUUWTD- European Union Urban Wastewater Treatment Directive

ERWAT- East Rand Water Care Company

FC- field capacity

FDE- Field Dried Extraction

ICRAF- International Centre for Agro-forestry research

LDE- Laboratory Dried Extraction

NMIT- Nitrogen mineralization immobilization turnover

SASOL- Suid Afrikaanse Steenkool en Olie Maatskappy / South African Coal and Oil Company

SOM- Soil organic matter

SMB- Soil microbe biomass

TSBF- Tropical Soil Biology and Fertility programme

UK- United Kingdom

USA- United States of America

USEPA- United States Environmental Protection Agency

WWTP- Waste water treatment plant xii

CHAPTER I: GENERAL INTRODUCTION

1.1 Soil fertility decline

Soil fertility is the status of a soil that gives an indication of its potential to supply plant nutrients. Its evaluation is based on soil physical and chemical properties. It varies with time, place, and agricultural use. Fertile soil, when located in an agro-ecological region suitable for crop growth, is considered potentially productive.

Many agricultural lands are continuously losing their productivity as a result of soil fertility decline and/or as a result of utilization of soils with inherent low soil fertility (Folmer et al., 1998; Dowgill

et al., 2002). Decrease in soil productivity has been observed in more than 10 % of cultivated land worldwide, since the 1980‟s (Burns et al., 2006; Francavigilia, 2004; CIAT, ICRAF and TSBF,

2002).

Low levels of food production in Africa results from intensive extraction of plant nutrients without any replenishing measures (Stoorvogel and Smaling, 1990; Buresh et al., 1997; Scoones, 2001). In

Kenya, according to Smaling (1993) most forest and grassland soils showed a significant decline in fertility after being cleared and cultivated continuously with no replenishment of nutrients.

The removal of soil nutrients by crops was greatly exceeding any inputs as a result of insufficient fallow period to recycle back plant nutrients, or in areas of continuous cultivation in, sub-Saharan

Africa, (Smaling, 1993). Negative nutrient balance for N, P, and K in several East and Southern

Africa studied soils was evident (Stoorvogel and Smaling, 1990; Stoorvogel et al., 1993; Dowgill et

al., 2002).

The evidence of soil fertility degradation is the manifestation of plant nutrient deficiencies, low soil organic matter content and higher soil erodibility. Along with erosion, nutrient depletion represents the major land degradation threats in Southern Africa.

Nitrogen (N) and phosphorus (P) are the essential macro-nutrients often limiting crop production, and can be supplied through applications of inorganic fertilizers. However, due to economic reasons

1

most farmers cannot afford to purchase mineral fertilizers (Waddington, 2003; Nhemachena et al.,

2003). Therefore the use of locally available organic sources of plant nutrients is a valuable alternative for the maintenance and recovery of soil fertility.

The Rockefeller Foundation hosted a workshop in March 2002, with the purpose to create a forum to address issues related to recovery measures of soil fertility decline. Various international institutes

(International center for tropical agriculture-CIAT, International center for agro-forestry research-

ICRAF and Tropical soil biology and fertility programme- TSBF) joined their efforts to find solutions for combating nutrient depletion.

An integrated natural resource management concept was proposed to steer the research related to soil fertility recovery. This concept resides in the utilization of locally available natural resources in both an economical and environmentally sustainable way. In agricultural lands nutrients exported by the crops need to be replaced through the addition of readily available sources of nutrients (cost effective) and sustainable agricultural practices management should be implemented (environmental friendly).

Therefore from an African perspective soil fertility management research should focus on ways to increase crop production with minimal use of inorganic fertilizers, and supplementing with organic sources such as animal manure, crop residues, legume based green manure, municipal and industrial wastes, and etc (CIAT, ICRAF and TSBF, 2002; Rowe and Giller, 2003).

1.2 Trends in sewage sludge disposal

Sewage sludge is a by-product of water care works plants, rich in organic matter and plant nutrients.

It is a possible organic source that can be utilized in urban and peri-urban areas, in South Africa and other African cities where water care works does exist.

Ever increasing volume of sewage sludge is produced as a result of the growing human population on earth. Additionally, better water quality is being demanded and stricter environmental laws prescribed, thereby also contributing to an increase in sewage sludge production.

2

Accumulation of produced sewage sludge is a problem due to its negative sanitary status and polluting effect. As a result sewage sludge disposal became a global challenge (Peverly, 1996;

Smith, 1996; Walter et al., 2006). The situation in South Africa with regards to sewage sludge production also reflects this global trend.

1.2.1 Disposal strategies

In the past incineration, ocean dumping and land filling at sacrificial site were common sewage sludge disposal strategies. Sewage sludge disposal through ocean dumping was banned in the USA in 1991. This practice was also banned in Europe in 1998 through the implementation of the

EUUWTD- 91/271/EC (European Union Urban Wastewater Treatment Directive. High energy requirement limits incineration and scarcity of land resource also reduces land filling as a disposal option. Sewage sludge disposal, through land application is increasingly seen as a viable strategy

(Mc Grath et al., 1994; Peverly, 1996; Snyman et al., 1998; Kelly et al., 1999; Bowler, 1999;

Debosz et al., 2002; IWA, 2003; Bengtsson and Tillman, 2004; Van Niekerk et al., 2005).

More than 60 % of produced sewage sludge in USA is land applied, and is expected to increase up to

80 % by 2010, while landfill disposal is at 34 % and may decrease to 30 % (USEPA, 1999). In UK sewage sludge land application was estimated to increase from 50 to 66 % and a landfill disposal reduction from 10 to 6 % between 1995 to 2005 (Bowler, 1999).

1.2.2 Advantages of sewage sludge land application

Sewage sludge is an organic material rich in plant nutrients and potentially could enhance soil fertility as a supplier of plant nutrients and improver of soil physical properties. Therefore land application has been considered a better utilization option (Mc Grath et al., 1994; Smith, 1996;

Peverly, 1996; Snyman et al., 1998; Kelly et al., 1999; Bowler, 1999; Debosz et al., 2002; IWA,

2003; Bengtsson and Tillman, 2004; Van Niekerk et al., 2005; Hseu and Huang, 2005).

3

Based on the advantages of the sewage sludge land application strategy, one could consider it as a solution for both agricultural and environmental problems stated above. Because it can enhance nutrient status of soil and reduce the level of the pollution risk, however, have some disadvantages.

1.2.3 Disadvantages of sewage sludge land application

Though sewage sludge land application strategy has a beneficial effect on soil fertility recovery and the maintenance of a safe environment, an excessive application may cause serious human health and environmental problems, as a result of heavy metal pollution, pathogens and NO

3

-N pollution of surface and ground waters (Wortman and Binder, 2002).

Based on the stated disadvantages it is obvious that a comprehensive soil nutrient management plan is decisive to maintain both the agronomical and environmental sustainability of sewage sludge land application (Bastian, 2005). Rulkens (2003), Snyman and van der Waals (2004) reported on the importance of establishing sustainable regulations for sewage sludge use in agriculture.

Characterization of sewage sludge and determination of the breakdown and release of nutrients and other elements are important considerations when determining suitable application rates (USEPA,

1994; Navas et al., 1997; Wortman and Binder, 2002; Bengtsson and Tillman, 2004).

1.2.4 Sewage sludge use regulations in South Africa

Not all produced sewage sludge are feasible for agricultural use, deciding whether such sewage sludge meet the legal requirements for use is a conjectural process and a great responsibility attributed to several government departments. The Department of Water Affairs and Forestry

(DWAF), Department of Environmental Affairs and Tourism (DEAT), Department of Health (DoH) and Department of Agriculture (DoA), join their efforts on maintaining a sustainable utilization of sewage sludge. For them to authorize, sewage sludge must go through the South African waste water sludge classification system.

Sewage sludge classification is based on three classes: the Microbial, the stability and the pollution classes, with three levels each (Table 1.1). Therefore, sewage sludge is tested for several criterions in order to be placed on the respective type. For Microbial class the criteria are faecal coliforms and

4

helminth ova content, for pollution are certain heavy metals and elements considered potentially toxic and for stability the indicator is the vector attraction potential (Snyman and Herselman, 2006).

Table1.1: Sewage sludge classification system

Classes Levels

Microbial

Stability

Pollution

A

1 a

B

2 b

C

3 c

Sewage sludge of microbial class “A”, Stability class “1” and pollutant class “a”, is used for land application, on the rate established, while all other classes have same restrictions. However, if it falls to class “B”, “2” no matter if pollutants are at level “a” its use is restricted. When, is sludge of microbial class “C”, is not allowed for agricultural use (Snyman and Herselman, 2006).

South African guidelines recommend application rates not exceeding crop N requirement to an upper limit of 10 tons of sewage sludge per ha per year, to prevent NO

3

-N leaching (Snyman and

Herselman, 2006). Differences in the sewage sludge sources and soil types might exert considerable influence on sludge N availability, though not considered.

The relative composition of domestic and industrial waste streams contributes to the final nutrient content of sewage sludge. Sewage sludge stability, which is a function of treatment process, may influence the way sewage sludge release nutrients. This explains the reason why relative composition of sewage sludge from different loads in the same treatment plant differs.

The majority of N in sewage sludge is present in an organic form and has to be converted into inorganic N forms that are available for plants. This conversion process is governed by soil living organisms, therefore soil environmental factors influencing microbial activity, will greatly influence the N mineralization rate.

5

Understanding the fate and transformations of nitrogen in sewage sludge amended soils is important for effective use of sewage sludge as soil amendment, in order to meet crop demand and at the same time also minimize environmental problems (Serna and Pomares, 1992; Gaines and Gaines, 1994;

Smith et al., 1998; Waddington, 2003).

Furthermore, research on the release of N from sewage sludge amended soils is necessary to parameterize models in order to predict N and nutrient balance, and gain short, medium and longer term predictive capability on N dynamics Modeling the movement of N in sewage sludge amended soils involves various parameters, such as temperature, moisture regime, quality of sewage sludge and period from application.

1.3 Sample handling strategy for N determination in sewage sludge amended soils

Changes in soil chemical properties „nutrient forms and content‟ occur as a result of pre-treatment given to soil sample after collection, nitrogen element, is easily transformed within its speciation forms.

Mineralization and nitrification are ongoing processes. Therefore, the handling of biosolid amended soil samples will determine how representative the determined nitrate and ammonium speciation is to what is available in the soil at the time of sampling.

Field validation of mineralization and nitrification rates is essential for accurate prediction and modeling of the environmental fate of nitrogen entering the soil system through biosolids application.

Soil nitrate and ammonium levels are temporarily highly variable as the net result of mineralization, immobilization, leaching, volatilization and denitrification; change with soil water content, soil temperature, quantity and quality of organic inputs (Follett, et al., 1987; Stenger et al., 1995; Er, et

al., 2004; Hai-Xing and Sheng-Xiu, 2006).

6

Inadequate sample handling procedure after sampling may lead to results that are not representative to the site situation. Therefore soil sampling and handling procedures should be consistent and representative.

This dissertation consists of two experiments to investigate: temperature, water potential and sludge stability effect on N mineralization, and the second was to test three sample handling procedures

(Direct field extraction, Field dried extraction and Laboratory dried extraction) in a sewage sludge amended soil.

1.4 Objectives of the study

The objectives of the study were to: i) Determine the net inorganic nitrogen release [(NO

3

-

plus NO

2

-

) and NH

4

+

] as a function of temperature and water potential; ii) Determine the influence of sewage sludge stabilization on N release; iii) Determine the rate constant, potentially mineralizable N, and half life time ; iv) Assess the influence of soil sample handling on the dynamic of NO

3

-N and NH

4

-N speciation in sewage sludge amended soils.

To fulfill these objectives, a laboratory incubation study was conducted under different environmental conditions in terms of temperature and soil water using a sandy clay loam soil. The soil was amended with sludge, corresponding to 10 t ha

-1

on a dry mass basis. Three types of sludge of different stability, collected from different wastewater care works plants were used. A sample handling strategy experiment was also conducted, where three different sample handling procedures were tested based on nitrate and ammonium determinations. This dissertation covers four parts as follow: General introduction, Literature review, Incubation experiments and Sample handling strategy experiment.

7

CHAPTER II: LITERATURE REVIEW

2.1 Introduction

Developing countries are faced with low crop production, caused either by the continued utilization of soils with inherent low soil fertility or soil fertility degradation. Nitrogen and phosphorus are the common plant nutrients limiting the crop production; supply of these nutrients through inorganic fertilizers increases the crop production. However, most farmers do not have financial support to purchase fertilizers (Stoorvogel and Smaling, 1990; Buresh et al., 1997; Folmer et al., 1998;

Scoones, 2001; Waddington, 2003). Organic sources are valuable nutrient sources to supplement inorganic fertilizers and an alternative for resource poor farmers to increase crop yield.

Organic sources can encompass any remains of plants, animals, microorganisms, animal excreta and municipal solid wastes. These organic material after being broken down, turns into important sources of plant nutrients and helps to maintain or build up soil organic matter.

In general soil organic matter has a positive effect on the physical, chemical and biological soil properties, such as water retention, aeration, erodibility, cation exchange capacity, nutrient availability and microbe activity. Therefore, soil organic matter is a key component of the soil, “the foundation of a fertile soil”. Hence the maintenance of sufficient soil organic matter levels is a prerequisite for sustainable crop yields. For this reasons, research on soil fertility management in developing countries is currently oriented to increase crop production using organic sources with minimal use of inorganic fertilizers (Ward et al., 1987; Buresh et al., 1997; Waddington, 2003; Wolf and Snyder, 2003).

These sources are an economically and environmental viable options, only if well managed.

However, the efficient use and management of organic sources requires a good understanding of their nutrient release “mineralization processes”.

According to Hseu and Huang (2005) more than 50 % of the total N in sewage sludge is organic, quoting (Sommers, 1977) therefore, it is necessary to determine N mineralization rate and predict N availability.

8

Mineralization of organic N in sewage sludge amended soils is a complex process mediated by soil organisms that are influenced by several factors such as soil type, pH, temperature, moisture, quality and quantity of applied sewage sludge, (Serna and Pomares, 1992; Sierra et al., 2001; Hernandez et

al., 2002; Wang et al., 2003; Zaman and Chang, 2004; Van Niekerk et al., 2005; Agehara and

Warncke, 2005).

Though mineralization rate is also a function of factors other than climatic ones (temperature and moisture), the obtained models for nitrogen mineralization considered these two as the dominant soil environmental factors. Therefore, they are still empirical models and cannot be reliably applied to a particular soil situation, because they miss factors like soil type (Leiros et al., 1999; Van Niekerk et

al., 2005).

This chapter will focus on nitrogen dynamics in the ecosystem, as well as factors affecting N transformations among different N-forms; the economical and environmental problems of production and disposal of sewage sludge; on the importance of sewage sludge use in agricultural lands, on N mineralization processes occurring in sewage sludge amended soils and also the kinetics involved on these processes.

9

2.2 Nitrogen dynamics in the ecosystem

Nitrogen is widely distributed in nature and can be found in the atmosphere, the lithosphere, and the hydrosphere. The atmosphere is the main reservoir of nitrogen with about 78 % of gaseous nitrogen

(N

2

) which is in equilibrium with all fixed forms of N in soil, seawater, and living and nonliving organisms. The distribution of N is given in Table 2.1. Despite the fact that N is the most abundant nutrient in nature, deficiencies in plants occur frequently in non leguminous cropping systems.

Organic nitrogen has to be converted into inorganic N (nitrate- NO

3

-

and ammonium- NH

4

+

forms) before it could be used by plants.

Table 2.1 Approximate N distribution in the ecosystem (Havlin et al., 2005)

Atmosphere

N source

Sea (both living and non-living)

Soil (non-living)

Plants

Microbes in soil

Animals (land)

People

Metric tons

3.9 × 10

15

2.4 × 10

13

1.5 × 10

11

1.5 × 10

10

6.0 ×10

9

2.0 ×10

8

1.0 × 10

7

The N dynamics is governed by interactions between abiotic soil environmental factors such as soil moisture, temperature, oxygen, and biotic components like soil organisms, plants, and by agronomic practices (McGill and Meyers, 1987; Leijder, 1988; Brady and Weil, 2002; Havlin et al., 2005).

Understanding the dynamics of different N pools in the ecosystem is an important tool to assess and predict soil N availability (Russell‟s, 1988; Havlin et al., 2005).

10

2.2.1 The nitrogen cycle

The conceptual idea of the N cycle date back to 1913 when it was first formulated by Lohnis, and since 1950‟s diagrams have been drawn to illustrate the pathway of N in the ecosystem (Paul and

Clark, 1988). However, its complexity is scientifically challenging (Jarvis, 1996). Cycling of N involve many transformations between inorganic and organic forms (Fig. 2.1).

Figure 2.1 Nitrogen cycle in the ecosystem (soil/plant/animal/air) (Stevenson, 1982)

The atmosphere is the primary source of N as shown in the above figure, whereby lightning oxidizes the atmospheric N

2

into NO

3

-

- N that is deposited in soils through rain precipitation, fixation through free living bacteria, and symbiotically leaving bacteria, industrially N-fixation and man application of organic and inorganic sources. Organic materials in soils undergo decomposition and accumulate

11

as soil organic matter that contains plant nutrients in organic forms, which in turn can transform into inorganic forms through mineralization.

Inorganic N in the form of NH

4

+

-N and NO

3

-

-N can be taken up by plants, or immobilized by soil microorganisms. Soil microbial population and plants compete for inorganic N forms. Rapidly growing microorganisms can immobilize NH

4

+ and NO

3

-

, therefore, depleting temporarily the availability of N to plants. NH

4

+

can also be adsorbed on the edges of clay particles, or fixed in soil clay minerals such as illite and vermiculite; meanwhile NO

3

- can also be lost to the atmosphere through denitrification or leached below the active root zone (Brady and Weil, 2002; Havlin et al.,

2005).

2.2.2 Mineralization of organic nitrogen

A significant component of soil total N is in organic forms, and can be converted into inorganic N forms available to plants through mineralization, a biochemical process mediated by microorganisms. The process involves two steps: ammonification and nitrification (Stevenson, 1982;

Paul and Clark, 1988; Brady and Weil, 2002; Havlin et al., 2005; Canali and Benedetti, 2005).

1 st

step: Ammonification process

Firstly the soil organic N compounds undergo an amminification process in which amino–N compounds (R-NH

2

) are formed which, in turns, are converted into NH

4

+

, in presence of heterotrophic organisms. These organisms are able to operate in both aerobic and anaerobic conditions.

SOM

R

NH

2

2

H

2

O

OH

 

R

OH

NH

4

, (Brady and Weil, 2002)

2 nd

step: Nitrification process

The obtained ammonium (NH

4

+

-N), in the presence of nitrifying autotrophic bacteria and oxygen

(aerobic conditions), is first oxidized into nitrite (NO

2

-

-N) in presence of nitrosomonas and then to nitrate (NO

3

-

-N) through nitrobacter.

NH

4

O

2

4

H

energy

NO

2

1

2

O

2

energy

NO

3

, (Brady and Weil, 2002)

12

2.2.3 Inorganic nitrogen losses

Not all mineralized N is used by plants and microorganisms, a fraction of it can be lost through volatilization, denitrification and leaching.

2.2.3.1 Volatilization

May occur under alkaline or dry soil conditions, losses can vary from 3 to 50 %; volatilization increase with increasing temperature up to about 45 o

C

NH

4

 

OH

 

NH

4

OH

NH

3

 

H

2

O

(Brady and Weil, 2002)

In calcareous soils volatilization is given by the equation.

2

NH

4

 

CaCO

3

NH

4

2

CO

3

Ca

NH

4

2

CO

3

2

NH

3

H

2

CO

3

H

2

O

CO

2

(Havlin et al., 2005)

2.2.3.2 Denitrification

Occur under anaerobic conditions, and warm environment. The anaerobic organisms obtain their oxygen from the nitrate and nitrite ions

2

NO

3

 

O

2

2

NO

2

 

O

2

2

NO

 

1

2

O

2

N

2

O

 

1

2

O

2

N

2

(Brady and Weil, 2002)

2.2.3.3 Leaching

Nitrate ions are very soluble and highly mobile in the soil. Therefore, soil water exceeding the water holding capacity result in excessive water movement causing losses of NO

3

- through runoff and leaching processes (Havlin et al., 2005).

Understanding the gain and loss processes for distinct N-forms, as well as the factors influencing their changes, forms the basis of an efficient management of N in agricultural land. In general, losses can range between 40 to 60 % of applied N, however, under poor management losses may reach 80

% (Leijder, 1988).

13

2.3 Occurrence and abundance of nitrogen in soils

Generally a high proportion of the total N in surface soils is organic (about 95 %). N content in mineral soils may vary between 0.02 to 0.5 %, while organic soils exhibit values up to 2.5 %. In general soil organic matter (SOM) contains about 5 % of N, therefore, the distribution of N in soils follows the same pattern as SOM distribution. For instance, aridisols are generally poor in both organic matter and organic N, on the other hand histosols and mollisols are rich in organic matter and consequently high in organic N. Andisols are an exception, having higher organic C than any other mineral soil, the reason is the presence of allophane clays that bind organic matter protecting it from being oxidized (Mengel and Kirkby, 1987; Brady and Weil, 2002; Havlin et al., 2005).

2.3.1 Forms of nitrogen taken up by plants

Plant roots absorb N in soil solution in the forms of NO

3

-

and NH

4

+ ions, the uptake of NO

3

- implies an exudation of HCO

3

-

and OH

- from the roots increasing the pH of the rhizosphere. NH

4

+ uptake is accompanied by the release of H

+ from the root into the soil solution resulting in a decreasing of the pH of the rhizosphere. In both cases the effect on pH may influence the availability and uptake of other nutrients. Under field conditions the rate of NH

4

+ uptake is lower compared to NO

3

-

, as a result most crops have higher response to NO

3

-N applications than to NH

4

-N fertilizers due to high mobility of nitrate and possible fixation of ammonium (Mengel and Kirkby, 1987; Brady and Weil,

2002; Havlin et al., 2005).

2.3.2 Role of nitrogen in plants

Nitrogen is a very important element for plant growth as an integral component of many plant compounds, such as chlorophyll, and proteins. Therefore, N has an important role in the photosynthesis process, carbohydrates utilization within the plant as well as in the transferring of genetic characteristics. N also stimulates the uptake of other plant nutrients, and induces vegetative growth (Stevenson, 1982; Leijder, 1988; Mengel and Kirkby, 1987; Havlin et al., 2005).

The nitrogen content in plant varies with plant age and depends on the plant part. The removal of soil N by crops also vary between plant species, being low in root crops 0.5 to 1.0 %, medium in trees and grain crops 1 to 2.5 %, and high in leguminous crops 3 to 5 % (Leijder, 1988).

14

2.3.3 Oversupply of nitrogen

Excessive N supply decreases the quality of products, because N enhances excessive vegetative growth, poor flowering and seed formation, and retard maturation. Plants may also grow taller and be more susceptible to lodging when exposed to wind and rain. Oversupply of N can also weaken tissue resulting in high susceptibility to pest and fungal diseases, e g. chocolate spot in maize, brown rust in barley, brown leaf spot in rice and fusarium graminearum in wheat. Undesirable color and flavor of fruits, lower sugar and vitamin content of certain vegetables and crop roots are also reported (Leijder, 1988; Mengel and Kirkby, 1987; Brady and Weil, 2002; Havlin et al., 2005).

Another negative effect is that an excess NO

3

- in soils may lead to environmental degradation of groundwater due to leaching and surface water due to runoff (Brady and Weil, 2002). Soil NO

3

-N exceeding the permissive contaminant level will negatively affect water quality (Sparks, 2003).

Drinking water polluted with NO

3

-

-N causes diseases in animals and humans such as

methemoglobinemia or blue baby syndrome (Brady and Weil, 2002).

The department of National Health and Population Development in South Africa established 10 mg

L

-1

N in the nitrate form, as the upper standard value for drinking water (Korentajer, 1991); This value is equal to the limit set by the United States regulatory agency for environmental protection

(Brady and Weil, 2002; Sparks, 2003).

2.3.4 Deficiency of nitrogen

Soil nitrogen deficiency limits crop productivity as it decreases the production level and quality of products (low protein and high sugar contents), The main symptoms are leaves with pale yellow green colors (chlorosis), which is first observed in the older leaves due to translocation of proteins from its chloroplasts to younger leaves. Other symptoms includes die-back from the tip, stunted plants, thin and spindly stems (low shoot-to-root ratio), and quicker maturity than healthy plants

(Mengel and Kirkby, 1987; Paul and Clark, 1988; Leijder, 1988; Russell‟s, 1988; Brady and Weil,

2002; Havlin et al., 2005).

15

2.4 Factors influencing nitrogen mineralization

Mineralization and immobilization processes are mediated by soil organisms, therefore all factors influencing the occurrence and activity of soil organisms will affect N mineralization/ immobilization turnover (NMIT). Environmental factors (temperature and moisture), nature, quality and abundance of organic source, soil type influence mineralization process, as they affect microbial activity (Terry et al., 1981; Mengel and Kirkby, 1987; Paul and Clark, 1988; Russell, 1988; Jarvis et

al., 1993; Leiros et al., 1999; Brady and Weil, 2002; De Neve et al., 2004; Er, et al., 2004; Snyman and Van der Waals, 2004; Zaman and Chang, 2004; Havlin et al., 2005).

2.4.1 Soil microbe biomass (SMB)

Soil microbial biomass (SMB) is an important component of soil organic matter (SOM) that regulates transformation and storage of soil nutrients. It forms part of the labile fraction of SOM, and contains 1 to 3 % of total carbon and up to 5 % of the total nitrogen. To understand the nutrient fluxes in natural and agricultural ecosystems, evaluation of the size, diversity and activity of the

SMB are necessary (Hortwath and Paul, 1994). Additions of carbon in the form of sugars leads to an increase in SMB activity and consequently a higher N released due to the increased N mineralization

(Heal et al., 1997; De Neve et al., 2004).

2.4.2 Soil water content and potential

Soil water content and potential are important factors controlling the microbial activity, and in turn, soil organic carbon and organic N turnover. Soil water influences the mobility of microbial cells in soil while water potential determines the ability of microbes to maintain their activity and survival during periods of water stress. Soil water also affects aeration, and regulates the oxygen supply to microbes (McInnes et al., 1992).

Both low and high soil water content influence the microbial activity negatively. Sierra et al. (2001) found nitrifiers more sensitive to changes in water potential, where their activity was inhibited at -

1500 kPa. Low soil water content decreases the mobility of soil microbes thus reducing the microbial activity, while high soil moisture creates an anaerobic condition. Therefore, limiting the

16

availability of oxygen to SMB thus, limiting the activity of nitrifying bacteria and favor denitrification process.

It is reasonable to expect that at water potential between –10 to –30 kPa, often used to approximate field capacity, optimal microbial activity can be expected. At this stage the soil water is available for plants and also for microbial growth. Soil microbial activity was reported to be optimum at –50 kPa and decreased as the soil becomes waterlogged (near zero water potential) or more dry (high negative water potentials). While at reduced soil water potential close to –1500 kPa plants suffer from water stress and microbial growth and its activity are depressed, (Mengel and Kirkby, 1987;

Paul and Clark, 1988; Leiros et al., 1999; Tan, 2000; Havlin et al., 2005). Fig. 2.2 shows the influence of soil moisture on the soil microbe activity.

1

0.8

0.6

0.4

0.2

0

0.1

0.2

0.4

0.6

0.8

Degree of soil saturation

0.9

Aerobic organisms

1

Anaerobic organisms

Figure 2.2 Influence of soil moisture on relative microbial activity (Doran and Smith, 1987).

According to Doran and Smith (1987) the activity of aerobic organisms reaches its maximum when

60 % of pore space is filled with water, and is restricted below 20 % and higher than 80 %

(equivalent to dry and water-logged conditions). The soil moisture regulates the proportion of nitrifying and denitrifying bacteria‟s activity. From Fig. 2.2 it is evident that well-aerated soil favor aerobic nitrifying bacteria and anaerobic conditions enhance the activity of denitrifying bacteria.

High salt concentration leads to osmotic stress inhibiting microbial activity. Nitrifying bacteria are very susceptible to salinity (Paul and Clark, 1988; Jarvis et al., 1993; Heal et al., 1997).

17

2.4.3 Temperature

Temperature is one of the main environmental factors controlling microbial activity, and therefore the decomposition and mineralization processes. The influence of temperature on nitrogen mineralization can be evaluated through the following equations: i) Arrhenius equation- which assumes the energy of activation for the process to be constant;

N

e

Ea

/

R

1 /

t

1 /

T

Where N is the rate of nitrogen mineralization at temperature t, T is the optimal incubation temperature, E a the activation energy expressed in kJ mol

-1

. ii) Van‟t Hoff equation, which assumes the exponential relationship between the rate of the mineralization process and the temperature:

N

e b

t

T

;

Q

10

e

10

b

Where N stands for mineralization rate, b a rate constant, t the temperature of mineralization, T the optimal incubation temperature, and Q

10

is the temperature coefficient. This coefficient (Q

10

) is equal to 2 over the range of 5 to 35 o

C, meaning that change in mineralization and nitrification rate is twofold when temperature shifts in 10 o

C.

Temperature increase accelerates the decomposition of organic matter and the mineralization process, up to a certain threshold. High temperature (> 45 o

C) has a negative effect on these processes. The optimum temperature ranges between 25 to 35 o

C, at extreme temperatures such as below 5 o

C and higher than 40 o

C, the microbial activity is depressed or ceases (Mengel and Kirkby,

1987; Paul and Clark, 1988; Brady and Weil, 2002; Havlin et al., 2005). Figure 2.3 shows how microbial activity varies with temperature. Soil microbe biomass activity reaches hundred percent or its maximum within 25 to 35 o

C, and at temperature less or equal 5 ºC and higher than 55 ºC no mineralization occurs, the microbe activity is inhibited.

Therefore, high levels of nitrogen released are expected within 25 to 35 ºC. Incubations under 20 ºC and over 40 ºC are expected to produce lower levels of mineralized nitrogen. Sierra et al. (2001) reported that at 30 ºC had greater N mineralization, and nitrification increased with temperature. Tajeda et al. (2002) found also that N mineralization was higher at 25 o

C than 15 o

C and that increasing temperature boosted mineralization as well as N losses which can exceed 50 %.

18

1

0.8

0.6

0.4

0.2

0

0 10 20 30 40

Temperature [ o

C]

50 60 70

MCB activity

Figure 2.3 Influence of temperature on microbial activity (Doran and Smith, 1987).

2.4.4 Substrate quality

In order to grasp the complexities involving organic substrates it is commonly conceptualize as discrete fractions related to their degradability: a pool of easily decomposable compounds also known as the rapid release pool, a pool of slow release and a third pool of resistant compounds.

Besides the environmental soil conditions the rate of N mineralization is also influenced by the quality of organic source and the stability of the organic N compounds present (Smith et al., 1998).

Sewage sludge follows the same trend as conversion of its organic N into inorganic N is influenced by its composition and stability. The C:N ratio and also the amount of lignin and polyphenols, exert an important role on the decomposition rate of organic material. At C:N ratio greater than 25 the mineralization will be negatively influenced as immobilization of released N may occur initially.

Substrates with C:N ratios less than 20 decompose rapidly. Wolf and Snyder (2003) also reported a

C:N of 20 to be the threshold level.

According to De Neve and Hofman (1996) many researchers have tried to quantify the critical C:N ratio for N mineralization, and found it to be 20 for short-term incubations and 30 – 40 for long-term incubations. This dependence of the critical C:N ratio on the incubation period could be explained through the consumption of N by soil organisms which become remineralized after the decay of microbial cells during the incubation.

19

According to Whitmore and Handayanto (1997) decomposition and mineralization are related. The

N mineralization can be expressed as a function of decomposable organic carbon as follows:

N mineralized = C decomposed (1/zE/y),

Where z represents the C:N ratio of the added organic material, E stands for microbiological efficiency factor “representing the fraction of decomposed C that is transformed into SOM”, 0.4 is the established value used in APSIM (Agricultural Production Systems Simulation Model) for soil

N, and y the C:N ratio of the recently formed SOM.

Palm and Sanchez (1991) reported that lignin and poliphenols are also determinants of N release from organic sources. Organic materials with considerable high lignin and poliphenol content, and/or high ratio poliphenol:N, cannot readily supply N. The existence of poliphenol-N polymers slow down the decomposition process. However, organic sources with low lignin content and low lignin to N ratio or low poliphenol to N ratio can be used successfully as a source of available N due to the relatively fast decomposition and mineralization rates.

It was found that polyphenolic compounds in the organic source influence NMIT in two ways:

i)

Polyphenolic compounds have direct toxicity effect on the SMB;

ii)

Polyphenolic compounds have high affinity for amide groups and can bind proteins, preventing N release (Heal et al., 1997; De Neve et al., 2004).

2.4.5 Time

The dynamics of N in soils is governed by mineralization and nitrification processes‟ changing continuously depending on the environmental conditions at specific time. Since factors controlling soil microbial activity change with time, therefore the length of incubation period would affect the quantity of N released and chemical composition of the soil medium. It was observed that this fact limits the use of mineralization models in predicting the long term N mineralization process (De

Neve and Hoffman, 1996; Maly et al., 2002; Benbi and Richter, 2002).

20

2.4.6 Soil pH

Both microbial diversity and activity are pH dependent. According to Brady and Weil (2002) decomposition and mineralization processes occur rapidly at near neutral pH and optimum moisture and aeration conditions. Under extreme acid conditions decomposition is inhibited. Nitrifying bacteria are more effective under slightly acid to neutral pH (6.6 to 8.0), below pH 6 nitrification rate declines and is negligible below pH 4.5 (Jenkinson, 1981; Terry et al., 1981; Mengel and Kirby,

1987; Paul and Clark, 1988). Sierra et al. (2001) also found that in a soil with pH 4.9, an introduction of nitrifiers with fresh sewage sludge had no effect on nitrication rate.

2.4.7 Soil texture

The effect of soil texture is indirect and expressed through soil structure and porosity, thus, regulates the soil water content for a particular water potential. The effect of soil texture manifests as follow:

i)

Influences aeration and moisture status;

ii)

Affects physical distribution of organic materials and their potential for degradation

(Thomsen et al., 1999; Thomsen et al., 2003).

Similarly to Thomsen findings, Jarvis et al. (1996) and Hassink et al. (1992) concluded that high clay content may decrease mineralization by two mechanisms:

i) Physically confining micro-organisms in small pores making them less active;

ii) Physically protecting non-living SOM from decomposition by surface adsorption on clay minerals.

The majority of mineralization studies have relied on moisture conditions adjusted to water field capacity (WFC) rather than water potential which makes it difficult, if not impossible, to compare mineralization rate across different textured soils, since the soil moisture held at WFC of different textured soils differ (Thomsen et al., 2003).

21

Hassink et al. (1992) found that sieving soils caused a temporary increase in mineralization of carbon and nitrogen, the increase was larger in loam and clayey soils than in sandy soils. This can be attributed to an increase in the contact surface between soil organisms and soil organic materials, which in turn depends on the soil water content. Similarly Stenger et al. (1995) found that nitrogen mineralization rates were twice as high in sieved soils compared to undisturbed one.

Hernandez et al. (2002) studying N mineralization potential in calcareous soils amended with sewage sludge concluded that the organic N mineralization of sewage sludge was influenced by soil type. Greater N mineralization rate was observed in sandy soils (where ranged from 30 % to 41 % of total N) than clayey soils (where organic N mineralized was about 13 % to 24 %). These results are confronting the Hassink‟s, (1992) and Stenger et al., (1995) findings.

2.5 Net nitrogen mineralized

Theoretically extractable inorganic N encompasses the three forms of inorganic N (NH

4

+

, NO

3

-

and

NO

2

-

) extracted with a 1 molar KCl solution at room temperature. The nitrite form is an intermediate stage of nitrification which in turn is jointly reduced with nitrate during the steam distillation by

Keeney and Nelson, (1982). Therefore, in this study the term nitrate is extensively used to designate both NO

3

-

and NO

2

-

.

2.6 Kinetics of nitrogen mineralization

The kinetic of N mineralization is described using first-order equation:

N min

= N

0

(1- e kt

), (Stanford and Smith, 1972)

Where N min

stands for amount of N mineralized at time t; N

0

is the potential mineralizable N; k is the first-order rate constant and t the incubation time.

22

Several research on N mineralization were based on the first-order equation (Paul and Clark, 1989;

Serna and Pomares, 1992; Smith et al., 1998; Rasiah and Kay, 1998; De Neve et al., 2004; Havlin et

al., 2005). Similarly, De Neve and Hofman (1996) used the first-order kinetics to describe N mineralization from organic residues:

N

(t)

= N

A

(1 - e

– kt

)

Where N t is the net N mineralization at time t, N

A is the part of total residue N that was mineralized, k the rate constant and t the incubation time.

Many researchers have studied different kinetic models to describe N mineralization and found discrepancies within undisturbed and disturbed samples. Some researchers used the single first order model, described by Stanford and Smith, (1972), and concluded that the model described better the

N mineralization of undisturbed soils. In disturbed soils samples the double first-order model described by Molina et al., (1980) was appropriate to account for the initial flush of N mineralization or for the existence of two considered pools of organic N, the rapidly (N

1

) and slowly (N

2

) mineralizable N pools (Dou et al., 1996; Hseu and Huang, 2005; Smith et al., 1998c; Benbi and

Richter, 2002).

N min

= N

1

(1- e

– k

1 t

) + N

2

(1- e

–k

2 t

), (Molina et al., 1980)

N o

= N

1

+ N

2

Where N min

represents the net mineralized N at time t, N

0

is the potential mineralizable N, estimated from N

1

plus N

2

representing the rapid and slow mineralizable pools respectively, and k

1

and k

2

the specific rate constants of inorganic N accumulation and t the incubation time.

Smith et al. (1998c) found that potentially mineralizable N was best estimated as 26 % of total applied N for (N

1

) and 42 % of total applied N for (N

2

). However Dou et al. (1996) found that the goodness of fit of different kinetic models depends on the duration of incubation. For instance, under short incubation time (≤ 15 weeks) the single first-order model was found to provide good fit of data and for long incubation period (> 15 weeks) the double first-order model provided better results.

23

2.7

Half life time (t

1/2

)

In addition to other parameters for modeling N mineralization the half-life time of the organic substrate is also of great importance in modeling the persistence of the organic substances in soil system. The half-life time for a dynamic system is the time required for the substrate to be reduced by half. For an organic substrate in a soil system it is the time needed to decompose and/or mineralize 50% of the initial amount added to soil system. Half life time are calculated based on the exponential decay models (Y = Yo e kt

), which gives an image of the half life constant independent of the initial valor. Where, Yo is the initial quantity and k the decay or growing rate per unit time

(Atkins, 1999; Ansie and Roumen, 2004).

Derivation:

N t

= N

0

e

–kt

; half life time is when N t

= N

0

/ 2

N

0

/2 = N

0 e

-kt

;

½ ln N

0

= ln N

0

- kt

1/2

= - ln [½N

0

/N

0

] = kt

1/2

; - ln ½= ln 2 hence ln2 = kt

1/2

; Thus half life time is given by t

1/2

= ln2/k

2.8 Sewage sludge or biosolid

Sewage sludge, as commonly called in South Africa, refers to a by-product of the municipal wastewater treatment company. It contains organic matter rich in essential plant nutrients, and in some cases also contains liming agents. Demand for better water quality and strict environmental laws lead to an increase in sewage sludge production, during wastewater treatment. Disposal of sewage sludge is an economic and environmental problem. Sewage sludge used to be disposed through land filling, sea dumping, and incineration. However, the incineration practice has been phased out due to high costs of ash treatment; sea dumping is a threat for aquatic organisms, decrease in availability of land area and the long term environmental problems restricted land filling.

Therefore, sludge disposal is becoming a serious challenge in the world (Peverly, 1996; Bowler,

1999; IWA, 2003; Sukkariyah, et al., 2005; Walter et al., 2006).

Municipal sludge, therefore, has a value in agriculture as soil conditioner and supplier of plant nutrients (nitrogen, phosphorus and some micronutrients). The nutrient value of the sewage sludge

24

depends on the source of wastewater and treatment process. For example dewatering of sewage sludge improves the physical aspect of biosolids, however, reduces its NH

4

+

content due to removal of soluble NH

4

-N with the liquid phase.

Land application and recycling of sewage sludge in agricultural lands is an option that reduces waste transport costs, prolongs the life span of sanitary landfill and reduces environmental pollution, thus is considered the most sustainable approach for disposing sewage sludge (Kaseva and Gupta, 1996;

IWA, 2003; Mendoza et al., 2006). In the UK biosolids applications in agricultural lands has been accepted for more than 40 years (Davis, 1989 as cited in Smith et al., 1998), and in USA more than

60 % of produced sludge is land applied (USEPA, 1994).

Although sewage sludge is a valuable resource it could cause negative environmental impact if used improperly. Excessive applications at rates higher than plant N demand, or applications at the wrong time of the year, may increase pollution risk of surface and ground waters (Kaseva and Gupta, 1996;

IWA, 2003; Sukkariyah et al., 2005; Mendoza et al., 2006). Other potential risks of sewage sludge include presence of heavy metals, pathogens and organic contaminants.

Therefore, in some European countries the practice of sewage sludge use in agriculture has been debated quite a lot heading for restriction in farmlands because food products are at risk of contamination which in turn might cause health problems (Mendoza et al., 2006). A better destiny of sewage sludge is recycling on green fields for e.g. on parks, sporting fields, road embankments, golf courses (USEPA, 1994). Another strategy is an on-site use as a source of energy (heat, electricity made from biogas). In South Africa the long term use of sewage sludge in agricultural land still needs to be studied under several field conditions (Snyman and Van der Waals, 2004). Currently composting of sewage sludge is an important strategy for use in farmland for food production (IWA,

2003), as many pollutants are reduced.

25

2.9 References

AGEHARA, S. AND WARNCKE, D.D., 2005. Soil moisture and temperature effect on N release from organic N sources. Soil Science Society of American Journal 69, 1844 –1855

ANSIE, H. AND ROUMEN, A., 2004. The mathematical modeling problem book. Pretoria Spring field house. 94 pp

ATKINS, P.W., 1999. Physical chemistry. The rates of chemical reactions. 6 th

Ed. Oxford

University Press, 761 -818

BASTIAN, R.K., 2005. Interpreting science in the real world for sustainable land application.

Journal of Environmental Quality 34, 174 – 183

BENBI, D. K. AND RICHTER, J., 2002. A critical review of some approaches to modeling nitrogen mineralization. Biology Fertility Soils 35, 168 – 183

BENGTSSON, M. AND TILLMAN, A.M., 2004. Actors and interpretations in an environmental controversy: the Swedish debate on sewage sludge use in agriculture.

Resources, Conservation and Recycling 42, 65 – 82

BLOEM, J., HOPKINS, D.W. AND BENEDETTI, A., 2006. Microbiological methods for assessing soil quality. CABI publishing 300 pp

BOWLER, I.R., 1999. Recycling urban waste on farmland: an actor- network interpretation.

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36

CHAPTER III:

SEWAGE SLUDGE STABILITY, TEMPERATURE AND SOIL WATER

POTENTIAL EFFECTS ON NET NITROGEN RELEASE

ABSTRACT

To take advantage of sewage sludge as a soil amendment, and to negate negative environmental effects, knowledge of N transformation processes in sewage sludge amended soil is required. The effect of temperature, water potential, and the stability of sewage sludge on sludge-N mineralization and nitrification rates were assessed during a 56-day laboratory incubation study. A sandy clay loam soil was amended with sludge from different wastewater treatment processes. Stable anaerobically digested and paddy dried sewage sludge, collected from Vlakplaas municipal treatment plant, unstable waste activated, partially digested and belt pressed sewage sludge, collected from

Olifantsfontein municipal treatment plant, and unstable activated, and anaerobically digested sludge from SASOL a petrochemical industry treatment plant. Sludges were applied at a rate corresponding to 10 tons ha

-1

on a dry mass basis, and incubated at 10, 25 and 45 ºC, and three levels of water potentials, -10, -100 and -1000 kPa. Treatments including a control were carried out in triplicate.

Extractable and exchangeable inorganic N-forms (NH

4

+

, NO

3

- plus NO

2

-

) were determined at six incubation times 0, 1, 7, 14, 28 and 56 days using the method of Bremner and Keeney (1966), followed by the steam distillation method of Mulvaney (1996). Mineralization rate constant and half life time were estimated based on the single first-order kinetics N

(t)

= N o

(1- e

–kt

) by Stanford and

Smith (1972). A general linear model procedure of the SAS statistical program was used to test for significance of differences between treatments

.

Soil temperature and water potential interactions as well as sludge stability, significantly influenced mineralization. Net N release increased with incubation time and temperature increase. Nitrification was inhibited at 10 ºC for both unstable sludges, and at 45 ºC for all sludges. However, nitrification was observed at both 10 ºC and 25 ºC for

Vlakplaas sludge and only at 25 ºC for Sasol sludge. Nitrification was negligible for Olifantsfontein sludge. On average, net N released was higher for unstable sludges. The high quantities of N released from unstable sludge were not a result of the higher mineralizable N potential, but rather as a result of the higher N content. Therefore they had higher N loading rates. Of the total N added 41

% and 36 % were mineralized from Sasol and Olifantsfontein sludges respectively, and 50 % from

Vlakplaas sludge. The Sasol sludge yielded a relatively high rate constant (0.093 week

-1

) and relatively shorter half life time (58 days) at 25 ºC compared to the approximated rate constants of

37

municipal sludges. The rate constant for Vlakplaas was 0.042 week

-1

(half life = 116 days) and

0.049 week

-1

(half life = 98 days) for Olifantsfontein.

Sludge-N mineralization rate will vary under uncontrolled field conditions, therefore further field validation of the sludge stability effect on N release is needed to regulate safe sewage sludge agricultural use.

Key words: Nitrogen, Sewage sludge, ammonium, nitrate, N mineralization, mineralization rate.

38

3.1 Introduction

Sewage sludge is a by-product from wastewater treatment plants, rich in organic matter and plant nutrients, which can be used as a soil amendment to enhance the physical, chemical and biological qualities of soils. Like other organic sources, sewage sludge can have positive influences on the properties of the amended soils, such as increased organic matter, nitrogen content, porosity, soil water holding capacity and biological soil quality (Navas et al., 1997; Lopez-Tercedo et al., 2005).

Sewage sludge contains organic forms of nitrogen, which undergo transformation, releasing inorganic N forms, i.e. ammonium (NH

4

+

) and nitrate (NO

3

-

) (Er, et al., 2004; Ashok, Paramasivam and Sajwan, 2006). Under favourable soil conditions (adequate microbial biomass, soil water) and favourable temperature for microbial activity the NH

4

+

form is converted rapidly into NO

3

-

. The availability of N in soils, as well as in sewage sludge amended soils, depends on the N-forms of the compounds present in the substrate and the rate at which inorganic N is released (Paul and Clark,

1988; Russel, 1988; Havlin, 2005). Therefore, knowledge of the dynamics and transformations of different N pools in the ecosystem is an important tool to assess soil N availability.

N mineralization and nitrification rate constants are important parameters in modelling soil N transformations (Smith et al., 1998 a,c). Predictive capability for N release and potential mineralizable N are essential in providing support for decision makers on land application rate and frequency, as well as helping in establishing irrigation intervals that reduce nitrate (NO

3

-

) losses from agricultural lands to surface and ground waters.

Sewage sludge stability is known to influence N release characteristics (Smith et al., 1998 a,b). The rate and extent of NO

3

release in sewage sludge amended soils was found to be dependent on sewage sludge type, soil temperature, soil water and quality as well as quantity of applied sewage sludge,

(Terry et al., 1981; Paul and Clark, 1988; Serna and Pomares, 1992; Hernandez et al., 2002; Wang et

al., 2003; De Neve et al., 2004; Zaman and Chang, 2004; Synman and Van der Waals, 2004;

Agehara and Warncke, 2005; Van Niekerk et al., 2005).

Several researchers have conducted incubation studies at field capacity, which is generally accepted as the optimum matrix potential for microbial activity (Thomsen et al., 1999; Thomsen et al., 2003).

39

Soils are of different textural classes, adjusting soil water to field capacity will not give a comparable situation like when using the concept of soil water potential, which may give an advantage to interpolate the N mineralization rate for different textured soils.

In this study, soil water potential and its interaction with temperature were of concern, because one of the objectives of the study was to find N mineralization and nitrification rates in sewage sludge amended soil that can be used in modeling the fate of N under different soil types and conditions.

A 56- day laboratory incubation study was conducted, as a factorial experiment with temperature as main factor and water potential secondary factor. Soil was amended with sewage sludge of different stability and incubated in a temperature controlled chamber at 10 ºC; in an incubation room at 25 ± 2

ºC and in a temperature controlled chamber at 45 ºC. Samples were extracted with a 1 molar potassium chloride solution and distilled with a micro-Kjeldahl system NH

4

+

and [NO

3

-

+ NO

2

-

] were then determined through titration with a 0.01M hydrochloric acid solution (HCl).

According to Doran and Smith (1987) microbial activity is maximal in a temperature range between

25 – 35 ºC. Therefore, high levels of nitrogen release were expected for treatment combination of 25

ºC and -10 kPa. At temperature below 20 ºC and over 40 ºC, lower nitrogen release rates were expected.

Sludge stability is expected to affect the N release rate, estimating higher values for unstable sludge, as the fast release pool of the stable sludge has been partly gone mineralization during the stabilization process in paddy drier beds.

40

3.2 Materials and methods

A laboratory incubation experiment was conducted at the Soil Science Laboratory of the University of Pretoria, using a red sandy clay loam soil collected from the Hatfield Experimental Farm

(University of Pretoria located at 25° 45‟ S and 28° 16‟ E).

3.2.1 Materials i) Sources of sludges

The sludges were collected from three waste-water treatment plants (WWTP), two are branches of the East Rand Water Care Company (ERWAT), a major waste-water care company in South Africa located near Kempton Park Pretoria, and the third was from a petrochemical company (SASOL) located near Secunda. Sasol sludge is not destined for agricultural use, however, it was include to compare the N release from a sludge that originated from the petrochemical industrial with the N release from municipal sludge.

i

1

) Vlakplaas WWTP- was a mixture of domestic and industrial wastewater sewage sludge that was anaerobically digested and paddy dried. This stable sewage sludge had an initial solid content of 50

%, and contained 1.93 % N.

i

2

) Olifantsfontein WWTP- was domestic wastewater sewage sludge that was activated, partially digested and belt pressed. The sewage sludge collected had an initial solids content of 18 %, and

5.33 % N on a dry mass basis.

i

3

) SASOL WWTP- was a petrochemical wastewater sludge that was activated, anaerobically digested. It was an unstable sludge, containing 9 % solids and had an N content of 7.91 %.

41

3.2.2 Methods i) Sludge characterization

Sludge samples were sent to the Agricultural Research Council (ARC) - Institute for Soil Climate and Water for analysis of some selected properties. The pH and inorganic N forms were analysed at the Soil Science Laboratory of the University of Pretoria. Table 3.1 shows some chemical characteristics. i- Total P and exchangeable bases – Acid-mixture digestion followed by colourimetric determinations ii- Total N determination - Kjeldahl digestion procedure iii- Total C was determined by means of Walkley and Black method iv- pH was determined potentiometrically, in a 1:2.5 sludge:water suspension v- Inorganic N forms (extractable and exchangeable NH

4

+

, NO

3

-

plus NO

2

-

), were determined by the Bremner and Keeney (1966) and Mulvaney (1996) methods

Table 3.1 Some chemical characteristics of the sludges used

Parameters analysed

pH

Total N (%)

Total C (%)

C : N

Total P (%)

Ca (%)

K (%)

Vlakplaas

6.3

1.93

11.6

6.0

2.43

1.58

0.11

Source of sludges

Olifantsfontein

6.7

5.33

29.9

5.6

3.97

3.32

0.45

SASOL

5.8

7.91

38.9

4.9

0.64

1.07

0.35

Na (%)

Mg (%)

NH

4

(%)

0.14

0.17

0.66

0.13

0.57

0.12

0.27

0.35

0.47

NO

3

(%) 0.24 0.01 0.01

Org N (%)* 1.03 5.2 7.43

*Org N calculated by difference: % Total N – Inorg N % (NH

4

+

+ NO

3

-

)

42

Although unstable Sasol and Olifantsfontein sludges contained more total N, their initially inorganic

N content was lower compared to the anaerobically digested and paddy dried Vlakplaas sludge. The lower values of inorganic N fraction of total N in unstable sludges is the consequence of limited mineralization that have taken place, and the high solubility of ammonium and nitrate in water and its loss during the dewatering stage. In the case of Vlakplaas, relatively high initial inorganic N was observed as more time had passed for organic N gets mineralized during the drying process.

The obtained values in percentage were then converted into mg kg

-1

, multiplying by 1000/100

to bring them to grams per kg and then multiplied by 1000 to express in mg per kg; i.e. total N

(1.93 *(1000/100)) *1000 = 19300

The principle of stechiometry shows that 1mol of either NH

4

or NO

3

gives 1 mol of N. Therefore, for convenience results were expressed in mmol per kg, as the molar basis makes easy and confident comparison among N specimens. Table 3.2 shows the distribution of total inorganic and organic N forms expressed in [mmol kg

-1

] of the sludge samples.

Table 3.2 Sludge N composition

Source of sludges

Vlakplaas*

Olifantsfontein**

Sasol**

Total N NH

4

+

1379 mmol kg

-1

367

NO

3

38.7

-

Org N

736

3807

5650

66.7

261

1.6

1.6

3714

5307

*stable sewage sludge, ** unstable sludges

Theoretically, the unstable sludges with high potentially mineralizable N, (98 - 94 %) of total N in organic form (Table 3.3) and with a C:N ratio less than 10 (4.9-5.6) indicating that their organic compounds are easily decomposable (Table 3.1), and expected to have higher N release than the

Vlakplaas sludge with 53 % of total N in organic form and a C/N ratio of 6.0. According to De Neve and Hofman (1996), Wolf and Snyder (2003) 20 is the critical C:N ratio for N mineralization for short-term incubations. Meaning that narrow ratio <20 would theoretically allow fast N release and a wide ratio >20 retard it.

43

Table 3.3 The percentage distribution of N-forms in the sludges.

Source of sludge

NH

4

+

NO

3

-

Org N

Vlakplaas*

%

26.6 28.0 53.4

Olifantsfontein**

Sasol**

1.75

4.62

0

0

97.6

93.9

*stable sewage sludge, ** unstable sludges

ii) Soil characterization

The soil sample was air-dried and passed through a 2 mm mesh sieve, then analyzed for selected soil physico-chemical properties shown in Table 3.4, using the following methods: i. Particle-size analysis was done using the hydrometer method, (Gee and Bauder, 1986) modified from Day (1965), which consists of measuring the density of a soil suspension based on settling speed of soil particles; ii. Water retention curve, was determined using the pressure plate extraction method (Dane and Hopmans, 1986); iii. Soil bulk density ρ b

is the mass per unit volume of soil, and was determined based on the

(Grossman and Reinsch, 2002) method; iv. EC and pH were determined potentiometrically, in a 1:2.5 soil : water suspension (The

Non – Affiliated Soil Analysis Work Committee, 1990); v. Available P was determined using the Bray I method (Bray and Kurtz, 1945) (The Non-

Affiliated Soil Analysis Work Committee, 1990);

44

vi. Exchangeable bases,

with the CH

3

COONH

4

- pH

7 extraction method, Ca, Mg, Na and K were determined with Inductively Coupled Plasma – Atomic Emission Spectroscopy

(ICP – AES) (The Non – Affiliated Soil Analysis Work Committee, 1990); vii.

Organic carbon (OC) was determined using the Walkley and Black method (The Non –

Affiliated Soil Analysis Work Committee, 1990); viii. Total N was determined by means of Kjeldahl digestion followed by colourimetric determination (Stevenson, 1996); ix. Inorganic N forms (extractable and exchangeable NH

4

+

, NO

3

-

and NO

2

-

), were determined by the Bremner and Keeney (1966) method, which consisted of a 1M KCl extraction followed by micro Kjeldahl steam distillation and titration with 0.01M HCl,

(Mulvaney, 1996) (The Non – Affiliated Soil Analysis Work Committee, 1990)

.

Table 3.4 Selected soil physical and chemical properties

Values Parameters Values Parameters

pH

analysed

EC (mS m

Clay (%)

Silt (%)

-1

)

5.80

analysed

P (mg kg

-1

)

0.12 Ca (mg kg

-1

)

30.0 Mg (mg kg

-1

)

19.2 Na (mg kg

-1

)

50.8 K (mg kg

-1

) Sand (%)

Total N (mg kg

-1

) 300 NH

4

(mg kg

-1

)

Org C (%) 0.85 NO

3

(mg kg

-1

)

34.4

940

270

8.00

75.0

8.64

52.3

45

3.2.3 Treatments

Sludge amended soils were incubated at three levels of temperature and three water potentials for a particular temperature, a schematic representations of treatments is given in Figure 3.1

Treatment selection was based on the established upper limits for sewage sludge land application in

South Africa (Snyman and Herselman, 2006), and also on the environmental soil conditions with marked influence in microbial activities, thus influencing nitrogen release (Doran and Smith, 1987;

Paul and Clark, 1988; Zaman and Chang, 2004; Leiros et al., 1999; Tan, 2000; Havlin, et al., 2005).

Samples were extracted and tested at six different incubation times (0, 1, 7, 14, 28 and 56 days).

Treatments were replicated three times. A control treatment was included for each temperature and water potential combination to enable calculation of released N from the sludge. For each sludge 273 samples were analysed for both nitrate and ammonium determination, therefore, in total 719 samples were incubated. Statistical analysis was done using a general linear model procedure of SAS statistical program, considering the incubation as a two factorial experiment.

Soil amended with sludge

T

1

T

2

T

3

W

1

W

2

W

1

W

2

W

W

1

2

W

3

W

3

Figure 3.1 Schematic representation of treatments

W

3

Where T stands for temperature: T

1

= 10 o

C, T

2

= 25 o

C, T

3

= 45 o

C and W stands for water potential:

W

1

= -10 kPa, W

2

= -100 kPa, W

3

= -1000 kPa. Samples were extracted after 0, 1, 7, 14, 28 and 56 days of incubation.

46

3.2.4 Procedure

3.2.4.1 Establishing water quantities corresponding to selected water potentials

The quantity of water corresponding to a particular water potential was established gravimetrically based on the water retention curve determination, using t he ceramic pressure plate extractor to obtain the relationship between the water content held in soil

(θm)

and matric potential (ψ m

)

(Dane and Hopmans,

1986). Rings were placed on the ceramic plate filled with soil, sufficient water was added to the plates to ensure conditions to approach saturation and left for 24. Afterwards the ceramic plate was taken to the extractor and adjusted to specific pressure left the time needed until no more water was extracted. The plate was then taken out and the content of the rings placed in containers of a know mass and weighed to obtain the wet sample mass (M ws

). The samples were then oven dried for 24 hours at 105 °C to obtain the mass of the soil (M ds

).

The percentage gravimetric water content was obtained based on equation 3 (referred below, under calculations step 4) , and was found to be 17.5, 12 and 10

% corresponding to water potentials of -10, -100 and -1000 kPa respectively.

3.2.4.2 Incubation

The amount of sludge added was equivalent to 10 ton ha

-1

on a dry mass basis (0.31g, 0.23g and

0.22g) for stable Vlakplaas, unstable Olifantsfontein and Sasol sludges respectively, were added and thoroughly mixed with 50 g of soil pre-incubated, for seven days, at room temperature (~25°C) and moistened with 50% of water corresponding to water potential of -10 kPa (4.25g), to stimulate microbial activity. After mixing the amended soil was weighed and while still on the scale water was added corresponding to 8.5g, 6.0g, and 5.0g to adjust water potentials equivalent to -10, -100, and -

1000 kPa respectively. The amended soil was then incubated at selected temperature for 56 days. An incubation chamber with temperature control was used to maintain the temperature of the low temperature treatment at 10 ºC. The 25 ºC treatment was done in an incubation room, while the high temperature treatment was subjected to a constant temperature of 45 ºC in a incubation chamber

Water potential and aeration were monitored as described below. After each incubation time (0, 1,

7, 14, 28 and 56 days), samples were extracted with a 1M KCl solution for extractable and exchangeable inorganic N determination (Bremner and Keeney, 1966).

47

3.2.4.3 Monitoring water potential and aeration

Samples incubated at 10 ºC and 25 ºC were opened and aerated using a small computer cooling fan for approximately 1 minute, every two days to ensure the aerobic condition needed for nitrification.

At the same time samples were weighed and water added to compensate for evaporation, in order o maintain conditions as close as possible to the water potential. This was again performed daily for the higher temperature treatment, however, it proved to be difficult to maintain the various water potentials at the high temperature treatment because the samples appeared to dry out quickly. It is more likely that conditions of alternating wetting and drying were simulated for the 45 ºC treatment rather than conditions of near water content.

48

3.2.5 Calculations

3.2.5.1 Mass of sludge used to amend the soil

The guidelines for sewage sludge application in South Africa established the upper limit application rate of 10 ton per ha per year. Therefore, to get the mass of sludge to be added to 50 g of soil used for incubation, the following calculations were made:

1 st

step – Soil bulk density (ρ b

), which is the mass of soil per unit volume, was estimated dividing a mass of oven-dried soil (m s

), by the volume occupied by that mass of soil (V t

)

ρ b = m s

/V t

(equation 1)

For a volume of 10 cm

3

the corresponding mass was 11.9 g, therefore the ρ b

was 1.19 g cm

-3

2 nd

step – Estimation of a mass of soil (M) corresponding to the area of 1 hectare, assuming a plough layer depth of 20 cm, and the previously estimated bulk density of 1.19 g cm

-3

.

M = V x ρ b

= A x d x ρ b

(equation 2)

M = 10 000 m

2

x 0.20 m x 1.19 x 10

3

kg m

-3

= 2.38 x 10

6

kg

Where A is the area in m

2

, and d is the ploughing depth

3 rd

step – The mass of sludge needed to apply to 50 g of soil (M s

) is given by:

M s

= 1 x 10

4

kg x (5 x 10

-2

kg / 2.38 x 10

6

kg) = 2.1 x 10

-4

kg

To achieve an equivalent sludge loading rate of 10 ton ha

-1

, in dry mass basis, 0.21 g of dried sludge was required to amend the 50 g of soil.

Considering that the (M s

) refers to the dry mass basis of sludge and since the collected samples were not completely dry as oven drying sludge is not recommended (N loss may occur), therefore a moisture correction factor was required to obtain the air dried sludge mass to be added (M add

).

49

4 th

step To obtain the moisture correction factor it was necessary to determine the moisture content. The thermo-gravimetric method based on convective oven drying at 105 o

C (Topp and

Ferré, 2002) was used to assess the water content for air dried stable sludge and for the unstable sludges previously dried at 70 o

C. Percentage of water was given by the equation:

% water = [(m bod

- m od

) /m bod

] x 100

(equation 3)

Where, m bod

stands for mass of sludge before oven drying and m od

is the oven dried mass of sludge.

Taking the air dried stable sludge as an example, the percentage moisture was 32.1 % based on values presented in Table 3.5.

Table 3.5 Stable Vlakplaas sludge moisture content

Mass m

sbod

m

sod

Replicates mass [g]

5.00 5.09 5.03

3.36 3.39 3.50

Mean % moisture

5.04

3.42 32.1

% moisture = (5.04 - 3.42)/5.04 x 100 = 32.1 %

The stable sewage sludge had a moisture content of 32.1 % meaning that 67.9 % of the wet sample was dry sludge. Therefore the moisture correction factor (f) was 100/67.9 = 1.47

Finally the mass of air dried sludge to be added (M add

) was given by the following equation:

M add

= M

Ss

x f (equation 4)

M add

= 0.21 x 1.47 = 0.31 g

50

3.2.5.2 Extractable and exchangeable NH

4

+

and NO

3

- plus NO

2

- determinations

The NH

4

+

and NO

3

-

+ NO

2

- contents in sludge amended soils were determined after each incubation period using Bremner and Keeney (1966) for extraction and Mulvaney‟s (1996) method for distillation, as described in Sparks (1996). An aliquot of 50 ml from the 100 mL extract was mixed with 20 mL of a 12.5 M NaOH solution, which creates conditions for NH

4

+

conversion into NH

3

, by means of pH increase to above 9.2.

NH

4

+

+ OH

-

NH

4

OH NH

3

+ H

2

O (equation 5)

The NH

3

formed volatilized during distillation and was collected in a mixture of boric acid and methyl red plus methyl blue indicators which change colour at a specific pH, forming a green coloured complex (alkaline pH) and purple to slight rose at acid pH

NH

3

+ H

3

BO

3

/ indicator NH

4

H

2

BO

3

(equation 6)

(Purple) pH < 4.4 (Green) pH > 6.2

The collected distilled solution was titrated with a 0.01 M HCl solution, and the volume recorded was used for calculations, to obtain the amount of NH

4

+

in the sludge amended soil, based on the neutralization principles.

NH

4

H

2

BO

3

-

+ HCl NH

4

Cl + H

3

BO

3

(equation 7)

(Green) (Purple)

A reducing agent, Devarda‟s alloy powder, was added to remaining extract in the distil tube after cooling, to convert NO

3

-

+ NO

2

- to NH

4

+

, which in turn, was taken back for distillation to convert

NH

4

+ into NH

3 in presence of the alkali in excess (see equation 5). The process was repeated the same way as described above. The volume of acid used was recorded for calculations, to obtain the amount of NH

4

+

equivalent to the amount of NO

3

-

+ NO

2

-

in the sludge amended soil, because it is an equimolar displacement reaction. Both NH

4

+

and (NO

3

-

+ NO

2

-

) amounts were obtained using the following equation:

51

NH

4

+

[m mol kg

-1

] = (V acid

x C acid

)/ 1000 x (V extract

/v aliquot

) x 1000/m

(amended soil)

x 1000 (equation 8)

Where V extract

is the volume of extracting solution, v aliquot

is the aliquot taken for digestion, C acid

is the concentration of the acid, V acid

is the volume of the acid used in titration for complete displacement of ammonium and m

(amended soil)

the mass of the soil plus sludge added. The first 1000 is for volume conversion from L to ml, and the second 1000 for mass conversion from g to kg, and the third 1000 is for converting mol to mmol.

3.2.5.3 Net N release from the sludge

The term net N release in this study encompasses all forms of inorganic N released from the sludge during incubation processes, plus the initial inorganic N content in the sludge, which are measured in a 1 M KCl extraction solution. The individual values of extractable and exchangeable inorganic N forms (NH

4

+

and NO

3

-

plus NO

2

-

,) were calculated based on equation 8. Therefore, net N release was calculated as the difference between extractable and exchangeable NH

4

+

and NO

3

-

plus NO

2

obtained in sludge amended soil and in the soil without any sludge (control) equation 9.

Net inorg N released = sludge N amended soil – control N released (equation 9)

Net inorganic N released = [NH

4

+

+ (NO

3

-

+ NO

2

-

)] amended soil

- [NH

4

+

+ (NO

3

-

+ NO

2

-

)] control

3.2.5.4 Potentially available N

This is a very important parameter in soil fertility studies for efficient use of N and for good environmental management. The potentially available N from sludge amended soil expressed in percentage can easily be calculated as follows:

Potentially available N = (Net inorganic N released) / Tot N added) *100 (equation 10)

Where Potentially available N is the inorganic N, Net inorganic N released is the initial inorganic

N added through sludge application plus net N mineralized during incubation, and Tot N added is the amount of total N present in the added sewage sludge.

52

3.2.5.5 Organic N mineralized or potential mineralizable N

Part of organic N was mineralized during incubation period, and was calculated by difference between total Org N and organic N present at time t. The potential mineralizable N was expressed in percentage basis and was calculated using equation 11. However, potential organic N was underestimated as a result of overestimation of Org N t

(having other inorganic N-forms, which were not captured).

Org N mineralized = Total Org N - Org N t

Potential mineralized N = Org N mineralized/ Total org N added)]* 100 (equation 11)

3.2.5.6 Partial N mass balance

An assessment of the N mass balance was important for this study, because it gives an insight into the fate of the different N-forms during the incubation process. Sludge N was reported on a % dry mass basis (Table 3.1), and therefore, it had to be converted into [mg kg

-1

] or [mmol kg

-1

]. For

convenience it is expressed in mmol per kg, as the molar basis makes easy and confident

comparison among N specimens. The mass balance linking different N-forms in sludge amended soils is presented in Table 3.14 for stable sludge, Table 3.15 for unstable Olifantsfontein and Table

3.16 for unstable Sasol sludge.

An example for calculations is shown below, taking the stable Vlakplaas sludge, which contained

0.66 % NH

4

+

and 0.24 % NO

3

-

+ NO

2

-

, in dry mass basis.

i) Amount of NH

4

+

contained in the mass of sludge used for incubation

Based on the percentage NH

4

+

in the stable sludge (0.66 %), the amount of NH

4

+

in the mass of sludge used for incubation was:

NH

4

+

= ((0.66 x 0.21g)/ 100) x 1000 = 1.386 mg / 18 = 0.08 mmol

Where, multiplying with a 1000 was to convert grams to milligrams, and to express the amount of

NH

4

+ in mmol results should be divided by the molar mass of NH

4

(1mmol is equal to 18 mg).

53

ii) Amount of NO

3

-

contained in the mass of sludge used for incubation

From Table 3.1, the NO

3

- in the stable sludge was (0.24 %), therefore, the amount of NO

3

-

in the mass of sludge used for incubation was:

NO

3

-

= (0.24 x 0.21g / 100) x 1000 = 0.504 mg /62 = 0.008 mmol

Where, 1000 is to convert grams into milligrams, and to express the amount of NO

3

- in mmol results should be divided by the molar mass of NO

3

For the other N-forms (Tot N and Org N), calculations were based on the same principle used in i) and ii) using the molar mass of N (14). However, results from these calculations, shown in Table 3.6, correspond to the N added to 50 g of soil. Therefore, conversion to a kg of soil was needed, to ensure uniformity of units with those of the net N, NO

3

-

and NH

4

+

released during incubation period.

Table 3.6 Sludge N-forms contained in 50g of soil amended

Sludge source

Vlakplaas

Olifantsfontein

Sasol

* Dry mass basis

Mass of sludge

added (g)

0.21*

0.21*

0.21*

NH

4

+

0.08

0.01

0.05

(mmol / 50 g soil)

NO

3

-

Org- N Tot N

0.01

0.00

0.15

0.78

0.29

0.80

0.00 1.11 1.19

iii)

Amounts of sludge N- forms contained in a kg of soil amended

The amounts of sludge N-forms present in 1kg of soil amended were deduced from Table 3.6 multiplying by a factor of 20 coming from 1000g/50g, and are presented in Table 3.7.

Note: Considering that the 10t per ha are applied to a total mass of soil corresponding to a

volume of soil given by an area of 1ha and a ploughing depth of 0.20 m, therefore the amount

of sludge-N forms should be referred to a 1kg of soil, as shown in Table 3.7.

54

Table 3.7 Equivalent amounts of N-forms contained in 1kg of soil amended

Sludge source

Vlakplaas

Olifantsfontein

Sasol mmol kg

-1

soil

Tot N NH

4

5.80 1.60

+

NO

3

-

0.20

Org- N

3.00

16.0

23.8

0.20

1.00

0.00

0.00

15.6

22.2

These amounts initially present in the sludge amended soil before incubation took place, were jointly used with the calculated amounts of net N released during incubation period to obtain the partial N mass balance after 56 day incubation.

3.2.5.7 Mineralization rate constant

Mineralization rate constant and half life time are important parameters required in modelling for predicting N fate in soil systems that are obtained from N mineralization kinetics.

Based on literature it was also assumed that first order kinetics model by Stanford and Smith, (1972) will be the best approach to determine rate constants for N mineralization (Benbi and Richter, 2002;

De Neve et al., 2004). Where data obtained from the incubation study was used to draw a graph based on natural logarithm (ln N/N o

) versus incubation time, and the slope gives an estimated mineralization rate constant (k).

N

(t)

= N o

(1- e

–kt

) (equation 12)

Where N

(t)

is the net N mineralized at time t; N o

the potentially mineralizable N; k is the mineralization rate constant and t the incubation time.

Derivation of equation 12

Nitrogen at instant t (N t

) was modeled assuming that the rate of mineralization was constant (k) i) dN

(t)

/dt = k, proportional to the remaining sludge mineralizable N, which is the difference

between potentially mineralizable N (N o

) and the cumulative already mineralized N at time t

(N

(t)

)

55

ii) dN

(t)

/dt = k (N o

- N

(t)

), not accounting for the initial N or assuming that N content is zero at the beginning of incubation the solution for equation i) is given by N

(t)

= kt.

Therefore the solution for equation ii) become N

(t)

= N o

(1-e

-kt

)

Derivation of k from equation 12

The rate constant is calculated as follows, or by plotting a ln N/N o

graph versus time the slope represents k:

N

(t)

= N o

(1- e

–kt

)

N t

/N o

=1 - e

-kt e

-kt

= 1- N t

/ N o

- kt = ln(1 – N t

/N o

)

-kt = ln (1) – ln (N t

/N o

) ; ln (1) = 0

-kt = - ln (N t

/N o

) ; k = ln (N t

/N o

)/ t equation 13

Considering the fact that the first flush of N mineralization on disturbed samples, during the initial two weeks of incubation, is an experimental artefact which results from a drying and rewetting of soil samples. Therefore, the inorganic N measured is not part of true potentially mineralizable N

(Nο) of the substrate and should be modelled separately through the double first order model, by

(Molina et al., 1980) to account for the initial flush of N mineralization.

N min

= N

1

(1- e

– k

1 t

) + N

2

(1- e

–k

2 t

) (equation 14)

N

1

represents the fast cycling pool of mineralizable N and k

1

the rate constant for this pool; N

2 represents the slow mineralizable N pool and k

2

the corresponding rate constant.

Theoretically it is assumed that these pools are of definite sizes that should not change with environmental conditions or with procedures used to fit the models to data (Cabrera et al., 2005).

Based on Smith et al. (1998c) findings potentially mineralizable N was also estimated at 26 % of total applied N for the fast cycling pool (N

1

) and 42 % of total applied N for the slow release pool

(N

2

).

56

3.2.5.8 Half life time

The half-life time for a given exponential decay process indicates how long it would take for 50% of initial amount added to decompose: Y t

= Y

0

/ 2

The value of t that satisfies the above equation is the half life time and is given by: t

1/2

= ln (2)/k equation 15

57

3.3 Results and discussion

The amounts of NH

4

+

, NO

3

-

and net N release during incubation are reflected in Figures 3.3, 3.4 and

3.5, illustrating how N mineralization was affected by incubation time, temperature, water potential and sludge stability. Talking on net N release one should expect the graphs of net inorganic N release starting from zero at day zero (as initial stage of the incubation), however, considering the aspect of sludge nitrogen availability for crops, they start from a value representing the inorganic N already present in the sludge.

3.3.1 Net inorganic N released after a 56-day incubation

Figure 3.2 (a) reflects net N mineralized and 3.2 (b) net N released, that is N liberated as a result of the mineralization of Organic N as well as inorganic N released from the sludge. As discussed previously net N mineralized is important in modelling N mineralization, however, net N release is also important from both a soil fertility and environment management point of view, because sludge can contain appreciable amounts of inorganic N depending on the stabilisation process it underwent.

a

12

11

10

9

8

7

6

5

4

3

2

1

0

b

12

11

10

9

8

7

4

3

6

5

0

-1

2

1

0 7 14 21 28 35 42 49 56

0 7 14 21 28 35 42 49 56

Incubation time [days]

Vlkp Olif Sas

Incubation time [days]

Vlak Olif Sas

Figure 3.2 Net N mineralized (a) compared to net N released (Mineralization plus N released) from sludges at

25 o

C

and -10kPa

58

Vlakplaas sludge that was anaerobically digested and then paddy dried for an extended time had much higher NH

4

+

and NO

3

-

levels (366.7 mmol kg

-1 and 38.7 mmol kg

-1

) respectively, than sludge perceived to be less stable. The Olifantsfontein sludge, for example, which was unstable activated partially digested and belt pressed containing 66.7 mmol kg

-1

NH

4

+

and 1.6 mmol kg

-1

NO

3

-

(Table

3.2). The data suggests that at an equivalent loading rate of 10 ton ha

-1 sludge addition elevated inorganic N levels in the soil between 2 and 5.7 mmol kg

-1

(Figure 3.2 b). It was expected that the amendment with Vlakplaas sludge will result in the highest initial N levels, however, the data does not reflect this. The reason might have been that KCl extraction have extracted also de dissolved organic N that was much higher for Olifantsfontein having 3714 mmol kg

-1 of organic N while

Vlakplaas had only 735.7 mmol kg

-1

. The availability of N is closely linked to dissolved organic C, which is easily extracted with salt extractant (Silveira, 2005; Dijkstra et al., 2007). This is also the reason why estimated initial inorganic and organic N values differ from the determined values at time T

0

.

The net N mineralization was significantly affected by the interaction between temperature and water potential. Sludge N mineralization increased with temperature, and highest net N release was observed at 45 ºC. This was also true for Zaman and Chang (2004), who reported greater N mineralization at 45 ºC and soil moisture around field capacity than at 25 ºC and 5 ºC.

These results contradict the optimum temperature range for mineralization (25 ºC – 35 ºC) stated by Doran and

Smith (1987), in Figure 2.3. In this study 25 ºC was optimum temperature range for nitrification.

However, these results are in agreement with Quemada and Cabrera (1997), who found the effect of optimal soil water content enhanced with temperature increase. Tajeda et al. (2002) also found that

N mineralization was higher at 25 o

C than 15 o

C, and that increasing temperature boosted mineralization as well as N losses which can exceed 50 %.

Figures 3.3, 3.4 and 3.5 show N release from Vlakplaas, Olifantsfontein and Sasol sludges, respectively. When comparing them net N release had different trends during the initial stage of incubation. The negative period illustrated in Figure 3.4 and Figure 3.5 was a direct result of the initial low inorganic N content of less stable sludge. For example, the unstable Olifantsfontein sludge contained 2 % inorganic and easily metabolizable N, while stable sludge contained 54 % of

59

available inorganic N. Therefore, in order to mineralize the unstable sludge, microorganisms had to metabolize easily available inorganic N from the soil and that of the sludge as source of energy.

These results are similar to findings of Wang‟s et al., (2003) that mineralization of organic N in soils amended with bioslids was strongly influenced by its quality and temperature. Probert et al. (2005) also observed that at the initial stage of incorporation of organic sources, inorganic N was immobilized even with substrates having C:N ratios less than 20.

3.3.2 Vlakplaas amended soil: Effects of temperature and water potential on the mineralization process

From Figure 3.3 the effect of incubation time, soil temperature and water content on net N release from stable sewage sludge amended soil were evident. The amount of NH

4

+

increased for the first 24 hours of incubation followed by a sharp decrease during the first week for T

1

, afterward the decrease was more gradual. This initial increase in the amount of NH

4

+

might have been due to boosting of microbial activity and subsequent ammonification, following moistening of sludge amended samples. At T

2, mineralization was insignificant, only nitrification was observed. At high temperature (45 o

C), the amount of NH

4

+

had increased sharply in the first day of incubation, and then an irregular increasing trend was observed. Negligible amounts of NO

3

-

were formed indicating that nitrification was inhibited or the nitrate formed was lost. As a result net released N was mainly in ammonium form.

Meanwhile NO

3

- levels increased along the incubation period, as a result of nitrifying bacteria activity. This occurred for all treatment combinations involving T

1

and T

2

. However, the trend was different for treatment combinations involving T

3

. In which NH

4

+

had increased and no nitrate was formed. The reason is that high temperatures increase mineralization but are unfavorable to nitrifying bacteria.

Results from previous research found that nitrifying bacteria are more sensitive to extreme temperature and moisture conditions than ammonifiers (Sierra et al., 2001; Zaman and Chang,

60

2004). Another suggestion is that the little NO

3

-

which may be formed might have been denitrified and lost by the time samples were aerated and/or the microbe biomass might have assimilated nitrate and nitrite under anaerobic warm conditions (Brady and Weil, 2002).

At 10 o

C both inorganic N forms (NH

4

+

and NO

3

-

) coexisted up to the end of incubation however, at

25 o

C, NH

4

+

was converted to NO

3

-

after 28 days of incubation complete conversion of NH

4

+

was observed. The optimum nitrifying conditions is shown by the complete conversion of NH

4

+

to NO

3

-

.

Ashok et al. (2006) found a sharp increase of NH

4

+

for the first fifteen days of incubation at 25 o

C, followed by a sharp decline indicating rapid transformation into nitrate-N.

Smith and Tibbett (2004) found an increase in NH

4

+

and decrease in NO

3

-

and no net nitrate accumulation, this contradicts with Smith et al., (1998a) results which reported net NO

3

accumulation in soils amended with undigested biolsolids at 25 o

C and soil water content at 40 %

FC, however, immobilization of inorganic N was significant during the initial stage of incubation.

61

a

1

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

0 7 14 21 28 35 42 49 56

Incubation time [days]

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

a

2

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

a

3

NH4

NO3

Total Nreleased

b

1 b

2 b

3

2

1.5

1

0.5

0

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

4.5

4

3.5

3

2.5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

c

1 c

2 c

3

4.5

3.5

2.5

1.5

0.5

-0.5

0 7 14 21 28 35 42 49 56

4.5

3.5

2.5

1.5

0.5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

-0.5

-0.5

0 7 14 21 28 35 42 49 56

0 7 14 21 28 35 42 49 56

Figure 3.3 Net N released, NH

4

+

and NO

3

-

from Vlakplaas sludge during a 56-day laboratory incubation at a temperature and water potential treatments given by letters: a

1

= T

1

W

1

, a

2

= T

1

W

2

,

a

3

= T

1

W

3

; b

1

= T

2

W

1

, b

2

= T

2

W

2

, b

3

= T

2

W

3

; c

1

= T

3

W

1

, c

2

= T

3

W

2

, and c

3

= T

3

W

3

62

Based on the ANOVA tables (Appendix A.

3

), it seems that at 25 o

C the rate of mineralization decreased to the point where it is approaching zero at the end of the 56 day incubation. Significant difference among incubation times were observed at T

2

for nitrification except day 28 and day-56. In general ammonium levels decreased with incubation time and nitrate increased with incubation time except at T

3

. The effect of incubation time at T

3

was higher for day 14, lower for day1.

The effect of temperature, water potential and their interactions were statistically significant

(Appendix A.

2.1

). Although, every single factor was statistically significant, only interaction effects are discussed as defined in statistics rule.

Levels of significance are presented in (Table 3.8), and there were no significant differences in net N released between the high temperature treatments. The

T

2

W

1 treatment was statistically separated from T

2

W

2

and T

2

W

3

While the T

1

treatments were all statistically different from each other. Differences for the majority of treatments were highly significant, except T

1

W

3

which shows no significant differences with treatments involving T

3

. The effect of T

1

W

1

treatment on net N release was not statistically different from that of T

2

W

1

(p > 0.05), however, it was significantly different with T

2

W

2 treatment (p < 0.05) and it had highly significant difference with the other treatments T

1

W

2,

T

1

W

3,

T

2

W

3

, T

3

W

1,

T

3

W

2,

and T

3

W

3

(p < 0.01).

Table 3.8 Levels of significance between temperature and water potential interaction on N mineralization from Vlakplaas sludge amended soil after a 56- day laboratory incubation.

T

1

W

1

T

1

W

2

T

1

W

3

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

1

W

2

T

1

W

3

<.0001**

0.0006** <.0001**

T

2

W

1

0.3809ns <.0001** 0.0041**

T

2

W

2

T

2

W

3

0.0449*

0.0019**

0.0067**

0.1319ns

<.0001** 0.0068**

<.0001** 0.0003** 0.1556ns

T

3

W

1

T

3

W

2

T

3

W

3

0.0031**

0.0016**

<.0001**

<.0001**

<.0001**

<.0001**

0.4476ns

0.6348ns

0.3455ns

0.0219*

0.0118*

<.0001** <.0001**

<.0001** <.0001** 0.7727ns

0.0005** <.0001** <.0001** 0.0980ns 0.1638ns

ns = not significant

(p > 0.05)

;* Significant at α= 5% (p < 0.05); **Highly significant at α= 1% (p < 0.01)

63

At low temperature it seems that water potential significantly influenced net N release, but did not show a consistent trend. At the high temperature treatment changes in water potential had no statistical significant effect on the amount of N released, this can be attributed to the difficulty of maintaining the treatment at the specific water potentials.

The effect of high temperature (45

o

C) was superior for NH

4

+ formation and negatively influenced

NO

3

-

formation (Table 3.9). Net N released increased with temperature (it was 2.77 at T

1

W

1

< 2.90 at

T

2

W

1

< 3.25 at T

3

W

1

). The expected trend that net in released will increase as water potentials approach field capacity was only observed for T

2

: 2.90 for T

2

W

1,

2.46 for T

2

W

2

, and 2.25 for T

2

W

3

.

The high temperature treatment showed an opposite trend that was the more negative the water potential the higher the observed N released, however the differences were not statistically significant. This could have been an experimental artifact sprouting from the difficulty to maintain the water content constant during the course of the incubation for this specific temperature treatment

(45

o

C). Dependency of N release on water potential was significant at 10

o

C treatment.

The effect of treatments with 25

o

C was superior for nitrification. In general, nitrifying bacteria were less active at 45

o

C and more active at 25

o

C whilst ammonifying bacteria, on the other hand, were less active at 25

o

C and more active at 45

o

C. The balance between the proportion of ammonifying and nitrifying bacteria is temperature dependent (Brady and Weil, 2002). Meaning that both ammonifying and nitrifying bacteria can operate concurrently, whenever, the environmental conditions are favorable. However, if the environmental conditions favor one type of bacteria is then when this unbalance on their activity is seen.

Nitrate levels at 10 o

C were comparable with those at 25

o

C, the reason is that at low temperature, if there is a good aeration, nitrifying bacteria might find favorable conditions (oxygen) required for nitrification.

64

Table 3.9 Ranking and treatment mean comparison of NH

4

+

, NO

3

and net N released, for the

Vlakplaas sludge amended soil after 56-days of laboratory incubation.

Treatment NH

4

+

Treatment NO

3

-

Treatment Net N released

T

3

W

3

T

3

W

2

T

3

W

1

T

1

W

3

T

1

W

2

T

1

W

1

T

2

W

3

T

2

W

1

T

2

W

2

3.28

(0.04)

3.13

(0.34)

3.05

0.70

(0.12)

CD

0.11

0.07

0.03

(0.06)

0.60

(0.05)

(0.00)

(0.00)

(0.00)

0. 80

(0.02)

A

AB

B

D

E

E

E

C

T

T

T

2

1

W

2

W

W

3

1

2

T

2

W

3

T

1

W

1

T

1

W

2

T

3

W

3

T

3

W

1

T

3

W

2

[mmol kg

-1

]

2.99

(0.07)

A

2.93

(0.07)

A

2.63

(0.02)

B

2.60

(0.04)

BC

2.52

(0.10)

C

1.99

(0.06)

D

0.22

(0.04)

E

0.20

(0.12)

E

0.16

(0.02)

E

T

T

T

T

3

1

3

1

W

3

W

3

W

W

2

T

3

W

1

T

2

W

1

T

1

W

1

T

2

W

2

T

2

W

3

2

3.50

3.36

2.77

2.03

(0.17)

0.12)

3.29

(0.40)

AB

3.25

(0.07)

2.90

(0.04)

(0.13)

2.46

(0.04)

2.25

(0.04)

(0.07)

A

AB

B

C

C

D

D

F

Treatments means in column followed by the same letter are not statistically different at α = 5%; LSD for

NH

4

+

= 0.15; LSD for NO

3

-

= 0.08 and LSD for Net N released = 0.21; Figures in brackets denote standard errors.

3.3.3 Olifantsfontein amended soil: Effects of temperature and water potential on the mineralization process

In general net N mineralization had a similar trend for all water potentials and temperatures; mineralized N was mainly in ammonium form, with little differences in treatments involving T

2

.

After two weeks of incubation a decrease in NH

4

+

and consequent increase in NO

3

-

was observed

(Figure 3.4). However, the trend of temperature and water potential effect for Olifantsfontein sludge did differ from the Vlakplaas sludge.

The initial inorganic nitrogen decrease observed after one day of incubation, could be due to microbial flush following sludge application (N negative period). The Vlakplaas sludge treatment did not show this, a possible reason for this could be the high initial inorganic N content. The

Olifantsfontein sludge, for example, contained 1.67 % of inorganic N, compared to 55 % for the

65

Vlakplaas sludge (Table 3.3). It seems that enough easily available N was applied with the Vlakplaas amendment to meet the immediate microbial metabolism demands. However, in the case of

Olifantsfontein amended treatment microorganisms were forced to assimilate inorganic N present in the soil and that from the sludge to meet their metabolic demands. Therefore the chance for N immobilization was higher for the less stable sludge, and the same was seen for the Sasol amendment having 4.6% of initial inorganic N.

General trend, during incubation for both NH

4

+

and NO

3

-

was the decrease in the initial stage of incubation, followed by a sharp increase in NH

4

+

for the following two weeks then a gradual increase was observed up to the end of incubation at week eight.

A negligible amount of nitrate was formed during the incubation process, except for treatments with

T

2

(25 o

C), where, starting from week two, nitrate formation was observed (Figure 3.4 b

1

, b

2

and b

3

).

These treatments also showed after the second week of incubation, a slightly decrease in NH

4

+

.

Treatment T

3

W

1

(Figure 3.4 c

1

) shows a decrease in NH

4

+ after one day of incubation followed by a sharp increase until week two. Then continued to increase, however, at a slower rate, until week four and decreased for the last four weeks of incubation. With a decrease in NH

4

+ an increase in NO

3

- was expected, however, this did not happen, apparently losses of ammonium might have occurred through volatilization of ammonia (NH

3

) or denitrification (N

2

O losses).

The absence of nitrification in all treatment with T

1

and T

3

might have been because of the NH

4

+ toxicity to nitrifiers. Although NH

4

+

is required for nitrification, however, when is excessive becomes toxic to nitrobacter, and reduces their activity (Brady and Weil, 2002). On average the amount of NH

4

+

was 109 mg kg

-1

for T

1 and 187 mg kg

-1

for T

3

, however, the amount of NH

4

+

in the treatments was far below the 400 mg kg

-1 considered the maximum concentration nitrifiers can tolerate (McIntosh and Frederick, 1958).

Another reason that may have caused this lack of nitrifications could be that nitrifying bacteria are less competitive than the heterotrophic ammonifying bacteria (Verhagen et al., 1992).

Greater mineralization was observed at 45 o

C and increased with water potential decrease (7.44;

9.19; 10.5 mmol kg

-1 for Figure 3.4 c

1

c

2

and c

3

) respectively. Nonetheless, greater nitrification was

66

observed at 25 o

C and decreased with water potential decrease (1.23; 0.44; 0.78 mmol kg

-1 for Figure

3.4 b

1

b

2

and b

3

) respectively. At 10

o

C the net N release increased as soil moisture changed from high negative to low negative water potential (T

1

W

1

> T

1

W

2

> T

1

W

3

). Sierra et al. (2001) found that nitrifying bacteria was more sensitive to changes in water potential than ammonifying bacteria. This supports the results found for stable sewage sludge amended soils where nitrification process was highly temperature dependent.

Theoretically the optimum temperature and water potential combination for mineralization was expected to be T

2

W

1

, as illustrated in Figure 2.2 and Figure 2.3 (Doran and Smith, 1987). However, in this experiment this combination appeared to be optimum only for nitrification. Zaman and Chang

(2004) found that the effect of soil moisture on mineralization was enhanced at lower temperature and the effect of soil moisture on mineralization was masked at higher temperature.

67

a

1

7

6

5

4

3

2

1

0

-1 0 7 14 21 28 35 42 49 56

1

0

-1

3

2

7

6

5

4

a

2

7

6

5

4

3

2

1

-1

0

a

3

Incubation time [days]

NH4

Total Nreleased

NO3

b

1 b

2 b

3

6

5

4

3

2

1

-1

0

8

7

2

1

0

-1

5

4

3

8

7

6

-1

1

0

3

2

4

8

7

6

5

c

1 c

2 c

3

6

5

4

3

2

1

0

-1

11

10

9

8

7

6

5

4

3

0

-1

2

1

11

10

9

8

7

6

5

4

3

0

-1

2

1

11

10

9

8

7

0 7 14 21 28 35 42 49 56

0 7 14 21 28 35 42 49 56

Figure 3.4 Net N released, NH

4

+

and NO

3

0 7 14 21 28 35 42 49 56

-

from Olifantsfontein sludge during a 56-day laboratory incubation at a temperature and water potential treatments given by letters: a

1

= T

1

W

1

, a

2

= T

1

W

2

,

a

3

= T

1

W

3

; b

1

= T

2

W

1

, b

2

= T

2

W

2

, b

3

= T

2

W

3

; c

1

= T

3

W

1

, c

2

= T

3

W

2

, and c

3

= T

3

W

3

68

The ANOVA tables (Appendix A.

2.2

) shows that temperature, soil water potential and their interactions affected significantly the net N release from Olifantsfontein sludge amended soil.

Therefore, only pre-planned interactions were discussed at significance level of 5 % (Table 3.10). In general the higher N release observed for the T

3

treatments where significantly different from that observed from medium and low temperature treatments. The exception was observed for T

2

W

3

and

T

3

W

1 which could not be statistically separated. The treatments involving low temperature and medium temperatures could not be statistically separated.

Table 3.10 Levels of significance between temperature and water potential interaction on N mineralization from Olifantsfontein sludge amended soil after a 56-day laboratory incubation

T

1

W

1

T

1

W

2

T

1

W

3

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

3

W

3

T

1

W

2

T

1

W

3

T

2

W

1

T

2

W

2

0.1706 ns

0.0367*

0.0503 ns

0.0878 ns

0.4178 ns

0.5110 ns

0.7100 ns

0.0004 ** <.0001 **

0.0001 ** <.0001 **

<.0001 ** <.0001**

0.8756 ns

0.6569 ns

<.0001**

<.0001**

<.0001**

0.7730ns

<.0001** <.0001**

<.0001** <.0001** 0.6434ns

<.0001** <.0001** <.0001** <.0001**

<.0001 ** <.0001 ** <.0001 ** <.0001** <.0001** <.0001** <.0001** <.0001**

ns = Not significant (p > 0.05);* Significant at α=5% (p < 0.05); ** Highly significant α=1% (p < 0.01)

The means of all treatments were ordered from the higher to lower value, (Table 3.11). Among treatments lower value of net N release was observed at 10 o

C for the interaction T

1

W

3

(5.72 mmol kg

-1

) and the highest value of net N released was found at 45 o

C for T

3

W

3

(10.5 mmol kg

-1

), at 25 o

C for T

2

W

3 net N released was (7.33 mmol kg

-1

). This scenario agrees with the theory that increased temperature leads to an increase in mineralization of organic material. Tajeda et al. (2002) also found that N mineralization was more extensive at 25 o

C than 15 o

C and that increasing temperature boosted mineralization as well as N losses. However, the lowest values of nitrification were

69

observed at 45 o

C and 10 o

C, the highest at 25 o

C, for example T

1

W

1

(0.24 mmol kg

-1

), T

2

W

1

(1.23 mmol kg

-1

) and T

3

W

1

(0.19 mmol kg

-1

). Under 25 o

C nitrification increased with increase in water potential T

2

W

1

(1.23 mmol kg

-1

), T

2

W

2

(0.78 mmol kg

-1

) and T

2

W

3

(0.44 mmol kg

-1

). Sierra et al.

(2001) found that nitrifiers were more sensitive to changes in water potential than ammonifiers.

Table 3.11 Ranking and mean comparison of NH

4

+

, NO

3

and net N released, for the unstable

Olifantsfontein sludge amended soil after 56-days of laboratory incubation

Treatment NH

4

+

Treatment NO

3

-

Treatment Net N released

[mmol kg

-1

]

T

3

W

T

3

W

2

T

T

T

T

3

2

1

1

W

W

W

W

3

1

3

1

2

T

1

W

3

T

2

W

2

T

2

W

1

10.4

(0.45)

A

9.03

(0.30)

B

7.25

(0.22)

C

6.55

(0.08)

D

6.03

(0.18)

E

5.78

(0.02)

E

5.44

5.39

4.52

(0.05)

(0.02)

(0.51)

F

F

G

T

T

T

T

T

T

T

T

T

2

W

2

W

3

2

W

1

W

1

W

3

W

3

W

3

W

1

W

1

2

3

1

1

2

3

2

1.23

0.78

0.12

(0.06)

(0.06)

0.44

(0.05)

0.28

(0.06)

0.24

(0.05)

0.16

(0.02)

0.12

(0.02)

(0.07)

A

B

C

D

D E

0.19

(0.04)

E

EF

F

F

T

T

3

T

T

T

T

T

T

T

3

3

2

1

1

2

2

1

W

W

1

W

3

W

1

W

2

W

2

W

1

W

3

3

W

2

10.5

9.19

5.72

(0.45)

(0.29)

7.44

(0.18)

7.33

(0.21)

5.83

(0.06)

5.76

(0.61)

(0.04)

A

B

C

C

6.27

(0.24)

D

5.92

(0.09)

DE

E

E

E

Treatment means in column followed by the same letter are not significantly different at α = 5%; LSD for

NH

4

+

= 0.32; LSD for NO

3

-

= 0.06 and LSD for Net N released = 0.36; Figures in brackets denote standard errors

Again, as was observed, for Vlakplaas sludge, the Olifantsfontein sludge also showed the highest N mineralization at treatments involving

T

3

. This is out from the range illustrated by Doran and Smith

(Figure 2.3), however, Zaman and Chang, (2004) also found high levels of N mineralized at 40

o

C.

70

3.3.4 The SASOL amended soil: Effects of temperature and water potential on the

mineralization process

Figure 3.5 illustrates how inorganic N forms where changing during the 56-day laboratory incubation, under all treatments. Similarly to other unstable sludge from domestic wastewater both ammonium and nitrate decreased after first day of incubation. The negative periods of NO

3

previously observed for unstable Olifantsfontein sludge amended soil were also observed during initial stage of incubation with the unstable Sasol sludge amended soil. This was also attributed to the initially low inorganic N in unstable Sasol sludge amended soil. Consequently the available NO

3

was assimilated by microbe population to get energy for their metabolism.

After one day incubation, the trend under interactions with T

1

(Figure 3.5 a

1

– a

3

) and with T

3

(Figure 3.5 c

1

– c

3

) was similar and differed from interactions with T

2

(Figure 3.5 b

1

– b

3

). No nitrification occurred at 10

o

C and 45

o

C

, however, at 25

o

C nitrification took place from the second week onwards until the end of incubation.

The absence of nitrification at 10

o

C and 45

o

C may be a result of nitrifying bacteria high sensitivity to extreme temperature and to NH

4

+ toxicity. The average amount of NH

4

+ for 10

o

C and 45

o

C ranged between 110 – 131 mg kg

-1

, however, this range was still far from 400 mg kg

-1

, (McIntosh and Frederick, 1958) and the 800 mg kg

-1

(Broadbent et al., 1957), found to be the maximum NH

4

+ in soil tolerated by nitrifiers. Other research conducted with the Sasol sludge involving leaching studies also revealed that water soluble arsenic, boron and selenium levels of this sludge is quite high. Especially arsenic is extremely biotoxic and it is reasonable to expect that it will have a negative effect on microbes involved in the mineralization process especially those involved in nitrification.

For T

1

and T

2

interactions with all water potential mineralization decreased from W

1

to W

3

. This was in accordance with (Doran and Smith, 1987; Leiros, et al., 1999). As soil water potential decreased

(reaching negative levels > - 50 kPa) soil microbe activity was reduced. However, at high temperature the situation was opposite, net N release increased from W

1

to W

3

, the same for unstable

Olifantsfontein and stable Vlakplaas sludge. Therefore, the effect of water potential on N release was

71

masked at high temperature. Zaman and Chang (2004) support these results, and also found higher mineralization at 40

o

C than at 20

o

C and at 5

o

C.

Considering what is referred in literature, water potential W

1

(- 10 kPa) is close to optimum soil moisture for mineralization. At this water potential, treatments with T

2

(25 o

C) resulted in the highest net N release 9.75 mmol kg

-1

. This was an exception because for other sludge amended soils, higher net N release was at 45 o

C. A possible explanation was the existence of 5 % of NH

4

+ in the sludge initially, which was nitrified and incremented the total net N released. Nevertheless, no nitrification was observed at 10 o

C and 45 o

C, since nitrifiers are depressed at cold and hot conditions (Brady and

Weil, 2002). Therefore, greater part of mineralized N remained in NH

4

form at 10 o

C and 45 o

C treatments.

72

6

5

4

3

2

1

0

-1

10

9

8

7

a

1

8

7

6

5

4

3

2

1

0

-1

0 7 14 21 28 35 42 49 56

Incubation time [days] b

1

2

1

0

-1

5

4

3

10

9

8

7

6

6

5

4

3

8

7

2

1

0

-1

NH4 NO3

a

2

Net Nrel

b

2

10

9

8

7

6

5

4

3

2

1

0

-1

6

5

4

3

8

7

2

1

0

-1

a

3 b

3 c

1

3

2

1

0

-1

5

4

9

8

7

6

0 7 14 21 28 35 42 49 56

7

6

8

5

4

3

2

9

-1

0

1

0 7 14 21 28 35 42 49 56

c

2

7

6

5

4

9

8

2

1

3

-1

0

0 7 14 21 28 35 42 49 56

c

3

Incubation time [days]

Figure 3.5 Net N released, NH

4

+

and NO

3

-

from Sasol sludge during a 56-day laboratory incubation at a temperature and water potential treatments given by letters: a

1

= T

1

W

1;

a

2

= T

1

W

2

;

a

3

= T

1

W

3

;

b

1

= T

2

W

1

; b

2

= T

2

W

2

; b

3

= T

2

W

3

; c

1

= T

3

W

1

; c

2

= T

3

W

2

; and c

3

= T

3

W

3

73

The ANOVA tables (Appendix A.

2.3

) shows that temperature, soil water potential and their interactions affected significantly the net N released from unstable Sasol sludge amended soil. Only interaction effect is discussed by rule. Table 3.12 illustrates treatments differences, their level of significance and which were not statistically different. For example treatments T

1

W

3

, T

2

W

1

and

T

3

W

1

had highly significant differences with all other treatments, even among them were statistically different.

Table 3.12

Levels of significance between temperature and water potential interaction on N mineralization from Sasol sludge amended soil after a 56- day laboratory incubation

T

1

W

1

T

1

W

2

T

1

W

3

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

1

W

1

T

1

W

2

T

1

W

3

0.0729ns

<.0001** <.0001**

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

<.0001** <.0001** <.0001**

0.1449ns 0.0030** <.0001** <.0001**

0.1449ns 0.0030** <.0001** <.0001** 1.0000ns

<.0001** <.0001** 0.0020** <.0001** <.0001** <.0001**

T

3

W

2

T

3

W

3

0.0008** 0.0505ns <.0001** <.0001** <.0001** <.0001**

0.0157*

0.0105*

0.0002** <.0001** <.0001** 0.2680ns 0.2680ns <.0001** <.0001**

ns = Not significant

(p > 0.05)

;* Significant at α= 0.05

(p < 0.05)

; ** Highly significant α= 0.01

(p < 0.01)

Treatment means for

NH

4

+

, NO

3

-

and net N released

were listed orderly from high to low compared using the least significant difference (LSD) Table 3.13. Treatments were compared along the column; those with same letter had similar effect on mineralization or nitrification, and with different letters affected differently. Interaction on suboptimal conditions of temperature and water potential (T

1

W

3

), as expected, gave lower net N released (5.0 mmol kg

-1

) and the interaction T

2

W

1 considered as the optimal condition for nitrification performed well giving the highest amount of both NO

3

-

and the net N release (9.75 mmol kg

-1

), was found to be the best combination for net N release. This was evident that ammonified N was readily nitrified. Therefore net N released after 56-

74

days of incubation was in nitrate form.

However, the T

3

W

3

treatment was superior with highest NH

4

+ mineralized (7.28 mmol kg

-1

) and insignificant NO

3

-

similarly to stable Vlakplaas and unstable

Olifantsfontein sewage sludge amended soils.

Table 3.13 Ranking and mean comparison of NH

4

+

, NO

3

and net N released, for Sasol sludge amended soil after 56-days of laboratory incubation

Treatment NH

4

+

Treatment NO

3

-

Treatment Net N released

T

3

W

3

T

1

W

1

T

3

W

2

T

1

W

2

T

3

W

1

T

1

W

3

T

2

W

1

T

2

W

2

T

2

W

3

7.28

(0.09)

A

6.15

(0.04)

B

5.97

(0.08)

C

5.87

(0.13)

C

5.44

(0.12)

D

4.28

(0.10)

E

0.21

(0.03)

F

0.00

(0.00)

G

0.00

(0.00)

G

T

2

W

1

T

2

W

2

T

2

W

3

T

1

W

3

T

1

W

1

T

1

W

2

T

3

W

1

T

3

W

2

T

3

W

3

[mmol kg

-1

]

9.75

(0.55)

A

7.47

(0.25)

B

7.18

(0.24)

B

0.69

(0.03)

C

0.69

(0.10)

C

0.65

(0.02)

C

0.20

(0.02)

D

0.19

(0.02)

D

0.10

(0.02)

D

T

2

W

1

T

3

W

3

T

2

W

2

T

2

W

3

T

1

W

1

T

1

W

2

T

3

W

2

T

3

W

1

T

1

W

3

9.75

(0.38)

A

7.47

(0.10)

B

7.10

(0.26)

C

7.10

(0.26)

C

6.83

(0.21)

C

6.50

(0.10)

D

6.13

(0.12)

E

5.63

(0.12)

F

5.00

(0.20)

G

Treatment means in column followed by the same letter are not statistically different at α = 5%; LSD for

NH

4

+

= 0.09; LSD for NO

3

-

= 0.28 and LSD for Net N released = 0.26; Figures in brackets denote standard errors

75

3.3.5 Partial N mass balance

The term partial used means that inorganic N losses were not included (volatilization and immobilization). Based on the sludge characterization results (Table 3.1), conversion was made into an easily comparable unit for nitrogen specimens [mmol per kg] for all N-forms (NH

4

+

, NO

3

-

, Org

N, Tot N) (Table 3.2). Organic N values were obtained by subtracting total inorganic N released from total N. The assumed total net inorganic N (report only ammonium and nitrate plus nitrite) because volatilization was not measured in this study. However, with this approach organic N was overestimated as a result of an underestimation of N mineralized (not accounting for N losses through immobilization and /or volatilization). Organic N mineralized was obtained by subtracting

Org N at instant time (t i

) from Org N at time (t

0

).

Table 3.14 illustrating the N mass balance shows that net N release from Vlakplaas sludge amended soil varies in the range of 1.87 – 3.50 mmol kg

-1

with temperature increase. On average 26.2 % of the total organic N was mineralized after 56 days of laboratory incubation, however, considering the total inorganic N released the trend for potentially available N supply was 47.8 % of total N at 10 ºC,

50.0 % at 25 ºC and 56.0 % at 45 ºC. Meaning that, Vlakplaas sludge may supply 38.8 mg kg

-1

of N at 10 ºC, 40.6 mg kg

-1

of N at 25 ºC and 45.6 mg kg

-1

of N at 45 ºC.

At 10 ºC a decrease in the amount of NH

4

+

was registered and an increase in NO

3

-

was observed, as a result of both mineralization and nitrification. Although at 25 ºC a decrease in NH

4

+

and an increase in NO

3

-

were also registered as a result of nitrification. High level of nitrification at 25 ºC was reflected by the higher disappearance rate of NH

4

+

. At 45 ºC mineralization was high and almost all

N mineralized was in form of ammonium, and the potentially available N was high (56.0 %) compared to that at 10 and 25 ºC. No nitrification was observed suggesting NO

3

-

assimilation or N

2

O losses.

76

T

0

T

1

W

1

T

1

W

2

T

1

W

3

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

3

W

3

Table 3.14 Partial N mass balance for the 56- day laboratory incubation with Vlakplaas sludge

Treatments

[mmol kg

-1

]

Tot N NH

4

+

NO

3

net N net N Org N Org N Mineralizable

%

Potentially

T

0 released mineralized mineralized org N available N

5.8

5.8

5.8

5.8

5.8

5.8

5.8

5.8

5.8

5.8

1.74

0.60

0.70

0.79

0.07

0.07

0.06

3.06

3.13

3.28

0.13

2.17

1.99

2.57

2.83

2.55

2.44

0.20

0.16

0.22

1.87

2.77

2.69

3.36

2.90

2.62

2.50

3.26

3.29

3.50

-

0.90

0.82

1.49

1.03

0.75

0.63

1.39

1.42

1.63

3.93

3.03

3.11

2.44

2.90

3.18

3.30

2.54

2.51

2.30

-

0.90

0.82

1.49

1.03

0.75

0.63

1.39

1.42

1.63

-

22.9

20.9

37.9

26.2

19.1

16.0

35.4

36.1

41.5

32.2

47.8

46.4

57.9

50.0

45.2

43.1

56.2

56.7

60.3

77

From Table 3.15 the partial N mass balance shows that net mineralized N from unstable

Olifantsfontein sludge amended soil varied in the range of 3.51 – 10.5 mmol kg

-1

with temperature increase. At higher temperature (45 ºC) and water potential of -10 kPa the total net mineralized N increased in the order of 46.5 % of total N. At 25 ºC after a 56- day incubation the potentially available N was 35.9 % of the total N, which is equivalent to 17.9 % of mineralizable organic N. Meaning that, Olifantsfontein sludge may supply in average 80.4 mg kg

-1

of N at 25

ºC and 104.1 mg kg

-1

of N at 45 ºC.

At 25 ºC, mineralization seemed to be less compared to all other treatment suggesting unfavourable condition at first glance. However, this was not the case the low levels of NH

4

+ indicate that conditions were optimal for the oxidation of it to higher oxidation status of N (N +3 and N+5). What happened is that the NH

4

+

formed was therefore very effectively nitrified as indicated by the relatively high amount of NO

3

-

compared to other treatments.

78

Table 3.15 Partial N mass balance for the 56- day laboratory incubation with Olifantsfontein sludge

Treatments

[mmol kg

-1

]

Tot N NH

4

+

NO

3

-

Net N Net N Org N Org N

T

0 released mineralized mineralized

12.5

(T

0

)

T

1

W

1

T

1

W

2

T

1

W

3

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

3

W

3

16.0

16.0

16.0

16.0

16.0

16.0

16.0

16.0

16.0

16.0

2.75

6.02

5.44

5.79

4.52

5.39

6.55

7.25

9.03

10.4

0.76

0.24

0.25

0.10

1.23

0.44

0.78

0.19

0.16

0.12

3.51

6.26

5.69

5.89

5.75

5.83

7.33

7.44

9.19

10.5

-

2.75

2.18

2.38

2.24

2.32

3.82

3.93

5.68

7.01

9.74

10.3

10.1

10.3

10.2

8.67

8.56

6.81

5.48

2.75

2.18

2.38

2.24

2.32

3.82

3.93

5.68

7.01

Mineralizable org N

-

22.0

17.5

19.1

17.9

18.6

30.6

31.5

45.5

56.1

%

Potentially available N

21.9

39.1

35.6

36.8

35.9

36.4

45.8

46.5

57.4

65.8

79

Table 3.16 shows that net mineralized N from Sasol sludge amended soil ranged from 3.11 – 9.75 mmol kg

-1

showing a maximum at 25 ºC. This maximum net N released was not a result of organic N mineralization only, was also from nitrification of the initially existing NH

4

+ and the

NH

4

+ coming from mineralization. Whereas, for 10 ºC and 45 ºC treatments net N mineralized was a result of N mineralization, as nitrification was insignificant.

The potentially available N at optimal mineralization condition was 41.1 % of the total N which is equivalent to 32.2 % of the total sludge organic N. The trend observed with potentially available N in average was 28.8 % at 10 ºC, 41.1 % at 25 ºC and 27.0 % at 45 ºC. Meaning that, the Sasol sludge amended soil sample may supply 85.4 mg kg

-1

of N at 10 ºC, 136 mg kg

-1

of N at 25 ºC and 89.6 mg kg

-1

of N at 45 ºC.

N mineralization seemed to be minimum at 25 ºC and higher at 45 ºC, however, the total N released, as well as the potential available N were higher at 25 ºC. Because at 25 ºC nitrifying bacteria encountered optimal conditions for their activity, therefore the NH

4

+

was converted to

NO

3

-

quickly.

80

Table 3.16 Partial N mass balance for the 56- day laboratory incubation with Sasol sludge

Treatments

[mmol kg

-1

]

Tot N NH

4

+

NO

3

-

Net N released

Net N mineralized

Org N Org N mineralized

(initial N)

T

1

W

1

23.7

23.7

2.67

6.15

0.44

0.69

3.11

6.84

-

3.73

20.6

16.9

-

3.73

T

1

W

2

T

1

W

3

23.7

23.7

5.87

4.27

0.65

0.69

6.52

4.96

3.41

1.85

17.2

18.7

3.41

1.85

Mineralizable org N

-

18.1

16.6

8.98

%

Potentially available N

13.1

28.8

27.5

20.9

T

2

W

1

T

2

W

2

T

2

W

3

T

3

W

1

T

3

W

2

T

3

W

3

23.7

23.7

23.7

23.7

23.7

23.7

0.00

0.00

0.20

5.44

5.97

7.28

9.75

7.47

7.18

0.20

0.19

0.09

9.75

7.47

7.38

5.64

6.16

7.37

6.64

4.36

4.27

2.53

3.05

4.26

14.0

16.2

16.3

18.1

17.5

16.3

6.64

4.36

4.27

2.53

3.05

4.26

32.2

21.1

20.7

12.3

14.8

20.7

41.1

31.5

31.1

23.8

26.0

31.1

81

3.3.6 Mineralization rate constant and half life time

A common approach in N modeling is to generate N release and mineralization parameters at optimum conditions for mineralization process (Serna and Pomares, 1992; Zaman et al 1999;

Hernandez et al., 2002). The same approach was followed here, data collected at

25

o

C

and water potential of approximately -10 kPa was used to assess the kinetics of N release from sludge amended soils. In order to determine the rate order of N release (pseudo first order or zero order) data from mineralization was presented in terms of natural logarithm of organic Nitrogen decay as a function of time then plotted against time to assess the linearity of this relationship, which is the diagnostic test for first order reaction (Figure 3.6). The organic N was taken as the difference between initially existing org N and the net N released at each incubation period. Thereafter the organic N values were converted into natural logarithm to provide data to compute the rate constants based on equation 13

The linear regression coefficient revealed that N mineralization for Olifantsfontein and Sasol were reasonable well approximated during the first 28 day utilizing first order kinetics (Figure 3.6 a). The organic N decay in the Vlakplaas amended soil seemed to follow first order kinetics during the whole incubation period (Figure 3.6 b). These results support findings of various other authors (Serna and Pomares, 1992; Benbi and Richter, 2002; Hernandez et al., 2002; Hseu and

Huang, 2005).

a b

6.0

6.0

5.5

y

Sasl

= -0.013x + 5.651

R² = 0.964

5.5

5.0

5.0

4.5

4.0

y

Olif

= -0.007x + 5.148

R² = 0.803

Sasl

Olif

Linear (Sasl)

Linear (Olif)

4.5

4.0

Vlkp

Linear (Vlkp)

3.5

3.5

y

Vlkp

= -0.006x + 4.019

R² = 0.854

3.0

3.0

0 7 14

Incubation time [days]

21 28

0 7 14 21 28 35

Incubation time [days]

42 49 56

Figure 3.6 The natural logarithm of organic N decay and estimated rate constants (slope of graphs) for

Sasol and Olifantsfontein sludge (a) compared to that of Vlakplaas (b)

82

The Vlakplaas sludge amended soil had the lowest mineralization rate constant (0.042 week

-1

) and longest corresponding half life time (116 days) while Sasol sludge amended soil exhibited the highest rate constant (0.093 week

-1

) and shortest half life time (58 days) (Table 3.17). There was small diference between the Vlakplaas and Olifantsfontein sludge amended soil having a rate of (0.049 week

-1

) and half life time of (98 days). The reason could be that both are municipal sludges therefore presenting simillar composition on organic compounds. These values are similar to Stantford and Smith, (1972) findings, ranging from (0.035 – 0.095 week

-1

) in 39 samples studied. Also Hseu and Huang (2005) reported that anaerobically digested sludges had rates from 0.047 – 0.075, and rates of 0.047 – 0.105 for aerobically digested sludges. Differently high mineralization rates were reported 0.089 – 0.883 week

-1

(Serna and Pomares, 1992) and

0.228 – 1.140 week (Hernandez et al., 2002). Van Niekerk et al., (2005) findings from the

Olifantsfontein sludge where relatively high (0.212 day

-1

). These results also support findings by

Dou et al., (1996), who reported the goodness of fit of different kinetic models dependent on incubation period, where single first-order model provided good fit of data for incubation period

(≤ 15 weeks); and double first-order model provided better results for incubation period (> 15 weeks.

Table 3.17 N mineralization rate constants and half life times of the fast cycling “pool”

Sludge type

Vlakplaas

Olifantsfontein

Sasol

C/N Total Org N

[mg kg

-1

]

6.0

4.5

5.0

55.0

175

288

k (Day

-1

) k [Week

-1

] Half life time

[days]

-0.006

-0.007

-0.013

-0.042

-0.049

-0.093

116

98

58

The incubation time was selected based on previous studies done on the sludge collected from

Olifantsfontein WCW. This study, showed that after 42 days the rate of N mineralization approached zero and ammonium formation was virtually negligible after 28 days (Van Niekerk at

al., 2005). Also from Figure 3.4 it‟s clearly reflected that after 28 days mineralization has reached slow release pool. However, to get some quantification on the potential sizes of slower cycling N pool the approach of Smith et al., (1998c) was used. The N pool sizes were estimated at 26 % of total organic N applied for rapid release pool (N

1

) and 42 % of total organic N applied for slow release pool (N

2

) based on the findings (Table 3.18)

83

Table 3.18 Estimated sizes of N pools of different types of sludge investigated

Sludge source

Vlakplaas

Olifantsfontein

Sasol

Tot Org N

(mmol kg

-1

)

(mg kg

-1

Tot Org N Rapid release pool

)

Slow release pool

3.93

12.5

20.6

55.0

175

288

14.3

45.5

74.9

23.1

73.5

121

Resistant pool

17.6

56.0

92.3

It is reasonable to expect that a double first order kinetic model by Molina et al., (1980) would better estimate the rate constant to account for the existence of different organic N pools, the rapidly (N

1

) and slowly (N

2

) N pools (Dou et al., 1996; Hseu and Huang, 2005; Smith et al.,

1998c; Benbi and Richter, 2002). However, it was not possible from this study to obtain rate constants of slower cycling pools.

Checking the Van‟t Hoff equation: testing the temperature coefficient (Q

10

) and mineralization rate considering 25 o

C as optimal incubation temperature

N

e k

t

T

;

Q

10

e

10

k

Table 3.19 Mineralization rate and temperature coefficient

Sludge source k Q

15

=e

15k

N=e k(10-25)

Q

10

=e

10k

Vlakplaas

-0.006 0.91 1.09 0.94

Q

20

=e

20k

0.89

N=e k(45-25)

0.89

Olifantsfontein

-0.007

Sasol

-0.013

0.90

0.82

1.11

1.22

0.93

0.88

0.87

0.77

0.87

0.77

N mineralization rate decreases with increase in temperature and increase with decrease in temperature relative to the optimal temperature, and the temperature coefficient increases with negative shifting of temperature. These results are not in agreement with Vant‟Hoff‟s assumptions that mineralization rate is twofold when temperature shifts 10 o

C in a temperature range between 5 to 35 o

C.

84

3.4 General discussion

Sewage sludge land application has been recognized as a viable alternative for disposal, because with this strategy two problems can be solved at once: Soil productivity (soils are restored, soil fertility enhanced) and environment (potential environmental pollution minimized).

The South Africa‟s guideline establishes an upper application limit of 10 ton per hectare per year regardless of the type of sludge produced under different process of treatment. What are the implications of the single application dose?

From the obtained net N release results, sludge stability (physical aspect depending on the treatment process) and initial N content shows significant differences in N loads. This difference will continuously be there as a result of different sources of sewage effluent and different treatment processes.

For instance, with the upper limit of 10 t ha

-1

year

-1

results from the three tested sludges, total N loaded based on total N content was 193 kg for Vlakplaas sewage sludge, 533 kg and 791 kg for unstable Olifantsfontein and Sasol sludges respectively. From which the potential available N was 96.5, 192, and 324 kg for the same order. Therefore, it‟s important for decision makers to consider these aspects (stability and total N content) for establishing an effective sludge land application rate. Future refinements of sludge utilization guidelines in South Africa should include upper limits for nitrogen application based on potential available N rather than general sludge loading rates.

The potential for environment nitrate pollution is high for unstable sludges because of their high levels of N content. Therefore, regulations on disposal management strategy need to be reviewed and re-established. Although disposal of sludge as land application seems to be safer; monitoring is important to prevent accumulation of organic pollutants on receiving plots. Site specific modelling N dynamics is an important tool for strategic sludge land application management.

85

Although, sewage sludge could help in improving soil productivity, its utilization is still limited to urban and peri-urban areas, where functional sewage system and facilities for waste water treatment are located. Therefore, many African countries are still far from exploiting the advantages brought up by sewage sludge land application. For example, in Mozambique, like many other countries, waste-water streams are still dumping to the sea. Remote rural areas have no sanitary facilities. Therefore even if a project for establishing a wastewater treatment company could appear in the big cities to divert the waste streams from dumping into the sea, produced sewage sludge will not help much for subsistence farmers, practicing their agriculture in rural areas because transport of high loads of sewage sludge can be costly and not economically viable.

In remote areas a problem of low fertility with consequent decrease in crop yields faced by rural farmers persists, therefore, other alternatives to counteract soil fertility decline must be found, such as the use of green manure as cover crop or mulching and animal manure. Results from this study are of concern to South Africa‟s environment, however, for Mozambique, lacking the high investments for establishment of municipal wastewater treatment plants; this work serves as a tool to investigate the dynamic of nutrients from other organic sources in order to recover and enhance soil productivity.

86

3.5 Conclusions and recommendations

3.5.1 Conclusions

Results from this study, emphasized the importance of sewage sludge as viable soil amendment as a source of nitrogen, given the fact that, it contains high organic matter with ability to release inorganic N nutrient (ammonium and nitrate essential for plant growth).

Temperature and soil water interaction as well as sludge stability, had a significant influence on

N release, thus on N availability from sludge amended soils. Greater mineralization was observed at 45 o

C and increased with water potential decrease; nonetheless, greater nitrification was observed at 25 o

C and decreased with water potential decrease. During the incubation period nitrification was suppressed in the Olifantsfontein amended soil. And the N released at 45 o

C was mainly in the NH

4

+ form. Although, at 25 o

C and -10kPa the potential for N release was high for

Vlakplaas, the amount of N released was less relative do Olifantsfontein, as a result of initial sludge N content.

Based on the potential N availability Vlakplaas would supply about 96.5 kg inorganic N that represents 27.5% of organic N, Olifantsfontein 192 kg and Sasol 323 kg that represent respectively 34.8, and 38 % of organic N mineralized. Results from this study are in agreement with van Niekerk‟s (2005) findings, who found that organic N mineralizable from Olifantsfontein was 33.6%. Also according the guidelines for the permissible utilization and disposal of sludge in

South Africa the about 30% of organic N is mineralized during the first year. Hernandez et al.,

2002 also found that sewage sludge organic N mineralized ranges from 30 to 41%.

There was a clear difference between the mineralisation rate of industrial and municipal sludge.

The Vlakplaas sludge amended soil had the lowest mineralization rate constant (0.042 week

-1

) and the longest corresponding half life time (116 days) while Sasol sludge amended soil exhibited the highest rate constant (0.093 week

-1

) and shortest half life time (58 days). Based on the half life times it is concluded that the persistence of stable sludges is longer than unstable

Olifantsfontein making it potentially a more efficient source in releasing plant nutrients gradually. Unstable Sasol sludge easily release its N increasing the potential for contamination of the ash dumping sites.

87

3.5.2 Recommendations

Mineralization and nitrification rates, rate constants of N mineralization and half-life time of sludge decay are useful parameters for modeling. Therefore to improve the N use efficiency from applied sewage sludge and minimize adverse impacts on the environment, it is recommended to establish specific application rates based on the kinetics of N release form sludge.

Determination of inorganic N released based on KCl extractable ammonium (NH

4

+

) and nitrate

(NO

3

-

) may not reflect the release of inorganic only, because KCl does not necessarily discretely extract inorganic N. It is quite possible that organic N present in the sludge, that is soluble in a polar solvent, will also be extracted along with the inorganic N. Therefore determination of organic N after each incubation time is recommended to refine mineralisation estimates and also to predict the dynamics of organic N.

Based on the potential N availability, rate constant and half life Vlakplaas sludge is more effective as it releases N for land application supplying at all temperature range tested amounts of net N release not exceeding the N requirement of the most common crops and at slower release rate. The Olifantsfontein sludge has also a lower release rate; however, may easily exposes the environment to potential nitrate pollution as a result of high levels of total N. It is recommended that sewage sludge be incorporated in soils at least one month before planting to assure for available inorganic N at the stage of crop development.

3.6 Limitations

Losses of N were not captured so the N mass balance given in this study was partial; organic N used for rate constant was an approximation of shorter term N release and longer term predictions only gives an indication of longer term trends.

The half lifetimes may not reflect the reality because the pool sizes were estimated, it is suggested that in the next experiments be determined.

88

3.7 Reference

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Inc. Harcourt Brace Jovanovich, Publishers, 265 pp

PROBERT, M.E., DELVE, R.J., KIMANE, S.K. AND DIMES, J.P., 2005. Modeling N mineralization from manure: representing quality aspects by varying C: N ratio of sub- pools. Soil Biology and Biochemistry 37, 279 – 287

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RUSSEL, E.W., 1988. Soil conditions and plant growth. 11 th

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mineralization, nitrification and nitrogen losses in an Oxisol amended with sewage

sludge. Australian Journal of Soil Research 39, 519 – 534

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Ed; revised and expanded. Marcel Dekker,

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94

CHAPTER IV: SAMPLE HANDLING STRATEGY

Handling of sewage sludge amended soil samples for nitrate and ammonium analysis

ABSTRACT

Field validation of mineralization and nitrification rates is essential for accurate prediction and modeling of environmental fate of nitrogen entering the soil system through sewage sludge application. Mineralization and nitrification are ongoing processes, therefore sampling and handling will determine how representative and accurate the determined nitrate and ammonium speciation is to that in the soil at the point in time of sampling. To establish an acceptable sample handling procedure for nitrate and ammonium determinations in sewage sludge amended soils three sample handling strategies (Direct Field Extraction-DFE, Field Drying and Extraction-FDE and Laboratory Drying and Extraction-LDE) were tested. The amounts of nitrate and ammonium speciation determined through DFE- procedure was expected to be the best procedure for equivalent amounts present in soil at the point in time of sampling. Samples were collected from sewage sludge amended fields that received recently (2 seasons) and long period (> 4 seasons) sewage sludge applications. Samples were replicated four times. A known soil volume that passed through a 2 mm sieve was directly transferred to containers with 100 cm

3 of 2M KCl solution just after sampling (DFE). Other sub samples were left to air-dry and immediately transferred to containers containing extract solution in the field (FDE). These soil suspensions were transported immediately to the laboratory, extracted and analysed for nitrate and ammonium using the Kjeldahl method. Other sub samples were taken to the Soil Science Laboratory of

Pretoria University, air dried for 24 hours sieved through a 2 mm sieve, extracted with a100 cm

3

2 M KCl solution (LDE) and analysed for nitrate and ammonium. Sample handling procedure significantly influenced the content of NO

3

-

and NH

4

+

speciation. The average NH

4

+

content for

DFE was 56.4 mg kg

-1

(dry land) and 59.5 mg kg

-1

for LDE. The average NO

3

- content for DFE was 394 mg kg

-1

(dry land) and 569 mg kg

-1

for LDE. Analytical results showed that laboratory drying resulted in an overestimation of soil nitrate content and no significant difference for NH

4

+ content. Artifacts introduced by long drying period resulted in an increase of mineralization as well as nitrification in sewage sludge amended samples. Therefore DFE procedure revealed to be the suitable sampling strategy for sewage sludge amended soils.

Keywords: Soil sampling strategy, sewage sludge, nitrate, mineralization, and nitrification.

95

4.1 Introduction and background

The truthfulness of a laboratory soil test results is not only influenced by the methods of analysis and technician‟s ability but is also influenced by the quality of the soil sample, by means of representative sample collection (Franzen and Cihacek, 2004; Ferro S., 2004). Inadequate sampling and sample handling procedure may result on misleading interpretation of laboratory results. Therefore sampling should be considered seriously as well as soil sample handling to provide representative, consistent and reliable laboratory results.

The dynamic of soil processes cause continuous changes in the forms, quantities and availability of plant nutrients over time. On the other hand the inorganic N forms in particular nitrate (NO

3

-

) which is easily mobile in soil solution, cause modifications in soil nitrate and ammonium concentrations throughout the time. This mobility brings in difficulties for modeling N fate in soils especially on soils amended with sewage sludge or other organic source.

To reduce this drawback it is essential to know and understand phenomenon‟s that might cause soil nutrients value to change between sampling and laboratory testing, as well as, planting time to avoid misinterpretations of laboratory results (Self and Soltanpour, 1997).

Besides environmental conditions, transformations of nitrogen forms in the soil-plantenvironment systems are time dependent. The soil micro-organisms composition exerts a big influence on the balance of NH

4

+

and NO

3

-

quantities in soil (Verhagen et al., 1992). Nitrifiers are found to be less competitive than heterotrophic bacteria for ammonium. Therefore, the amount of NH

4

+

and NO

3

-

determined depends on how samples were handled after collection up until the stage of laboratory analysis.

The ability to extrapolate soil laboratory results to the field conditions depends not only on the fertility expert experience but on how representative the soil sample is to that of real field condition (Ferro S., 2004; Franzen and Cihacek, 2004). For that reason sampling and sample

96

handling for a sewage sludge amended soil, where organic compounds are in continuous mineralization, needs special attention to keep the representativeness of nutrient contents.

Selection of sample handling procedure must be based on the type of species to analyse and the purpose of the results (Self and Soltanpour, 1997). According to Tack and Verloo (2001) sample handling guideline is strongly dependent on the ultimate goal of a particular sampling.

According Self and Soltanpour (1997) for nitrate analyses soil samples should be air dried within

12 hours after sampling, to prevent microbial activity from mineralizing organic materials and causing changes on the ultimate soil ammonium and nitrate contents.

Lack of standard handling procedure for sewage sludge amended soils may lead to wrong interpretations in terms of N status. A standardized procedure for sample handling is necessary to ensure representativeness and reliability of laboratory test results (Theocharopoulos et al., 2001).

Standardization of sample handling procedure becomes an urgent need to facilitate interpretation and comparability of data among different laboratories. Therefore adequate sample handling of sewage sludge amended soils are crucial for effective recommendations on the management of sewage sludge land application.

Since the N transformations among organic and inorganic forms are governed by biological soil environment, there is a need to suppress the microbial activity from the sampling stage to the instant of laboratory analysis in order to keep the real amount of NH

4

+

and NO

3

- present in soil at the point in time of sampling (Wollum, 1994).

According the equation NH

4

+

+ OH

-

= H

2

O + NH

3

, ammonium in soil solution is highly dependent on the pH of the soil. Ammonium may volatilize liberating ammonia as soil dries out driving the reaction equilibrium to the right stimulating NH

4

+

decrease. Ammonium and nitrate content in soil are also time dependent, when the soil environment is adequate for the activity of

Nitrosomonas and Nitrobacter may lead to a decrease of NH

4

+

and increase of NO

3

-

(Brady and

Weil, 2002).

97

A trial was conducted to compare the field extractions with conventional sampling and handling procedures and showed considerable differences in ammonium and nitrate results.

4.1.1 Objectives

The aim of this study was to establish an appropriate sample handling procedure for determination of nitrate (NO

3

-

) and ammonium (NH

4

+

) speciation in sewage sludge amended soils.

To fulfill this objective three sample handling strategies were tested, there are as follows: i. Direct Field Extraction- DFE ii. Field Drying and Extraction - FDE iii. Laboratory Drying and Extraction - LDE

98

4.2 Material and methods

4.2.1 Material

A. Amended soil samples

Samples were collected from an existing crop trial at Harbeesfontein, a waste water treatment facility of East Rand Water Company near Kempton Park, Gauteng province,

South Africa, with sandy clay loam soils that have received 16 ton per ha of activated anaerobically digested sewage sludge. Distributed in two seasons, half (8 t ha

-1

) was applied in winter season and another half in summer season of the year 2005. Samples were taken in triplicate.

B. Equipment

Plastic bottles with 200 cm

3

capacity, plastic cup with 10 cm

3

capacity, aluminum foil tart plate folder, weighing scale, horizontal shaking, filtration stand, fridge, kjeldhal distillation apparatus, and titration system.

C. Chemicals

Potassium chloride (KCl) 1 M solution, Sodium hydroxide (NaOH) 12.5M, Devarda‟s alloy powder, Hydrochloric acid (HCl) 0.01M, ethanol (C

2

H

5

OH), Boric acid (H

3

BO

3

) and indicator (methyl blue and methyl red).

4.2.2 Methods

A. Sample handling strategies

Three sample handling strategies were tested in samples collected from the plots that have received 16 ton of sewage sludge. There are as follow:

 Direct Field Extraction (DFE) – samples were collected and immediately extracted in the field, then taken to the laboratory for analysis.

 Field Drying and Extraction (FDE) – samples were collected, air dried immediately, sieved and extracted in the field, then taken to the laboratory for analysis.

 Laboratory Drying Extraction (LDE) – samples were collected, taken to the laboratory air dried for 24 hours sieved, extracted and then analysed.

99

i) Direct Field Extraction

A known volume of instant collected soil samples that passed through a 2 mm sieve, were directly transferred to containers with 100 cm

3

2 M KCl solution to extract the extractable and exchangeable ammonium and nitrate and taken to the laboratory within few hours for subsequent analysis.

ii)

Field Drying and Extraction

The collected soil samples were spread out in aluminum foil tart plate left to dry in the field. Afterwards the samples were sieved through a 2 mm sieve then a known volume of these air dried soil was directly transferred to containers with 100 cm

3

2 M KCl solution to extract the extractable and exchangeable ammonium and nitrate and taken to the laboratory for subsequent ammonium and nitrate determinations.

iii) Laboratory Drying and Extraction

Collected samples were taken to the laboratory air dried for 24 hours at room temperature

(~ 22 – 25 o

C), sieved to pass a 2 mm sieve, 10 g of soil were extracted in 100 cm

3

of 2

M KCl solution and ammonium and nitrate were determined.

NB.1 For field extractions DFE and FDE the used plastic cups for measuring the soil volume were filled with respective soil samples taken to the laboratory weighed and then oven dried and weighed again to obtain the mass of soil extracted in dry mass basis, for the final calculations.

NB.2 If there is time constraint after filtration extracts should be kept in the fridge. At the moment of determination samples are taken out from the fridge left to reach room temperature and then carry out the analysis.

100

B. Extractable and exchangeable NH

4

+

and NO

3

-

determinations

Sample extracts from all handling strategies were kept in the fridge, while waiting to be analysed, due to time constraint, to stop any possible conversion of N-forms. The temperature in the fridge was at 1.9 o

C, sufficient to prevent any microbial activity. At the moment of determination samples were taken out from the fridge left until they reached room temperature then NH

4

+ and

NO

3

-

determined.

Procedure

50 ml of soil extracts was transferred into a distil tube and 20 ml of a 12.5M NaOH solution was added (sufficient amount to convert all NH

4

+

present in the soil extract into NH

4

OH) and distilled through micro- Kjeldahl steam distil system. The NH

3

formed was collected in mixture solution of H

3

BO

3

-indicator with purple colour. Ammonia entering in this solution formed a green complex with boric acid- indicator and then titrated with HCl 0.01M until the green colour changes. At the end point of titration volume of hydrochloric acid was recorded. In the remained extract on the Kjeldahl distil tube approximately 2 mg of devarda‟s alloy powder was added after cooling to reduce all NO

3

-

and NO

2

-

into NH

4

+

, which in turn react with the excess of NaOH and distilled again following the same procedure, and the volume of hydrochloric acid was recorded.

The first step of distillation was for ammonium determination and the second for nitrate.

C. Extractable and exchangeable NH

4

+

and NO

3

- calculation

The concentration of NH

4

+

and NO

3

- in the samples was obtained based on the equi-molar displacement reaction principle as explained in chapter III– 3.2.6.1 (equation 8).

101

4.3 Results and discussion

4.3.1 Sample handling effect on NH

4

+

and NO

3

-

content in sewage sludge amended soil

Under dry land condition the content of soil NH

4

+ speciation showed a little increase along the drying process. It was almost the same for all sample handling strategies whilst for NO

3

-

content an increase was observed from Direct Field Extraction to Laboratory Drying and Extraction (Fig.

4.1). This could be explained by the fact that the organic N mineralizes first into ammonium, which in turn at well aerated conditions is converted into nitrate through nitrifying bacteria activity. Results are in agreement with findings of (Ashok et al., 2006) who reported an increase in NH

4

+ concentration during the first fifteen days of incubation on sewage sludge amended soil followed by a sharp decline indicating rapid transformation into NO

3

-

.

600

500

400

300

200

100

0

DFE FDE

Sample handling strategies

LDE

NH4 NO3

Figure 4.1 Concentration of NH

4

+

and NO

3

-

versus sample handling procedures

102

4.3.2 Statistical analysis

The general linear model procedure for SAS program and the Tukey‟s test grouping were used.

Based on the ANOVA tables sample handling procedures were significantly different. Difference between DFE and FDE was highly significant for ammonium, while in relation to nitrate content these strategies were not statistically different. The effects of DFE and LDE relative to ammonium content were not significantly different however their effects on nitrate content were statistically different at 5 % of significance level. Effects of FDE and LDE were significantly different for both ammonium and nitrate content (Table 4.1).

Table 4.1 Levels of significance for sample handling strategies

Sampling strategy

DFE

FDE

FDE LDE

NH

4

+

NO

3

-

NH

4

+

NO

3

-

0.0008 ** 0.3593 ns 0.2191 ns 0.0103*

- - 0.003 ** 0.036 *

ns = Not significant (p > 0.05);* Significant at α=5% (p < 0.05); ** Highly significant α=1% (p < 0.01)

From Table 4.2, ammonium content obtained with DFE was not significantly different from that of the LDE, The reason is that mineralized NH

4

+

was being simultaneously converted into NO

3

and replaced by mineralization of organic N from the system soil/sewage sludge. However the ammonium content for FDE was significantly higher compared to DFE and LDE. The reason could be that drying in an open sun increased mineralization as a result of temperature effect. On the other hand the shortest time from collection-drying and extraction did not give chance for nitrifying bacteria to perform. The nitrate content for DFE and for FDE samples was significantly lower from that of the LDE samples as a result of mineralization and nitrification processes occurring along the period going from sample collection, drying up until the sample extraction in the laboratory.

103

Table 4.2 Ranking and treatment mean comparison

Treatment NH

4

+

[mg kg

-1

]

t grouping Treatment NO

3

-

[mg kg

-1

]

t grouping

70.42 a 568.8 a

FDE

LDE

DFE

59.54

56.43 b b

LDE

FDE

DFE

441.1

393.9 b b

*Treatment means followed with the same letter are not statistically different at = 5% (p < 0.05)

104

4.4 Conclusions and recommendations

4.4.1 Conclusions

The sample handling strategy had greater influence on determined soil nitrate and ammonium content. Artifacts introduced by drying result in an overestimation of nitrification as well as mineralization in the sewage sludge amended soils. The evidences were sufficient to conclude that the Direct Field Extraction strategy was more adequate to figure the soil NH

4

+

and NO

3

content at the point in time of sampling.

The results agreed with Franzen and Cihacek (2004) findings who concluded that samples intended for NO

3

-N determination should be transported immediately to a soil testing laboratory in a cold ice chest or air-dried immediately after collection and then taken for immediate laboratory analysis to prevent alteration of N concentrations through microbial activity.

4.4.2 Recommendations

When developing models to assess nitrate pollution risk and in soil fertility management for an effective use of sewage sludge nitrogen, the Direct Field Extraction strategy is recommended

Concurrently to application of DFE strategy, samples should be collected closer to planting time to minimize the gap between the determined soil nitrates NO

3

-

content with the availability of N at a point in time of sampling.

105

4.5 References

ASHOK, A.K., PARAMASIVAM, S. AND SAJWAN, K.S., 2006. Nitrogen transformation from three organic amendments in a sandy soil. Communications in Soil Science and

Plant Analysis. 52, 1 – 11

BRADY, N.C. AND WEIL, R.R., 2002. The nature and properties of soils. 13 th

Ed. Pearson

Education Prentice Hall

SELF, J.R. AND SOLTANPOUR, P.N. 1997. Soil Sampling. Colorado State University

Cooperative Extension 0.500, 1 – 3

TACK, F.M.G. AND VERLOO, M.G., 2001. Guidelines for sampling in Flanders Belgium. The

Science of Total Environment 264, 187 – 191

THEOCHAROPOULOS, S. P., WAGNER, G., SPRENGANT, J., MORH, M-E., DESAULES,

A., MUNTAU, H., CHRISTOU, M. AND QUEVAUVILLER, P., 2001. European soil sampling guidelines for soil pollution studies. The Science of the Total Environment 264,

51 – 62

VERHAGEN, F.J.M., DUYTS, H. AND LAANBROEK, H.J., 1992. Competition for ammonium between nitrifying and heterotrophic bacteria in continuous percolated soil columns.

Applied and Environmental Microbiology 58, 3303 – 3311

WEAVER, R. W., ANGLE, S. BOTTOMLEY, P., BEZDICEK, D., SMITH, S., TABATABAI,

A., AND WOLLUM, A., 1994. Methods of Soil Analysis Part 2- Microbiological and

Biochemical Properties. Soil Science Society of America Inc Book Series: 5

WOLLUM, A. G. II, 1994. Soil Sampling for Microbiological Analysis. In Weaver et al., 1994.

Methods of Soil Analysis Part 2- Microbiological and Biochemical Properties. Soil

Science Society of America Inc Book Series: 5, pp 1 – 13

106

5. APPENDICE

A

1

. Statistical analysis for temperature and water potential effect on net N release

107

A

1.1

Stable ‘Vlakplaas’ sewage sludge amended soil 10:45 Monday, March 19, 2007 3

Obs Temp Moist rep V1

1 T1 W1 1 2.681

2 T1 W1 2 2.912

3 T1 W1 3 2.713

4 T1 W2 1 2.075

5 T1 W2 2 2.063

6 T1 W2 3 1.944

7 T1 W3 1 3.224

8 T1 W3 2 3.463

9 T1 W3 3 3.403

10 T2 W1 1 2.700

11 T2 W1 2 3.106

12 T2 W1 3 2.883

13 T2 W2 1 2.477

14 T2 W2 2 2.421

15 T2 W2 3 2.489

16 T2 W3 1 2.211

17 T2 W3 2 2.282

18 T2 W3 3 2.262

19 T3 W1 1 3.213

20 T3 W1 2 3.332

21 T3 W1 3 3.214

22 T3 W2 1 3.069

23 T3 W2 2 3.757

24 T3 W2 3 3.058

25 T3 W3 1 3.528

26 T3 W3 2 3.651

27 T3 W3 3 3.324

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 4

The GLM Procedure

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

Moist 3 W1 W2 W3

Rep 3 1 2 3

Number of Observations Read 27

Number of Observations Used 27

108

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 5

The GLM Procedure

Dependent Variable: V1 Total mineralized N

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 6.71439496 0.83929937 27.70 <.0001

Error 18 0.54534667 0.03029704

Corrected Total 26 7.25974163

R-Square Coeff Var Root MSE V1 Mean

0.924881 6.067564 0.174060 2.868704

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 3.27215030 1.63607515 54.00 <.0001

Moist 2 1.03258007 0.51629004 17.04 <.0001

Temp*Moist 4 2.40966459 0.60241615 19.88 <.0001

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 3.27215030 1.63607515 54.00 <.0001

Moist 2 1.03258007 0.51629004 17.04 <.0001

Temp*Moist 4 2.40966459 0.60241615 19.88 <.0001

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 6

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1 #

NOTE: This test controls the Type I experiment wise error rate, but it generally has a higher

Type II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.030297

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.2094

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 3.34956 9 T3

B 2.71978 9 T1

B 2.53678 9 T2

109

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 7

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher

Type II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.030297

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.2094

Means with the same letter are not significantly different.

Tukey Grouping Mean N Moist

A 3.03867 9 W3

A 2.97267 9 W1

B 2.59478 9 W2

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 8

The GLM Procedure

Level of Level of --------------V1-------------

Temp Moist N Mean Std Dev

T1 W1 3 2.76866667 0.12515723

T1 W2 3 2.02733333 0.07241777

T1 W3 3 3.36333333 0.12433959

T2 W1 3 2.89633333 0.20332814

T2 W2 3 2.46233333 0.03629509

T2 W3 3 2.25166667 0.03661056

T3 W1 3 3.25300000 0.06841783

T3 W2 3 3.29466667 0.40043019

T3 W3 3 3.50100000 0.16516356

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 9

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp V1 LSMEAN Error Pr > |t| Number

T1 2.71977778 0.05802015 <.0001 1

T2 2.53677778 0.05802015 <.0001 2

T3 3.34955556 0.05802015 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 0.0387 <.0001

2 0.0387 <.0001

3 <.0001 <.0001

110

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W1 2.97266667 0.05802015 <.0001 1

W2 2.59477778 0.05802015 <.0001 2

W3 3.03866667 0.05802015 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 0.0002 0.4317

2 0.0002 <.0001

3 0.4317 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Stable sewage sludge ‘Vlakplaas’ 10:45 Monday, March 19, 2007 10

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T1 W1 2.76866667 0.10049384 <.0001 1

T1 W2 2.02733333 0.10049384 <.0001 2

T1 W3 3.36333333 0.10049384 <.0001 3

T2 W1 2.89633333 0.10049384 <.0001 4

T2 W2 2.46233333 0.10049384 <.0001 5

T2 W3 2.25166667 0.10049384 <.0001 6

T3 W1 3.25300000 0.10049384 <.0001 7

T3 W2 3.29466667 0.10049384 <.0001 8

T3 W3 3.50100000 0.10049384 <.0001 9

Least Squares Means for effect Temp*Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3 4 5 6 7 8 9

1 <.0001 0.0006 0.3809 0.0449 0.0019 0.0031 0.0016 <.0001

2 <.0001 <.0001 <.0001 0.0067 0.1319 <.0001 <.0001 <.0001

3 0.0006 <.0001 0.0041 <.0001 <.0001 0.4476 0.6348 0.3455

4 0.3809 <.0001 0.0041 0.0068 0.0003 0.0219 0.0118 0.0005

5 0.0449 0.0067 <.0001 0.0068 0.1556 <.0001 <.0001 <.0001

6 0.0019 0.1319 <.0001 0.0003 0.1556 <.0001 <.0001 <.0001

7 0.0031 <.0001 0.4476 0.0219 <.0001 <.0001 0.7727 0.0980

8 0.0016 <.0001 0.6348 0.0118 <.0001 <.0001 0.7727 0.1638

9 <.0001 <.0001 0.3455 0.0005 <.0001 <.0001 0.0980 0.1638

111

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

A

1.2

Unstable ‘Olifantsfontein’ sewage sludge amended soils 09:16 Monday, March 19, 2007 1

Obs Temp Moist rep V1

1 T1 W1 1 6.015

2 T1 W1 2 6.493

3 T1 W1 3 6.293

4 T1 W2 1 5.816

5 T1 W2 2 5.975

6 T1 W2 3 5.967

7 T1 W3 1 5.760

8 T1 W3 2 5.696

9 T1 W3 3 5.696

10 T2 W1 1 5.277

11 T2 W1 2 6.440

12 T2 W1 3 5.551

13 T2 W2 1 5.756

14 T2 W2 2 5.871

15 T2 W2 3 5.855

16 T2 W3 1 7.548

17 T2 W3 2 7.129

18 T2 W3 3 7.305

19 T3 W1 1 7.239

20 T3 W1 2 7.597

21 T3 W1 3 7.490

22 T3 W2 1 8.870

23 T3 W2 2 9.268

24 T3 W2 3 9.427

25 T3 W3 1 10.581

26 T3 W3 2 10.859

27 T3 W3 3 9.984

Unstable sewage sludge ‘Olifantsfontein’ 09:16 Monday, March 19, 2007 2

The GLM Procedure

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

112

Moist 3 W1 W2 W3

Rep 3 1 2 3

Number of Observations Read 27

Number of Observations Used 27

113

Unstable sewage sludge ‘Olifantsfontein’ 09:16 Monday, March 19, 2007 3

The GLM Procedure

Dependent Variable: V1 net nitrogen mineralized

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 70.03128141 8.75391018 98.38 <.0001

Error 18 1.60160200 0.08897789

Corrected Total 26 71.63288341

R-Square Coeff Var Root MSE V1 Mean

0.977642 4.200020 0.298292 7.102148

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 50.94189430 25.47094715 286.26 <.0001

Moist 2 8.42576585 4.21288293 47.35 <.0001

Temp*Moist 4 10.66362126 2.66590531 29.96 <.0001

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 50.94189430 25.47094715 286.26 <.0001

Moist 2 8.42576585 4.21288293 47.35 <.0001

Temp*Moist 4 10.66362126 2.66590531 29.96 <.0001

Unstable sewage sludge ‘Olifantsfontein’ 09:16 Monday, March 19, 2007 4

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experiment wise error rate, but it generally has a higher

Type II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.088978

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.3589

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 9.0350 9 T3

B 6.3036 9 T2

B 5.9679 9 T1

114

Unstable sewage sludge ‘Olifantsfontein’ 09:16 Monday, March 19, 2007 5

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher

Type II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.088978

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.3589

Means with the same letter are not significantly different.

Tukey Grouping Mean N Moist

A 7.8398 9 W3

B 6.9783 9 W2

C 6.4883 9 W1

Unstable sewage sludge ‘olifantsfontein’ 09:16 Monday, March 19, 2007 6

The GLM Procedure

Level of Level of --------------V1-------------

Temp Moist N Mean Std Dev

T1 W1 3 6.2670000 0.24005833

T1 W2 3 5.9193333 0.08957864

T1 W3 3 5.7173333 0.03695042

T2 W1 3 5.7560000 0.60799753

T2 W2 3 5.8273333 0.06229232

T2 W3 3 7.3273333 0.21039091

T3 W1 3 7.4420000 0.18376343

T3 W2 3 9.1883333 0.28691869

T3 W3 3 10.4746667 0.44708649

Unstable sewage sludge ‘Olifantsfontein’ 09:16 Monday, March 19, 2007 7

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp V1 LSMEAN Error Pr > |t| Number

T1 5.96788889 0.09943054 <.0001 1

T2 6.30355556 0.09943054 <.0001 2

T3 9.03500000 0.09943054 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

115

1 0.0282 <.0001

2 0.0282 <.0001

3 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W1 6.48833333 0.09943054 <.0001 1

W2 6.97833333 0.09943054 <.0001 2

W3 7.83977778 0.09943054 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 0.0026 <.0001

2 0.0026 <.0001

3 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Unstable sewage sludge ‘Olifantsfontein’ 09:16 Monday, March 19, 2007 8

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T1 W1 6.2670000 0.1722187 <.0001 1

T1 W2 5.9193333 0.1722187 <.0001 2

T1 W3 5.7173333 0.1722187 <.0001 3

T2 W1 5.7560000 0.1722187 <.0001 4

T2 W2 5.8273333 0.1722187 <.0001 5

T2 W3 7.3273333 0.1722187 <.0001 6

T3 W1 7.4420000 0.1722187 <.0001 7

T3 W2 9.1883333 0.1722187 <.0001 8

T3 W3 10.4746667 0.1722187 <.0001 9

Least Squares Means for effect Temp*Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3 4 5 6 7 8 9

1 0.1706 0.0367 0.0503 0.0878 0.0004 0.0001 <.0001 <.0001

2 0.1706 0.4178 0.5110 0.7100 <.0001 <.0001 <.0001 <.0001

3 0.0367 0.4178 0.8756 0.6569 <.0001 <.0001 <.0001 <.0001

4 0.0503 0.5110 0.8756 0.7730 <.0001 <.0001 <.0001 <.0001

5 0.0878 0.7100 0.6569 0.7730 <.0001 <.0001 <.0001 <.0001

6 0.0004 <.0001 <.0001 <.0001 <.0001 0.6434 <.0001 <.0001

7 0.0001 <.0001 <.0001 <.0001 <.0001 0.6434 <.0001 <.0001

8 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

116

9 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

A

1.3

Unstable ‘Sasol’ sludge amended soil 14:05 Friday, March 19, 2007 1

Obs Temp Moist rep V1

1 T1 W1 1 6.6

2 T1 W1 2 7.0

3 T1 W1 3 6.9

4 T1 W2 1 6.4

5 T1 W2 2 6.5

6 T1 W2 3 6.6

7 T1 W3 1 4.8

8 T1 W3 2 5.2

9 T1 W3 3 5.0

10 T2 W1 1 9.7

11 T2 W1 2 9.0

12 T2 W1 3 9.6

13 T2 W2 1 6.8

14 T2 W2 2 7.2

15 T2 W2 3 7.3

16 T2 W3 1 7.0

17 T2 W3 2 6.9

18 T2 W3 3 7.4

19 T3 W1 1 5.5

20 T3 W1 2 5.7

21 T3 W1 3 5.7

22 T3 W2 1 6.2

23 T3 W2 2 6.2

24 T3 W2 3 6.0

25 T3 W3 1 7.2

26 T3 W3 2 7.4

27 T3 W3 3 7.3

Unstable sludge ‘Sasol’ 14:05 Friday, March 19, 2007 2

The GLM Procedure

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

Moist 3 W1 W2 W3

Rep 3 1 2 3

117

Number of observations 27

Unstable sludge ‘Sasol’ 14:05 Friday, March 19, 2007 3

The GLM Procedure

Dependent Variable: V1 total mineralized N

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 37.49407407 4.68675926 102.05 <.0001

Error 18 0.82666667 0.04592593

Corrected Total 26 38.32074074

R-Square Coeff Var Root MSE V1 Mean

0.978428 3.160126 0.214303 6.781481

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 16.49407407 8.24703704 179.57 <.0001

Moist 2 3.68518519 1.84259259 40.12 <.0001

Temp*Moist 4 17.31481481 4.32870370 94.25 <.0001

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 16.49407407 8.24703704 179.57 <.0001

Moist 2 3.68518519 1.84259259 40.12 <.0001

Temp*Moist 4 17.31481481 4.32870370 94.25 <.0001

Unstable sludge ‘Sasol’ 14:05 Friday, March 19, 2007 4

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.045926

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.2578

Means with the same letter are not significantly different.

118

Tukey Grouping Mean N Temp

A 7.8778 9 T2

B 6.3556 9 T3

B 6.1111 9 T1

Unstable sludge ‘Sasol’ 14:05 Friday, March 19, 2007 5

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.045926

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.2578

Means with the same letter are not significantly different.

Tukey Grouping Mean N Moist

A 7.3000 9 W1

B 6.5778 9 W2

B 6.4667 9 W3

Unstable sludge ‘Sasol’ 14:05 Friday, March 19, 2007 6

The GLM Procedure

Level of Level of --------------V1-------------

Temp Moist N Mean Std Dev

T1 W1 3 6.83333333 0.20816660

T1 W2 3 6.50000000 0.10000000

T1 W3 3 5.00000000 0.20000000

T2 W1 3 9.43333333 0.37859389

T2 W2 3 7.10000000 0.26457513

T2 W3 3 7.10000000 0.26457513

T3 W1 3 5.63333333 0.11547005

T3 W2 3 6.13333333 0.11547005

T3 W3 3 7.30000000 0.10000000

Unstable sewage sludge ‘Sasol’ 14:05 Friday, March 19, 2007 7

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp V1 LSMEAN Error Pr > |t| Number

T1 6.11111111 0.07143445 <.0001 1

T2 7.87777778 0.07143445 <.0001 2

T3 6.35555556 0.07143445 <.0001 3

119

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 <.0001 0.0263

2 <.0001 <.0001

3 0.0263 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W1 7.30000000 0.07143445 <.0001 1

W2 6.57777778 0.07143445 <.0001 2

W3 6.46666667 0.07143445 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 0.2859

3 <.0001 0.2859

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Unstable sludge ‘Sasol’ 14:05 Friday, March 19, 2007 8

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T1 W1 6.83333333 0.12372810 <.0001 1

T1 W2 6.50000000 0.12372810 <.0001 2

T1 W3 5.00000000 0.12372810 <.0001 3

T2 W1 9.43333333 0.12372810 <.0001 4

T2 W2 7.10000000 0.12372810 <.0001 5

T2 W3 7.10000000 0.12372810 <.0001 6

T3 W1 5.63333333 0.12372810 <.0001 7

T3 W2 6.13333333 0.12372810 <.0001 8

T3 W3 7.30000000 0.12372810 <.0001 9

Least Squares Means for effect Temp*Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3 4 5 6 7 8 9

1 0.0729 <.0001 <.0001 0.1449 0.1449 <.0001 0.0008 0.0157

120

2 0.0729 <.0001 <.0001 0.0030 0.0030 0.0001 0.0505 0.0002

3 <.0001 <.0001 <.0001 <.0001 <.0001 0.0020 <.0001 <.0001

4 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

5 0.1449 0.0030 <.0001 <.0001 1.0000 <.0001 <.0001 0.2680

6 0.1449 0.0030 <.0001 <.0001 1.0000 <.0001 <.0001 0.2680

7 <.0001 0.0001 0.0020 <.0001 <.0001 <.0001 0.0105 <.0001

8 0.0008 0.0505 <.0001 <.0001 <.0001 <.0001 0.0105 <.0001

9 0.0157 0.0002 <.0001 <.0001 0.2680 0.2680 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

A

2

Statistical analysis for temperature and water potential on NH

4

+

and NO

3

-

A

2.1

Stable „Vlakplaas‟ sewage sludge amended soil

A 2.1.1 Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 1

Obs Temp Mois Rep VI

1 T1 W1 1 0.650

2 T1 W1 2 0.602

3 T1 W1 3 0.554

4 T1 W2 1 0.671

5 T1 W2 2 0.838

6 T1 W2 3 0.599

7 T1 W3 1 0.822

8 T1 W3 2 0.782

9 T1 W3 3 0.790

10 T2 W1 1 0.066

11 T2 W1 2 0.066

12 T2 W1 3 0.066

13 T2 W2 1 0.033

14 T2 W2 2 0.033

15 T2 W2 3 0.033

16 T2 W3 1 0.113

17 T2 W3 2 0.113

18 T2 W3 3 0.113

19 T3 W1 1 3.115

20 T3 W1 2 2.996

21 T3 W1 3 3.055

22 T3 W2 1 2.958

23 T3 W2 2 3.526

24 T3 W2 3 2.906

25 T3 W3 1 3.324

121

26 T3 W3 2 3.249

27 T3 W3 3 3.259

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 2

The GLM Procedure

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

Mois 3 W1 W2 W3

Rep 3 1 2 3

VI 21 0.033 0.066 0.113 0.554 0.599 0.602 0.65 0.671 0.782 0.79 0.822 0.838 2.906

2.958 2.996 3.055 3.115 3.249 3.259 3.324 3.526

Number of observations 27

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 3

The GLM Procedure

Dependent Variable: VI NH

4

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 47.91692052 5.98961506 381.58 <.0001

Error 18 0.28254200 0.01569678

Corrected Total 26 48.19946252

R-Square Coeff Var Root MSE VI Mean

0.994138 9.574163 0.125287 1.308593

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 47.77301807 23.88650904 1521.75 <.0001

Mois 2 0.11353252 0.05676626 3.62 0.0478

Temp*Mois 4 0.03036993 0.00759248 0.48 0.7475

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 47.77301807 23.88650904 1521.75 <.0001

Mois 2 0.11353252 0.05676626 3.62 0.0478

Temp*Mois 4 0.03036993 0.00759248 0.48 0.7475

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 4

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

122

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.015697

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.1507

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 3.15422 9 T3

B 0.70089 9 T1

C 0.07067 9 T2

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 5

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.015697

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.1507

Means with the same letter are not significantly different.

Tukey Grouping Mean N Mois

A 1.39611 9 W3

B A 1.28856 9 W2

B 1.24111 9 W1

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 6

The GLM Procedure

Level of Level of --------------VI-------------

Temp Mois N Mean Std Dev

T1 W1 3 0.60200000 0.04800000

T1 W2 3 0.70266667 0.12260642

T1 W3 3 0.79800000 0.02116601

T2 W1 3 0.06600000 0.00000000

T2 W2 3 0.03300000 0.00000000

T2 W3 3 0.11300000 0.00000000

T3 W1 3 3.05533333 0.05950070

T3 W2 3 3.13000000 0.34393023

T3 W3 3 3.27733333 0.04072264

123

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 7

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp VI LSMEAN Error Pr > |t| Number

T1 0.70088889 0.04176226 <.0001 1

T2 0.07066667 0.04176226 0.1079 2

T3 3.15422222 0.04176226 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 <.0001

3 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Mois VI LSMEAN Error Pr > |t| Number

W1 1.24111111 0.04176226 <.0001 1

W2 1.28855556 0.04176226 <.0001 2

W3 1.39611111 0.04176226 <.0001 3

Least Squares Means for effect Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3

1 0.4323 0.0172

2 0.4323 0.0853

3 0.0172 0.0853

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Effect of temperature and moist on NH

4

release-day 56 08:00 Sunday, November 28, 2008 8

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Mois VI LSMEAN Error Pr > |t| Number

T1 W1 0.60200000 0.07233436 <.0001 1

T1 W2 0.70266667 0.07233436 <.0001 2

124

T1 W3 0.79800000 0.07233436 <.0001 3

T2 W1 0.06600000 0.07233436 0.3736 4

T2 W2 0.03300000 0.07233436 0.6537 5

T2 W3 0.11300000 0.07233436 0.1357 6

T3 W1 3.05533333 0.07233436 <.0001 7

T3 W2 3.13000000 0.07233436 <.0001 8

T3 W3 3.27733333 0.07233436 <.0001 9

Least Squares Means for effect Temp*Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3 4 5 6 7 8 9

1 0.3381 0.0714 <.0001 <.0001 0.0001 <.0001 <.0001 <.0001

2 0.3381 0.3637 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

3 0.0714 0.3637 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

4 <.0001 <.0001 <.0001 0.7507 0.6514 <.0001 <.0001 <.0001

5 <.0001 <.0001 <.0001 0.7507 0.4444 <.0001 <.0001 <.0001

6 0.0001 <.0001 <.0001 0.6514 0.4444 <.0001 <.0001 <.0001

7 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.4748 0.0436

8 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.4748 0.1670

9 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0436 0.1670

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 9

The UNIVARIATE Procedure

Variable: VI (NH4)

Moments

N 27 Sum Weights 27

Mean 1.30859259 Sum Observations 35.332

Std Deviation 1.3615526 Variance 1.85382548

Skewness 0.64353633 Kurtosis -1.491104

Uncorrected SS 94.434656 Corrected SS 48.1994625

Coeff Variation 104.047097 Std Error Mean 0.26203092

Basic Statistical Measures

Location Variability

Mean 1.308593 Std Deviation 1.36155

Median 0.671000 Variance 1.85383

Mode 0.033000 Range 3.49300

Interquartile Range 2.88300

NOTE: The mode displayed is the smallest of 3 modes with a count of 3.

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 4.994039 Pr > |t| <.0001

125

Sign M 13.5 Pr >= |M| <.0001

Signed Rank S 189 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.765424 Pr < W <0.0001

Kolmogorov-Smirnov D 0.301856 Pr > D <0.0100

Cramer-von Mises W-Sq 0.490143 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 2.769634 Pr > A-Sq <0.0050

Quantiles (Definition 5)

Quantile Estimate

100% Max 3.526

99% 3.526

95% 3.324

90% 3.259

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 10

The UNIVARIATE Procedure

Variable: VI (NH4)

Quantiles (Definition 5)

Quantile Estimate

75% Q3 2.996

50% Median 0.671

25% Q1 0.113

10% 0.033

5% 0.033

1% 0.033

0% Min 0.033

Extreme Observations

-----Lowest---- ----Highest----

Value Obs Value Obs

0.033 15 3.115 19

0.033 14 3.249 26

0.033 13 3.259 27

0.066 12 3.324 25

0.066 11 3.526 23

Frequency Counts

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

126

0.033 3 11.1 11.1 0.671 1 3.7 51.9 2.996 1 3.7 77.8

0.066 3 11.1 22.2 0.782 1 3.7 55.6 3.055 1 3.7 81.5

0.113 3 11.1 33.3 0.790 1 3.7 59.3 3.115 1 3.7 85.2

0.554 1 3.7 37.0 0.822 1 3.7 63.0 3.249 1 3.7 88.9

0.599 1 3.7 40.7 0.838 1 3.7 66.7 3.259 1 3.7 92.6

0.602 1 3.7 44.4 2.906 1 3.7 70.4 3.324 1 3.7 96.3

0.650 1 3.7 48.1 2.958 1 3.7 74.1 3.526 1 3.7 100.0

127

Effect of temperature and moist on NH

4

release 08:00 Sunday, November 28, 2008 11

The UNIVARIATE Procedure

Variable: VI (NH4)

Stem Leaf # Boxplot

3 5 1 |

3 0011233 7 +-----+

2 9 1 | |

2 | |

1 | |

1 | + |

0 666678888 9 *-----*

0 000111111 9 +-----+

----+----+----+----+

Normal Probability Plot

3.75+ +++*

| * ** *++*

| *** ++++

| +++

| ++++

| ++++

| +*********

0.25+ * * * * +**+*

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

A 2.1.2 Effect of temperature and moist on NO

3

release 08:50 Sunday, November 28, 2008 1

Obs Temp Mois Rep VI

1 T1 W1 1 2.554

2 T1 W1 2 2.634

3 T1 W1 3 2.602

4 T1 W2 1 2.055

5 T1 W2 2 1.956

6 T1 W2 3 1.964

7 T1 W3 1 2.912

8 T1 W3 2 3.031

9 T1 W3 3 3.043

10 T2 W1 1 2.944

11 T2 W1 2 2.992

12 T2 W1 3 2.864

13 T2 W2 1 2.642

14 T2 W2 2 2.602

15 T2 W2 3 2.638

16 T2 W3 1 2.410

17 T2 W3 2 2.609

18 T2 W3 3 2.530

19 T3 W1 1 0.095

20 T3 W1 2 0.334

21 T3 W1 3 0.164

22 T3 W2 1 0.151

23 T3 W2 2 0.191

24 T3 W2 3 0.151

25 T3 W3 1 0.273

26 T3 W3 2 0.193

27 T3 W3 3 0.205

128

Effect of temperature and moist on NO

3

08:50 Sunday, November 28, 2008 2

The GLM Procedure

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

Mois 3 W1 W2 W3

Rep 3 1 2 3

VI 25 0.095 0.151 0.164 0.191 0.193 0.205 0.273 0.334 1.956 1.964 2.055 2.41 2.53

2.554 2.602 2.609 2.634 2.638 2.642 2.864 2.912 2.944 2.992 3.031 3.043

Number of observations 27

Effect of temperature and moist on NO

3

release 08:50 Sunday, November 28, 2008 3

The GLM Procedure

Dependent Variable: VI NO3

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 36.92927941 4.61615993 986.31 <.0001

Error 18 0.08424400 0.00468022

Corrected Total 26 37.01352341

R-Square Coeff Var Root MSE VI Mean

0.997724 3.789836 0.068412 1.805148

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 35.11181896 17.55590948 3751.08 <.0001

Mois 2 0.59937607 0.29968804 64.03 <.0001

Temp*Mois 4 1.21808437 0.30452109 65.07 <.0001

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 35.11181896 17.55590948 3751.08 <.0001

Mois 2 0.59937607 0.29968804 64.03 <.0001

Temp*Mois 4 1.21808437 0.30452109 65.07 <.0001

Effect of temperature and moist on NO

3

release 08:50 Sunday, November 28, 2008

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

129

Error Degrees of Freedom 18

Error Mean Square 0.00468

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.0823

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 2.69233 9 T2

B 2.52789 9 T1

C 0.19522 9 T3

Effect of temperature and moist on NO

3

release 08:50 Sunday, November 28, 2008 5

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.00468

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.0823

Means with the same letter are not significantly different.

Tukey Grouping Mean N Mois

A 1.91178 9 W3

A 1.90922 9 W1

B 1.59444 9 W2

Effect of temperature and moist on NO

3

release 08:50 Sunday, November 28, 2008 6

The GLM Procedure

Level of Level of --------------VI-------------

Temp Mois N Mean Std Dev

T1 W1 3 2.59666667 0.04026578

T1 W2 3 1.99166667 0.05499394

T1 W3 3 2.99533333 0.07241777

T2 W1 3 2.93333333 0.06466323

T2 W2 3 2.62733333 0.02203028

T2 W3 3 2.51633333 0.10020146

T3 W1 3 0.19766667 0.12300542

T3 W2 3 0.16433333 0.02309401

T3 W3 3 0.22366667 0.04314317

Effect of temperature and moist on NO

3

release 08:50 Sunday, November 28, 2008 7

The GLM Procedure

130

Least Squares Means

Standard LSMEAN

Temp VI LSMEAN Error Pr > |t| Number

T1 2.52788889 0.02280405 <.0001 1

T2 2.69233333 0.02280405 <.0001 2

T3 0.19522222 0.02280405 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 <.0001

3 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Mois VI LSMEAN Error Pr > |t| Number

W1 1.90922222 0.02280405 <.0001 1

W2 1.59444444 0.02280405 <.0001 2

W3 1.91177778 0.02280405 <.0001 3

Least Squares Means for effect Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3

1 <.0001 0.9377

2 <.0001 <.0001

3 0.9377 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Effect of temperature and moist on NO3 release 08:50 Sunday, November 28, 2008 8

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Mois VI LSMEAN Error Pr > |t| Number

T1 W1 2.59666667 0.03949777 <.0001 1

T1 W2 1.99166667 0.03949777 <.0001 2

T1 W3 2.99533333 0.03949777 <.0001 3

T2 W1 2.93333333 0.03949777 <.0001 4

T2 W2 2.62733333 0.03949777 <.0001 5

T2 W3 2.51633333 0.03949777 <.0001 6

T3 W1 0.19766667 0.03949777 <.0001 7

T3 W2 0.16433333 0.03949777 0.0006 8

T3 W3 0.22366667 0.03949777 <.0001 9

131

Least Squares Means for effect Temp*Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3 4 5 6 7 8 9

1 <.0001 <.0001 <.0001 0.5897 0.1675 <.0001 <.0001 <.0001

2 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

3 <.0001 <.0001 0.2816 <.0001 <.0001 <.0001 <.0001 <.0001

4 <.0001 <.0001 0.2816 <.0001 <.0001 <.0001 <.0001 <.0001

5 0.5897 <.0001 <.0001 <.0001 0.0623 <.0001 <.0001 <.0001

6 0.1675 <.0001 <.0001 <.0001 0.0623 <.0001 <.0001 <.0001

7 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.5581 0.6472

8 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.5581 0.3022

9 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.6472 0.3022

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Effect of temperature and moist on NO3 release-day 56 08:50 Sunday, November 28, 2008 9

The UNIVARIATE Procedure

Variable: VI (NO3)

Moments

N 27 Sum Weights 27

Mean 1.80514815 Sum Observations 48.739

Std Deviation 1.19314586 Variance 1.42359705

Skewness -0.5870878 Kurtosis -1.5745519

Uncorrected SS 124.994639 Corrected SS 37.0135234

Coeff Variation 66.096839 Std Error Mean 0.22962103

Basic Statistical Measures

Location Variability

Mean 1.805148 Std Deviation 1.19315

Median 2.530000 Variance 1.42360

Mode 0.151000 Range 2.94800

Interquartile Range 2.43700

NOTE: The mode displayed is the smallest of 2 modes with a count of 2.

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 7.861423 Pr > |t| <.0001

Sign M 13.5 Pr >= |M| <.0001

Signed Rank S 189 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.764426 Pr < W <0.0001

Kolmogorov-Smirnov D 0.249457 Pr > D <0.0100

Cramer-von Mises W-Sq 0.459846 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 2.75771 Pr > A-Sq <0.0050

132

Quantiles (Definition 5)

Quantile Estimate

100% Max 3.043

99% 3.043

95% 3.031

90% 2.992

Effect of temperature and moist on NO3 release 08:50 Sunday, November 28, 2008 10

The UNIVARIATE Procedure

Variable: VI (NO

3

)

Quantiles (Definition 5)

Quantile Estimate

75% Q3 2.642

50% Median 2.530

25% Q1 0.205

10% 0.151

5% 0.151

1% 0.095

0% Min 0.095

Extreme Observations

-----Lowest---- ----Highest----

Value Obs Value Obs

0.095 19 2.912 7

0.151 24 2.944 10

0.151 22 2.992 11

0.164 21 3.031 8

0.191 23 3.043 9

Frequency Counts

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

0.095 1 3.7 3.7 1.964 1 3.7 40.7 2.638 1 3.7 74.1

0.151 2 7.4 11.1 2.055 1 3.7 44.4 2.642 1 3.7 77.8

0.164 1 3.7 14.8 2.410 1 3.7 48.1 2.864 1 3.7 81.5

0.191 1 3.7 18.5 2.530 1 3.7 51.9 2.912 1 3.7 85.2

0.193 1 3.7 22.2 2.554 1 3.7 55.6 2.944 1 3.7 88.9

0.205 1 3.7 25.9 2.602 2 7.4 63.0 2.992 1 3.7 92.6

0.273 1 3.7 29.6 2.609 1 3.7 66.7 3.031 1 3.7 96.3

0.334 1 3.7 33.3 2.634 1 3.7 70.4 3.043 1 3.7 100.0

1.956 1 3.7 37.0

Effect of temperature and moist on NO3 release 08:50 Sunday, November 28, 2008 11

133

The UNIVARIATE Procedure

Variable: VI (NO3)

Stem Leaf # Boxplot

3 000 3 |

2 56666666999 11 +-----+

2 0014 4 | |

1 | + |

1 | |

0 | |

0 122222233 9 +-----+

----+----+----+----+

Normal Probability Plot

3.25+ ++++ * *

| *** *****+** *

| ** ++++

1.75+ **++++

| ++++

| ++++

0.25+ * *++++** ****

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

A

2.2

Unstable ‘Olifantsfontein’ sewage sludge amended soil NH

4

+

and NO

3

-

Effect of temperature and moist on NH

4

and NO

3 release 12:58 Sunday, December 12, 2008 1

Obs Temp Moist Rep V1 V2

1 T1 W1 1 5.842 0.265

2 T1 W1 2 6.201 0.186

3 T1 W1 3 6.041 0.265

4 T1 W2 1 5.773 0.040

5 T1 W2 2 5.813 0.159

6 T1 W2 3 5.773 0.159

7 T1 W3 1 5.494 0.345

8 T1 W3 2 5.391 0.225

9 T1 W3 3 5.431 0.265

10 T2 W1 1 4.183 1.300

11 T2 W1 2 5.111 1.180

12 T2 W1 3 4.274 1.220

13 T2 W2 1 5.364 0.383

14 T2 W2 2 5.404 0.483

15 T2 W2 3 5.404 0.443

16 T2 W3 1 6.626 0.848

17 T2 W3 2 6.466 0.728

18 T2 W3 3 6.546 0.768

19 T3 W1 1 7.014 0.223

20 T3 W1 2 7.452 0.143

21 T3 W1 3 7.293 0.203

22 T3 W2 1 8.711 0.172

23 T3 W2 2 9.069 0.133

24 T3 W2 3 9.308 0.172

25 T3 W3 1 10.490 0.146

26 T3 W3 2 10.730 0.106

27 T3 W3 3 9.852 0.106

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 2

The GLM Procedure

134

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

Moist 3 W1 W2 W3

Rep 3 1 2 3

V1 25 4.183 4.274 5.111 5.364 5.391 5.404 5.431 5.494 5.773 5.813 5.842 6.041 6.201

6.466 6.546 6.626 7.014 7.293 7.452 8.711 9.069 9.308 9.852 10.49 10.73

V2 22 0.04 0.106 0.133 0.143 0.146 0.159 0.172 0.186 0.203 0.223 0.225 0.265 0.345

0.383 0.443 0.483 0.728 0.768 0.848 1.18 1.22 1.3

Number of observations 27

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 3

The GLM Procedure

Dependent Variable: V1 NH

4

,

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 85.39071667 10.67383958 147.89 <.0001

Error 18 1.29909400 0.07217189

Corrected Total 26 86.68981067

R-Square Coeff Var Root MSE V1 Mean

0.985014 4.006221 0.268648 6.705778

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 64.12620156 32.06310078 444.26 <.0001

Moist 2 10.31011622 5.15505811 71.43 <.0001

Temp*Moist 4 10.95439889 2.73859972 37.95 <.0001

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 64.12620156 32.06310078 444.26 <.0001

Moist 2 10.31011622 5.15505811 71.43 <.0001

Temp*Moist 4 10.95439889 2.73859972 37.95 <.0001

Effect of temperature and moist on NH

4

and NO

3

release 12:58 Sunday, December 12, 2008 4

The GLM Procedure

Dependent Variable: V2 NO

3

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 8 3.42497363 0.42812170 165.31 <.0001

Error 18 0.04661533 0.00258974

135

Corrected Total 26 3.47158896

R-Square Coeff Var Root MSE V2 Mean

0.986572 12.88221 0.050889 0.395037

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 2.41788007 1.20894004 466.82 <.0001

Moist 2 0.44846052 0.22423026 86.58 <.0001

Temp*Moist 4 0.55863304 0.13965826 53.93 <.0001

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 2.41788007 1.20894004 466.82 <.0001

Moist 2 0.44846052 0.22423026 86.58 <.0001

Temp*Moist 4 0.55863304 0.13965826 53.93 <.0001

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 5

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.072172

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.3232

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 8.8799 9 T3

B 5.7510 9 T1

B 5.4864 9 T2

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 6

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V2

136

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.00259

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.0612

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 0.81700 9 T2

B 0.21211 9 T1

B 0.15600 9 T3

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 7

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.072172

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.3232

Means with the same letter are not significantly different.

Tukey Grouping Mean N Moist

A 7.4473 9 W3

B 6.7354 9 W2

C 5.9346 9 W1

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 8

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V2

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 18

Error Mean Square 0.00259

Critical Value of Studentized Range 3.60930

Minimum Significant Difference 0.0612

Means with the same letter are not significantly different.

137

Tukey Grouping Mean N Moist

A 0.55389 9 W1

B 0.39300 9 W3

C 0.23822 9 W2

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 9

The GLM Procedure

Level of Level of --------------V1------------- --------------V2-------------

Temp Moist N Mean Std Dev Mean Std Dev

T1 W1 3 6.0280000 0.17985272 0.23866667 0.04561067

T1 W2 3 5.7863333 0.02309401 0.11933333 0.06870468

T1 W3 3 5.4386667 0.05192623 0.27833333 0.06110101

T2 W1 3 4.5226667 0.51153918 1.23333333 0.06110101

T2 W2 3 5.3906667 0.02309401 0.43633333 0.05033223

T2 W3 3 6.5460000 0.08000000 0.78133333 0.06110101

T3 W1 3 7.2530000 0.22172280 0.18966667 0.04163332

T3 W2 3 9.0293333 0.30047019 0.15900000 0.02251666

T3 W3 3 10.3573333 0.45378556 0.11933333 0.02309401

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 10

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp V1 LSMEAN Error Pr > |t| Number

T1 5.75100000 0.08954942 <.0001 1

T2 5.48644444 0.08954942 <.0001 2

T3 8.87988889 0.08954942 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 0.0512 <.0001

2 0.0512 <.0001

3 <.0001 <.0001

Standard LSMEAN

Temp V2 LSMEAN Error Pr > |t| Number

T1 0.21211111 0.01696317 <.0001 1

T2 0.81700000 0.01696317 <.0001 2

T3 0.15600000 0.01696317 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

138

Dependent Variable: V2

i/j 1 2 3

1 <.0001 0.0311

2 <.0001 <.0001

3 0.0311 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W1 5.93455556 0.08954942 <.0001 1

W2 6.73544444 0.08954942 <.0001 2

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 11

The GLM Procedure

Least Squares Means

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W3 7.44733333 0.08954942 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 <.0001

3 <.0001 <.0001

Standard LSMEAN

Moist V2 LSMEAN Error Pr > |t| Number

W1 0.55388889 0.01696317 <.0001 1

W2 0.23822222 0.01696317 <.0001 2

W3 0.39300000 0.01696317 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V2

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 <.0001

3 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

139

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T1 W1 6.0280000 0.1551041 <.0001 1

T1 W2 5.7863333 0.1551041 <.0001 2

T1 W3 5.4386667 0.1551041 <.0001 3

T2 W1 4.5226667 0.1551041 <.0001 4

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 12

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T2 W2 5.3906667 0.1551041 <.0001 5

T2 W3 6.5460000 0.1551041 <.0001 6

T3 W1 7.2530000 0.1551041 <.0001 7

T3 W2 9.0293333 0.1551041 <.0001 8

T3 W3 10.3573333 0.1551041 <.0001 9

Least Squares Means for effect Temp*Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3 4 5 6 7 8 9

1 0.2851 0.0151 <.0001 0.0094 0.0297 <.0001 <.0001 <.0001

2 0.2851 0.1304 <.0001 0.0880 0.0028 <.0001 <.0001 <.0001

3 0.0151 0.1304 0.0006 0.8292 <.0001 <.0001 <.0001 <.0001

4 <.0001 <.0001 0.0006 0.0009 <.0001 <.0001 <.0001 <.0001

5 0.0094 0.0880 0.8292 0.0009 <.0001 <.0001 <.0001 <.0001

6 0.0297 0.0028 <.0001 <.0001 <.0001 0.0047 <.0001 <.0001

7 <.0001 <.0001 <.0001 <.0001 <.0001 0.0047 <.0001 <.0001

8 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

9 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

Standard LSMEAN

Temp Moist V2 LSMEAN Error Pr > |t| Number

T1 W1 0.23866667 0.02938106 <.0001 1

T1 W2 0.11933333 0.02938106 0.0007 2

T1 W3 0.27833333 0.02938106 <.0001 3

T2 W1 1.23333333 0.02938106 <.0001 4

T2 W2 0.43633333 0.02938106 <.0001 5

T2 W3 0.78133333 0.02938106 <.0001 6

T3 W1 0.18966667 0.02938106 <.0001 7

T3 W2 0.15900000 0.02938106 <.0001 8

T3 W3 0.11933333 0.02938106 0.0007 9

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 13

The GLM Procedure

Least Squares Means

Least Squares Means for effect Temp*Moist

140

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V2

i/j 1 2 3 4 5 6 7 8 9

1 0.0101 0.3524 <.0001 0.0002 <.0001 0.2536 0.0712 0.0101

2 0.0101 0.0012 <.0001 <.0001 <.0001 0.1078 0.3524 1.0000

3 0.3524 0.0012 <.0001 0.0013 <.0001 0.0469 0.0101 0.0012

4 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

5 0.0002 <.0001 0.0013 <.0001 <.0001 <.0001 <.0001 <.0001

6 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

7 0.2536 0.1078 0.0469 <.0001 <.0001 <.0001 0.4700 0.1078

8 0.0712 0.3524 0.0101 <.0001 <.0001 <.0001 0.4700 0.3524

9 0.0101 1.0000 0.0012 <.0001 <.0001 <.0001 0.1078 0.3524

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 14

The UNIVARIATE Procedure

Variable: V1 (NH4,)

Moments

N 27 Sum Weights 27

Mean 6.70577778 Sum Observations 181.056

Std Deviation 1.82598562 Variance 3.33422349

Skewness 0.9495203 Kurtosis -0.0641734

Uncorrected SS 1300.81111 Corrected SS 86.6898107

Coeff Variation 27.2300348 Std Error Mean 0.3514111

Basic Statistical Measures

Location Variability

Mean 6.705778 Std Deviation 1.82599

Median 6.041000 Variance 3.33422

Mode 5.404000 Range 6.54700

Interquartile Range 2.04800

NOTE: The mode displayed is the smallest of 2 modes with a count of 2.

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 19.08243 Pr > |t| <.0001

Sign M 13.5 Pr >= |M| <.0001

Signed Rank S 189 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.883629 Pr < W 0.0058

Kolmogorov-Smirnov D 0.184091 Pr > D 0.0194

Cramer-von Mises W-Sq 0.238222 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 1.310152 Pr > A-Sq <0.0050

141

Quantiles (Definition 5)

Quantile Estimate

100% Max 10.730

99% 10.730

95% 10.490

90% 9.852

Effect of temperature and moist on NH

4

and NO

3

release 12:58 Sunday, December 12, 2008 15

The UNIVARIATE Procedure

Variable: V1 (NH4,)

Quantiles (Definition 5)

Quantile Estimate

75% Q3 7.452

50% Median 6.041

25% Q1 5.404

10% 5.111

5% 4.274

1% 4.183

0% Min 4.183

Extreme Observations

-----Lowest---- -----Highest----

Value Obs Value Obs

4.183 10 9.069 23

4.274 12 9.308 24

5.111 11 9.852 27

5.364 13 10.490 25

5.391 8 10.730 26

Frequency Counts

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

4.183 1 3.7 3.7 5.813 1 3.7 44.4 7.293 1 3.7 74.1

4.274 1 3.7 7.4 5.842 1 3.7 48.1 7.452 1 3.7 77.8

5.111 1 3.7 11.1 6.041 1 3.7 51.9 8.711 1 3.7 81.5

5.364 1 3.7 14.8 6.201 1 3.7 55.6 9.069 1 3.7 85.2

5.391 1 3.7 18.5 6.466 1 3.7 59.3 9.308 1 3.7 88.9

5.404 2 7.4 25.9 6.546 1 3.7 63.0 9.852 1 3.7 92.6

5.431 1 3.7 29.6 6.626 1 3.7 66.7 10.490 1 3.7 96.3

5.494 1 3.7 33.3 7.014 1 3.7 70.4 10.730 1 3.7 100.0

5.773 2 7.4 40.7

142

Effect of temperature and moist on NH

4 and NO

3 release 12:58 Sunday, December 12, 2008 16

The UNIVARIATE Procedure

Variable: V1 (NH

4

,)

Stem Leaf # Boxplot

10 57 2 0

9 139 3 |

8 7 1 |

7 035 3 +-----+

6 02556 5 *--+--*

5 14444458888 11 +-----+

4 23 2 |

----+----+----+----+

Normal Probability Plot

10.5+ * +*+++

| ** *+++++

| *++++

7.5+ +++***

| +++*****

| * **+*+*** **

4.5+ * * +++++

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 17

The UNIVARIATE Procedure

Variable: V2 (NO3)

Moments

N 27 Sum Weights 27

Mean 0.39503704 Sum Observations 10.666

Std Deviation 0.36540752 Variance 0.13352265

Skewness 1.48548872 Kurtosis 1.09630973

Uncorrected SS 7.685054 Corrected SS 3.47158896

Coeff Variation 92.4995586 Std Error Mean 0.07032271

Basic Statistical Measures

Location Variability

Mean 0.395037 Std Deviation 0.36541

Median 0.225000 Variance 0.13352

Mode 0.265000 Range 1.26000

Interquartile Range 0.32400

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 5.617489 Pr > |t| <.0001

Sign M 13.5 Pr >= |M| <.0001

Signed Rank S 189 Pr >= |S| <.0001

143

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.770147 Pr < W <0.0001

Kolmogorov-Smirnov D 0.26866 Pr > D <0.0100

Cramer-von Mises W-Sq 0.457782 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 2.519833 Pr > A-Sq <0.0050

Quantiles (Definition 5)

Quantile Estimate

100% Max 1.300

99% 1.300

95% 1.220

90% 1.180

75% Q3 0.483

50% Median 0.225

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 18

The UNIVARIATE Procedure

Variable: V2 (NO3)

Quantiles (Definition 5)

Quantile Estimate

25% Q1 0.159

10% 0.106

5% 0.106

1% 0.040

0% Min 0.040

Extreme Observations

-----Lowest---- ----Highest----

Value Obs Value Obs

0.040 4 0.768 18

0.106 27 0.848 16

0.106 26 1.180 11

0.133 23 1.220 12

0.143 20 1.300 10

Frequency Counts

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

0.040 1 3.7 3.7 0.203 1 3.7 44.4 0.483 1 3.7 77.8

0.106 2 7.4 11.1 0.223 1 3.7 48.1 0.728 1 3.7 81.5

0.133 1 3.7 14.8 0.225 1 3.7 51.9 0.768 1 3.7 85.2

0.143 1 3.7 18.5 0.265 3 11.1 63.0 0.848 1 3.7 88.9

0.146 1 3.7 22.2 0.345 1 3.7 66.7 1.180 1 3.7 92.6

0.159 2 7.4 29.6 0.383 1 3.7 70.4 1.220 1 3.7 96.3

0.172 2 7.4 37.0 0.443 1 3.7 74.1 1.300 1 3.7 100.0

0.186 1 3.7 40.7

144

Effect of temperature and moist on NH4 and NO3 release 12:58 Sunday, December 12, 2008 19

The UNIVARIATE Procedure

Variable: V2 (NO3)

Stem Leaf # Boxplot

12 20 2 0

10 8 1 0

8 5 1 |

6 37 2 |

4 48 2 +--+--+

2 02266648 8 *-----*

0 41134566779 11 +-----+

----+----+----+----+

Multiply Stem.Leaf by 10**-1

Normal Probability Plot

1.3+ * * +++

| * ++++++

| *+++++

0.7+ ++*+*+

| +++++**

| +++**** ***

0.1+ * * **+**+* *

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

A

2.3

Unstable Sasol sludge amended soil NH

4

+

and NO

3

-

N forms in unstable Sasol sludge amended soils 58 Monday, December 13, 2008 1

Obs Temp Moist rep V1 V2

1 T1 W1 1 6.147 0.586

145

2 T1 W1 2 6.107 0.785

3 T1 W1 3 6.186 0.705

4 T1 W2 1 5.719 0.666

5 T1 W2 2 5.958 0.634

6 T1 W2 3 5.942 0.658

7 T1 W3 1 4.181 0.657

8 T1 W3 2 4.381 0.721

9 T1 W3 3 4.269 0.705

10 T2 W1 1 0.000 10.217

11 T2 W1 2 0.000 9.141

12 T2 W1 3 0.000 9.898

13 T2 W2 1 0.000 7.169

14 T2 W2 2 0.000 7.607

15 T2 W2 3 0.000 7.647

16 T2 W3 1 0.174 7.056

17 T2 W3 2 0.214 7.016

18 T2 W3 3 0.230 7.454

19 T3 W1 1 5.313 0.178

20 T3 W1 2 5.465 0.226

21 T3 W1 3 5.544 0.210

22 T3 W2 1 6.050 0.168

23 T3 W2 2 5.970 0.208

24 T3 W2 3 5.890 0.188

25 T3 W3 1 7.230 0.111

26 T3 W3 2 7.390 0.095

27 T3 W3 3 7.230 0.079

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 2

The GLM Procedure

Class Level Information

Class Levels Values

Temp 3 T1 T2 T3

Moist 3 W1 W2 W3 rep 3 1 2 3

V1 21 0 0.174 0.214 0.23 4.181 4.269 4.381 5.313 5.465 5.544 5.719 5.89 5.942 5.958

5.97 6.05 6.107 6.147 6.186 7.23 7.39

V2 26 0.079 0.095 0.111 0.168 0.178 0.188 0.208 0.21 0.226 0.586 0.634 0.657 0.658

0.666 0.705 0.721 0.785 7.016 7.056 7.169 7.454 7.607 7.647 9.141 9.898 10.217

Number of observations 27

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 3

The GLM Procedure

Dependent Variable: V1 NH

4

,

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 10 213.7838917 21.3783892 3737.42 <.0001

Error 16 0.0915215 0.0057201

Corrected Total 26 213.8754132

R-Square Coeff Var Root MSE V1 Mean

0.999572 1.933938 0.075631 3.910741

146

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 202.1543016 101.0771508 17670.5 <.0001

Moist 2 0.0344281 0.0172140 3.01 0.0777

Temp*Moist 4 11.5686655 2.8921664 505.62 <.0001

rep 2 0.0264965 0.0132483 2.32 0.1308

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 202.1543016 101.0771508 17670.5 <.0001

Moist 2 0.0344281 0.0172140 3.01 0.0777

Temp*Moist 4 11.5686655 2.8921664 505.62 <.0001

rep 2 0.0264965 0.0132483 2.32 0.1308

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 4

The GLM Procedure

Dependent Variable: V2 NO

3

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 10 370.1365704 37.0136570 719.47 <.0001

Error 16 0.8231346 0.0514459

Corrected Total 26 370.9597050

R-Square Coeff Var Root MSE V2 Mean

0.997781 7.580685 0.226817 2.992037

Source DF Type I SS Mean Square F Value Pr > F

Temp 2 358.1249639 179.0624819 3480.60 <.0001

Moist 2 4.2575299 2.1287649 41.38 <.0001

Temp*Moist 4 7.6830899 1.9207725 37.34 <.0001

rep 2 0.0709867 0.0354934 0.69 0.5159

147

Source DF Type III SS Mean Square F Value Pr > F

Temp 2 358.1249639 179.0624819 3480.60 <.0001

Moist 2 4.2575299 2.1287649 41.38 <.0001

Temp*Moist 4 7.6830899 1.9207725 37.34 <.0001

rep 2 0.0709867 0.0354934 0.69 0.5159

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 5

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 16

Error Mean Square 0.00572

Critical Value of Studentized Range 3.64914

Minimum Significant Difference 0.092

Means with the same letter are not significantly different.

Tukey Grouping Mean N Temp

A 6.23133 9 T3

B 5.43222 9 T1

C 0.06867 9 T2

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 6

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V2

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 16

Error Mean Square 0.051446

Critical Value of Studentized Range 3.64914

Minimum Significant Difference 0.2759

Means with the same letter are not significantly different.

148

Tukey Grouping Mean N Temp

A 8.1339 9 T2

B 0.6797 9 T1

C 0.1626 9 T3

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 7

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V1

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 16

Error Mean Square 0.00572

Critical Value of Studentized Range 3.64914

Minimum Significant Difference 0.092

Means with the same letter are not significantly different.

Tukey Grouping Mean N Moist

A 3.94767 9 W2

A 3.92211 9 W3

A 3.86244 9 W1

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 8

The GLM Procedure

Tukey's Studentized Range (HSD) Test for V2

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 16

Error Mean Square 0.051446

Critical Value of Studentized Range 3.64914

Minimum Significant Difference 0.2759

Means with the same letter are not significantly different.

Tukey Grouping Mean N Moist

A 3.5496 9 W1

B 2.7717 9 W2

B 2.6549 9 W3

149

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 9

The GLM Procedure

Level of Level of --------------V1------------- --------------V2-------------

Temp Moist N Mean Std Dev Mean Std Dev

T1 W1 3 6.14666667 0.03950105 0.69200000 0.10013491

T1 W2 3 5.87300000 0.13360763 0.65266667 0.01665333

T1 W3 3 4.27700000 0.10023971 0.69433333 0.03330666

T2 W1 3 0.00000000 0.00000000 9.75200000 0.55265812

T2 W2 3 0.00000000 0.00000000 7.47433333 0.26518170

T2 W3 3 0.20600000 0.02884441 7.17533333 0.24215973

T3 W1 3 5.44066667 0.11740670 0.20466667 0.02444040

T3 W2 3 5.97000000 0.08000000 0.18800000 0.02000000

T3 W3 3 7.28333333 0.09237604 0.09500000 0.01600000

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 10

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp V1 LSMEAN Error Pr > |t| Number

T1 5.43222222 0.02521043 <.0001 1

T2 0.06866667 0.02521043 0.0150 2

T3 6.23133333 0.02521043 <.0001 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 <.0001

3 <.0001 <.0001

Standard LSMEAN

Temp V2 LSMEAN Error Pr > |t| Number

T1 0.67966667 0.07560564 <.0001 1

T2 8.13388889 0.07560564 <.0001 2

T3 0.16255556 0.07560564 0.0472 3

Least Squares Means for effect Temp

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V2

i/j 1 2 3

1 <.0001 0.0002

2 <.0001 <.0001

3 0.0002 <.0001

150

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W1 3.86244444 0.02521043 <.0001 1

W2 3.94766667 0.02521043 <.0001 2

N forms in unstable Sasol sewage sludge 21:58 Monday, December 13, 2008 11

The GLM Procedure

Least Squares Means

Standard LSMEAN

Moist V1 LSMEAN Error Pr > |t| Number

W3 3.92211111 0.02521043 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3

1 0.0295 0.1137

2 0.0295 0.4838

3 0.1137 0.4838

Standard LSMEAN

Moist V2 LSMEAN Error Pr > |t| Number

W1 3.54955556 0.07560564 <.0001 1

W2 2.77166667 0.07560564 <.0001 2

W3 2.65488889 0.07560564 <.0001 3

Least Squares Means for effect Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V2

i/j 1 2 3

1 <.0001 <.0001

2 <.0001 0.2909

3 <.0001 0.2909

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

151

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T1 W1 6.14666667 0.04366575 <.0001 1

T1 W2 5.87300000 0.04366575 <.0001 2

T1 W3 4.27700000 0.04366575 <.0001 3

T2 W1 -0.00000000 0.04366575 1.0000 4

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 12

The GLM Procedure

Least Squares Means

Standard LSMEAN

Temp Moist V1 LSMEAN Error Pr > |t| Number

T2 W2 -0.00000000 0.04366575 1.0000 5

T2 W3 0.20600000 0.04366575 0.0002 6

T3 W1 5.44066667 0.04366575 <.0001 7

T3 W2 5.97000000 0.04366575 <.0001 8

T3 W3 7.28333333 0.04366575 <.0001 9

Least Squares Means for effect Temp*Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V1

i/j 1 2 3 4 5 6 7 8 9

1 0.0004 <.0001 <.0001 <.0001 <.0001 <.0001 0.0113 <.0001

2 0.0004 <.0001 <.0001 <.0001 <.0001 <.0001 0.1358 <.0001

3 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

4 <.0001 <.0001 <.0001 1.0000 0.0042 <.0001 <.0001 <.0001

5 <.0001 <.0001 <.0001 1.0000 0.0042 <.0001 <.0001 <.0001

6 <.0001 <.0001 <.0001 0.0042 0.0042 <.0001 <.0001 <.0001

7 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

8 0.0113 0.1358 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

9 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

Standard LSMEAN

Temp Moist V2 LSMEAN Error Pr > |t| Number

T1 W1 0.69200000 0.13095281 <.0001 1

T1 W2 0.65266667 0.13095281 0.0001 2

T1 W3 0.69433333 0.13095281 <.0001 3

T2 W1 9.75200000 0.13095281 <.0001 4

T2 W2 7.47433333 0.13095281 <.0001 5

T2 W3 7.17533333 0.13095281 <.0001 6

T3 W1 0.20466667 0.13095281 0.1376 7

T3 W2 0.18800000 0.13095281 0.1704 8

T3 W3 0.09500000 0.13095281 0.4787 9

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 13

The GLM Procedure

Least Squares Means

Least Squares Means for effect Temp*Moist

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: V2

152

i/j 1 2 3 4 5 6 7 8 9

1 0.8345 0.9901 <.0001 <.0001 <.0001 0.0181 0.0151 0.0053

2 0.8345 0.8248 <.0001 <.0001 <.0001 0.0278 0.0232 0.0083

3 0.9901 0.8248 <.0001 <.0001 <.0001 0.0177 0.0147 0.0052

4 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

5 <.0001 <.0001 <.0001 <.0001 0.1260 <.0001 <.0001 <.0001

6 <.0001 <.0001 <.0001 <.0001 0.1260 <.0001 <.0001 <.0001

7 0.0181 0.0278 0.0177 <.0001 <.0001 <.0001 0.9294 0.5620

8 0.0151 0.0232 0.0147 <.0001 <.0001 <.0001 0.9294 0.6224

9 0.0053 0.0083 0.0052 <.0001 <.0001 <.0001 0.5620 0.6224

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 14

The UNIVARIATE Procedure

Variable: V1 (NH4,)

Moments

N 27 Sum Weights 27

Mean 3.91074074 Sum Observations 105.59

Std Deviation 2.86809648 Variance 8.22597743

Skewness -0.5324572 Kurtosis -1.5540873

Uncorrected SS 626.810528 Corrected SS 213.875413

Coeff Variation 73.3389573 Std Error Mean 0.55196543

Basic Statistical Measures

Location Variability

Mean 3.910741 Std Deviation 2.86810

Median 5.465000 Variance 8.22598

Mode 0.000000 Range 7.39000

Interquartile Range 5.87600

153

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 7.085119 Pr > |t| <.0001

Sign M 10.5 Pr >= |M| <.0001

Signed Rank S 115.5 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.781574 Pr < W <0.0001

Kolmogorov-Smirnov D 0.243105 Pr > D <0.0100

Cramer-von Mises W-Sq 0.426203 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 2.582121 Pr > A-Sq <0.0050

Quantiles (Definition 5)

Quantile Estimate

100% Max 7.390

99% 7.390

95% 7.230

90% 7.230

75% Q3 6.050

50% Median 5.465

N forms in unstable Sasol sewage sludge 21:58 Monday, December 13, 2008 15

The UNIVARIATE Procedure

Variable: V1 (NH4,)

Quantiles (Definition 5)

Quantile Estimate

25% Q1 0.174

10% 0.000

5% 0.000

1% 0.000

0% Min 0.000

Extreme Observations

----Lowest---- ----Highest----

Value Obs Value Obs

0 15 6.147 1

0 14 6.186 3

0 13 7.230 25

0 12 7.230 27

0 11 7.390 26

Frequency Counts

Percents Percents Percents

154

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

0.000 6 22.2 22.2 5.313 1 3.7 48.1 5.970 1 3.7 74.1

0.174 1 3.7 25.9 5.465 1 3.7 51.9 6.050 1 3.7 77.8

0.214 1 3.7 29.6 5.544 1 3.7 55.6 6.107 1 3.7 81.5

0.230 1 3.7 33.3 5.719 1 3.7 59.3 6.147 1 3.7 85.2

4.181 1 3.7 37.0 5.890 1 3.7 63.0 6.186 1 3.7 88.9

4.269 1 3.7 40.7 5.942 1 3.7 66.7 7.230 2 7.4 96.3

4.381 1 3.7 44.4 5.958 1 3.7 70.4 7.390 1 3.7 100.0

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 16

The UNIVARIATE Procedure

Variable: V1 (NH4,)

Stem Leaf # Boxplot

7 224 3 |

6 000112 6 +-----+

5 355799 6 *-----*

4 234 3 | |

3 | + |

2 | |

1 | |

0 000000222 9 +-----+

----+----+----+----+

Normal Probability Plot

7.5+ ++*+ * *

| **+**

| ********+

| *** +++

| ++++

| +++

| ++++

0.5+ * * *+** ****

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

N forms in unstable Sasol sludge 21:58 Monday, December 13, 2008 17

The UNIVARIATE Procedure

Variable: V2 (NO3)

Moments

N 27 Sum Weights 27

Mean 2.99203704 Sum Observations 80.785

Std Deviation 3.77725839 Variance 14.267681

Skewness 0.86063538 Kurtosis -1.1365031

Uncorrected SS 612.671417 Corrected SS 370.959705

Coeff Variation 126.243704 Std Error Mean 0.72693372

Basic Statistical Measures

Location Variability

Mean 2.992037 Std Deviation 3.77726

Median 0.666000 Variance 14.26768

Mode 0.705000 Range 10.13800

155

Interquartile Range 6.96100

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 4.11597 Pr > |t| 0.0003

Sign M 13.5 Pr >= |M| <.0001

Signed Rank S 189 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.705827 Pr < W <0.0001

Kolmogorov-Smirnov D 0.387156 Pr > D <0.0100

Cramer-von Mises W-Sq 0.733721 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 3.822379 Pr > A-Sq <0.0050

Quantiles (Definition 5)

Quantile Estimate

100% Max 10.217

99% 10.217

95% 9.898

90% 9.141

75% Q3 7.169

50% Median 0.666

N forms in unstable Sasol sewage sludge 21:58 Monday, December 13, 2008 18

The UNIVARIATE Procedure

Variable: V2 (NO3)

Quantiles (Definition 5)

Quantile Estimate

25% Q1 0.208

10% 0.111

5% 0.095

1% 0.079

0% Min 0.079

Extreme Observations

-----Lowest---- -----Highest----

Value Obs Value Obs

0.079 27 7.607 14

0.095 26 7.647 15

0.111 25 9.141 11

0.168 22 9.898 12

0.178 19 10.217 10

Frequency Counts

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

0.079 1 3.7 3.7 0.586 1 3.7 37.0 7.056 1 3.7 74.1

156

0.095 1 3.7 7.4 0.634 1 3.7 40.7 7.169 1 3.7 77.8

0.111 1 3.7 11.1 0.657 1 3.7 44.4 7.454 1 3.7 81.5

0.168 1 3.7 14.8 0.658 1 3.7 48.1 7.607 1 3.7 85.2

0.178 1 3.7 18.5 0.666 1 3.7 51.9 7.647 1 3.7 88.9

0.188 1 3.7 22.2 0.705 2 7.4 59.3 9.141 1 3.7 92.6

0.208 1 3.7 25.9 0.721 1 3.7 63.0 9.898 1 3.7 96.3

0.210 1 3.7 29.6 0.785 1 3.7 66.7 10.217 1 3.7 100.0

0.226 1 3.7 33.3 7.016 1 3.7 70.4

N forms in unstable Sasol sewage sludge 21:58 Monday, December 13, 2008 19

The UNIVARIATE Procedure

Variable: V2 (NO3)

Stem Leaf # Boxplot

10 2 1 |

9 19 2 |

8 |

7 012566 6 +-----+

6 | |

5 | |

4 | |

3 | + |

2 | |

1 | |

0 111222222667777778 18 *-----*

----+----+----+----+

Normal Probability Plot

10.5+ +*+

| * *++

| ++

| **** **++

| +++

5.5+ ++

| +++

| ++

| +++

| +++

0.5+ * * * ** ********** **

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

157

158

A

3

. Statistical analysis for incubation time and water potential effect on net N release

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 1

19:24 Thursday, November 25, 2008

Obs Days Mois Rep VI

1 1 W1 1 3.332

2 1 W1 2 3.173

3 1 W1 3 3.252

4 1 W2 1 3.002

5 1 W2 2 2.994

6 1 W2 3 2.998

7 1 W3 1 2.785

8 1 W3 2 2.753

9 1 W3 3 2.745

10 7 W1 1 3.141

11 7 W1 2 3.102

12 7 W1 3 3.087

13 7 W2 1 4.264

14 7 W2 2 3.390

15 7 W2 3 3.564

16 7 W3 1 3.411

17 7 W3 2 2.497

18 7 W3 3 2.791

19 14 W1 1 3.872

20 14 W1 2 3.991

21 14 W1 3 3.846

22 14 W2 1 3.784

23 14 W2 2 3.844

24 14 W2 3 3.825

25 14 W3 1 3.947

26 14 W3 2 3.804

27 14 W3 3 3.848

28 28 W1 1 2.898

29 28 W1 2 2.854

30 28 W1 3 2.963

31 28 W2 1 3.736

32 28 W2 2 3.780

33 28 W2 3 3.748

34 28 W3 1 3.448

35 28 W3 2 2.952

36 28 W3 3 3.259

37 56 W1 1 3.115

38 56 W1 2 2.996

39 56 W1 3 3.055

40 56 W2 1 2.958

41 56 W2 2 3.526

42 56 W2 3 2.906

43 56 W3 1 3.324

44 56 W3 2 3.249

45 56 W3 3 3.259

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 2

19:24 Thursday, November 25, 2008

The GLM Procedure

Class Level Information

Class Levels Values

Days 5 1 14 28 56 7

159

Mois 3 W1 W2 W3

Rep 3 1 2 3

VI 44 2.497 2.745 2.753 2.785 2.791 2.854 2.898 2.906 2.952 2.958 2.963 2.994 2.996

2.998 3.002 3.055 3.087 3.102 3.115 3.141 3.173 3.249 3.252 3.259 3.324 3.332

3.39 3.411 3.448 3.526 3.564 3.736 3.748 3.78 3.784 3.804 3.825 3.844 3.846

3.848 3.872 3.947 3.991 4.264

Number of observations 45

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 3

19:24 Thursday, November 25, 2008

The GLM Procedure

Dependent Variable: VI N03

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 14 6.54535458 0.46752533 10.94 <.0001

Error 30 1.28249800 0.04274993

Corrected Total 44 7.82785258

R-Square Coeff Var Root MSE VI Mean

0.836162 6.241598 0.206761 3.312622

Source DF Type I SS Mean Square F Value Pr > F

Days 4 3.84301658 0.96075414 22.47 <.0001

Mois 2 0.70371551 0.35185776 8.23 0.0014

Days*Mois 8 1.99862249 0.24982781 5.84 0.0002

Source DF Type III SS Mean Square F Value Pr > F

Days 4 3.84301658 0.96075414 22.47 <.0001

Mois 2 0.70371551 0.35185776 8.23 0.0014

Days*Mois 8 1.99862249 0.24982781 5.84 0.0002

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 4

19:24 Thursday, November 25, 2008

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 30

Error Mean Square 0.04275

Critical Value of Studentized Range 4.10208

Minimum Significant Difference 0.2827

Means with the same letter are not significantly different.

160

Tukey Grouping Mean N Days

A 3.86233 9 14

B 3.29311 9 28

C B 3.24967 9 7

C B 3.15422 9 56

C 3.00378 9 1

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 5

19:24 Thursday, November 25, 2008

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 30

Error Mean Square 0.04275

Critical Value of Studentized Range 3.48651

Minimum Significant Difference 0.1861

Means with the same letter are not significantly different.

Tukey Grouping Mean N Mois

A 3.48793 15 W2

B 3.24513 15 W1

B 3.20480 15 W3

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 6

19:24 Thursday, November 25, 2008

The GLM Procedure

Level of Level of --------------VI-------------

Days Mois N Mean Std Dev

1 W1 3 3.25233333 0.07950052

1 W2 3 2.99800000 0.00400000

1 W3 3 2.76100000 0.02116601

14 W1 3 3.90300000 0.07731106

14 W2 3 3.81766667 0.03066486

14 W3 3 3.86633333 0.07324161

28 W1 3 2.90500000 0.05483612

28 W2 3 3.75466667 0.02274496

28 W3 3 3.21966667 0.25032845

56 W1 3 3.05533333 0.05950070

56 W2 3 3.13000000 0.34393023

161

56 W3 3 3.27733333 0.04072264

7 W1 3 3.11000000 0.02787472

7 W2 3 3.73933333 0.46262872

7 W3 3 2.89966667 0.46658904

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 7

19:24 Thursday, November 25, 2008

The GLM Procedure

Least Squares Means

Standard LSMEAN

Days VI LSMEAN Error Pr > |t| Number

1 3.00377778 0.06892019 <.0001 1

14 3.86233333 0.06892019 <.0001 2

28 3.29311111 0.06892019 <.0001 3

56 3.15422222 0.06892019 <.0001 4

7 3.24966667 0.06892019 <.0001 5

Least Squares Means for effect Days

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3 4 5

1 <.0001 0.0058 0.1332 0.0172

2 <.0001 <.0001 <.0001 <.0001

3 0.0058 <.0001 0.1645 0.6590

4 0.1332 <.0001 0.1645 0.3353

5 0.0172 <.0001 0.6590 0.3353

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Standard LSMEAN

Mois VI LSMEAN Error Pr > |t| Number

W1 3.24513333 0.05338535 <.0001 1

W2 3.48793333 0.05338535 <.0001 2

W3 3.20480000 0.05338535 <.0001 3

Least Squares Means for effect Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3

1 0.0031 0.5971

2 0.0031 0.0008

3 0.5971 0.0008

162

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 8

19:24 Thursday, November 25, 2008

The GLM Procedure

Least Squares Means

comparisons should be used.

Standard LSMEAN

Days Mois VI LSMEAN Error Pr > |t| Number

1 W1 3.25233333 0.11937327 <.0001 1

1 W2 2.99800000 0.11937327 <.0001 2

1 W3 2.76100000 0.11937327 <.0001 3

14 W1 3.90300000 0.11937327 <.0001 4

14 W2 3.81766667 0.11937327 <.0001 5

14 W3 3.86633333 0.11937327 <.0001 6

28 W1 2.90500000 0.11937327 <.0001 7

28 W2 3.75466667 0.11937327 <.0001 8

28 W3 3.21966667 0.11937327 <.0001 9

56 W1 3.05533333 0.11937327 <.0001 10

56 W2 3.13000000 0.11937327 <.0001 11

56 W3 3.27733333 0.11937327 <.0001 12

7 W1 3.11000000 0.11937327 <.0001 13

7 W2 3.73933333 0.11937327 <.0001 14

7 W3 2.89966667 0.11937327 <.0001 15

Least Squares Means for effect Days*Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3 4 5 6 7 8

1 0.1424 0.0067 0.0006 0.0022 0.0010 0.0484 0.0057

2 0.1424 0.1706 <.0001 <.0001 <.0001 0.5858 0.0001

3 0.0067 0.1706 <.0001 <.0001 <.0001 0.4004 <.0001

4 0.0006 <.0001 <.0001 0.6169 0.8295 <.0001 0.3866

5 0.0022 <.0001 <.0001 0.6169 0.7751 <.0001 0.7116

6 0.0010 <.0001 <.0001 0.8295 0.7751 <.0001 0.5134

7 0.0484 0.5858 0.4004 <.0001 <.0001 <.0001 <.0001

8 0.0057 0.0001 <.0001 0.3866 0.7116 0.5134 <.0001

9 0.8479 0.1991 0.0108 0.0003 0.0013 0.0006 0.0721 0.0035

10 0.2524 0.7365 0.0915 <.0001 <.0001 <.0001 0.3803 0.0003

11 0.4743 0.4404 0.0368 <.0001 0.0003 0.0001 0.1926 0.0009

12 0.8833 0.1084 0.0046 0.0009 0.0032 0.0015 0.0352 0.0083

13 0.4058 0.5121 0.0474 <.0001 0.0002 0.0001 0.2341 0.0006

14 0.0072 0.0001 <.0001 0.3401 0.6460 0.4577 <.0001 0.9282

15 0.0453 0.5646 0.4179 <.0001 <.0001 <.0001 0.9750 <.0001

163

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 9

19:24 Thursday, November 25, 2008

The GLM Procedure

Least Squares Means

Least Squares Means for effect Days*Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 9 10 11 12 13 14 15

1 0.8479 0.2524 0.4743 0.8833 0.4058 0.0072 0.0453

2 0.1991 0.7365 0.4404 0.1084 0.5121 0.0001 0.5646

3 0.0108 0.0915 0.0368 0.0046 0.0474 <.0001 0.4179

4 0.0003 <.0001 <.0001 0.0009 <.0001 0.3401 <.0001

5 0.0013 <.0001 0.0003 0.0032 0.0002 0.6460 <.0001

6 0.0006 <.0001 0.0001 0.0015 0.0001 0.4577 <.0001

7 0.0721 0.3803 0.1926 0.0352 0.2341 <.0001 0.9750

8 0.0035 0.0003 0.0009 0.0083 0.0006 0.9282 <.0001

9 0.3381 0.5992 0.7350 0.5209 0.0044 0.0677

10 0.3381 0.6615 0.1985 0.7483 0.0003 0.3638

11 0.5992 0.6615 0.3897 0.9065 0.0011 0.1826

12 0.7350 0.1985 0.3897 0.3295 0.0103 0.0329

13 0.5209 0.7483 0.9065 0.3295 0.0008 0.2224

14 0.0044 0.0003 0.0011 0.0103 0.0008 <.0001

15 0.0677 0.3638 0.1826 0.0329 0.2224 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

164

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 10

19:24 Thursday, November 25, 2008

The UNIVARIATE Procedure

Variable: VI (N03)

Moments

N 45 Sum Weights 45

Mean 3.31262222 Sum Observations 149.068

Std Deviation 0.42178874 Variance 0.17790574

Skewness 0.30701524 Kurtosis -0.8878836

Uncorrected SS 501.633822 Corrected SS 7.82785258

Coeff Variation 12.7327751 Std Error Mean 0.06287655

Basic Statistical Measures

Location Variability

Mean 3.312622 Std Deviation 0.42179

Median 3.252000 Variance 0.17791

Mode 3.259000 Range 1.76700

Interquartile Range 0.75400

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 52.68454 Pr > |t| <.0001

Sign M 22.5 Pr >= |M| <.0001

Signed Rank S 517.5 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.952973 Pr < W 0.0659

Kolmogorov-Smirnov D 0.131144 Pr > D 0.0500

Cramer-von Mises W-Sq 0.150683 Pr > W-Sq 0.0228

Anderson-Darling A-Sq 0.907237 Pr > A-Sq 0.0203

Quantiles (Definition 5)

Quantile Estimate

100% Max 4.264

99% 4.264

95% 3.947

90% 3.848

75% Q3 3.748

50% Median 3.252

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 11

19:24 Thursday, November 25, 2008

The UNIVARIATE Procedure

Variable: VI (N03)

Quantiles (Definition 5)

Quantile Estimate

25% Q1 2.994

165

10% 2.791

5% 2.753

1% 2.497

0% Min 2.497

Extreme Observations

-----Lowest---- ----Highest----

Value Obs Value Obs

2.497 17 3.848 27

2.745 9 3.872 19

2.753 8 3.947 25

2.785 7 3.991 20

2.791 18 4.264 13

Frequency Counts

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

2.497 1 2.2 2.2 3.055 1 2.2 35.6 3.564 1 2.2 71.1

2.745 1 2.2 4.4 3.087 1 2.2 37.8 3.736 1 2.2 73.3

2.753 1 2.2 6.7 3.102 1 2.2 40.0 3.748 1 2.2 75.6

2.785 1 2.2 8.9 3.115 1 2.2 42.2 3.780 1 2.2 77.8

2.791 1 2.2 11.1 3.141 1 2.2 44.4 3.784 1 2.2 80.0

2.854 1 2.2 13.3 3.173 1 2.2 46.7 3.804 1 2.2 82.2

2.898 1 2.2 15.6 3.249 1 2.2 48.9 3.825 1 2.2 84.4

2.906 1 2.2 17.8 3.252 1 2.2 51.1 3.844 1 2.2 86.7

2.952 1 2.2 20.0 3.259 2 4.4 55.6 3.846 1 2.2 88.9

2.958 1 2.2 22.2 3.324 1 2.2 57.8 3.848 1 2.2 91.1

2.963 1 2.2 24.4 3.332 1 2.2 60.0 3.872 1 2.2 93.3

2.994 1 2.2 26.7 3.390 1 2.2 62.2 3.947 1 2.2 95.6

2.996 1 2.2 28.9 3.411 1 2.2 64.4 3.991 1 2.2 97.8

2.998 1 2.2 31.1 3.448 1 2.2 66.7 4.264 1 2.2 100.0

3.002 1 2.2 33.3 3.526 1 2.2 68.9

Effect of incubation time on net N release for stable ‘Vlakplaas’- at 45 o

C 12

19:24 Thursday, November 25, 2008

The UNIVARIATE Procedure

Variable: VI (N03)

Stem Leaf # Boxplot

42 6 1 |

41 |

40 |

39 59 2 |

38 024557 6 |

37 4588 4 +-----+

36 | |

35 36 2 | |

34 15 2 | |

33 239 3 | + |

32 5566 4 *-----*

31 0247 4 | |

30 00069 5 | |

29 015669 6 +-----+

28 5 1 |

27 4589 4 |

166

26 |

25 0 1 |

24

----+----+----+----+

Multiply Stem.Leaf by 10**-1

Normal Probability Plot

4.25+ *+

| +++

| ++

| ++* *

| ******

| *** ++

| +++

| *+

| **

3.35+ ++**

| +***

| ++***

| ++***

| ******

| **+

| * * **

| ++

| +++

2.45+ *++

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

A.

3.1

Effect of incubation time on N0

3

release-Temperature 2

1

19:27 Thursday, November 25, 2008

Obs Days Mois Rep VI

1 1 W1 1 0.138

2 1 W1 2 0.130

3 1 W1 3 0.345

4 1 W2 1 0.140

5 1 W2 2 0.307

6 1 W2 3 0.192

7 1 W3 1 0.286

8 1 W3 2 0.258

9 1 W3 3 0.262

10 7 W1 1 0.820

11 7 W1 2 0.932

12 7 W1 3 1.099

13 7 W2 1 0.680

14 7 W2 2 0.636

15 7 W2 3 0.596

16 7 W3 1 0.762

17 7 W3 2 0.875

18 7 W3 3 0.835

19 14 W1 1 1.097

20 14 W1 2 1.514

21 14 W1 3 1.570

22 14 W2 1 1.295

23 14 W2 2 1.179

24 14 W2 3 0.845

25 14 W3 1 0.930

26 14 W3 2 1.363

27 14 W3 3 0.950

28 28 W1 1 2.792

29 28 W1 2 2.713

30 28 W1 3 2.769

167

31 28 W2 1 2.612

32 28 W2 2 2.533

33 28 W2 3 2.477

34 28 W3 1 2.616

35 28 W3 2 2.743

36 28 W3 3 2.465

37 56 W1 1 2.944

38 56 W1 2 2.992

39 56 W1 3 2.864

40 56 W2 1 2.642

41 56 W2 2 2.602

42 56 W2 3 2.638

43 56 W3 1 2.410

44 56 W3 2 2.609

45 56 W3 3 2.530

Effect of incubation time on N03 release-Temperature 2 2

19:27 Thursday, November 25, 2008

The GLM Procedure

Class Level Information

Class Levels Values

Days 5 1 14 28 56 7

Mois 3 W1 W2 W3

Rep 3 1 2 3

VI 45 0.13 0.138 0.14 0.192 0.258 0.262 0.286 0.307 0.345 0.596 0.636 0.68 0.762

0.82 0.835 0.845 0.875 0.93 0.932 0.95 1.097 1.099 1.179 1.295 1.363 1.514

1.57 2.41 2.465 2.477 2.53 2.533 2.602 2.609 2.612 2.616 2.638 2.642 2.713

2.743 2.769 2.792 2.864 2.944 2.992

Number of observations 45

Effect of incubation time on N03 release-Temperature 2 3

19:27 Thursday, November 25, 2008

The GLM Procedure

Dependent Variable: VI N03

Sum of

Source DF Squares Mean Square F Value Pr > F

Model 14 44.83849191 3.20274942 178.86 <.0001

Error 30 0.53719467 0.01790649

Corrected Total 44 45.37568658

R-Square Coeff Var Root MSE VI Mean

0.988161 8.857106 0.133815 1.510822

168

Source DF Type I SS Mean Square F Value Pr > F

Days 4 44.14732947 11.03683237 616.36 <.0001

Mois 2 0.43200111 0.21600056 12.06 0.0001

Days*Mois 8 0.25916133 0.03239517 1.81 0.1145

Source DF Type III SS Mean Square F Value Pr > F

Days 4 44.14732947 11.03683237 616.36 <.0001

Mois 2 0.43200111 0.21600056 12.06 0.0001

Days*Mois 8 0.25916133 0.03239517 1.81 0.1145

Effect of incubation time on N03 release-Temperature 2 4

19:27 Thursday, November 25, 2008

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 30

Error Mean Square 0.017906

Critical Value of Studentized Range 4.10208

Minimum Significant Difference 0.183

Means with the same letter are not significantly different.

Tukey Grouping Mean N Days

A 2.69233 9 56

A 2.63556 9 28

B 1.19367 9 14

C 0.80389 9 7

D 0.22867 9 1

Effect of incubation time on N03 release-Temperature 2 5

169

19:27 Thursday, November 25, 2008

The GLM Procedure

Tukey's Studentized Range (HSD) Test for VI

NOTE: This test controls the Type I experimentwise error rate, but it generally has a higher Type

II error rate than REGWQ.

Alpha 0.05

Error Degrees of Freedom 30

Error Mean Square 0.017906

Critical Value of Studentized Range 3.48651

Minimum Significant Difference 0.1205

Means with the same letter are not significantly different.

Tukey Grouping Mean N Mois

A 1.64793 15 W1

B 1.45960 15 W3

B 1.42493 15 W2

Effect of incubation time on N03 release-Temperature 2 6

19:27 Thursday, November 25, 2008

The GLM Procedure

Level of Level of --------------VI-------------

Days Mois N Mean Std Dev

1 W1 3 0.20433333 0.12188656

1 W2 3 0.21300000 0.08545759

1 W3 3 0.26866667 0.01514376

14 W1 3 1.39366667 0.25844213

14 W2 3 1.10633333 0.23363504

14 W3 3 1.08100000 0.24442381

28 W1 3 2.75800000 0.04063250

28 W2 3 2.54066667 0.06782576

28 W3 3 2.60800000 0.13917255

56 W1 3 2.93333333 0.06466323

56 W2 3 2.62733333 0.02203028

56 W3 3 2.51633333 0.10020146

7 W1 3 0.95033333 0.14040062

7 W2 3 0.63733333 0.04201587

7 W3 3 0.82400000 0.05729747

Effect of incubation time on N03 release-Temperature 2 7

19:27 Thursday, November 25, 2008

The GLM Procedure

Least Squares Means

Standard LSMEAN

Days VI LSMEAN Error Pr > |t| Number

1 0.22866667 0.04460504 <.0001 1

14 1.19366667 0.04460504 <.0001 2

28 2.63555556 0.04460504 <.0001 3

56 2.69233333 0.04460504 <.0001 4

170

7 0.80388889 0.04460504 <.0001 5

Least Squares Means for effect Days

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3 4 5

1 <.0001 <.0001 <.0001 <.0001

2 <.0001 <.0001 <.0001 <.0001

3 <.0001 <.0001 0.3752 <.0001

4 <.0001 <.0001 0.3752 <.0001

5 <.0001 <.0001 <.0001 <.0001

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

171

Standard LSMEAN

Mois VI LSMEAN Error Pr > |t| Number

W1 1.64793333 0.03455092 <.0001 1

W2 1.42493333 0.03455092 <.0001 2

W3 1.45960000 0.03455092 <.0001 3

Least Squares Means for effect Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3

1 <.0001 0.0006

2 <.0001 0.4835

3 0.0006 0.4835

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

Effect of incubation time on N03 release-Temperature 2 8

19:27 Thursday, November 25, 2008

The GLM Procedure

Least Squares Means

comparisons should be used.

Standard LSMEAN

Days Mois VI LSMEAN Error Pr > |t| Number

1 W1 0.20433333 0.07725820 0.0129 1

1 W2 0.21300000 0.07725820 0.0098 2

1 W3 0.26866667 0.07725820 0.0016 3

14 W1 1.39366667 0.07725820 <.0001 4

14 W2 1.10633333 0.07725820 <.0001 5

14 W3 1.08100000 0.07725820 <.0001 6

28 W1 2.75800000 0.07725820 <.0001 7

28 W2 2.54066667 0.07725820 <.0001 8

28 W3 2.60800000 0.07725820 <.0001 9

56 W1 2.93333333 0.07725820 <.0001 10

56 W2 2.62733333 0.07725820 <.0001 11

56 W3 2.51633333 0.07725820 <.0001 12

7 W1 0.95033333 0.07725820 <.0001 13

7 W2 0.63733333 0.07725820 <.0001 14

7 W3 0.82400000 0.07725820 <.0001 15

Least Squares Means for effect Days*Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 1 2 3 4 5 6 7 8

1 0.9373 0.5604 <.0001 <.0001 <.0001 <.0001 <.0001

2 0.9373 0.6141 <.0001 <.0001 <.0001 <.0001 <.0001

3 0.5604 0.6141 <.0001 <.0001 <.0001 <.0001 <.0001

4 <.0001 <.0001 <.0001 0.0133 0.0076 <.0001 <.0001

5 <.0001 <.0001 <.0001 0.0133 0.8182 <.0001 <.0001

172

6 <.0001 <.0001 <.0001 0.0076 0.8182 <.0001 <.0001

7 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0559

8 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0559

9 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.1800 0.5424

10 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.1190 0.0011

11 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.2411 0.4339

12 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0347 0.8253

13 <.0001 <.0001 <.0001 0.0003 0.1637 0.2411 <.0001 <.0001

14 0.0004 0.0005 0.0021 <.0001 0.0002 0.0003 <.0001 <.0001

15 <.0001 <.0001 <.0001 <.0001 0.0149 0.0254 <.0001 <.0001

Effect of incubation time on N03 release-Temperature 2 9

19:27 Thursday, November 25, 2008

The GLM Procedure

Least Squares Means

Least Squares Means for effect Days*Mois

Pr > |t| for H0: LSMean(i)=LSMean(j)

Dependent Variable: VI

i/j 9 10 11 12 13 14 15

1 <.0001 <.0001 <.0001 <.0001 <.0001 0.0004 <.0001

2 <.0001 <.0001 <.0001 <.0001 <.0001 0.0005 <.0001

3 <.0001 <.0001 <.0001 <.0001 <.0001 0.0021 <.0001

4 <.0001 <.0001 <.0001 <.0001 0.0003 <.0001 <.0001

5 <.0001 <.0001 <.0001 <.0001 0.1637 0.0002 0.0149

6 <.0001 <.0001 <.0001 <.0001 0.2411 0.0003 0.0254

7 0.1800 0.1190 0.2411 0.0347 <.0001 <.0001 <.0001

8 0.5424 0.0011 0.4339 0.8253 <.0001 <.0001 <.0001

9 0.0057 0.8607 0.4081 <.0001 <.0001 <.0001

10 0.0057 0.0088 0.0006 <.0001 <.0001 <.0001

11 0.8607 0.0088 0.3178 <.0001 <.0001 <.0001

12 0.4081 0.0006 0.3178 <.0001 <.0001 <.0001

13 <.0001 <.0001 <.0001 <.0001 0.0076 0.2567

14 <.0001 <.0001 <.0001 <.0001 0.0076 0.0979

15 <.0001 <.0001 <.0001 <.0001 0.2567 0.0979

NOTE: To ensure overall protection level, only probabilities associated with pre-planned

comparisons should be used.

Effect of incubation time on N03 release-Temperature 2 10

19:27 Thursday, November 25, 2008

The UNIVARIATE Procedure

Variable: VI (N03)

Moments

N 45 Sum Weights 45

Mean 1.51082222 Sum Observations 67.987

Std Deviation 1.01551248 Variance 1.0312656

Skewness 0.1281016 Kurtosis -1.65573

Uncorrected SS 148.091957 Corrected SS 45.3756866

Coeff Variation 67.2158821 Std Error Mean 0.15138366

Basic Statistical Measures

Location Variability

Mean 1.510822 Std Deviation 1.01551

Median 1.179000 Variance 1.03127

Mode . Range 2.86200

173

Interquartile Range 1.92900

Tests for Location: Mu0=0

Test -Statistic- -----p Value------

Student's t t 9.980088 Pr > |t| <.0001

Sign M 22.5 Pr >= |M| <.0001

Signed Rank S 517.5 Pr >= |S| <.0001

Tests for Normality

Test --Statistic--- -----p Value------

Shapiro-Wilk W 0.864314 Pr < W <0.0001

Kolmogorov-Smirnov D 0.212041 Pr > D <0.0100

Cramer-von Mises W-Sq 0.391966 Pr > W-Sq <0.0050

Anderson-Darling A-Sq 2.378979 Pr > A-Sq <0.0050

Quantiles (Definition 5)

Quantile Estimate

100% Max 2.992

99% 2.992

95% 2.864

90% 2.769

75% Q3 2.609

50% Median 1.179

Effect of incubation time on N03 release-Temperature 2 11

19:27 Thursday, November 25, 2008

The UNIVARIATE Procedure

Variable: VI (N03)

Quantiles (Definition 5)

Quantile Estimate

25% Q1 0.680

10% 0.258

5% 0.140

1% 0.130

0% Min 0.130

Extreme Observations

-----Lowest---- ----Highest----

Value Obs Value Obs

0.130 2 2.769 30

0.138 1 2.792 28

0.140 4 2.864 39

0.192 6 2.944 37

0.258 8 2.992 38

Frequency Counts

174

Percents Percents Percents

Value Count Cell Cum Value Count Cell Cum Value Count Cell Cum

0.130 1 2.2 2.2 0.845 1 2.2 35.6 2.530 1 2.2 68.9

0.138 1 2.2 4.4 0.875 1 2.2 37.8 2.533 1 2.2 71.1

0.140 1 2.2 6.7 0.930 1 2.2 40.0 2.602 1 2.2 73.3

0.192 1 2.2 8.9 0.932 1 2.2 42.2 2.609 1 2.2 75.6

0.258 1 2.2 11.1 0.950 1 2.2 44.4 2.612 1 2.2 77.8

0.262 1 2.2 13.3 1.097 1 2.2 46.7 2.616 1 2.2 80.0

0.286 1 2.2 15.6 1.099 1 2.2 48.9 2.638 1 2.2 82.2

0.307 1 2.2 17.8 1.179 1 2.2 51.1 2.642 1 2.2 84.4

0.345 1 2.2 20.0 1.295 1 2.2 53.3 2.713 1 2.2 86.7

0.596 1 2.2 22.2 1.363 1 2.2 55.6 2.743 1 2.2 88.9

0.636 1 2.2 24.4 1.514 1 2.2 57.8 2.769 1 2.2 91.1

0.680 1 2.2 26.7 1.570 1 2.2 60.0 2.792 1 2.2 93.3

0.762 1 2.2 28.9 2.410 1 2.2 62.2 2.864 1 2.2 95.6

0.820 1 2.2 31.1 2.465 1 2.2 64.4 2.944 1 2.2 97.8

0.835 1 2.2 33.3 2.477 1 2.2 66.7 2.992 1 2.2 100.0

Effect of incubation time on N03 release-Temperature 2 12

19:27 Thursday, November 25, 2008

The UNIVARIATE Procedure

Variable: VI (N03)

Stem Leaf # Boxplot

28 649 3 |

26 0112441479 10 +-----+

24 16833 5 | |

22 | |

20 | |

18 | |

16 | |

14 17 2 | + |

12 06 2 | |

10 008 3 *-----*

8 2448335 7 | |

6 0486 4 +-----+

4 |

2 66914 5 |

0 3449 4 |

----+----+----+----+

Multiply Stem.Leaf by 10**-1

Normal Probability Plot

2.9+ ++ * * *

| *********

| *** ++

| ++

| ++

| ++

| ++

1.5+ ++ *

| ++ *

| ++ **

| +****

| +**

| ++*

| *****

0.1+ * * * *+

+----+----+----+----+----+----+----+----+----+----+

-2 -1 0 +1 +2

175

176

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