D. Peyton thesis

D. Peyton thesis
 NATIONAL UNIVERSITY OF IRELAND, GALWAY
Nutrient, metal and microbial losses in runoff following treated sludge
application to an Irish grassland soil
Dara Patrick Peyton, BAgrSc (Hons)
Research supervisors:
Dr. Mark Healy, Civil Engineering NUI Galway
Dr. Owen Fenton, Teagasc, Environment Research Centre, Johnstown Castle, Wexford
Thesis submitted in fulfilment of the requirements for the degree of Master of Engineering
Science
June 2015
The National University of Ireland requires the signatures of all persons using or
photocopying this thesis. Please sign below, and give the address and date.
To my wonderful parents, brothers, sisters and girlfriend for your guidance and support.
ii SUMMARY
Treated sewage sludge, commonly referred to as ‘biosolids’, is the organic by-product of
urban waste water treatment. When spread on grassland or arable land, biosolids may provide
an excellent source of nutrients and metals required for plant and crop growth. As biosolids
are often considered a waste product, they may be used as a cheap source of organic fertiliser
and may provide an excellent opportunity to improve crop profit margins by means of
reducing the input costs of chemical fertilisers.
While there are many benefits associated with the use of biosolids as an organic fertilizer
amendment, there are currently many concerns associated with their potential to contaminate
soil, vegetation and water. In addition, current legislation does not consider the relationship
between biosolids application rate and surface runoff. Therefore, the aim of this research was
to: (1) undertake a literature review outlining the current situation of biosolids use,
legislation, societal issues, various treatments of sewage sludge in Ireland, and advantages
and disadvantages associated with their use, (2) produce a lime stabilised biosolid for use in a
field scale experiment, (3) undertake a field-scale experiment to assess losses of nutrients
(nitrogen and phosphorus), metals (copper (Cu), nickel (Ni), lead (Pb), zinc (Zn), cadmium
(Cd), chromium (Cr), microbial matter (total and faecal coliforms) following successive
rainfall events on land onto which biosolids had been applied.
As part of this holistic investigation, three biosolids commonly used in Ireland were utilised:
anaerobically digested, lime stabilised (LS) and thermally dried (TD). In addition,
anaerobically digested biosolids, sourced from the Seventh Framework Programme (FP7)
END-O-SLUDGE project, was also utilised and the fifth treatment was an unamended
grassland control. For comparison with another commonly spread organic fertiliser using in
Ireland, dairy cattle slurry (DCS) was also used in the experiment. Biosolids and DCS were
iii surface applied in accordance with the legislation in Ireland. A rainfall simulator was used to
generate runoff over three successive events (24 hr, 48 hr and 360 hr) after a single
application.
Losses from biosolids-amended plots were higher than the study control (soil only) plots, and
followed a general trend of highest losses occurring during the first rainfall event and reduced
losses in the subsequent events. However, with the exception of total coliforms and some
metal parameters (Cu), the greatest losses were from the DCS-amended plots. For example,
average losses over the three rainfall events for dissolved reactive phosphorus and
ammonium-nitrogen were 4.5 and 11.6 mg L-1, respectively, which were far in excess of the
losses from the biosolids plots. Metal losses from DCS-amended plots were higher (Cd, Cr),
or of the same magnitude as the biosolids-amended plots (Ni, Pb, Zn).
When compared with slurry treatments, biosolids do not pose a greater risk in terms of losses
along the runoff pathway. This finding has important policy implications, as it shows that
fears surrounding the reuse of biosolids as a soil fertiliser, mainly concerning contaminant
losses upon land application, may be unfounded.
iv DECLARATION
This dissertation is the result of my own work, except where explicit reference is made to the
work of others, and has not been submitted for another qualification to this or any other
university.
Dara Patrick Peyton
v ACKNOWLEDMENTS
First, I would like to thank my two supervisors, Dr. Owen Fenton and Dr. Mark Healy, for
granting me the opportunity to complete my masters on such a diverse and interesting project.
I would like to thank them for their guidance, enthusiasm, honesty and most of all their
patience over the past two years and wish them every success into the future.
I would also like to thank Teagasc, the Environmental Protection Agency of Ireland (who
provided the necessary funding for this project) and the authorities at the National University
of Ireland, Galway, for providing the facilities and funding to carry out this research study.
Over the past two years I have been very fortunate to receive help form many people along
the way. However, I would like to give special mention to Dr. David Wall for his help at
critical moments during the planning and execution of this project. I also wish to thank all the
technical and farm staff in Johnstown Castle, Teagasc, without whom this work would not
have been possible. A special thanks to Denis Brennan, Theresa Cowman, Paddy Sills, Sean
Colfer, Linda Finn, Olivia Fagan, Paddy Hayes, Nicky Hayes, Pat Donnelly, John Sinnott,
Alan Cuddihy, Donal Doyle, Brendan Connick and Rioch Fox. A special thank you also to
Miriam McGuire for all the many cups of tea and laughs. I wish to thank my fellow postgrads and wish them the best of luck in their future careers.
I would also like to thank my girlfriend, Maria, and her family, for being so kind,
encouraging and understanding. Last, but certainly not least, to my wonderful parents, Martin
and Maria, and brothers and sister, Antoinette, Emmet, Martina and Shane and the rest of my
family, who always provided me with the support and encouragement I needed. I thank you
all from the bottom of my heart.
vi ABBREVIATIONS
AD
Anaerobic digestion
ATAD
Autothermal, thermophilic aerobic digestion
ADIRE
Anaerobically digestion Biosolid sourced in Ireland
ADUK
Anaerobically digestion Biosolid sourced in the United Kingdom
APHA
American Public Health Association
BS
British Standards
BSE
Bovine Spongiform Encephalopathy
Ca
Calcium
Cd
Cadmium
Cr
Chromium
Cu
Copper
DAFF
Department of Agriculture, Fisheries and Food
DAFM
Department of Agriculture, Food and The Marine
DCS
Dairy Cattle Slurry
DM
Dry matter
DRP
Dissolved reactive phosphorus
DS
Dried solids
DSC
Dry Solids Content
DUP
Dissolved un-reactive phosphorus
EC
European Commission
EPA
Environment Protection Agency
EU
European Union
Fe
Iron
FC
Faecal Coliforms
FRV
Fertiliser Replacement Value
FSAI
Food Safety Authority of Ireland
FWMC
Flow-weighted mean concentration
hr
Hour
ha
Hectare
Hg
Mercury
K
Potassium
vii Pb
Lead
LS
Lime stabilised
M3
Mehlich-III P
Mg
Magnesium
Mn
Manganese
N
Nitrogen
Ni
Nickel
OM
Organic matter
OMFs
Organomineral fertilisers
P
Phosphorus
P2O5
Phosphorus pentoxide
Pb
Lead
PCPs
Personal Care Products
PDS
Particle size distribution
Pm
Morgan’s P
PP
Particulate phosphorus
PBT
Persistence, Bioaccumulation and Toxicity
PPCPs
Pharmaceuticals and Personal Care Products
RS1
Rainfall simulation event 1
RS2
Rainfall simulation event 2
RS3
Rainfall simulation event 3
FP7
Seventh Framework Programme
SS
Suspended sediment
STP
Soil test phosphorus
TC
Total Coliforms
TD
Thermally dried
TS
Total Solids
TDP
Total dissolved phosphorus in water
TN
Total nitrogen
TON
Total oxidized nitrogen
TP
Total phosphorus
U.S.A.
United States of America
USEPA
United States Environment Protection Agency
viii UC
Christiansen coefficient
WEF
Water Environment Federation
WWTP
Wastewater Treatment Plant
WFD
Water Framework Directive
Zn
Zinc ix TABLE OF CONTENTS
ABBREVIATIONS ..........................................................................................................vii
LIST OF FIGURES ........................................................................................................ xiii
LIST OF TABLES ............................................................................................................ xv Chapter 1 –INTRODUCTION .......................................................................... 1 1.1. Overview .................................................................................................................................. 1 1.2. Procedure ................................................................................................................................. 3 1.3. Structure of dissertation ........................................................................................................... 4 Chapter 2 - LITERATURE REVIEW .............................................................. 6 2.1. Overview .................................................................................................................................. 6 2.2. Introduction .............................................................................................................................. 6 2.3. Sewage Sludge as a Resource .................................................................................................. 7 2.4. Legislation governing disposal of biosolids ............................................................................. 9 2.5. Wastewater treatment ............................................................................................................. 12 2.5.1. Preliminary treatment .......................................................................................................... 13 2.5.2. Primary treatment ................................................................................................................ 14 2.5.3. Secondary treatment ............................................................................................................ 14 2.4.4.Tertiary treatment ................................................................................................................. 14 2.5.5. Sludge treatment ................................................................................................................. 15 2.6. Types of treated biosolids ....................................................................................................... 16 2.6.1. Anaerobic digestion ............................................................................................................ 17 2.6.2. Thermal drying .................................................................................................................... 19 2.6.3. Lime Stabilisation ............................................................................................................... 20 2.6.4. Composting ......................................................................................................................... 21 2.6.5. Autothermal Thermophililic Aerobic Digestion .................................................................. 22 2.7. Existing and emerging issues concerning the use of biosolids on agricultural land .............. 23 2.7.1. Nutrient and metal losses .................................................................................................... 23 2.7.2. Behaviour of metals in the soil/Uptake by plants ............................................................... 24 2.7.3. The microbial risk associated with the landspreading of biosolids ..................................... 25 2.7.4. Pharmaceutical and personal care products ........................................................................ 27 2.7.5. Public perception of the land spreading of biosolids .......................................................... 29 x 2.8. Summary ................................................................................................................................ 31 Chapter 3 - DESIGN OF A RAINFALL SIMULATOR ................................ 33 3.1 Overview ................................................................................................................................. 33 3.2 Rainfall simulators and their importance in agricultural research .......................................... 33 3.3 Rainfall simulator in the current study .................................................................................... 35 3.4 Rainfall simulator construction ............................................................................................... 35 3.5 Areal uniformity and intensity calibration .............................................................................. 37 3.6 Summary ................................................................................................................................. 39 Chapter 4 - METHODOLOGY TO INCORPORATE CALCIUM OXIDE
INTO DEWATERED SLUDGE ...................................................................... 41 4.1. Overview ................................................................................................................................ 41 4.2. Introduction ............................................................................................................................ 41 4.3.1. Sample collection and analysis ........................................................................................... 42 4.3.2. Monitoring of pH and temperature and microbes ............................................................... 43 4.3.3. Test 1 (preliminary test) ...................................................................................................... 44 4.3.4. Test 2 (Full-scale bench test) ............................................................................................... 45 4.4. Results .................................................................................................................................... 46 4.4.1. Test 1 (preliminary test) ...................................................................................................... 46 4.4.2. Test 2 (Full–scale Bench test) ............................................................................................. 47 4.5 Discussion ............................................................................................................................... 48 4.5.1. Preliminary test ................................................................................................................... 48 4.5.2. Full–scale Bench test .......................................................................................................... 51 4.5.3. Importance of uniform lime incorporation and potential problems .................................... 51 4.5. Conclusion ............................................................................................................................. 53 Chapter 5 - PLOT-SCALE RAINFALL SIMULATOR STUDY ................. 54 5.1. Overview ................................................................................................................................ 54 5.2. Introduction ............................................................................................................................ 54 5.3 Materials and Methods ............................................................................................................ 55 5.3.1. Field Site characterisation ................................................................................................... 55 5.3.2. Micro-plot installation and characterisation ........................................................................ 57 xi 5.3.3. Biosolids characterisation ................................................................................................... 60 5.3.4. Slurry Characterisation ....................................................................................................... 62 5.3.5. Rainfall event simulation and application ........................................................................... 64 5.3.6. Runoff sample collection .................................................................................................... 66 5.3.7. Nutrient and metal runoff analysis ...................................................................................... 67 5.3.8. Total and faecal coliform analysis ....................................................................................... 68 5.3.9 Data analysis ....................................................................................................................... 68 5.4. Results .................................................................................................................................... 69 5.4.1. Nutrient losses in runoff ...................................................................................................... 69 5.4.2. Metal losses in runoff .......................................................................................................... 71 5.4.3. Microbial losses in runoff (Total and faecal coliform) ........................................................ 74 5.4.4. Soil test P, Mehlich-3 P, K, LR, pH and metal .................................................................... 76 5.5 Discussion ............................................................................................................................... 76 5.5.1. Incidental nutrient losses for all rainfall events .................................................................. 76 5.5.2. Incidental metal losses for all rainfall events ...................................................................... 78 5.5.3. Incidental pathogen losses for all rainfall events ................................................................ 79 5.5.4. Soil characteristics before and after experiment ................................................................. 82 5.6. Conclusion ............................................................................................................................. 83 5.7. Summary ................................................................................................................................ 83 Chapter 6 - CONCLUSIONS AND RECOMMENDATIONS ..................... 84 6.1. Overview ................................................................................................................................ 84 6.2. Conclusions ............................................................................................................................ 84 6.3 Recommendations for future work ......................................................................................... 85 References .......................................................................................................... 86 xii LIST OF FIGURES
Figure 2.1. Trends in unit cost of nitrogen (N), phosphorus (P) and potassium (K) in
chemical fertilisers in Ireland from 1980 to 2011 (Lalor et al. 2012). ....................................... 8 Figure 2.2. Illustration of a simplified wastewater treatment process (adapted from Antille et
al., 2011; Metcalf et al., 2003). ................................................................................................ 13 Figure 2.3. A 50 g sample of anaerobically digested biosolids (ADIRE) ............................... 19 Figure 2.4. A 50 g sample of thermally dried biosolids (TD) .................................................... Figure 2.5. A 50 g sample of lime stabilised biosolids (LS). .................................................. 21 Figure 3.1. Principal components of the rainfall simulator (top) and of Perspex plate (bottom)
.................................................................................................................................................. 36 Figure 3.2. Amsterdam-styled drip-type rainfall simulators fitted with wind shield in use in
field. ......................................................................................................................................... 38 Figure 3.3. Calibration area and positions of collection containers ........................................ 39 Figure 4.1. The spreadsheet provided by Clogrennane Lime, which shows a 19% dry solid
content with the amount of CaO required, highlighted, to get the required heat. ........................ Figure 4.2. The experimental setup for the preliminary test. A) – temperature monitoring of 2
kg sludge cake and B) – a temperature probe close up. ........................................................... 44 Figure 4.3. The measurement of lime and sludge, and sealed container mixture with
temperature probes inserted. .................................................................................................... 45 Figure 4.4. Shows final lime-sludge mixture and storage outside for 48 hours...................... 46 Figure 4.5. Temperature vs. time over 12 hr. Horizontal bar indicates 52○C, which is the
temperature guideline (Fehily, Timoney and Company, 1999)................................................ 48 Figure 4.6. A) Standard lime-sludge mixing apparatus at a WWTP, B) Pugmill Augers, C)
completion of sludge and lime mixture on transfer belt, D) truck collection. ......................... 49 Figure 4.7. Illustration of a standard mixing apparatus at a WWTP....................................... 50 xiii Figure 5.1. The “W” soil sample procedure outlined in the S.I. No 610 2010. This soil
sample procedure was carried out for the Upper, Middle and Lower sections of the field ..... 56 Figure 5.2. Picture of micro-plot fitted with runoff off collection channel and micro-plot set
up.............................................................................................................................................. 57 Figure 5.3. Anaerobically digested biosolid source from END-O-SLUDGE, 2014 (ADUK)
.................................................................................................................................................. 62 Figure 5.4. A) and B) show site set up, C) Quadrant used to apply biosolids evenly, D)
Rainout shelters to excluded natural rainfall ........................................................................... 66 Figure 5.5. A) Sterile collection cups for Microbes, B) Collection cups for nutrients and
metals ....................................................................................................................................... 67 Figure 5.6. Flow weighted mean concentrations of phosphorus (top) and nitrogen (bottom) in
the runoff over three successive rainfall events at 24 hr (RS1), 48 hr (RS2) and 360 hr (RS3)
after application to grassland. .................................................................................................. 71 Figure 5.7. Flow weighted mean concentrations of cadmium (A), chromium (B), copper (C),
nickel (D), lead (E) and zinc (F) in the runoff over three successive rainfall events at 24 hr.
(RS1), 48 hr. (RS2) and 360 hr. (RS3) after application to grassland...................................... 73 Figure 5.8. Total coliforms (top) and faecal coliforms (bottom) in the runoff per 100ml over
three successive rainfall events at 24 hr (RS1), 48 hrs (RS2) and 360 hr (RS3) after
application to grassland............................................................................................................ 75 xiv LIST OF TABLES
Table 2.1. Limit values for metal concentrations in sludge and soil (taken from Lucid et al.,
2013). ....................................................................................................................................... 11 Table 2.2. Microbiological standards used to classify biosolids as Class A or Class B
biosolids (Fehily, Timoney and Company., 1999; USEPA, 1993) ........................................... 16 Table 2.3. Global municipal sewage sludge treatment processes............................................ 17 Table 4.1. Results for 100 g, 200 g and 2000 g of dewatered sludge mixed with varying
percentages of quicklime (CaO). ............................................................................................. 47 Table 4.2. Sample pH of lime - sludge mix at 24, 48 and 72 hour periods..………………...47 Table 5.1. Soil characteristics from the upper, middle and lower section of the 0.6 ha field
site. ........................................................................................................................................... 56 Table 5.2. Average topographical and soil characteristics for the 25 individual micro-plots
pooled together as per treatment applied, on the day before experiment (t0) and immediately
after the experiment ended (t360) .............................................................................................. 59 Table 5.3. Average soil metals concentration of copper (Cu), nickel (Ni), lead (Pb), zinc (Zn),
cadmium (Cd), chromium (Cr) before start of experiment (t0) and after the experiment (t360)60 Table 5.4. The average total and faecal coliforms (±std. dev.) for soil and biosolids on the day
before experiment (t0) and after the experiment (t360) ............................................................. 61 Table 5.5. Nutrient and metal characteristics of the biosolids................................................ 63 xv Chapter 1 –INTRODUCTION
1.1. Overview
In the European Union (EU), implementation of directives and other legislative measures in
recent decades concerning collection, treatment and discharge of wastewater, as well as
technological advances in the upgrading and development of wastewater treatment plants
(WWTPs) (Robinson et al., 2012), has resulted in a rise in the number of households
connected to sewers, which has increased the pressure on WWTPs (European Community
(EC), 2014). Consequently, production of untreated sewage sludge in the EU has increased
from 5.5 million tonnes of dry matter (DM) in 1992 to an estimated 10 million tonnes in 2010
(Eurostat, 2014), with production further expected to increase to 13 million tonnes in all EU
member states by 2020 (EC, 2010).
The treatment and disposal of sewage sludge presents a major challenge in wastewater
management and, consequently, there is a need to find a cost-effective and innovative
solution for its disposal (Hall, 2000). In the EU, the drive to reuse sewage sludge has been is
a result of various directives, which advocate the re-use of sludge and limit the disposal of
biodegradable municipal waste via landfill. In addition, the minimisation, recycling and
recovering of waste is one of the six key goals outlined by the Environment Protection
Agency (EPA). The legislation concerning sewage sludge production has actively prompted
those involved in sludge management to find alternative uses for sludge, such as in the
production of energy, bio-plastics, polymers, and other potentially useful materials (Healy et
al., 2015). Recycling to land is currently considered the most economical and beneficial way
for sewage sludge management (Haynes et al., 2009; Peters et al., 2009; Healy et al., 2015). Recycling of biosolids to agricultural land is relatively less expensive compared to
incineration and landfill per tonne of raw sludge (DM) (Antille et al., 2013). However, before
1 this can occur, it must be treated by one or more of the recommended process as set down in
the guidelines to prevent harmful effects on soil, vegetation, animals and humans (EC, 2014),
after which they may be referred to as ‘biosolids’. The term ‘biosolids’ was formally created in 1991 by the Name Change Task Force of the Water Environment Federation (WEF., 2005)
to differentiate raw, untreated sewage sludge from treated and tested sewage sludge that can
legally be utilized as a soil amendment and fertiliser.
Although there are many benefits associated with the use of biosolids on agricultural land,
biosolids can, and often do, contain other less useful and potentially dangerous constituents
such as metals, so-called ‘emerging’ organic pharmaceutical contaminants and human enteric
pathogens, which have been discussed by Lu et al. (2012) and Singh et al. (2008), amongst
others. These concerns become more prevalent when losses due to episodic rainfall events
following land application are transferred to water bodies via direct discharge surface
pathways or groundwater discharge. Although much research work has investigated their
impact on nutrient, metal and suspended sediment (SS) release, many knowledge gaps still
exist surrounding the potential impact arising from the landspreading of biosolids. In
addition, the relative impact of different types of biosolids (lime stabilised (LS),
anaerobically digested (AD) and thermally dried (TD)), when spread at the same application
rate, has not yet been compared on a micro-plot field scale.
The specific objectives of this current runoff study were to:
1) Review the legislation and guidelines governing the application of biosolids to land
and to elucidate research to date involving their use.
2) Develop a simple, novel, field-scale micro-plot study to determine the impact of land
applications of three types of biosolids (1) AD biosolids from a WWTP in the United
Kingdom (ADUK) (2) AD biosolids sourced in Ireland (ADIRE) (3) TD biosolids (4)
2 LS biosolids, (5) grass-only (the study control), and compare them to a commonly
spread organic amendment in Ireland (6) dairy cattle slurry (DCS).
3) Conduct in-field simulated rainfall events (24, 48 and 360 hr after land application of
biosolids) to measure incidental losses of nutrients, metals and microbial matter
1.2. Procedure
A literature review examined current legislation governing the landspreading of biosolids and
the potential impact that this could have on water quality when spread within (and outside)
current guideline limits. The literature review suggested that further investigation was
warranted into the potential impact of biosolids on surface runoff following landspreading
within current maximum legal application rates in Ireland and, in particular, the impact of
surface runoff of so-called ‘emerging’ organic pharmaceutical and personal care products
(PPCPs), sometimes found in biosolids, as they have been shown to have the highest risk
ranking of PPCPs based on the factors of persistence, bioaccumulation and toxicity. The
relative impact of environmental pollution of different types of biosolids (AD, LS, and TD),
when spread at the same application rate, has not been compared at micro-field scale in
Ireland. As a result of these knowledge gaps, the experiments were designed accordingly.
Thirty micro-plots, each measuring 0.9 m long and 0.4 m wide, were hydraulically isolated,
and the soil was characterised for texture, particle size distribution (% sand/silt/clay),
nutrients and metals. Following this, AD and TD biosolids and dewatered sludge cake were
collected from a WWTP in Ireland. The dewatered sludge cake was manually lime stabilised
under laboratory conditions to create LS biosolids for use in the experiment (this was to
ensure the biosolids came from the same source). The biosolids were then characterised for
nutrient, microbial and metal content. In addition, AD biosolids, sourced from the Seventh
Framework Programme (FP7) END-O-SLUDGE project, was used in the experiment. The
maximum permissible application rate under European legislation for the different types of
3 biosolids was then determined based on the soil test phosphorus (STP) content of the microplots, the legal limits for N, P, metal application; DM, nutrient, and metal concentration of the
biosolids.
Biosolids were then randomly assigned to the twenty five micro-plots, and three rainfall
simulations were conducted over a period of 15 days after land application. Grass samples
from each plot were also collected prior to each rainfall simulation event to examine the
uptake of metals. In addition, surface runoff from five micro-plots amended with DCS, which
is commonly land applied as an organic fertiliser in Ireland, was examined so that a
comparison of environmental losses could be made with the biosolids. 1.3. Structure of dissertation
Chapter 2 presents the literature review that was conducted in this study. Chapter 3 discusses
importance of rainfall simulators in agricultural research and the design of the rainfall similar
used in this study. Chapter 3 also describes the rainfall simulator and how it was calibrated.
Chapter 4 describes a bench-scale test used to determine the incorporation of lime (calcium
oxide, CaO) into dewatered sludge and to create LS biosolids. Chapter 5 describes the field
rainfall simulator study and presents the surface runoff results for biosolids and DCS. Finally,
Chapter 6 presents the conclusions and recommendations of the study.
1.4 Study outcomes to date
Book chapter:
Healy, M.G., Clarke, R., Peyton, D., Cummins, E., Moynihan, E.L., Martins, A., Beraud, P.,
Fenton, O. 2015. Resource Recovery from sludge. p. 139 - 162. In K. Konstantinos, K.P.
4 Tsagarakis (Eds.) Sewage treatment plants: economic evaluation of innovative technologies
for energy efficiency. IWA, London.
Journal:
Peyton, D.P, Healy, M.G, Fleming, G.T.A., Grant, J., Wall, D., Morrison, L., Cormican, M.,
Fenton, O. Nutrient, metal, microbial and persona care product losses in runoff following
treated sludge application to an Irish grassland soil: a rainfall simulation study. Submitted to
Science of the Total Environment.
Conferences:
Healy, M.G., Morrison, L., Forrestal, P.J., Peyton, D., Fleming, G.T.A., Danaher, M., Wall,
D., Cormican, M., Fenton, O. 2015. Characterisation of metal concentrations in treated
municipal sludge in Ireland and impacts on runoff water quality following land application.
International Conference on Solid Wastes 2015: Knowledge Transfer for Sustainable
Resource Management. Hong Kong SAR, China. 19 – 23 May, 2015
Healy, M.G., Peyton, D., Fleming, G., Danaher, M., Morrison, L., Wall, D., Grant, J.,
Cormican, M., Fenton, O. 2014. Measurement of surface runoff of mixed contaminants
arising from the landspreading of treated sewage sludge. ASA, CSSA, and SSSA
International Annual Meeting. Nov 2 – 5, Long Beach, CA.
Peyton, D.P, Healy, M.G, Fleming, G.T.A., Grant, J., Wall, D., Morrison, L., Cormican, M.,
Fenton, O. 2015. Nutrient, metal, microbial and persona care product losses in runoff
following treated sludge application to an Irish grassland soil: a rainfall simulation study. 25th
Annual SETAC Europe Conference Meeting 3-7 May Barcelona, Spain 2015 (poster
presentation)
5 Chapter 2 - LITERATURE REVIEW
2.1. Overview
This chapter reviews the use of biosolids in agriculture, and investigates their potential
impact on surface and groundwater quality.
2.2. Introduction
Sewage sludge is the inevitable organic by-product of urban waste water treatment (Fehily,
Timoney and Company, 1999), and is formed when wastewater undergoes various physical,
chemical and biological processes to separate water from solids. Following appropriate
treatment of sewage sludge by one of more the recommended process, treated sewage sludge,
hereby referred to as “biosolids”, may be successfully recycled and applied to agricultural
land as an organic fertiliser (USEPA, 2012). When spread on tillage or grassland, they offer
an excellent source of nutrient and metals required for plant and crop growth (Lucid et al,
2014). As demands for food and energy are expected to increase from a growing population
(FAO, 2009), the demands for nitrogen (N), phosphorus (P), and potassium (K) are also
expected to increase at an average rate of 2.5% per year to 2020 (Heffer et al., 2013), and as a
result, the price of chemical fertiliser is also expected to increase (Heffer et al., 2013).
As biosolids are often considered a waste product, they may be used as a cheap source of
fertiliser and may provide an excellent opportunity to improve crop profit margins by means
of reducing the input costs of chemical fertilisers. The recycling of biosolids to agricultural
land is also seen as a means to reduce dependence on phosphate rock (Antille et al., 2013).
Although there are many benefits associated with the land application of biosolids on
6 agricultural land, environmental pollution as a result of losses of nutrients and, in particular,
other less useful and potentially dangerous constituents such as metals, human enteric
pathogens, and so-called ‘emerging’ PPCP contaminants, following an episodic rainfall event,
may result in the limitation of biosolids as a fertiliser. It is therefore essential to investigate
the many knowledge gaps currently associated with the landspreading of biosolids, so that
any potential nutrient recovery from biosolids is considered against possible adverse impacts
on the environment are minimised.
2.3. Sewage Sludge as a Resource
Biosolids may be used as an agricultural fertiliser, as they contain organic matter (OM) and
inorganic elements (Girovich, 1996). The recycling of biosolids to agriculture as a source of
the fundamental nutrients and metals required for plant growth is going to be essential for
future sustainable development, as it is estimated that there are only reserves of 50-100 years
of P depending on future demand (Cordell et al., 2009). Evans (2009) highlighted that up to
95% of P can be recovered from wastewaters and concentrated into the raw sludge. As P is a
limited resource, any recovery and utilisation is a significant step in reducing the rate of
depletion. When spread on arable or grassland, and provided that it is treated to the approved
standards, biosolids may offer an excellent source of nutrients and metals required for plant
and crop growth (Jeng et al., 2006). Biosolids may also contribute to improving soil physical
and chemical characteristics (Mondini et al., 2008). It increases water absorbency and tilth,
and may reduce the possibility of soil erosion (Meyer et al., 2001).
Land application of biosolids to agricultural land can be relatively inexpensive in countries in
which it is considered to be a waste material. An alternative, but costly, option in such
countries is to pay tipping fees for its disposal (Sonon et al., 2009). However, in some
countries sewage sludge is seen not as a waste but instead as a product containing valuable
7 nutrients (e.g. the U.K and Ireland) with an associated fertiliser replacement value (FRV) and
cost for its usage.
As the world population increases, pressure on natural resources, especially food, oil and
water, will increase. Inorganic fertilizer prices are tied to crude oil prices globally and
demand (Bremer, 2009): when prices of oil are high, inorganic fertilizer prices also climb.
For instance, in Ireland, the cost of inorganic fertilisers has continually increased, with the
cost of a mean kg of N, P and K rising from €0.41, 1.06 and 0.23 in 1980 to €103, 203, 105 in
2011 (Fig. 2.1). Similar price increases of 13% were seen in the U.K. in 2010 (Tasker, 2010).
Recent fertiliser increases since 2008 can be attributed to increases in both energy costs and
global demand for fertilisers. Increased prices and volatility are important considerations, as
they lead to volatility in farm input costs and profit margins, and make farm planning more
difficult and risky (Lalor et al., 2012).
Figure 2.1. Trends in unit cost of nitrogen (N), phosphorus (P) and potassium (K) in
chemical fertilisers in Ireland from 1980 to 2011 (Lalor et al. 2012).
8 Nutrient price equivalents of sewage sludge will depend on the nutrient availability and the
FRV of the nutrients in the sludge. The FRV of nutrients in cattle slurry over time was
calculated in Lalor et al. (2012) assuming a total N, P and K content in slurry of 3.6, 0.6 and
4.3 kg m-3, respectively, and an assumption of respective FRV of 25%, 100% and 100%
(Coulter., 2004). Of course in biosolids, as in other nutrient streams, micronutrients used by
the plant give added value to the product. In addition, factors such as transport and land
application costs would also need to be considered in an overall assessment. It is therefore
essential that such data are known for biosolids.
There is a good body of literature that has examined its fertilisation potential (Smith et al.,
2002; Epstein, 2003; Singh et al., 2008). Siddique et al. (2004) mixed AD-treated sewage
sludge, poultry litter, cattle slurry and an inorganic P fertiliser with five soil types at rates
equivalent to 100 mg P kg-1 soil and, following incubation at 25oC for 100 d, found that ADbiosolids and poultry litter had a slower rate of P release compared with cattle slurry and
inorganic P fertiliser. This may indicate that it may have good long-term fertilisation
potential. 2.4. Legislation governing disposal of biosolids
The drive to recycle biosolids to agricultural land has been accelerated by, amongst other
legislation, the Landfill Directive, 1999/31/EC (EC, 1999), the Urban Wastewater Treatment
Directive 91/271/EEC (EC 1991), the Waste Framework Directive (2008/98/EC; EC 2008),
and the Renewable Energy Directive (2009/28/EC; EC 2009), which places an increased
emphasis on the production of biomass-derived energy. However, one of the main pieces of
legislation governing the use of biosolids in agriculture in Ireland and the EU is the Sewage
Sludge Directive 86/278/EEC (EEC, 1986), which seeks to encourage the use of sewage
sludge in agriculture and to regulate its use in such a way as to prevent harmful effects on
9 soil, vegetation, animals and man. In Ireland, the directive is enacted in the “Codes of Good
Practice for the Use of Biosolids in Agriculture” (Fehily, Timoney and Company, 1999)
which set out limits for metal application (Table 2.1), and S.I. No. 610 of 2010, which sets
out nutrient limits for various crops grown in Ireland.
The Directive 86/278/EEC and the Codes of Good Practice specifies rules for the sampling
and analysis of sludge and soils. It also sets out requirements for the keeping up to date
records on the quantities of sludge produced by each EU member state, the quantities used in
agriculture, the composition and properties of the sludge, the type of sludge treatment, and
the sites where the sludge is used and disposed. It also sets out requirements on the
concentrations of metals in biosolids intended for agricultural use and in biosolids-treated
soils (Table 2.1). The Directive 86/278/EEC and the Codes of Good Practice also specifies
rules which detail issues such as constraints on grazing for animals and cultivation of crops
following land application of biosolids, the types of crops and lands on which the biosolids
may be spread, the times of the year when the land application of biosolids is prohibited, and
safe spreading distances from entities such as watercourses. As a result of the legislation, land
application of biosolids in the EU is typically based on its nutrient and metal content,
although individual member states often have more stringent limits than the Directive (EC
2010; Milieu et al. 2013a,b,c). Generally, when applying biosolids based on these guidelines
and depending on the nutrient and metal content of the biosolids, P in the majority of cases
becomes the limiting factor. However, while the guidelines aim to prevent harmful effects,
they do not consider the relationship between biosolids application rate, nutrient availability,
and surface runoff of nutrients, microbes and metals.
10 Table 2.1. Limit values for metal concentrations in sludge and soil (taken from Lucid et al., 2013).
Limit values
Copper
(Cu)
Nickel (Ni)
Lead (Pb)
Cadmium
(Cd)
Zinc (Zn)
Chromium
(Cr)
Mercury
(Hg)
--------------------------------------------- mg kg-1 --------------------------------------------European Uniona
For concentrations of
heavy metals in soil
50 - 140
For heavy metal
concentrations in sludge
for use in agriculture
1,000
1,750
-
30 - 75
50 - 300
150 – 300
300 -400
750 - 1,200
2,500
4,000
-
1-3
-
1 - 1.5
20 - 40
-
16 - 25
-------------------------------------------- kg ha-1y-1 -----------------------------------------For amount of heavy metal
that may be applied
annually to soil
12.0
3.0
15.0
30.0
0.15
-
0.1
7.5
3.0
4.0
7.5
0.05
3.5
0.1
Ireland
For average annual rate of
addition of metal (over a
10 yr period)b
a
Limit values taken from Directive 86/278/EEC (EEC, 1986).
b
Limit values taken from (Fehily, Timoney and Company, 1999).
11 While the Directive 86/278/EEC and the Codes of Good Practice share many of the
regulations, there are a number of exemptions and provisions in the current regulation which
should be removed or amended with the Codes of Good Practice, as it will give rise to further
food safety concerns. For example, the Codes of Good Practice states that untreated
wastewaters sludge should not be landspread or injected into soil. However, 86/278/EEC
states the latter provided that it has been injected or incorporated into the soil.
2.5. Wastewater treatment
The purpose of wastewater treatment is to remove contaminants from wastewater, including
household sewage and runoff, while producing an environmentally safe fluid waste stream
(treated effluent) and a solid waste (treated sludge) suitable for disposal or reuse as a farm
fertiliser. Wastewater treatment involves the physical, chemical, and biological treatment or a
combination of these processes depending on the nature of the inflow influent wastewater,
together the water quality objectives of the receiving bodies (Grey, 2002). The treatment
process is classified into five main stages: preliminary, primary secondary, tertiary and sludge
treatment. A simplified wastewater treatment process is illustrated in Fig. 2.2 comprising the
five main treatment processes.
12 Figure 2.2. Illustration of a simplified wastewater treatment process (adapted from Antille et
al., 2011; Metcalf et al., 2003).
2.5.1. Preliminary treatment
The purpose of preliminary treatment is to protect the operation of the wastewater treatment
plant. Preliminary wastewater treatment involves the removal of coarse solids and other large
materials that may cause operational and maintenance of subsequent treatment units (FAO,
2014). Solids that may be removed during this process may consist of pieces of wood,
plastics, paper, cloth, together with some faecal matter. Heavy inorganic solids such as sand
and gravel, as well as metals or glass, are removed at this stage, and finally excessive
amounts of oils or greases in the influent wastewater are also removed. Flow equalization of
the inflow is also controlled at this stage (EPA, 1997).
13 2.5.2. Primary treatment
The purpose of primary treatment is to remove organic and inorganic solids by sedimentation.
There are two main methods employed during this stage. The first is physical settlement,
which involves the removal of settleable solids from base of the tank (removed as primary
sludge). The second method is chemical coagulation and flocculation. This involves the
addition of chemical coagulants to the influent, where the coagulant encourages insoluble
material to form flocks. Following further settlement, these are removed as primary sludge.
Primary treatment can reduce the biochemical oxygen demand (BOD) by 30 - 40%, SS by 40
- 70%, and faecal coliforms (FC) by up to 50% (Grey, 2002).
2.5.3. Secondary treatment
Secondary treatment involves the removal of biodegradable dissolved and colloidal OM. This
treatment process uses microorganisms to convert soluble and colloidal OM into carbon
dioxide, water and new cells (Lehany, 2003). Secondary settlement tanks are used to separate
microorganisms from the treated wastewater to produce clarified secondary effluent. The
biological solids removed during secondary treatment are combined with the primary sludge
for sludge treatment (FAO, 2014). Secondary sludge is composed mainly of biological cells,
in contrast to the primary sludge, which is composed mainly of faecal solids (Lehany, 2003).
There are several secondary biological treatment processes available, which include trickling
filters or biofilters, fixed film reactors, activated sludge systems, and stabilisation ponds
(FAO, 2014; Gray, 2002; Metcalf et al., 2003;).
2.4.4.Tertiary treatment
Tertiary treatment further removes BOD, SS, bacteria, potentially toxic element and nutrients
(Lehany, 2003). Tertiary treatment is needed when wastewater is discharged to sensitive
water bodies (Antille, 2011). A number of systems are available for tertiary treatment, and a
14 detailed overview of them is given in Metcalf et al. (2003). These include: prolonged
settlement in lagoons or irrigation onto grasslands or percolation areas, wetlands, disinfection
by either of the two main methods - ultraviolet (UV) treatment or chlorination, chemical
precipitation (e.g. ferric chloride, aluminium sulphate or lime), which react with the soluble
phosphate to produce an insoluble precipitate.
2.5.5. Sludge treatment
Sludge is the organic by product arising from the treatment of wastewater, which requires
further treatment (i.e. to produce biosolids) for their safe use as an agricultural fertiliser. One
of the main objectives of sludge treatment is reduced water content (dewatering) prior to
disposal. Primary and secondary sludge typically comprise 97 to 99.5% water (RuizHernandoet et al., 2013) and as a result, dewatering is necessary to reduce the total sludge
volume as well increasing its handling characteristics. Sludge dewatering is completed by
gravity thickening, using a belt filter press or by using drying beds. Dewatering using these
methods will leave a composition of solids in treated sewage sludge of between 12 and 30%,
and between 80 and 90% for sludge treated by thermal drying (Lehany, 2003). An important objective of sludge treatment is the reduction or removal of pathogens to an
acceptable level and reduction of attractiveness of sewage sludge to vectors. As untreated
sewage sludge contains high levels of pathogens (e.g., bacteria, viruses, protozoa, helminths)
(Sidhu et al., 2009), if applied to agricultural lands, they will have the potential to
contaminate soil, vegetation and water. Due to the lack of well-developed methods for the
detection and enumeration of pathogens (Sidhu et al., 2009), the use of indicator organisms
such as FC along with Salmonella species, are used to evaluate the microbiological
contamination of biosolids. The microbiological standards used are derived from the USEPA
15 part 503 biosolids rule (USEPA, 1993) (Table 2.2). Class A biosolids are treated to a higher
standard than Class B biosolids and also require less or no restrictions on buffer
requirements, public access, or crop harvesting restriction (USEPA, 1993), while these are
required for virtually all forms of Class B biosolids (USEPA, 2012). While Class A biosolids
are treated to a higher standard than Class B biosolids, the long-term application of Class B
biosolids to land is still regarded as sustainable, with the risk of pathogens posing a low threat
to human health (Pepper, 2008). In Ireland, the microbiological standards are defined under
the code of good practice for the use of biosolids in agriculture (Fehily, Timoney and
Company., 1999), and are equivalent to Class A biosolids.
Table 2.2. Microbiological standards used to classify biosolids as Class A or Class B
biosolids (Fehily, Timoney and Company., 1999; USEPA, 1993)
Type of biosolids
Microbiological standards used to classify biosolids
Class A
Either the density of faecal coliforms in the biosolids must be less
than 1 x 103 most probable number (MPN) per gram total solids
(DM), or the density of Salmonella species bacteria in the biosolids
must be less than 3 MPN per 4 g of total solids (DM) and time of use
or disposal.
Class B
Class B biosolids are treated by the same process as Class A
biosolids, but can contain detectible levels of faecal coliforms up to 2
x 106 MPN g-1 DS. For this reason, Class B biosolids are required to
have site restriction, preventing crop harvesting, animal grazing and
access to the public for specific period of time following application
until pathogen levels have further reduced (USEPA, 1993).
2.6. Types of treated biosolids
Stabilisation is designed to control potential putrefaction process, odour releases and vector
attraction. A variety of sewage sludge treatment technologies can be employed and are
implemented according to regulations. As can be seen from Table 2.3, significant differences
in sewage sludge treatment exist. At present, in Ireland, there are five main methods adopted
16 for the treatment of biosolids before land application: AD, TD, composting, LS and
autothermal, thermophilic aerobic digestion (Fehily, Timoney and Company, 2007). Table 2.3. Global municipal sewage sludge treatment processes
Denmarka
Francea
Aerobic


Anaerobic


Lime


Composting


Germanya
Greecea,b
Irelanda
Italya
Spaina
Swedena
UKa
Czech
Rep.a
Polanda
USAc
Portugald





























Stabilisation











Conditioning
Lime


Inorganics





Polymers

Thermal


Drying belts

Dewatering

Filter press














Centrifuges
Belt filter press















Others

Thermal
Solar drying





Pasteurisation
Long-term
storage




Cold
fermentation bag
filling
 Common use  most common use
a
Kelessidis at al., (2012); b Tsagarakis et al. (1999) c Lu et al., (2012)
2.6.1. Anaerobic digestion
Anaerobic digestion is a common method for the treatment of sewage sludge prior to land
application. It involves the incubation of sludge under anaerobic conditions for a mean
17 retention time of at least 12 days of primary digestion at the mesophilic temperature range of
35°C, or of at least 20 days of primary digestion at a temperature of 25°C, or the thermophilic
temperature of 55oC for a mean retention time of 48-72 hr. The AD process works by the
stabilising the organic material and reducing the pathogenic content by utilising certain
microbes that thrive in an environment that lacks oxygen. During the process, organic
material is converted to methane, carbon dioxide and digestate. Anaerobic digestion produces
Class A biosolids at thermophilic temperatures and Class B biosolids at mesophilic
temperatures (Epstein, 2002). It is required that the AD process undergo a pasteurisation
phase in which there is a retention period of at least 1 hr for a temperature of 70oC and 2 hr
for a temperature of 55oC (Fehily, Timoney and Company, 1999). Anaerobically digested
biosolids are shown in Fig. 2.3. The advantages of AD are that the methane gas can be
subsequently used as an energy source (Epsten, 2002), the mass and volume of the sludge are
reduced, a low running cost and high loading rates (Grey, 2002). The disadvantages include
long start up times due to slow growth rate of anaerobic bacteria, the highly polluted
supernatant arising from thickening and dewatering and the sensitivity to chemicals, pH
variation and toxic overloads (Spinosa et al., 2001). 18 Figure 2.3. A 50 g sample of anaerobically digested biosolids (ADIRE)
2.6.2. Thermal drying
Thermal drying technology is based on the removal of water from dewatered solids by
evaporation of water, which dramatically reduces achieves both volume and weight. The
result is a Class A product with a DM content of approximately 90% (Fig. 2.4). The high
temperatures used in the production of TD biosolids ensure a sufficient reduction in pathogen
numbers and the temperatures used, while high, are generally low enough to prevent
oxidation of OM. In recent years, TD biosolids pellets have been mixed with urea, potash and
other substance to created organomineral fertilisers (OMFs) (Antille et al., 2013). The
advantages of thermal drying is that approximately 90-95% DM can be achieved, and that the
sludge generated is stable, odourless and amenable to long-term storage, and that spreading
techniques are similar to those used for mineral fertilizers. The disadvantage is the high
capital investment and on-going operational cost (Lehaney et al., 2003)
19 Figure 2.4. A 50 g sample of thermally dried biosolids (TD)
2.6.3. Lime Stabilisation
Lime stabilisation, commonly known as alkaline stabilisation, raises the pH level of the
sludge, thus making conditions unfavourable for the growth of organisms. Lime stabilisation
is increasingly used in countries because it is a cost effective way of stabilisation municipal
sludge (Krach et al., 2008). Materials that may be used for alkaline stabilization include
hydrated lime, CaO, commonly known as quicklime or burnt lime; fly ash, lime and cement
kiln dust, and carbide lime (USEPA, 2000). However, CaO is commonly used because it has
a high heat of hydrolysis, which can significant enhance pathogen destruction (USEPA,
2000). The high temperature and pH inhibits biological action, therefore inactivating
pathogens in the treated biosolids product (Joyce et al., 2014). The rate at which lime is
added to achieve these regulations is dependent on dry solid content content of the sludge
produced (Andreadakis, 2000). In addition, the extent of heat generated is also dependent on
the lime dose rate (Smith et al., 1998).
20 The effectiveness of the lime stabilisation process for pathogen reduction and odour is
dependent on significant lime addition and incorporation (Burns et al., 2007). Uniform lime
incorporation is critical to the lime stabilisation process, as it is important to eliminate regions
with low pH within the lime-sludge mix. Poor lime incorporation will result in inadequately
stabilised regions, leading to microbial regrowth, driving further pH reduction and causing
increased odour (Burns et al., 2007). Lime stabilised biosolids also offer the benefit of a
substitute for agricultural lime (Jacobs et al., 2003). Lime biosolids are shown in Fig. 2.5.
Figure 2.5. A 50 g sample of lime stabilised biosolids (LS). 2.6.4. Composting
Composting is the biological degradation of OM, resulting in the formation of a stable end
product. Composting of sludge produces a humus-rich material that can be applied directly to
land to provide a nutrient benefit, or to add organic content and improve the tilth of a soil
(Fehily, Timoney and Company, 2007). However, composted biosolids generally spread as a
21 soil improver rather than fertiliser, as their fertilising capability is a function of time and
maturity of the material (Fehily, Timoney and Company, 2007).
The method of composting is wide ranging and varied, but the two main methods involve
windrows or aerated static piles. Due to the waterr content and the fine particle size of sludge,
it needs to be mixed with an amendment material to provide further bulking and space for the
passage of air through the material. The amendment material is generally shredded green
waste, woodchip and, in some cases, shredded tires (USEPA, 2002). Composted biosolids
may also be mixed with other materials e.g. household or commercial food waste. The
‘Codes of Good Practice for the Use of Biosolids in Agriculture’ gives time – temperature
recommendations for the sanitisation of material when composting biosolids. Windrow
composting must be held at 55°C for at least 15 days, during which time the material must be
turned 5 times. In-vessel or static pile composting requires maintaining a temperature of 55°C
for a minimum of 3 days. However, the beneficial reuse of compost as an organic fertiliser
can be limited, as Sidhu (2001) highlighted that composted biosolids have a Salmonella regrowth potential. As a result, long-term storage is not recommended 2.6.5. Autothermal Thermophililic Aerobic Digestion
Autothermal thermophilic aerobic digestion (ATAD) is a biological sludge treatment process
that converts soluble organics to lower energy forms through fermentative anaerobic and
aerobic processes. Autothermal TAD is an exothermic process where sludge is subjected to
temperatures > 55 °C and a hydraulic retention time of 6–15 days (Layden et al., 2007).
Organic solids are degraded and the heat released during the microbial degradation maintains
thermophilic temperatures. Autothermal TAD can produce a biologically stable product while
reducing both sludge mass and volume (Bernard et al., 2000). Minimum concentrations of
total volatile solids of 3 – 4% and total solids (TS) of 5-6% are also typical requirements
22 (Fehily, Timoney and Company, 2007). At present, there is only one plant in Ireland
producing Class A biosolids by ATAD, which is located in Killarney, County Kerry. 2.7. Existing and emerging issues concerning the use of biosolids on agricultural land
2.7.1. Nutrient and metal losses
Phosphorus and reactive N losses to a surface waterbody originates from either the soil
(chronic) or in runoff, where episodic rainfall events follow land application of fertiliser
(incidental sources) (Brennan et al., 2012). Such losses to a surface waterbody occur via
primary drainage systems (end of pipe discharges, open drain networks) (Ibrahim et al.,
2013), runoff and/or groundwater discharges. Application of biosolids to soils may also
contribute to STP build-up in soils, thereby contributing to chronic losses of P, metal and
pathogen losses in runoff (Gerba et al., 2005). Dissolved reactive P losses may also be
leached from an agricultural system to shallow groundwater (Galbally et al., 2013) and,
where a connectivity exists, may affect surface water quality for long periods of time
(Domagalski et al., 2011; Fenton et al., 2011).
The metal content of treated sludge and of the soil onto which it can be spread, is also
regulated by legislation in Europe (86/278/EEC; EEC, 1986). However, guidelines governing
the application of treated sewage sludge to land (e.g. Fehily Timoney and Company 1999)
mean that is frequently the case that application rates are determined by the nutrient content
of the sludge and not its metal content (Lucid et al. 2013). Regardless, concerns have been
raised about the potential for transfer of metals into water bodies, soil structures and,
consequently, the food chain (Navas et al., 1999). In countries such as the USA, where treated
sewage sludge is land applied in the majority of states (e.g. exclude Maryland) based on the
N requirement of the crop being grown and not on a soil-based test (McDonald et al., 2011),
excessive metal losses may potentially occur.
23 2.7.2. Behaviour of metals in the soil/Uptake by plants
The potential of biosolids to contaminating soils with heavy metals has caused great concern
about their application on agricultural land (Wuana et al., 2011). Heavy metals most
commonly found in biosolids are lead (Pb), nickel (Ni), cadmium (Cd), chromium (Cr),
copper (Cu), and zinc (Zn), and the metal concentrations are governed by the nature and the
intensity of the industrial activity, as well as the type waste water treatment employed
(Silveira et al., 2003). As a result, emphasis concerning land application of biosolids has been
placed on these heavy metals. In Ireland, the code of good practice for the use of biosolids in
agriculture places maximum concentrations limits on the loadings of these metals to
agricultural land (Table 2.1). However, many other factors, including, application rate, pH
and other soil characteristic such as OM content and redox potential, affect the accumulation
of the metals in biosolid-amended soils (Hue et al., 1994; Singh et al., 2008; Smith, 2009).
As the application of biosolids to land may pose a risk to soil contamination due to metal
accumulation, an understanding of behaviour of metals in the soil is essential for assessing
environmental risks. One of the main concerns with the possible accumulation of metals in
soil is the possibly of them being incorporated into plants. As a consequence, the
consumption of plants containing high levels of metals may pose a serious threat to human
health via the food chain (Silvera et al., 2003). Studies examining the uptake of metals by
plants have focused on metals behaviour and fate in soils; and on three hypotheses, plateau,
time bomb, and soil-plant barrier (Lu et al., 2012). The plateau hypotheses considers that
metal bioavailability is greatly reduced as they are so tightly held by the OM and clay content
of the soil, that they are retained in the soils surface horizon or plow layer, instead of leaching
down the soil profile (Lu et al., 2012). Therefore, metal concentrations in plant tissues will
reach a plateau as biosolids loading increases and will remain at this plateau even after land
spreading has stopped (Ross, 1994). Time bomb theory suggest that metal concentration
24 bound to biosolids could be realised to soluble forms over time, therefore, becoming toxic to
plants, as a time bomb (Lu et al., 2012). The soil-plant barrier theory indicates that plants play
an important role in protecting the food chain, since transfer of metals to the edible part of the
crop is under the physiological control of the plant (McBride, 2002). In addition, metals are
tightly bonded to soil, limiting their transfer to the roots of a plant (McBride, 2002).
2.7.3. The microbial risk associated with the landspreading of biosolids
During wastewater treatment, the sludge component of the waste becomes separated from the
water component. As the survival of many microorganisms and viruses in wastewater is
linked to the solid fraction of the waste, the numbers of pathogens present in sludge may be
much higher than the water component (Straub et al., 1992). Although treatment of municipal
sewage sludge using lime, AD, or temperature, may substantially reduce pathogens, complete
sterilisation is difficult to achieve (Sidhu et al., 2009) and some pathogens, particularly
enteric viruses, may persist. Persistence may be related to factors such as temperature, pH,
water content (of treated sludge), and sunlight (Sidhu et al., 2009). There can be also
resurgence in pathogen numbers post-treatment, known as the ‘regrowth’ phenomenon. This
may be linked to contamination within the centrifuge, reactivation of viable, but nonculturable, organisms (Higgins et al., 2007), storage conditions post-centrifugation (Zaleski et
al., 2005), and proliferation of a resistant sub-population due to newly available niche space
associated with reduction in biomass and activity (McKinley et al., 1985).
The risk associated with sludge-derived pathogens is largely determined by their ability to
survive and maintain viability in the soil environment after landspreading. Survival is
determined by both soil and sludge characteristics. The major physico-chemical factors that
influence the survival of microorganisms in soil are currently considered to be soil texture
and structure, pH, moisture, temperature, UV radiation, nutrient and oxygen availability, and
25 land management regimes (van Elsas et al., 2011), whereas survival in sludge is primarily
related to temperature, pH, water content (of treated sewage sludge), and sunlight (Sidhu et
al., 2009). Pertinent biotic interactions include antagonism from indigenous microorganisms,
competition for resources, predation and occupation of niche space (van Elsas et al., 2002).
Pathogen-specific biotic factors that influence survival include physiological status and initial
inoculum concentration (van Veen et al., 1997).
Following landspreading, there are two main scenarios which can lead to human infection.
First, pathogens may be transported via overland or sub-surface flow to surface and ground
waters, and infection may arise via ingestion of contaminated water or accidental ingestion of
contaminated recreational water (Jaimeson et al., 2002; Tyrrel et al., 2003). Alternatively, it is
possible that viable pathogens could be present on the crop surface following biosolids
application, or may become internalised within the crop tissue, where they are protected from
conventional sanitization (Itoh et al., 1998; Solomon et al., 2002). In this case, a person may
become infected if they consume the contaminated produce. Therefore, it is critical to
accurately determine the pathogen risk associated with land application of biosolids to fully
understand the potential for environmental loss and, consequently, human transmission.
However, survival patterns of sludge-derived pathogens in the environment are complex, and
a lack of a standardised approach to pathogen measurement makes it difficult to quantify their
impact. For example, Avery et al. (2005) spiked treated and untreated sludge samples with a
known concentration of E. coli to quantify the time taken to achieve a reduction. The
pathogen response was variable and ranged from 3 to 22 days, depending on sludge
properties. Lang et al. (2007) investigated indigenous E. coli survival in dewatered,
mesosphilic anaerobically digested (DMAD) sludge, and in different soil types post DMAD
sludge application. Again, decimal reduction times proved variable, ranging from 100 days
26 when applied to air-dried sandy loam, to 200 days in air-dried, silty clay textured soil. This
time decreased to 20 days for both soil types when field moist soil was used, demonstrating
the importance of water content in regulating survival behaviour.
Therefore, in order to quantify pathogen risk in a relevant, site-specific manner, it is
necessary to incorporate both soil and treated sewage sludge characteristics in risk assessment
modelling. This has been done previously by conducting soil, sludge and animal slurry
incubation studies, where pathogens are often spiked to generate a survival response (Vinten
et al., 2004; Lang et al., 2007; Moynihan et al., 2013). Pathogen decay rate is then calculated
based on decimal reduction times, or a first-order exponential decay model previously
described by Vinten et al. (2004), and has been shown to be highly contingent on soil type
and sludge or slurry combinations. Currently, the Safe Sludge Matrix provides a legal
framework for grazing animals and harvesting crops following landspreading of treated
sewage sludge, and stipulates that a time interval of three weeks and 10 months should be
enforced to ensure safe practice, respectively (ADAS, 2001). However, further work is
required to determine if these regulations are overly stringent, particularly in light of the
comparatively higher pathogen concentrations reported for animal manures and slurries. For
example, E. coli concentrations ranged from 3x102 to 6x104 colony forming units (CFU) g-1
in sludge (Payment et al., 2001), compared to 2.6x108 to 7.5x104 CFU g-1 in fresh and stored
cattle slurry, respectively (Hutchison et al., 2004). Therefore, environmental losses associated
with treated sewage sludge application may not be as extensive as previously thought and
further comparisons on pathogen risk should form the basis of future research.
2.7.4. Pharmaceutical and personal care products
Pharmaceuticals comprise a diverse collection of thousands of chemical substances, including
prescription and over-the-counter therapeutic drugs and veterinary drugs (USEPA, 2012).
27 Pharmaceuticals are specifically designed to alter both biochemical and physiological
functions of biological systems in humans and animals (Walters et al., 2010). Pharmaceuticals
are referred to as ‘pseudo-persistent’ contaminants (i.e. high transformation/removal rates are
compensated by their continuous introduction into the environment) (Barceló et al., 2007).
Pharmaceuticals are likely to be found in any body of water influenced by raw or treated
waste water, including river, lakes, streams and groundwater, many of which are used as a
drinking water source (Yang et al., 2011). Between 30 and 90% of an administered dose of
many pharmaceuticals ingested by humans is excreted in the urine as the active substance
(Cooper et al., 2008). In a survey conducted by the US Environmental Agency (McClellan et
al., 2010), the mean concentration of 72 pharmaceuticals and personal care products were
determined in 110 treated sewage sludge samples. Composite samples of archived treated
sewage sludge, collected at 94 U.S. wastewater treatment plants from 32 states and the
District of Columbia were analysed by liquid chromatography tandem mass spectrometry
using EPA Method 1694. The two most abundant contaminants found in the survey were the
disinfectants triclocarban and triclosan. The second most abundant class of pharmaceuticals
found were antibiotics, particularly ciprofloxain, ofloxacin, 4-epitetra-cycline, tetracycline,
minocycline, doxycycline and azithromycin (McClellan et al., 2010). It was concluded that
the recycling of biosolids was a mechanism for the release of pharmaceuticals in the
environment.
Pharmaceuticals have received increasing attention by the scientific community in recent
years, due to the frequent occurrence in the environment and associated health risks (Chen et
al., 2013). In 2007, the European Medicines Agency (EMEA) issued a guidance document
(ERApharm) on environmental risk assessment of human medicinal products. It relies on the
risk quotient approach used in the EU and is also used for industrial chemicals and biocides,
where the predicted environmental concentration is compared to the predicted no-effect
28 concentration. The overall objective of ERApharm is to improve and complement existing
knowledge and procedures for environmental risk of human and veterinary pharmaceuticals.
The project covers fate and exposure assessment, effects assessment and environmental risk
assessment (Lienert et al., 2007). A considerable amount of work focused on three case
studies. Two of the case studies focused on human pharmaceuticals, β-blocker atenolol and
the anti-depressant fluoxetine, and the third on a veterinary parasiticide ivermectin. Atenolol
did not reveal any unacceptable risk to the environment but cannot be representative for other
β-blockers, some of which show significantly different physiochemical characteristics and
varying toxicological profiles in mammalian studies (Knacker et al., 2010). Although found
in trace levels (several nanograms per litre), some therapeutic compounds such as synthetic
sex hormones and antibiotics, have been found to cause adverse effects on aquatic organisms
(Chen et al., 2013). Therefore, understanding their environmental behaviour and impact has
recently become a topic of interest for many researchers.
2.7.5. Public perception of the land spreading of biosolids
Managing municipal and industrial biosolids by recycling to land application is currently a
strategic policy directive in the EU. Management and treatment capacity of land application,
as well as the economic benefits, makes recycling biosolids to agricultural land appealing.
Although recycling biosolids to land is seen as a plausible management option, it is a
contentious issue that has cause much public opposition and concern (Beecher et al., 2005).
Concerns have been raised over potential health, safety, quality of life and environmental
impacts that land spreading of biosolids may have (USEPA, 2002). While governmental
bodies have laws, restriction and recommendation in place, public acceptance of land
application of biosolids still remain mixed. There are a number of reasons that can be
attributed to this and while traditional ways of addressing concerns has been through
29 scientific research (Tyson, 2002), many questions still remain. In addition to this, mistrust of
the opinions of politicians and technical advisors, resulting from failed past environmental
industrial incidence (Giusti, 2009), has created a sceptical public when it comes to new
technology.
As public perception can be critical in influencing the choice of options used for biosolids
management (USEPA, 2002), scepticism and mistrust of authorises and published science has
led to the banning or restriction of land application in some countries. Although the quality of
biosolids have improved over time with advancement in treatment technology (Robinson et
al., 2012), public concerns remains about the long-term health effect of exposure to
substances present in biosolids – especially through pathways such as food and soil. Food
scares worldwide in recent decades such as the bovine spongiform encephalopathy (BSE),
foot and mouth and, more recently, the Ecoli Cumcumber scares (BBC, 2011) and horsemeat
scandel in Europe (EC, 2014), have had a detrimental effect on public confidence and
farming practices. Although none of these presented cases are attrutued to the use of
biosolids, the fact that diseases could be contracted by humans via the direct food chain
resulting from farming practices has lead many people concerned about the use of biosolids
in agriculture. This concern has seen the introduction of “sludge free labels” being added to
packaging of food in some countries, mainly because the use of sludge is not considered to be
acceptable for products with a high-quality image (EC, 2010). In surveys undertaken on
public attitudes towards the land applcation of biosolids, interviewees are not enthusiastic
about recycling biosolids into food growing land (Tanto et al., 2010). Surveys also showed
that communities perceived greater health risk associated with exposure to biosolids than
animal manure due to the presence of pathogens (Robinson, et al., 2012). This perception
could be, in part, due to the fact that biosolids are heavily regulated or the fact that animal
manure is more commonly seen and used.
30 As biosolids are brought to forefront of the general public’s mind through increased land
application, knowledge and awareness has been heightened (Robinson et al., 2012). As
awareness, plays a key role in public perception of risk (Robinson et al., 2012), the public at
large are now beginning to assess for themselves whether or not this activity is safe. While governments and environmental authorities have tried to manage and reduce risk associated
with the reuse of treated sludge, effective management strategies should be to make sure that
the public is aware of the risks associated their reuse (Robinson et al., 2012). People’s
acceptance of risk is often subjective and depends in part on their basic values and beliefs, as
well as their training and experience (Harrison et al., 1999). In the past, waste management
programs have tried to improve acceptability by explaining the risk factors, where lack of
knowledge was deemed the primary issue (Nancarrow et al., 2008). While programs to
increase public knowledge have helped in educating with facts, little attention has been given
to addressing the values and beliefs driving the public’s perception (Robinson et al., 2012).
Research on public perception have shown that it is not often the overall concern with
biosolids, but rather the associated factors such as the increase in vehicle movements, odour,
or noise of machinery and equipment (Tyson, 2002; Beecher et al. 2004). Research has also
shown that the public are far more likely to be tolerant and, in some cases, supportive if they
have had their questions and concerns addressed (Tyson, 2002; Beecher et. al 2004). Norway
is a prime example of a country that has gained the trust of public acceptance with more than
90% its sludge used as a soil improvement product on land (EC, 2010).
2.8. Summary
The use of organic biosolids as a replacement for inorganic (i.e. chemical) fertilisers has
potential, provided they are spread within guideline limits. Where legislation is followed,
land application of biosolids should not pose any greater risk to the environment than other
organic fertilisers in terms of nutrient, metal and microbe losses. However, further research
31 will have to be carried out on emerging PPCPs to ensure their safe long-term use. At present,
public perception is one of the major stumbling blocks surrounding their use as an organic
amendment. However, further data on their potential impact on surface runoff of nutrients,
microbes and metals will address some of these concerns. These will be addressed in the
following chapters.
32 Chapter 3 - DESIGN OF A RAINFALL SIMULATOR
3.1 Overview
This chapter outlines the design, calibration and operation of the outdoor rainfall simulator
used in this study.
3.2 Rainfall simulators and their importance in agricultural research
Rainfall simulators are an important tool in arable and grassland agricultural research and
have been widely used for the assessment of soil hydrologic properties (Mohanty et al., 1996;
Loch et al., 1987), soil erosion (Iserloh et al., 2012; Sukhanovskii, 2007), infiltration and
runoff generation, and the movement of nutrients, metals or polluting agents in field and
laboratory conditions (Brennan et al., 2012; Fernandez - Galvez et al., 2008; Kramers et al.,
2009; Kurz et al., 2006; Lucid et al., 2013; Regan, 2012).
While natural rainfall is desirable, data collection can be slow, as precipitation characteristics
such as intensity, spatial and temporal frequency and duration of natural rainfall cannot be
controlled (Humphry et al., 2002). The use of rainfall simulators provide the opportunity for
increased experimental control over the variables that govern natural rainfall (Júnior et al.,
2011). As rainfall simulators provide this control, they allow for quick, specific and
reproducible rainfall events (Iserloh et al., 2012), and therefore dependable data.
As stated in Bowyer-Bower et al. (1989), types and design of rainfall simulators have been
developed since the first attempts by Dudley et al. (1932). Design characteristics must take
into account operation requirements, drop sizes to be replicated, plot size, water usage,
portability, ease of use and cost. However, designs are often centralised around two
established dispersal methods: ‘spray type’ simulators using water sprayed from an irrigation
sprinkle nozzle, or ‘drop forming’ simulators, which drip water from a suitable apparatus
33 (Bowyer-Bower et al., 1989). A more detailed synopses of these rainfall simulators can be
found in Bubenzer et al. (1979), Agassi et al. (1999) and Bowyer-Bower et al. (1989).
Desirable rainfall characteristics should include drop size distribution similar to natural
rainfall, rainfall intensity in the range of the requirement of the research program, uniformity
over the study area, accurate reproduction of rainfall events, fall velocity, kinetic energy
similar to natural rainfall and portability if for use in situ (Tossell et al., 1987; Humphry et al.,
2002; Pall et al., 1983; Bowyer-Bower et al., 1989).
While rainfall simulators are a useful tool, there is no standardisation of rainfall simulator
design, which may impede on drawing comparisons between results (Iserloh et al., 2012). In
addition, their overall performance can be limiting (Humphry et al., 2002). Renard (1985)
listed some of the disadvantages associated with the use of rainfall simulators, including the
fact that areas simulated are typically small, ranging from less than a square metre up to
several hundred square metres, depending on the design used. Most simulators do not
produce drop size distribution similar to natural rainfall. Terminal velocities of natural rainfall
is not produced by some simulators and as a result, the kinetic energy produced may only be
40 – 50% of natural rainfall in some nozzle drop formers or free falling dropper simulators.
Although there are many disadvantages to the use of rainfall simulators, the key factor is
whether the advantages outweigh the disadvantages (Neff, 1979). In many instances,
simulated rainfall is the only effective way to obtain results in reasonable time frame and
under controlled conditions (ASCE, 1996). Furthermore, the acquisition of data provides
fundamental information on the cause/effect relationship of many agricultural research
questions, as well as improving decision making on environmental protection (Iserloh et al.,
2012). In addition, the cost associated with simulated rainfall is relatively inexpensive when
34 compared to long-term hydrologic experiments that rely solely on natural rain events (Foster,
2005).
3.3 Rainfall simulator in the current study
In the current study, an Amsterdam drip-type rainfall simulator, as described by BowyerBower et al. (1989), was used to provide rainfall for the runoff experiment (Chapter 5). This
type of rainfall simulator has been successfully used in micro-plot runoff experiments
(Holden et al., 2002; Kurz et al. 2006; Brennan et al. 2012; Mohr et al. 2013). The simulator
is driven solely by gravity, with raindrops falling from heights of one or two metres, which
makes achievement of terminal velocity difficult (Bowyer-Bower et al., 1989). However,
their accuracy in replicating rainfall between experimental sites is an advantage (BowyerBower et al., 1989). In addition, these simulators are cheap and easily transported, making
them potentially advantageous over their spray-type counterparts, which can be time
consuming to construct and transport (Bowyer-Bower et al., 1989). In addition, these
simulators allow for simple, small-scale side-by-side rainfall simulations to be conducted on
different treatments.
3.4 Rainfall simulator construction
The simulator used in the current study was designed to form droplets of median diameter 2.3
mm, spaced 30 mm apart in a 1000 mm × 500 mm × 8 mm Perspex plate over a 0.5 m2
simulator area. The principal components are shown in Fig. 3.1. Drops are formed by
controlling flow though Tygon tubing of 2.3 mm outside diameter (OD) and 0.7 mm internal
diameter (ID). The ID tubing determines the rate of water drop formation, which is then
further slowed down by lengths of fishing line inserted into each tube. The Perspex plate of
drop formers contained 420 drop formers arranged in a 14 × 30 matrix. The water reservoir
consisted of two 25 L water tanks mounted above the Perspex plate. The pressure head in the
35 two tanks are maintained at a target level of ± 10 mm. An adaptation of the rainfall simulator
as used by Brennan et al. (2012), was the addition of gate flow pressure values, inside of
manometer board, which were used to control flow rate to the Perspex plate, which, in turn,
controls the rainfall intensity.
Figure 3.1. Principal components of the rainfall simulator (top) and of Perspex plate
(bottom) 36 The simulator was supported by a metal frame, which was fitted with adjustable legs so that
the simulators could be levelled. This ensured that water droplets fell from a level surface.
The frames of the simulators were also fitted with plastic sheets so that simulated rainfall was
protected from wind effects (Fig. 3.2). A wire mesh was hung 200 mm below the Perspex
plate so that water droplets could be the intercepted, coagulating them and dispersing others
to create drop sizes, similar to that of natural rainfall. A fall height of 2 m was achieved with
this rainfall simulator. The simulator was calibrated to achieve a target rainfall intensity of 11
mm hr-1, which is not uncommon hourly rate for a short term rainfall event in Ireland (Met
Eireann, 2015). The rainfall simulators can be seen in use in this YouTube video:
https://www.youtube.com/watch?v=JYhsmE8SHvU.
3.5 Areal uniformity and intensity calibration
Uniformity of the areal distribution of rainfall is an important measurement of a rainfall
simulator’s performance, as it reflects the ability of the simulator to evenly distribute rainfall
over a surface area being examined. Rainfall intensity measurement is also important, as
variations in intensity can influence the experimental results. Performance tests for intensity
and uniformity were conducted in accordance with Tossell et al. (1987). The target area for
simulated rainfall was 0.36 m2 (0.9 × 0.4 m). The simulation area was reduced so that the
effect of edge effects could be eliminated. The intensity of simulated rain was determined by
collecting a volume of water during a known period of rainfall. Large trays of known area
were placed underneath the rainfall simulator in the target area to take a representative
sample of simulated rainfall. This enabled the calculation of rainfall intensity:
Volume of water collected (L) x 60 min
Length (m) x width (m) x 60 min
37 [3.1]
Figure 3.2. Amsterdam-styled drip-type rainfall simulators fitted with wind shield in use in
field.
Uniformity was determined by positioning 15 collection containers (68 mm ID and 75mm
deep) under the rainfall simulator (Fig. 3.3) during an experimental run. They were then
weighed. The uniformity of application could then be determined after Christiansen (1942).
The Christiansen uniformity coefficient (UC) is a measure of the spatial distribution of
simulated rain falling over a defined area, and is calculated by:
[3.2]
38 where X is the mean rainfall intensity (mm hr-1), n is the number of observations, and Xi (i =
1, 2, 3, . .,n) are the individual observations. As the number and size of the collection
containers will affect the results of uniformity trails, greater theoretical accuracy may be
achieved by increasing the number of collection containers. However, this can be extremely
time consuming, and the amount of information collected is offset by the time involved
(Tossell et al., 1987). Conversely, few large gauges covering the entire plot can be
misleading; therefore, it is more informative to use small collection containers spaced evenly
over the plot.
Figure 3.3. Calibration area and positions of collection containers
3.6 Summary
This chapter gives a brief explanation of the importance of rainfall simulators as a tool in
arable and grassland agricultural research. The chapter also gives a brief explanation and
guide on how to preform one of the most importance steps in using a rainfall similar i.e.
calibration. The rainfall simulator described in this chapter was a drop-forming rainfall
39 simulator and will be used in the surface runoff experiment in Chapter 5. The simulator
provided everything required for this research in terms of portability, ease of use and cost, but
more importantly, it produced desirable rainfall characteristics.
40 Chapter 4 - METHODOLOGY TO INCORPORATE CALCIUM
OXIDE INTO DEWATERED SLUDGE
4.1. Overview
In this chapter, a bench-scale test was used to incorporate calcium oxide (CaO) into
dewatered sludge under laboratory conditions. This created lime-adjusted biosolids for use in
the micro-plot scale experiment described in Chapter 5.
4.2. Introduction
Lime stabilisation, commonly known as alkaline stabilisation, is an internationally recognised
method used by WWTPs for the treatment of sewage sludge. Alkaline stabilisation of sludge
works by raising the pH level of the sludge, thus making unfavourable conditions for the
growth of organisms. The process of alkaline stabilisation is increasingly used in countries,
as it is a cost-effective way of stabilisation sewage sludge (Krach et al., 2008). Materials that
may be used for alkaline stabilization include hydrated lime, CaO, fly ash, lime and cement
kiln dust, and carbide lime (USEPA, 2000). However, CaO is commonly used because it has
a high heat of hydrolysis, which can significantly enhance pathogen destruction (USEPA,
2000), creating a better stabilised sludge product.
In accordance with Irish regulation set out under the “Code of Good Practice for the Use of
Biosolids in Agriculture”, the quantity of lime added must increase the pH of the lime-sludge
mix to ≥12 and the temperature to 70˚C for 30 minutes, or to increase the pH above 12 for 72
hr and maintain a temperature of ≥ 52˚C for 12 hr, or greater (Fehily, Timoney and Company,
1999). The high temperature and pH inhibits biological action, therefore inactivating
pathogens in the treated biosolids product (Joyce et al., 2014). The rate at which lime is
41 added to achieve these regulations is dependent on the DS content of the sludge
(Andreadakis, 2000). In addition, the extent of heat generated is also dependent on the lime
dose (Smith et al., 1998). The exothermic reaction is shown in the following hydration
reaction:
CaO (quicklime) + H2O (water) = Ca(OH)2 hydrated lime + Heat [4.1]
The effectiveness of the lime stabilisation is dependent on the achievement and maintenance
of pH ≥12, which is dependent on lime addition and significant lime incorporation (Burns et
al., 2007). Uniform lime incorporation is critical to the lime stabilisation process, as poor
lime incorporation will result in inadequately stabilised regions, leading to microbial
regrowth, driving further pH reduction and causing increased odour (Burns et al., 2007).
Therefore, the objectives of the bench-scale test was to created lime-adjusted biosolids for
use in the micro-plot scale experiment described in Chapter 5, while following the protocols
for pathogen kill and heat requirement currently in place in Ireland.
4.3. Materials and Methods
4.3.1. Sample collection and analysis
Dewatered sludge cake was collected in sealed 50 L-capacity plastic storage boxes from a
WWTP in Ireland and transported to Teagasc, Environment Research Centre, Johnstown
Castle, Co Wexford, where it was labelled and stored at 4oC until lime was added. To
determine the amount of CaO that needed to be added to the mixture, the dry solid content
content of the dewatered sludge cake was determined by drying eight representative 50 g
samples at 105oC for 24 hr. The dry solid content content of the sludge cake was determined
to be 19±0.64%. The CaO was obtained from Clogrennane Lime, Co. Carlow, Ireland - a
major provider of CaO to WWTP facilities in Ireland. In addition, an in-house spread sheet,
42 provided by Clogrennane Lime, was used to calculate the amount of lime to add to this dry
solid content to comply with the current regulations (Fig. 4.1).
Figure 4.1. The spreadsheet provided by Clogrennane Lime, which shows a 19% dry solid
content with the amount of CaO required, highlighted, to get the required heat.
4.3.2. Monitoring of pH and temperature and microbes
To determine the pH of the sludge-lime mixture (Section 4.3.3 and 4.3.4), 10 g of sludge-lime
mixed was added to 20 mL of deionized water (1:2 ratio sludge-lime mixture:water). The mix
was then shaken for 5 min using an adapted New Brunswick Scientific Gyrotory Shaker,
before allowing to stand for 5 min. The pH was then measured using a Jenway 3510 pH
meter, and temperature was measured using a Testo 925 Thermometer probe and a
temperature probe attached to the Jenway 3510.
43 4.3.3. Test 1 (preliminary test)
First, a single replication of 100 g of dewatered sludge cake was mixed with CaO at 12%,
13% and 16 %, based on the wet weight of the sludge. This was equivalent to 12 g, 13 g and
16 g of CaO, respectively. As dewatered sludge cake had been stored in the cold room at 4oC
and only removed earlier that day, samples were too cold to generate the heat required for
stabilisation (≥52oC). A larger volume of sludge and lime addition, coupled with a warmer
room temperature equivalent, was needed. Therefore, a single replication of 200 g dewatered
sludge cake (which was allowed to stabilise to room temperature) was mixed with CaO at
17%, 20% and 25% based on the wet weight of the sludge (Fig. 4.2). This was equivalent to
34 g, 40 g and 50 g of CaO, respectively.
Figure 4.2. The experimental setup for the preliminary test. A) – temperature monitoring of 2
kg sludge cake and B) – a temperature probe close up.
Another test was conducted to test the theory that a greater quantity of dewatered sludge cake
would be a more crucial factor in increasing and maintaining the sludge-lime mix at the
recommend temperature. This test mixed 2 kg of dewatered sludge cake with 20% or 400g of
CaO. Sludge and lime were hand mixed for 5 min until the lime was sufficiently incorporated
into the sludge.
44 4.3.4. Test 2 (Full-scale bench test)
Results from the preliminary tests allowed the following setup to be justified. A 16% limesludge mix was used in this test. 15 kg of dewatered cake was mixed with 2.4 kg of CaO (Fig.
4.2). Sludge and lime were hand mixed together until lime was sufficiently incorporated in
the plastic container that had been used for collection and storage of sludge. Similar to the
preliminary tests (Section 4.3.3), the mixing time was 5 min. To ensure proper lime
incorporation to the sludge, CaO was added in stages and not at once. After mixing, two
temperature probes were inserted into the sludge-lime mixture and the box lid was closed.
This provided better insulation to the mixture and helped maintain temperature (Fig. 4.3).
Figure 4.3. The measurement of lime and sludge, and sealed container mixture with
temperature probes inserted.
Temperature was measured with two temperature probes every 10 min after the mixing time
had stopped for the first 3 hr and then every hour after that for 12 hr. Four pH measurements
were taken daily for 72 hr, three representative samples of 10 g each, with the fourth a
composite samples of five 2 g samples pooled together. While the lime–sludge mixture was
being tested daily for pH, it was stored outdoors for 48 hr, stirring once a day with a spade to
allow for the further reduction of water content by air drying (Fig. 4.4). The final limesludge is shown in Fig. 4.4.
45 Figure 4.4. Shows final lime-sludge mixture and storage outside for 48 hours
4.4. Results
4.4.1. Test 1 (preliminary test)
This first test using 100 g of dewatered sludge cake mixed together with CaO at 12%, 13%
and 16% recorded peak temperatures, after 10 min, of 23oC, 26oC and 29.1oC, respectively.
The sludge was at pH 5.88 before any addition of lime, and increased over the recommend
pH of 12 for all three lime mixes, and had pH readings ranging from 12.4 - 12.6 (Table 4.1).
For the second test (200 g), the subsample removed from the cold room had an initial
temperature of between 12.9oC – 13.5oC. After mixing, the temperature was 34oC, 41.2oC and
44oC, respectively, for the 17%, 20% and 25% CaO mixes. Temperature decreased to 29.3oC,
39.1oC and 41oC, respectively, after 30 min. Temperature of the 25% reduced to 22.4oC after
90 min. A pH test for the 25% mixture was 12.4 (Table 4.1).
For the third test (2000 g), temperature ranged from 15.2oC – 15.6oC before the addition of
lime to the sludge. The recommended ≥52oC was exceeded; temperatures of 57.7oC and
56.5oC were reached after half hour (Table 4.1). However, these temperatures fell below 52oC
after 30 min to an average temperature of 41oC.
46 Table 4.1. Results for 100 g, 200 g and 2000 g of dewatered sludge mixed with varying
percentages of quicklime (CaO).
Weight of sludge
w/w
Weight of Mix used
d/w
Percentage
Mix
Temperature (◦C)
pH
g
g
%
After
mix
½ hr
after
After
mix
24
hrs
100
12
12
23
-
12.6
-
100
13
13
26.1
-
12.6
-
100
16
16
29.1
-
12.4
12.4
200
34
17
34
29.3
-
-
200
40
20
41.2
39.1
-
-
200
50
25
44
41
12.4
-
2000
400
20
≥52
41
-
-
4.4.2. Test 2 (Full–scale Bench test)
When 16% CaO was added to the dewatered sludge cake, the recommended ≥52oC was
observed in temperature gauge B after 50 min and remained above ≥52oC for 90 min. The
peak temperature observed in gauge B was 53.6oC. For gauge A, the peak temperature
observed was 51.4oC after 60 min before declining exponentially. The average temperature
for both gauges showed that temperature reached ≥52oC after 50 min, but fell below after 90
min. Fig. 4.5 shows a graph of both temperature gauges, with the average temperature of both
A and B gauges over the 12-hour observation period. The pH was measured in the sample
over a 72-hr period, and showed that pH remained above the recommend value of 12 as
recommend in the legislation (Table 4.2). In addition, the average TC and FC (±std. dev.)
biosolids also proved to be a Class A standard (Table 5.4)
Table 4.2 Sample pH of lime - sludge mix at 24, 48 and 72 hr periods.
Sample
Day 1 (24 hours)
Day 2 (48 hours)
Day 3 (72 hours)
pH
1
12.73
12.66
12.70
2
12.72
12.70
12.62
47 3
12.74
12.71
12.59
4*
12.74
12.66
12.58
*Composite sample
Figure 4.5. Temperature vs. time over 12 hr. Horizontal bar indicates 52○C, which is the
temperature guideline (Fehily, Timoney and Company, 1999) 4.5 Discussion
4.5.1. Preliminary test
Obtaining the guideline temperature for the required time period, for achievement of a lime
adjusted sludge treatment sample proved difficult. No sample during the 100 g or 200 g tests
reached the recommended guideline temperature; even with the increase in lime to 25% wet
weight. This was also the case for the greater quantity of dewatered sludge cake used in the
third preliminary test. Although the temperature target of ≥52oC was obtained using a 20%
lime mix in the 2 kg test, preliminary test results suggested that obtaining and maintaining the
required temperature guideline was quantity dependent (i.e. the amount of sludge
48 incorporated into the mix) rather than an excessive lime dose. Dewatered sludge, when
mixed on a bigger scale such as at a WWTP, will have increased insulation in storage
mounds. Fig. 4.6 shows a typically lime biosolid processing at a WWTP, which combines all
processed sludge together on a truck trailer before removal to a bigger storage mound before
application. The mixing process is better illustrated in Fig. 4.7
Figure 4.6. A) Standard lime-sludge mixing apparatus at a WWTP, B) Pugmill Augers, C)
completion of sludge and lime mixture on transfer belt, D) truck collection.
49 Figure 4.7. Illustration of a standard mixing apparatus at a WWTP
As a result, quantity dependence proved to be the case when comparing the 20% lime mix at
200 g with 2000 g in the mini-scale test. It was concluded from the mini-scale test that a 20%
amount, although reaching the target, would not be a representative liming amount used by
the wastewater treatment industry to stabilise sludge. It was felt that for economic reasons, a
20% liming amount to sludge would not be cost-effective, but as treatment plants deal with
higher volumes of sludge, the amount required would not have to be the same to reach the
recommended heating requirement. It was concluded that with a larger amount of sludge,
such as the amount which was used in the full-scale test, the lime dosage could be smaller
due to greater heating capacity and insulation of heat in a mound. It was for this reason and
with consultation of the spread sheet provided by Clogrennane lime, a 16% liming
requirement based on wet weight was used in the full-scale test. Although slightly higher than
that recommended by Clogrennane Lime, whose recommendation is 14%, it was felt that the
increase in lime would ensure that temperature was reached, while at the same time not
overdosing the dewatered sludge on the smaller laboratory scale study. A 16% liming
requirement is also in line with recommendation used by the European Lime Association,
50 whose recommendations for typical CaO addition for advanced treatment of dewatered
sludge is 50-90% CaO per unit DS (European Lime Association, 2014). A 16% liming based
on dry weight, used in this study, would give an 84% CaO per unit DS.
4.5.2. Full–scale Bench test
For the full-scale test, the temperature reached the recommended temperature for gauge B,
but not for gauge A. However, gauge B did not stay above the recommended ≥ 52 °C for the
12-hr period. However, as biosolids are stored in mounds in WWTPs, the area of the heap
exposed to the elements will cool quickly and may not maintain the ≥ 52 °C for a 12-hr
period. Further study is required to ensure that WWTPs are complying with these
recommendations. The temperature results in this test are similar to a study undertaken by
Smith et al. (1998), who reported maximum temperature reached within 1 hr before declining
exponentially when mixing 100g (DW) dewatered biosolids (15% dry solids content) mixed
with lime at different rates of 5, 15, 20, 25, 30, 40, 50% by weight based on wet weight. Although the heating requirement was not maintained for the required 12 hr as per code of
good practice, the average total and faecal coliforms were of Class A standard. This result is
similar to the experiences of lime stabilization of sludge conducted by Araque (2006) and
Torres et al. (2009), and proves that the code of good practice concerning the heating
requirement may need updating and if it commonly being obtained or followed at WWTP.
4.5.3. Importance of uniform lime incorporation and potential problems
Uniform lime incorporation is critical to the lime stabilisation process as it is important for
the elimination of regions with low pH within the lime-sludge mix. Poor lime incorporation
will result in inadequately stabilised regions, leading to microbial regrowth, driving further
pH reduction and causing increased odour (Burns et al., 2007). A study by Krach et al. (2008)
showed that longer mixing times and proper lime dosage could efficiently reduce odour
51 offensiveness and that lime biosolids with a better mixing time has a much slower pH
decrease than biosolids with poor mixing. It has also been noted that a drop in pH levels
creates a favourable environment for the reactivation of regrowth of pathogens (Wong at al.,
2000). North et al. (2008) found that faecal coliform levels were reduced by longer mixing
times as a result of a more uniform distribution of lime into the mixture.
The slurry pH method used to test lime biosolids pH can be prone to error (Burns et al.,
2007). The disadvantage of using this method is that when biosolids are made into a slurry,
the lime and biosolids are homogenized together, making all the lime reactive, thus masking
regions with poor lime incorporation. In addition to this, the heating pasteurisation
requirement stated in Irish good practices, especially the monitoring temperature for an
extended period (i.e. >52◦C for 12 hr), has also failed to be replicated in studies by Lozada et
al. (2009) and Smith et al. (1998). However, the experiences of lime stabilization of Araque
(2006) and Torres et al. (2009) showed that the biosolids derived from WWTPs that do not
fulfil this requirement may also achieve Class A biosolid status in terms of microbial kill. In
addition, the overdosing of lime to obtain the heating requirement may result in higher than
normal operation cost.
Other problems with the heating requirement is the overall monitoring as the way that lime
biosolids are produced in Ireland means this measurement is not that feasible. In addition,
under Section 51 of Waste Management Act, lime stabilisation plants in Ireland are exempt
from a waste permit/licence if sludge goes onto agriculture land, resulting in no processing
standard monitoring e.g. temperature and no testing for pathogens before release of material
(Cré, 2013). As there is currently a knowledge gap surrounding the heating requirement, the
effectiveness of lime stabilisation in Ireland and pH maintenance and pathogen survival in
storage, there is a need for research into lime stabilising process and its effectiveness to
52 minimise food safety concerns. This study also hypothesised that a slower rotor or longer
rotor mixing area before the conveyor belt will allow better incorporation of lime and
therefore a better chance at fulfilling the regulations.
4.5. Conclusion
The objective of the study was to produce a lime stabilised biosolids under laboratory
conditions following as closely as possible the guidelines set down in code of good practice.
Maintaining temperatures above ≥52°C for 12 hr, as stated in the code of good practice, does
not seem to be practical at small scale, but may be possible at full scale, provided a sufficient
amount of lime is incorporated into large volumes of sludge. A decrease in temperature was
measured within 12 hr in all tests. However, the recommended pH was achieved and
maintained for the 72-hr period. The heating requirement and uniformity of lime
incorporation requires further study to ensure that WWTPs are complying with temperature
regulations. 53 Chapter 5 - PLOT-SCALE RAINFALL SIMULATOR STUDY
5.1. Overview
This plot scale experiment was designed and developed to understand the potential
environmental impact of surface runoff resulting from the land spreading of three types of
biosolids on agricultural land. Biosolids were surface applied to grassland with no
incorporation into the soil, and simulated rainfall was used to produce surface runoff. For
comparison to a commonly spread organic fertiliser in Ireland, DCS was also applied to plots.
Surface runoff was collected and tested for nutrients, metals, and microbes.
5.2. Introduction
Incidental losses of nutrient, metal and microbes as a result of an episodic rainfall event soon
after land application of biosolids are of particular concern, as they have the potential to
cause eutrophication and pollution to water bodies. As land application is currently promoted
through legislation in the European Union, any potential benefits arising from the reuse of
biosolids must be considered against possible adverse impacts associated with their use. The
objectives of this study was to simultaneously assess, surface runoff of nutrients (P and N),
metals (Cd, Cr Cu, Pb, Ni, and Zn) and microbes (FC and TC), under controlled conditions
in field conditions during and after rainfall simulation events, using three types of treated
biosolids. For comparison, a commonly spread organic fertiliser in Ireland, DCS, was also
applied to plots, and surface runoff was tested for the same parameters as the biosolids.
54 5.3 Materials and Methods
5.3.1. Field Site characterisation
The study site was a 0.6-ha plot located at Teagasc, Johnstown Castle Environment Research
Centre, Co. Wexford, Ireland (latitude 52.293415, longitude -6.518497) in the southeast of
Ireland. The area has a cool maritime climate, with an average temperature of 10oC and mean
annual precipitation of 1002 mm. The site has been used as a grassland sward for over twenty
years with nutrient inputs (organic and inorganic) applied based on routine soil testing. The
site has undulating topography with average slopes of 6.7% along the length of the site and
3.6% across the width. Overall, the site is moderately drained with a soil texture gradient of
clay loam to sand silt loam, as classified by Brennan et al. (2012). Soil nutrient analysis for
the field site was characterised by dividing the site into an upper, middle and lower section,
and by taking three bulked soil samples (n=20) before characterising each section separately
(Fig. 5.1). The soil nutrient status at these locations (Morgan’s P (Pm), K, and magnesium
(Mg)) was determined using Morgan’s extractant (Morgan, 1941), and are presented in Table
5.1. Mehlich-3 P extractant was also used to determine P levels (Mehlich, 1984). Soil pH
(n=3) was determined using a pH probe (Mettler-Toledo Inlab Routine) and a 2:1 ratio of
deionised water to soil. The optimal location for the 25 individual micro-plots in the field site
was then determined by topography and slope, but most significantly, the area chosen had the
soil nutrient analysis, pH levels and soil texture, which permitted biosolids application.
55 Figure 5.1. The “W” soil sample procedure outlined in the S.I. No 610 2010. This soil
sample procedure was carried out for the Upper, Middle and Lower sections of the field
Table 5.1. Soil characteristics from the upper, middle and lower section of the 0.6 ha field
site.
Position
pH
Morgan
P
Mehlich
3-P
WEP
mg L-1
mg L-1
mg kg-
P
index
1
a
a
a
b
b
LR
Sand
mg L-1
t/ha
%
%
%
K
Mg
mg L-1
Silt
Clay
b
TexturalcClass
Upper
5.6
2.3
36.1
6.8
1.0
128.9
133.0
4.0
44%
36%
21%
Clay Loam
Middle
5.4
2.3
35.3
5.6
1.0
70.5
108.8
5.5
47%
36%
18%
Sandy Silt
Loam
Lower
5.5
2.6
25.9
9.0
1.0
121.6
137.0
5.0
52%
30%
18%
Sandy Loam
Average
5.5
2.4
32.6
7.1
1.0
107.0
126.3
4.8
47.7
34
19
Std. dev
0.1
0.2
4.6
1.4
0.0
26.0
12.5
0.6
4
3.5
1.7
a
Morgan’s extractable potassium (K) and magnesium (Mg), lime requirement (LR)
Brennan et al. (2012) cUSDA classification system
b
56 5.3.2. Micro-plot installation and characterisation
Thirty grassland micro-plots, each 0.9 m in length and 0.4 m in width (0.36 m2), were
isolated using continuous 2.2 m-long, 100 mm-wide rigid polythene plastic strips, which
were pushed to a depth of 50 mm into the soil to isolate three sides of the plot. A 0.6-m
polypropylene plastic runoff collection channel was fitted at the end of each plot (Fig. 5.2).
Micro-plots were orientated with the longest dimension in the direction of the slope. Once
installed, plots were left uncovered to allow natural rainfall to wash away any soil that had
been disturbed during their construction (Fig. 5.2).
Figure 5.2. Picture of micro-plot fitted with runoff off collection channel and micro-plot set
up.
57 For textural analysis, each micro-plot was tested at before start of experiment (t0) for particle
size distribution (% sand/silt/clay) using the hydrometer method (ASTM D422, 2002).
Results of analyses are presented in Table 5.2. Soil nutrient status of each micro-plot was
taken at t0 and analysed for soil pH, Mehlich 3-P, Pm, K, Mg, water extractable P (WEP),
organic matter (OM) and lime requirement (LR) (Table 5.2). In addition, composited soil
samples were oven dried and grinded to 2 mm before being sent to ALS Environmental
Global, Co. Dublin, Ireland at t0 for metal content (Cu, Ni, Pb, Zn, Cd, Cr) by Inductively
Couples Plasma Optical Emission Spectrometry (ICP-OES) (MEWAM, 1992), following
aqua-regia digestion (MEWAM, 1986) (Tables 5.3). Soil nutrient and metal status analysis
was also repeated immediately at the end of the experiment (t360) (Tables 5.2 and 5.3).
Background checks were performed on the soil microbial status (TC and FC) (Table 5.4) at t0
and t360 by taking composite soil samples from the four corners outside the micro-plots (top
left, top right, bottom left, bottom right). Total coliforms were tested in accordance with ISO
4832 (ISO, 2006) at both t0 and FC were tested in accordance with ISO 16649-2 (ISO, 2001)
at t0 and ISO 4831 (ISO, 2006) at t360.
58 Table 5.2.Average topographical and soil characteristics for the 30 individual micro-plots pooled together as per treatment applied, on the day
before experiment (t0) and immediately after the experiment ended (t360)
Treatment
Slope
pH0/pH360
WEP0/WEP360
Morgans
P0/P360
Mehlich
3P0/P360
K0/K360a
Mg0/Mg360a
LR0/LR360a
Sandb
Siltb
Clayb
ADUK
%
2.89
5.94/5.90
mg kg-1
7.10/5.9
mg L-1
3.60/5.57
mg L-1
38.0/37.1
mg L-1
94.94/60.78
mg L-1
147.13/147.80
t/ha
2.70/3.00
%
45.70
%
39.49
%
14.82
Loam
g/cm3
1.3
TD
3.69
5.90/5.90
9.25/7.5
4.80/6.79
47.4/41.9
66.08/55.66
156.75/164.00
2.30/2.70
47.41
37.63
14.97
Loam
1.3
LS
2.84
5.90/6.25
6.60/5.4
3.82/6.24
38.3/32.7
58.20/52.12
136.47/146.40
2.60/1.00
48.74
36.58
14.69
Loam
1.3
ADIRE
2.87
5.96/5.93
7.7/6.1
4.32/6.11
41.4/35.7
78.39/55.74
152.68/147.40
2.40/2.70
48.17
36.55
15.28
Loam
1.4
SOIL
3.53
5.99/5.96
8.6/6.9
4.71/5.59
46.8/39.2
65.95/54.30
149.49/149.60
2.80/2.90
45.52
39.43
15.05
Loam
1.4
DCS
2.73
5.81/6.10
2.86/1.63
5.00/9.13
31.93/-
62.40/208.42
84.20/167.17
3.30/1.60
50.00
29.20
20.80
Loam
1.4
a
b
Morgan’s extractable potassium (K) and magnesium (Mg), lime requirement (LR) and Organic Matter (OM)
ASTM D422. (2002).
c
USDA classification system
59 Textural
classC
BD
Table 5.3. Average soil metals concentration of copper (Cu), nickel (Ni), lead (Pb), zinc (Zn),
cadmium (Cd), chromium (Cr) before start of experiment (t0) and after the experiment (t360)
Treatment
Cd0/Cd360
Cr0/Cr360
Cu0/Cu360
Pb0/Pb360
Ni0/360
Zn0/Zn360
--------------------------------------------------------------mg kg – 1-------------------------------------------------------------
ADUK
<0.20/0.54
11.8/13.8
8.12/6.74
15.5/27.2
7.14/9
35.2/29.8
TD
<0.2/0.56
11.5/14.4
9.54/7.8
16.12/25
6.86/9.42
33.2/31.2
LS
<0.2/0.54
11.6/13.8
7.8/7.4
15/22
7.2/8.96
34.6/27.6
ADIRE
<0.2/0.54
12/14.4
8.42/7.34
16/21.8
7.66/9.4
36/30
SOIL
<0.2/0.56
11.8/14.4
8.62/7.16
17.22/24.4
7.28/9.34
35.2/31.2
5.3.3. Biosolids characterisation
Three types of biosolids were examined in this study: two types of AD sludge, one sourced
from a WWTP in Ireland (ADIRE) and another used in an EU-funded FP7 project (END-OSLUDG, 2014) (ADUK); TD and LS biosolids (Fig. 2.2, 2.3, 2.4). With the exception of
ADUK (Fig. 5.3), all biosolids were sourced from the same WWTP in Ireland. As the Irish
WWTP only employed two methods to treat sludge (anaerobic digestion and thermal drying),
an untreated, dewatered sewage sludge cake was also collected from the same WWTP, so that
it could be manually lime treated as described in Chapter 4. The treated sludge and the
dewatered sludge cake were collected in sealed, 50 L-capacity plastic storage boxes and
transported to Teagasc, Environment Research Centre, Johnstown Castle, Co Wexford, South
East Ireland, where they were labelled and stored at 4oC. The treated sludge samples (each at
n=3) were tested for (Brookside Laboratories Inc, Ohio, USA): DM, total Kjeldahl nitrogen
(TKN), nitrite (NO2-N), NH4-N, organic-N, total P (TP), P as phosphorus pentoxide (P2O5),
K, K as potassium oxide (K2O), pH, and metal content (Cu, Ni, Pb, Zn, Cd, Cr, Hg) (Table
5.5). Water extractable P was also tested after Kleinman et al. (2007) (Table 5.5). In addition,
the biosolid samples (each at n=3) were also tested for TC and FC using the same methods as
for soil (Table 5.4).
60 Table 5.4. The average total and faecal coliforms (±std. dev.) for soil, biosolids and DCS on the day before experiment (t0) and after the
experiment (t360). Standard deviation in brackets.
Microbe
SLURRY
Soil
<1.0 x 107
5.43 x 104
(6.34 x 103)
<1.0 x 107
<1.0 x 102
<1.0 x 102
1.10 x 103
<1.0 x 102
1.3 x 101 (4.7 x
100)
5.0 x 101 (5.0 x
100)
-
<3.0 x 10-1 (0)
2.3 x 100 (0)
1.3 x 103
(6.9 x 102)
7.7 x 100
(4.9 x 100)
ADUK
TD
LS
Presumptive Coliforms
(cfu g-1) (t0)
<1.0 x 107
<1.0 x 107
<1.0 x 107
ß-Glucuronidase + E. coli
(cfu g-1) <100 (t0)
6.5 x 103
(3.6 x 103)
<1.0 x 102
7.4 x 102 (4.5 x
102)
1.7 x 101 (2.1 x
101)
6.3 x 101 (4.5 x
101)
1.9 x 100 ( 1.7 x
100)
Total coliform
(Product) (t360)
Faecal Coliforms
(MPN) (t360)
(t0) - Test performed by Tellab, Co. Carlow, before experiment
(t360) - Test performed CLS Labs, Co. Galway, end of experiment
61 ADIRE
-
Figure 5.3. Anaerobically digested biosolid source from END-O-SLUDGE, 2014 (ADUK)
5.3.4. Slurry Characterisation
Dairy cattle slurry was collected from the dairy farm unit at the Teagasc, Environmental
Research Centre, Johnstown Castle. The storage tanks were agitated and slurry samples were
transported to the laboratory in 25 L drums. Slurry samples were stored at 4°C prior to land
application. Slurry pH was determined using a pH probe and a 2:1 ratio of deionised water to
soil (Table 5.5). The DCS (each at n=3) were tested for (Southern Scientific Ireland, Co.
Kerry, Ireland): DM, N (Kjeldahl, 1883), P and K and metal content (Cu, Ni, Pb, Zn, Cd and
Cr) (Table 5.5). In addition, the DCS samples (each at n=3) were also tested for TC and FC
immediately after collection using the same methods as for soil (Table 5.4).
62 Table 5.5. Nutrient and metal characteristics of the biosolids and slurry
Treatment
DM
%
Total N
Total P
Total K
pH
--------------------mg kg – 1--------------------
WEP
(dry)
OM
g kg-1
%
Cu
Ni
Pb
Cd
Cr
Hg
NO3-N
NH4-N
Organic N
a
P2O5
b
K2O
---------------------------------------------------------------------------------mg kg – 1---------------------------------------------------------------------------------
25.1
43216.3
23512.1
2145.8
7.8
15.5
-
287.0
140.2
115.3
682.8
1.84
31.46
0.0
3979.4
3846.6
39369.7
53875.6
2584.9
(0.1)
(1670.8)
(273.9)
(39.8)
(0.0)
(7.6)
-
(4.0)
(1.5)
(0.8)
(3.0)
(0.0)
(0.5)
(0.0)
(14.0)
(293.7)
(1961.8)
(627.5)
(47.9)
34.2
17620.5
3938.7
2229.5
12.6
8.9
28.4
111.7
12.2
10.7
218.5
0.4
8.1
0.0
2922.3
449.2
17171.3
9137.5
2686.0
(0.2)
(395.5)
(396.1)
(43.8)
(0.0)
(0.3)
(0.5)
(11.4)
(0.3)
(1.0)
(20.1)
(0.0)
(0.3)
(0.0)
(13.1)
(28.6)
(395.1)
(790.2)
(52.3)
87.10
51446.0
17114.4
2055.1
6.9
492.7
79.5
504.8
19.6
62.2
876.9
1.0
22.1
0.4
1148.2
573.3
50872.7
39215.9
2475.6
(0.07)
(2897.3)
(186.9)
(50.7)
(0.0)
(25.6)
(2.0)
(18.8)
(2.0)
(0.6)
(5.5)
(0.0)
(0.06)
(0.5)
(1.0)
(32.1)
(2875.8)
(428.3)
(61.2)
23.6
54577.8
25185.7
2198.7
8.1
302.2
72
756.4
26.3
91.6
1109.6
1.5
31.7
0
4234.6
3428
51149.8
57710.5
2648.6
(0.2)
(1530.3)
(609.0)
(78.4)
(0.0)
(1.0)
(1.0)
(20.7)
(1.3)
(3.1)
(21.6)
0.0
(1.9)
0.0
(38.1)
(239.7)
(1775.5)
(1395.4)
(94.5)
8.35
2.2
0.5
4.38
8.2
93.3
-
3.9
0.44
<0.25
14.3
<0.25
0.71
-
-
-
-
-
-
(0.2)
(0.2)
(0)
(0.4)
(0)
(3.34)
-
0
(0.3)
0
(0.2)
0
(0.62)
-
-
-
-
-
-
ADUK
LS
TD
ADIRE
DCS
a
P2O5 - Phosphorus pentoxide
b
K2O - Potassium oxide
(Standard deviation in brackets)
63 Zn
5.3.5. Rainfall event simulation and application
One Amsterdam drip-type rainfall simulator, as described in Chapter 3, was used to provide
rainfall in this study (Fig. 3.2). The simulator was calibrated to deliver a rainfall intensity of
11 mm hr-1. Water samples, used in the rainfall simulations, were collected over the duration
of the three rainfall events, and had average concentrations of: 0.07±0.0 mg NH4-N L−1, 3.81 ±0.02 mg NO3-N L−1, 3.80±0.02 mg total oxidised nitrogen (TON) L-1, 0.01±0.00 mg
dissolved reactive phosphorus (DRP) L−1, 0.02±0.0 mg TP L−1, 0.30±0.09 µg Cd L−1,
0.38±0.07 µg Cr L−1, 10.10±0.75 µg Cu L−1, 0.65±0.46 µg Ni L−1, 0.93±1.25 µg Pb L−1,
78.91±6.67 µg Zn L−1, 11.04±1.05 µg aluminium (Al) L−1, 0.00±0.00 µg iron (Fe) L−1and
9.95±0.05 µg manganese (Mn) L−1.
The six treatments (four biosolids, DCS and one soil-only study control) used in this study
were assigned to 30 micro-plots by dividing the plots in five blocks (five ‘blocks’ each
containing six micro-plots). As metal content was not limiting in soil, DCS or biosolids
application to the micro-plots was governed by the P content of the biosolids, and DCS and
the P index of the soil. For comparable results, all micro-plots were classified into Index 2 P
soil, which meant that all biosolids and DCS treatments were applied to all plots at a rate of
40 kg P ha-1 (Coulter et al., 2008). As a result of the P content and the DM of each individual
biosolid, application rates per individual plot was of 96.6 g of TD, 242.2 g of ADIRE, 1063.3
g of LS, 243.9 g of ADUK biosolids were applied to each designated plot. The DCS was
spread at 2880 g per individual plot.
Prior to application, grass on all plots was cut to 50 mm, 48 hr before the first rainfall
simulation (RS1). For better control of rainfall simulations and to prevent runoff losses
caused by natural rainfall events, individual micro-plots were covered from the time of grass
64 cutting to the end of the last rainfall event by ‘rainout’ shelters (Fig. 5.4D) (Hoekstra et al.,
2014). Biosolids were hand surface applied to each micro-plot. To ensure even distribution,
each micro-plot was divided into four quadrants (each 0.09 m2 in area) and a proportionate
amount of biosolids was applied in each quadrant (Fig. 5.4C). The DCS was applied in rows
using a watering can to replicate normal trailing shoe application. The biosolids and DCS
were then left 24 hr with the soil before RS1. The RS1 event occurred 24 hr after biosolids
and DCS application, so as to demonstrate losses representative of a worst-case scenario. The
second rainfall event (RS2) was two days (48 hr) after initial biosolids/DCS application,
which was representative of current legislation, and the third (RS3) 15 days (360 hr) after
initial application.
Volumetric water content of the soil in each plot (n=3) was measured immediately prior to
each rainfall event using a time domain reflectometry
device (Delta-T Devices Ltd.,
Cambridge, UK), which was calibrated to measure resistivity in the upper 50 mm of the soil
in each plot. Prior to each rainfall event, collection channels from the micro-plots were also
rinsed with boiling hot water to sterilise them.
65 Figure 5.4. A) and B) show site set up, C) Quadrant used to apply biosolids evenly, D)
Rainout shelters to excluded natural rainfall
5.3.6. Runoff sample collection
Surface runoff was judged to occur once 50 mL of water was collected from the runoff
collection channel from the start of simulated rainfall to runoff. The collection of the first 50
mL (t=0) was used to indicate time to runoff (TR), and was used for part of the microbial
analysis. Samples for nutrient and metal analysis were collected every 10 min (t=10, T=20,
T=30) from TR to allow for the flow weighted mean concentration (FWMC) to be calculated
(Brennan et al., 2012). After this time, another 50 ml of surface runoff water was collected for
microbial analysis, so that it could be bulked with the first 50 ml of runoff to create a 100 ml
66 sample for microbial analysis. The rainfall simulator was then switched off and a final sample
(T=F) was collected to determine the final runoff ratio. This sample was also analysed for
nutrient and metal content. Immediately after collection, all samples were stored in cool
boxes with ice until they were returned to the laboratory for analysis. Fig. 5.5 shows the
collection of water samples for microbes, nutrients and metal.
Figure 5.5. A) Sterile collection cups for Microbes, B) Collection cups for nutrients and
metals
5.3.7. Nutrient and metal runoff analysis
Runoff water samples were filtered through 0.45 μm filters (Sarstedt - Filtropur S 0.45) and a
sub-sample was analysed calorimetrically for DRP, NO3-N, NO2-N and NH4-N using a
nutrient analyser (Aquachem Labmedics Analytics, Thermo Clinical Labsystems, Finland). A
second filtered sub-sample was analysed for total dissolved phosphorus (TDP) using acid
persulphate. Unfiltered runoff water samples were analysed for TP with an acid persulphate
digestion and total reactive phosphorus (TRP) using the Aquachem Analyser. Metal analysis
67 was tested on the filtered samples using inductively coupled plasma optical emission
spectroscopy (ICP-OES). Particulate phosphorus was calculated by subtracting TDP from TP.
The DRP was subtracted from the TDP to give the dissolved un-reactive phosphorus (DUP).
All samples were tested in accordance with the Standard Methods (APHA, 2005).
5.3.8. Total and faecal coliform analysis
The two 50 ml runoff water samples from the start of rainfall simulation experiment and near
the end were bulked together in one sterile collection pot in the laboratory. The water volume
in the collection pot was then prepared by serial dilution using sterile water form a Millipore
automatic sanitization module. For detection and enumeration of total and faecal coliforms,
IDEXX Coilisure Quanti Tray/2000 method (IDEXX Laboratories, Westbrook, ME) was
used to determine the most probable number (MPN) in each sample. Samples were incubated
at 37±0.5°C degrees for 24 hr. All analyses were carried out in accordance with the standard
methods (APHA, 2005). 5.3.9
Data analysis
The structure of the data set was a blocked one-way classification (treatments) with repeated
measures over time (rainfall events (RS1– RS3)). The analysis was conducted using Proc
Mixed in SAS software (SAS, 2013) with the inclusion of a covariance model to estimate the
correlation between rainfall events. A large number of covariates were recorded, including
measurements on the simulators and for each analysis; this set of covariates was screened for
any effects that should be included in an analysis of covariance. The interpretation was
conducted as a treatment by time factorial. Comparisons between means were made with
compensation for multiple testing effects using the Tukey adjustment to p-values. Significant
interactions were interpreted using simple effects before making mean comparisons. For
68 comparison of soil characteristics before and after the experiment, the relationship between
the paired measurements, adjusted for treatment, was tested and, given a significant
relationship, the difference between each pair of results was analysed by treatment. In some
cases an intercept only model was fitted to determine if there had been an overall change
across all treatments. Residual checks were made in all cases to ensure that the assumptions
of the analyses were met.
5.4. Results
5.4.1. Nutrient losses in runoff
The average FWMC of TP, comprising DUP, PP and DRP, for all treatments and rainfall
events is shown in Fig. 5.6. The application of TD and ADIRE biosolids and DCS
significantly increased the average FWMC of DRP in RS1 and RS2 compared to the study
control, but this highly mobile P fraction was low for the other biosolids treatments. The
highest median FWMC of DRP in the biosolids treatments (0.86 mg L-1) was measured
during RS1 for TD-amended plots, and this decreased significantly (p=0.02) over subsequent
rainfall events to 0.14 mg L-1 for RS3. In comparison, the median FWMC of DRP from the
ADIRE treatment was highest for RS2 (0.78 mg L-1), although results for the three events
were not significantly different. However, losses for DRP from biosolids treatments were low
compared to the DCS. Dissolved reactive phosphorus losses for DCS during RS1 was 7.0 mg
L-1 and remained higher than any of the biosolids treatment losses during all simulation
events.
Losses of PP were detected across all treatments, including the study control. Particulate P
comprised >45% of TP losses for ADUK, ADIRE and LS biosolids, and the study control.
69 Particulate P losses comprised only 14% and 32 % of TD biosolids and DCS, respectively,
due to the high proportion of DRP losses. However, when only considering the PP losses,
DCS plots for RS1 and RS2 had significantly higher PP losses (p < 0.05) than all other
measurements, which were statistically indistinguishable. The average FWMC of TN across all treatments is shown in Fig. 5.6. There was a significant
interaction between treatment and the rainfall simulation for NH4-N. The application of all
biosolids treatments and DCS increased the average FWMC of NH4-N for RS1 compared to
the study control, and while there was a downward trend between RS1 and RS3 for all
treatments except the control, the decrease was not significant for LS. The ADUK-amended
plots had the highest FWMC of surface runoff of NH4-N for all biosolids treatments in RS1
(15.3 mg L-1). Thermally dried and ADIRE treatments had the next highest FWMCs of NH4N, but these were not significantly different from each other or from the LS runoff during
RS1. While total losses from DCS were greatest, they were significantly different only from
LS (p=.005) and the control (p<0.001). The median FWMC of NH4-N in RS1 for DCS was
17.4 mg L-1. The addition of biosolids and DCS had no effect on FWMCs of NO3-N in runoff,
except for LS biosolids, which significantly reduced, relative to the control, the incidental
losses of NO3-N during RS1 and RS2 (p<0.001), before it increased during RS3. Nitrite
losses were negligible in all treatments, with only exception being the DCS.
70 Figure 5.6. Flow weighted mean concentrations of phosphorus (top) and nitrogen (bottom) in
the runoff over three successive rainfall events at 24 hr (RS1), 48 hr (RS2) and 360 hr (RS3)
after application to grassland.
5.4.2. Metal losses in runoff
The average FWMC of metals (Cu, Ni, Pb, Zn, Cd, Cr) in runoff are shown in Fig. 5.7. All
runoff samples were below their respective drinking water standards intended for human
71 consumption (S.I. No. 122 of 2014). There was no difference in the FWMCs in surface runoff
of Cd and Cr of any treatment compared to the study control, except for DCS. Cadmium
losses for DCS during RS1 were significantly lower than other treatments, but were
significantly higher during RS3. For Cu, the LS-amended plots had significantly higher
FWMCs than all other treatments (p<0.001), with the highest median concentration of 202 µg
L-1 measured during RS1. There was a decreasing trend in Ni concentrations across all
treatments from RS1 to RS3, except for the study control, but there were no significant
differences within treatments. All Ni concentrations were elevated compared to control. The
highest median FWMC for Pb (1.5 µg L-1) was measured during RS3 for the DCS and the
second highest was 0.82 µg L-1 during RS1 for TD-amended plots. However, there was no
significant difference between the treatments and the study control. The highest median
FWMC of Zn (30.8 µg L-1) was during RS1 for DCS-amended plots, but there were no
significant differences across treatments or events.
72 A
B
C
D
E
F
Figure 5.7. Flow weighted mean concentrations of cadmium (A), chromium (B), copper (C),
nickel (D), lead (E) and zinc (F) in the runoff over three successive rainfall events at 24 hr.
(RS1), 48 hr. (RS2) and 360 hr. (RS3) after application to grassland
73 5.4.3. Microbial losses in runoff (Total and faecal coliform)
The average losses of TC and FC are shown in Fig. 5.8. The ADUK-amended plots produced
runoff with the lowest number of TC (averaged over the three rainfall simulations), but
produced the highest average number of FC: 7.1 × 103 MPN per 100 ml during RS1 and RS2.
For TC losses there was an interaction between treatment and event (p=0.01), but only the
highest and lowest event outcomes were significantly different. While median losses from the
TD-amended plots increased with successive rainfall events from 1.9 × 105 MPN per 100 ml
during RS1 to 1.0 × 106 MPN per 100 ml during RS3, there were no significant differences
within treatments. There was no evidence of interaction between treatment and event for TC,
so it is impossible make inference about the factors separately. There was no change from
RS1 to RS2, but there was a decrease from RS2 to RS3 (p<0.0001) from a median of 7.6 ×
101 MPN per 100 ml during RS1 to 5.4 × 101 MPN per 100 ml during RS3. Overall losses
from DCS (3.1 × 102 MPN) were greatest and significantly greater than LS, ADIRE and the
control. ADUK losses (1.7 × 102 MPN) were not statistically different from DCS, but were
significantly greater than the control (p=0.009). The highest median count of TC and FC
measured in LS biosolids-amended plots was 5.6 × 105 and 1.5 × 101 MPN per 100 ml,
respectively. The highest median loss of TC for DCS-amended plots was 1.5 × 105 MPN per
100 ml.
74 Figure 5.8. Total coliforms (top) and faecal coliforms (bottom) in the runoff per 100ml over
three successive rainfall events at 24 hr (RS1), 48 hrs (RS2) and 360 hr (RS3) after
application to grassland
75 5.4.4. Soil test P, Mehlich-3 P, K, LR, pH and metal
Morgan’s P, Mehlich-3 P, WEP, Mg, K, pH, LR and metals results from analysis of plots
before (t0) and at the end of the experiment (t360) are presented in Tables 5.2 and 5.3. Average
Pm (3.6 to 4.8 mg L-1), Mehlich-3 P (38.0 to 47.4 mg L-1), K (58.2 to 94.94 mg L-1), LR (2.3
to 2.6 t ha-1) and pH (5.90 to 5.99) across all plots before application of treatments were
similar. At the end of the experiment, Pm increased across all treatments (p<0.0001), with no
significant differences between treatments. The Pm of the control plots also increased by
18%. Mehlich-3 P decreased across all treatments (p=0.0001), with no significant differences
between treatments. Potassium concentrations showed no significant decrease for LS and TD
treatments, while the greatest reduction was in the ADUK plots (35%) and the lowest in the
lime-amended plots (10%). Magnesium showed no significant changes over the duration of
the experiment. Lime requirement increased in the ADUK, TD, control plots and ADIRE by
11%, 10% 8% and 3.8%, respectively, but reduced by 56% in the lime-amended plots.
Average metal results across all treatments before the start of the experiment were similar. At
the end of the experiment, Cd and Cr (p<0.0001) increased across all treatments, while Cu
showed a significant decrease only for TD. Lead (p=<0.0001) and Ni (p<0.0001) increased
across all treatments, but there were no significant differences between treatments. The
average increase for Pb was 50.8% and was 27.6% for Ni. Zinc decreased (p<0.0001) across
all treatments, but there was no difference between treatments.
5.5 Discussion
5.5.1. Incidental nutrient losses for all rainfall events
With the exception of LS biosolids, FWMCs of TP and DRP across all treatments were
significantly higher than the study control and, in some cases, were in breach of maximum
76 admissible concentrations (MAC) for surface water. The volumetric water content of all study
micro-plots was approximately 40% and the runoff ratio (the volume of runoff as a
percentage of the volume of water applied to each micro-plot) was broadly similar across
treatments (data not shown). Therefore, the nutrient load from each micro-plot was
proportional to the FWMCs.
The FWMCs of TP and TN generally decreased across successive rainfall events. This trend
is similar to several studies that have examined runoff of nutrients resulting from the land
application of different types of biosolids and DCS (Rostagno et al., 2001; Penn et al., 2002;
Ojeda et al., 2006; Eldridge et al., 2009; Lucid et al., 2014). The DRP losses measured in the
current study were proportional to the WEP of the biosolids. Several studies have shown that
WEP is an effective quantitative indicator of dissolved P losses from surface applied biosolids
(Kleinman et al., 2002; Elliot et al., 2005; Kleinman et al., 2007). Thermally dried and
ADIRE biosolids, which also had high WEPs (Table 5.5), had the highest losses of dissolved
P from their respective plots.
All biosolids treatments had elevated FWMCs of NH4-N in runoff compared to the study
control across all rainfall simulations, whereas the study control and biosolids-amended plots
had the same NO3-N concentrations. Ammonium can be volatilised (or rapidly mobilised by
runoff and leaching) after organic matter spreading (Quilbé et al., 2005). ADUK biosolids,
which had the highest initial NH4-N concentration in the biosolids at the time of application
(3846 mg kg-1 DM), also had the highest FWMC of NH4-N in runoff compared to biosolids
treatments during RS1. Similar trends were noted for the ADIRE and LS biosolids. However,
the initial concentration of NH4-N in TD biosolids before application (573 mg kg-1; Table 5.5)
was lower than the ADIRE biosolids (3428 mg kg-1; Table 5.5), but had similar losses of
77 NH4-N in surface runoff during RS1. These types of anomalies may be due to the consistency
of the biosolids, which means that different types of biosolids will have varying surface area
exposure to rainfall. Therefore, TD biosolids could possibly be easier diluted and transported
in the runoff compared to the ADIRE, ADUK and LS biosolids, due to their finer particle
granulated consistency. This is also the reason for the high proportion of runoff measured for
the DCS. Dairy cattle slurry had the highest FWMC of NH4-N and DRP. A possible reason
for this is that DCS had a DM of 8%, and was highly mobile following an episodic rainfall
event. This study shows that biosolids, although having a higher DM than DCS, are not as
easily mobilised.
5.5.2. Incidental metal losses for all rainfall events
The concentrations of metals in runoff were below drinking water standards intended for
human consumption (S.I. No. 122 of 2014). Similar results have been reported for several
runoff studies using different types of biosolids at higher application rates than the current
study (Joshua et al., 1998; Dowdy et al., 1991; Eldridge et al., 2009; Lucid et al., 2013). This
shows that the codes of good practice for the use of biosolids in agriculture (Fehily Timoney
and Company, 1999) are appropriate in limiting metal application and, therefore, losses to
waterbodies. The metal content in the biosolids was not the limiting factor for the spreading
rate, and the soil metal content was also below maximum permissible guidelines (Fehily
Timoney and Company, 1999). The soil pH and clay content were within the recommended
guidelines set out in code of good practices (Fehily Timoney and Company, 1999).
While there was generally low FWMC of metals over all rainfall simulations, the LS
biosolids-amended plots released the highest quantity of Cu, Ni and Zn compared to other
78 plots. One possible explanation for this is that Cu, Ni and Zn are more soluble metals (Joshua
et al., 1998), and as LS biosolids consists of larger sized particles of a more compact
consistency, time to runoff increased (results not shown), giving these metals more contact
time to dissolve and subsequently be released compared to the other biosolids treatments.
Metal concentration was low in DCS in comparison to the biosolids before application and,
as a result, did not cause excessive losses of metals in runoff. However, the FWMC of Cd and
Cr in DCS-amended plots were higher than any of the biosolids plots, with peak
concentrations of 1.68 ug L
-1
during RS3 for Cd and 3.89 ug L
-1
during RS1 for Cr,
respectively. However, even at these concentrations, they were still well below drinking water
standards.
5.5.3. Incidental pathogen losses for all rainfall events
Understanding the environmental persistence and fate of enteric pathogens introduction
following land application of biosolids and organic amendments is necessary, as it provides a
sound scientific basis for management practices designed to mitigate the potential
microbiological health risks associated with spreading on agricultural land (Lang et al.,
2007). The risk associated with biosolids-derived and other organic amendment pathogens is
largely determined by their ability to survive and maintain viability in the soil environment
after land spreading. In general, enteric pathogens are poorly adapted to survival in the soil
environment, and pathogens that are land applied from biosolids and DCS are influenced by
climatic and agronomic variables (Lang et al., 2003). When biosolids and DCS are
incorporated into the soil, pathogen survival is affected by factors such as pH, OM, soil
texture, temperature, moisture content, and competition with other microorganisms (Lang et
al., 2007). These factors have been reviewed by Erickson et al. (2014). However, when
79 biosolids and DCS are surface applied, as in the current study, desiccation and ultraviolet
light are the key factors in the decay of pathogens (Lu et al., 2012). Desiccation of pathogens
is influenced by the soil, biosolids and DCS moisture content. In the current study, soil
moisture remained consent at approximately 40%, which was unlikely to affect pathogen
survival or regrowth. However, as the rainfall simulator provided moisture to the biosolids,
there may have been regrowth of the FC in the ADIRE and LS biosolids between RS1 and
RS2. Similar FC regrowth in AD biosolids was also reported by Zaleski et al. (2005). All TC
and FC in biosolids decayed by RS3, which was most likely due to desiccation of pathogens
rather than the influence of UV, as all plots were covered by the rainout shelter, which
prevented natural rainfall between RS2 and RS3.
ADUK biosolids had significantly higher concentrations of FC in runoff during RS1 and RS2
compared to other treatments. At the start of the experiment, the ADUK biosolids were above
the recommended standards of >1 × 103 MPN g-1 (Fehily Timoney and Company., 1999),
and, as a result, were equivalent to Class B microbial matter under the US EPA Part 503
regulations (USEPA, 1993), which allows detectible levels of FC up to 2 × 106 MPN g-1 DS.
All the Irish biosolids were some 10-fold below the Class A Irish standard. Dairy cattle slurry
had high FC losses compared to the Irish biosolids, suggesting that pathogen losses to surface
water bodies following land application of untreated organic fertiliser may be a concern in
Ireland.
It is important to evaluate the risks arising from the application of biosolids to land relative to
other common agricultural practices such as the land application of animal waste (Vinten et
al., 2010), which is commonly spread as an organic fertiliser. Hubbs (2002) reported that land
application of DCS as a fertiliser had FC concentrations in surface runoff of up to 1.2 × 105
80 CFU per 100 ml, two days after application, and after five rainfall events over 30 days, the
mean FC concentrations in runoff, although decreasing, remained at high levels compared to
the biosolids in the same study (4.0 × 103 CFU per 100 ml). This was also observed in the
current study, as the DCS had the second highest FC during RS1 and RS2, but was the
highest by RS3, showing that FC survive for a longer period in DCS compared to biosolids,
and may result in losses of pathogen to waterbodies for a longer period following application.
Moreover, Payment et al. (2001) found that the pathogen concentration was lower in
untreated sludge (3 × 102 to 6 × 102 cfu g-1) compared to fresh and stored cattle slurries (2.6 ×
108 to 7.5 × 104 cfu g-1) (Hutchison et al., 2004). When considered within this context, the
risk of infectious diseases arising from the land application of biosolids appears to be low in
magnitude. This study also provided no buffering capacity to the runoff samples, and
overland flow was not sampled at delivery end of the transfer continuum, so the bacterial
results represent a worst case scenario.
While this study and many others focus on the TC group as an indicator of the presence of
pathogens, the drawback of relying on them is that it they are a poor indicator for the
presence of viruses and parasitic protozoa, which may survive for much longer periods
(NHMRC, 2003). However, due to the lack of well-developed methods for the detection and
enumeration of these pathogens (Sidhu et al., 2009), the use of indicator organisms allows for
the limitation of potential contaminating effects.
81 5.5.4. Soil characteristics before and after experiment
In the current study, differences in soil nutrient concentration following amendments were observed. The application of all biosolids increased the Pm in all amended plots from an Index
2 soil to an Index 3. Whilst the Pm of the control plots also increased from an Index 2 soil to
an Index 3 soil, the increase was less than half the increase of the nearest biosolids
amendment (ADIRE). Lime stabilised biosolids had the greatest increase in Pm, and this may
have been a result of the evaluated pH in the soil as liming improves the availability of soil P.
This result also shows that although LS biosolids are low in nutrient content, they can be
applied for their pH adjusting characteristics and, as a result, may enhance nutrient
availability to soil and plants.
This study also investigated the accumulation of metals before and after the experiment.
Results showed that while there was an increase for some metals, none exceed the
recommended guideline limits for soil set out in code of good practices (Fehily Timoney and
Company, 1999). It should be noted, however, that the current study encompassed a single
application of biosolids, and that concerns have been raised about the accumulation of metals
in both soil and crops after repeated applications of biosolids (McBride, 2003; Bai et al.,
2010). However, in Ireland, the application rate of biosolids to land is governed by legislation
and whilst best practice is followed, problems in terms of metal or nutrient build-up will be
avoided.
82 5.6. Conclusion
The results of this plot-scale study showed that there were elevated losses of nutrients and
faecal coliforms from biosolids-amended plots compared to unamended plots. However,
nutrient and pathogen losses were higher from DCS-amended plots. Metal concentrations in
runoff were below their respective drinking water limits for human consumption for both
biosolids and DCS. The runoff concentrations measured in this study represented a ‘worst
case’ scenario for potential losses, as further buffering may be possible further down the
transfer continuum. This study was conducted at micro-plot scale, but the results should be
verified at field-scale. In addition, future work should also be carried out to assess ‘emerging’
organic pharmaceutical contaminants that may be present in biosolids. Notwithstanding these
caveats, these results are significant as they show that issues surrounding the reuse of a
resource, mainly concerning fears over elevated losses of nutrients, metals and pathogens,
may be unfounded. 5.7. Summary
The results of this study, while indicative only, allow comparison to be made between
amendments when applied at the same rate. The findings of this study need to be verified at
full field scale. In addition, further research is required to determine their effect on the
physical and chemical properties of soil.
83 Chapter 6 - CONCLUSIONS AND RECOMMENDATIONS
6.1. Overview
The objective of this study was to determine the impact of land application of three types of
biosolids and compare them to another commonly spread organic fertiliser, dairy cattle slurry.
To achieve this, a simple, novel, field-scale micro-plot study was designed and conducted,
which examined the possible impacts arising from the land application of these treatments on
surface runoff water and soil properties. The main conclusions and recommendations arising
from this study are now presented.
6.2. Conclusions
1. Losses from biosolids-amended plots were higher than the study control (soil only)
plots, and followed a general trend of highest losses occurring during the first rainfall
event and reduced losses in the subsequent events.
2. With the exception of total coliforms and some metal parameters, the greatest losses
were from the dairy cattle slurry-amended plots. This means that biosolids do not pose
a greater risk in terms of runoff losses following land application.
3. Preliminary tests examining ways to incorporate lime into sewage sludge suggested
that it may be difficult to satisfy the Code of Good Practice standards, which state that
the quantity of lime added to sewage sludge must increase the pH of the lime-sludge
mix to ≥12 and the temperature to 70˚C for 30 min, or increase the pH above 12 for
72 hr and maintain a temperature of ≥ 52˚C for 12 hr. While the pH criterion was
84 achieved in our preliminary studies, there was difficulty in achieving the temperature
criterion. This finding may have implications for the quality of biosolids produced at
field-scale from lime stabilisation.
6.3 Recommendations for future work
1. There is currently a knowledge gap concerning the effectiveness of lime stabilisation
in adhering to the pH and temperature requirements of the Codes of Good Practice.
There is a need for research into the lime stabilising process and its effectiveness to
minimise food safety concerns.
2. Biosolids spread at the maximum application rate on grassland had no adverse impact
on surface water quality compared to dairy cattle slurry in terms of nutrients and
metal losses in surface runoff. However, further testing in a larger field-scale
experiment will be needed verify the findings of this study.
3. This study did not examine the surface runoff for the presence of emerging
contaminants, such as pharmaceuticals or personal care products. While the findings
of this study suggest that there are no issues in runoff of nutrients, metals and
microbial matter (in comparison to dairy cattle slurry), the surface runoff water from
the biosolids-amended micro-plots of the current study must be tested for these, and
other, emerging contaminants. At the time of writing, surface runoff water samples
from our micro-plots are awaiting testing for a selection of emerging contaminants.
4. Gaseous emission studies following the land application of organic and chemical
fertilisers are commonly conducted. However, little work has been conducted
examining gaseous emissions following biosolids application to land. Work is needed
to address this knowledge gap.
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