AMBIENT AIR QUALITY ASSESSMENT IN OPENCAST METAL MINES

AMBIENT AIR QUALITY ASSESSMENT IN OPENCAST METAL MINES
AMBIENT AIR QUALITY ASSESSMENT IN
OPENCAST METAL MINES
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF
BACHELOR OF TECHNOLOGY
IN
MINING ENGINEERING
BY
RAJAT SAHU
109MN0586
&
PARTHA SARATHI PANDA
109MN0121
DEPARTMENT OF MINING ENGINEERING
NATIONAL INSTITUTE OF TECHNOLOGY
ROURKELA – 769 008
2013
AMBIENT AIR QUALITY ASSESSMENT IN
OPENCAST METAL MINES
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTSFOR THE DEGREE OF
BACHELOR OF TECHNOLOGY
IN
MINING ENGINEERING
BY
RAJAT SAHU
PARTHA SARATHI PANDA
UNDER THE GUIDANCE OF
Dr. H. B. SAHU
DEPARTMENT OF MINING ENGINEERING
NATIONAL INSTITUTE OF TECHNOLOGY
ROURKELA – 769 008
2013
National Institute of Technology
Rourkela
CERTIFICATE
This is to certify that the thesis entitled “AMBIENT AIR QUALITY ASSESSMENTIN
OPENCAST METAL MINES” submitted by Sri Rajat Sahu and Sri Partha Sarathi
Panda in partial fulfilment of the requirements for the award of Bachelor of Technology
degree in Mining Engineering at National Institute of Technology, Rourkela is an authentic
work carried out by them under my supervision and guidance.
To the best of my knowledge, the matter embodied in the thesis has not been submitted to any
other University/Institute for the award of any Degree or Diploma.
Prof. H. B. Sahu
Dept. of Mining Engineering
National Institute of Technology
Rourkela – 769008
i
ACKNOWLEDGEMENT
We are indebted to Dr H. B. Sahu, Associate Professor of Department of Mining Engineering his
inspiring direction, valuable suggestions and remarkable explanation throughout this project work.
We thank him for his able guidance and painstaking effort in improving our understanding of this
project.
We are thankful to Mr Anup Mallick, Scientist; and Mr N. Mallick, Regional Officer, SPCB
Rourkela Regional office for extending help in carrying out the air sampling.
We are also thankful Sri B. K. Pradhan, Technical Assistant and staff members of Department
of Mining Engineering, NIT Rourkela for their help.
We extend our veneration towards those whose details are mentioned in the reference section. We
acknowledge our indebtedness to all of them.
We feel privileged to have very good batch mates and thank them for extending all sorts of help for
successfully accomplishing this project.
Partha Sarathi Panda
Date :
Rajat sahu
Dept. of Mining engineering
National Institute of Technology
Rourkela – 769008
ii
CONTENTS
Sl. No
*
*
*
*
*
1
1.1
2
3
3.1
3.2
4
4.1
4.2
4.2.1
4.2.2
4.3
4.3.1
4.3.2
5
5.1
5.2
5.3
6
6.1
6.2
6.3
7
7.1
8
Topic
Certificate
Acknowledgement
Abstract
List of figures
List of tables
INTRODUCTION
Objectives
LITERATURE REVIEW
HEALTH IMPACTS OF PARTICULATE MATTER AND
GASSES IN OPEN CAST METAL MINES
Effect of particulate matter on various systems human body
Effect of mine gasses on human health.
AIR SAMPLING TECHNIQUES
Basic Sampling methods
Gravimetric sampling
PM 10 and PM2.5 Samplers of High volume type
Personal samplers for PM2.5 and PM10 Particulate matter
sampling.
Air sampling and analysis methods as recommended by CPCB
Guidelines for sampling and analysis of Particulate matter
(PM10) in ambient air
Guidelines for sampling and analysis of Particulate matter
(PM2.5) in ambient air
AIR QUALITY MODELLING
Gaussian Plume Model
Meteorological parameters that effects the air quality modelling.
Preferred and recommended air quality models
AIR QUALITY ANALYSIS
Procedure of on-field air sampling
Observations
Air quality Index
DISCUSSION AND CONCLUSION
Measures of dust control
REFERENCES
iii
Page no.
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vi
vii
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3
5
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20
22
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24
27
28
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35
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48
50
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ABSTRACT
The term ‘mining’ is more or less synonymous to environmental pollution. The growing
emphasis on open cast mining operation in recent years to achieve ever increasing production
targets has further aggravated the problem of air pollution. Great amount of respirable dust
concentration are added into the environment by the mining activities due to mechanization,
escalating production, large scale blasting etc. Major sources of air pollution in open cast
mines are drilling, blasting, overburden loading and unloading, material handling and
workshops.
The National Ambient Air Quality Standards (NAAQS) are the basis for India’s Central
Pollution Control Board (CPCB) to regulate air pollutants including particulate matter and five
other criteria pollutants. PM2.5 and PM10 particles are currently accepted indicators for
respirable pollutants. Several methods normally exist to measure the amount the dust.
Method of sampling
Air Sampling: Air sampling is capturing the contaminants from a known volume of air,
measuring the amount of contaminants captured, and expressing it as a concentration.
There are many different methods for taking air samples. But the most widely used and
preferred method gravimetric sampling. Here a pump is connected to a filter medium; the
pump should be capable of drawing air through the filter at a constant rate for a time in excess
of 8 hours even in adverse conditions such as extreme cold or heat. For this particular work,
‘ENVIROTECH APM 460NL’ size selective air sampler was used. The sampling system
comprises of an omni directional air inlet, size selective impactor, filter medium, oil-less rotary
suction pump, dry gas meter for overall sampling procedure. The sampling was performed as
per CPCB guidelines.
Results and discussion
In the month of December-2012, air sampling was carried out in Raikela Tantra iron ore mines
in four locations namely, core zone-Mine office area and buffer zones- village Dengula, Tensa
town and village Bahamba. The air quality index (USEPA, 2011) was calculated for the above
mentioned locations and other parameters like PM 10, PM2.5, SO2, NOx and CO were compared
to NAAQS.
iv
Table 1: AQI of Sampled air quality data and conc. of other gaseous pollutants at Raikela
Tantra iron ore mines
Location
Village
Dengula
30
Tesnsa Town
PM 2.5
Mines
office area
29
NAAQS
Unit
41
Village
Bahamba
27
60
μgm/m3
PM 10
82
88
97
75
100
μgm/m3
SO2
4
4
4
4
80
μgm/m3
NOx
9
16
9
9
80
μgm/m3
CO
0.1
0.1
0.1
0.1
4
mg/m3
AQI
77.56
79.53
100.98
73.63
Remarks
Moderate
Moderate Unhealthy for Moderate
sensitive group
From the above sampled data, it is observed that the level of pollution comes to be in Moderate
level. The concentration of gaseous pollutants was much lower than the NAAQS limits. In
overall sense, it can be said that in opencast mines particulate matter pollution is more
prominent. The PM10 concentrations at these sites were observed close to NAAQS limits.
Conclusion
The study reveals that the air quality index varies from simple to moderate category. However,
the AQI for Tensa town is coming under ‘unhealthy to sensitive people’ group. Thus various
dust suppression measures need to be taken to control particulate matter dispersion within
environment. It is noticed that majority of the concern is the particulate matter pollution caused
by transportation, crushing and grinding operations. It is suggested that in addition to teh fixed
and mobile sprinklers, the mine management should adopt some additional dust suppression
measures viz., proper housekeeping, black topping of permanent roads, utilization of wetting,
binding and agglomerating agents, foam suppression. Development of a green belt around the
periphery of the mines with plants having thick foliage should also be stressed upon.
References
Chander, S., Alaboyun, A.R. and Aplan, F.F., 1991, Mechanism of capture of coal dust
particles by sprays, Proceedings of the Third Symposium on Respirable Dust in the
Mineral Industries (Pittsburgh, PA, October 17-19, 1990). Littleton, CO: Society for
Mining, Metallurgy, and Exploration, Inc.
Chaulya, S.K., 1999, Air quality status of an open pit mining area in India, Environmental
Monitoring and Assessment, vol-105, P.P: 369–389.
Ghose, M.K. and Majee, S.R., 2001, Air pollution caused by opencast mining and its abatement
measures in India”, Journal of Environmental Management, Vol. 63, P.P: 193–202.
v
LIST OF FIGURES
Fig no.
Title of the figure
Page no.
3.1
Size comparison of PM2.5and PM10
13
4.1
Photographic view of PM10 sampler
21
4.2
Schematic PM10 Sampler (Cyclonic Inlet)
23
5.1
Co-ordinates of a Gaussian plume
30
5.2
Gaussian plume from a stack
31
6.1
PM Conc. in Raikela Tantra Iron ore Mine (Mining site)
36
6.2
PM Conc. in Khondbond Iron & Manganese Mine (Mining site)
37
6.3
PM Conc. in Khondbond Iron & Manganese Mine (Near plant area)
38
6.4
PM Conc. in Joda east Iron ore mine (Mining area)
39
6.5
PM Conc. in Joda east Iron ore mine (Residential area)
40
6.6
PM Conc. in Jilling Langalota iron & manganese mine
40
6.7
PM Conc. in Bhulbeda iron mines
41
7.1
Mobile water sprinkling truck system
51
7.2
Application of foam near crusher area
54
vi
LIST OF TABLES
Table
no.
1
Title of the table
AQI of Sampled air quality data and conc. of other gaseous pollutants
Page
no.
V
‘Raikela Tantra iron ore mines’
4.1
NAAQS for particulate matter PM10
22
4.2
NAAQS for particulate matter PM2.5
24
6.1
Sampled Air Quality data of ‘Raikela Tantra iron mines’
36
6.2
Air quality of Khondbond iron and manganese mines (mining site)
37
6.3
Air quality of Khondbond iron and manganese mines (Near plant area)
38
6.4
Air quality of Joda east Iron ore mine (Mining area)
39
6.5
Air quality of Joda east Iron ore mine (Residential area)
39
6.6
Air quality of Jilling Langalota iron & manganese mine
40
6.7
Air quality of Bhulbeda iron ore mine
41
6.8
Observed Air Quality data of ‘Oraghat Iron ore mines’ during 2009-
41
2012
6.9
Recent Air Quality Data of different open cast metal mines obtained
42
from SPCB, Regional office, Rourkela
6.10
Joda East iron ore mine, M/s Tata Steel Ltd.
45
6.11
Khondbond iron and manganese mines , M/s Tata Steel Ltd.
45
6.12
Bhulbeda iron ore mines , M/s Mineral Trading Syndicate
46
6.13
Jilling Langalota iron and manganese mines, M/s Essel Mining &
46
Industries Ltd.
7.1
Comparison between different particulate matter control measures
vii
55
Chapter 1
INTRODUCTION
1. INTRODUCTION
Mining is a vital industry for industrial and economic growth of any country. The development
of infrastructure and core sector is directly linked with increased production of minerals, like
coal for power sector, iron ore for steel sector, limestone for cement for housing and
infrastructure development.
With increased industrialization, urbanization and other
developmental activities; there is a greater need for increased production of minerals. The
emphasis therefore is now on surface mining which is adopted for quick and economic
extraction with higher percentage of recovery compared to underground mining; in fact bulk of
the minerals obtained in India now comes from opencast mines. Some of the important
minerals like limestone, dolomite, iron ore, bauxite, granite, silica and magnetite etc. are
obtained exclusively by opencast mining.
Opencast mining is more damaging to the
environment than underground mining as are less to remove substantial amount of land to
reach the mineral It starts within a natural ecosystem and it not only disturbs the existing
ecosystems, but also generates an artificial one, which has its own factors including pollutants
and contaminants.
The important environmental problems that arise out of the opencast
mining operation are air, water and soil pollution. In this project various aspects of air
pollution and their effect on the local habitat of a iron ore mine are discussed (Chaulya, 1999).
Air pollution in the open cast mining areas are caused by drilling, blasting, overburden loading
and unloading, material loading and unloading, road transport and losses from exposed
overburden dumps, material handling plants, exposed pit faces and workshops. In development
stage of an opencast mine, massive overburden (OB) has to be taken out to reach the mineral
deposit. This necessitates the use of excavators, loaders, dumpers, and conveyor belts, which
results into massive discharge of fine particulates from OB material. Likewise, normal
production and operation will need excavation, size reduction, waste removal, transportation,
loading, and stockpiling. All these operations generates particulate matter and is reported that
plying of heavy earth moving machinery on haul roads of mechanized opencast mines could
contribute as much as 80% of the dust emitted.
Characterization of potential health risks resulting from exposures to ambient air toxics
requires assessing the impact of ambient sources on personal exposures. This is a challenging
task because the variables needed to assess individual and population exposures are not always
available (Ghose and Majee, 2001).
2
The National Ambient Air quality Standards (NAAQS) are the basis for the Central Pollution
Control Board to regulate air pollutants, including particulate matter (PM) and five other
criteria pollutants. Particles with an aerodynamic equivalent diameter (AED) less than or equal
to a nominal 10 micrometre (also known as PM10) and 2.5 micrometre (PM2.5) are the currently
accepted indicators for PM pollutants.
1.1OBJECTIVES
Keeping the aforementioned problems in mind the current work has been carried with teh
following objectives:
Assessment of the ambient air quality in the open cast iron and manganese ore mines in
the Keonjhar district of Odisha.
Collection of data from EIA reports and SPCB, Rourkela for the above areas.
Analysis of data for variation of air quality.
Classification of air quality according to standard Air Quality Index.
3
Chapter 2
LITERATURE REVIEW
2. LITERATURE REVIEW
The following is a brief review of scholarly work of different researchers in the field of
Ambient Air Quality Assessment:
Stein and Corn (1975) observed that to provide a clear picture on the physical nature of the
size fractions, additional characterizing parameters based on density, particulate matter size by
optical microscopy, random and projected area & specific surface area need to be provided.
They collected air samples from underground coal mines from Pittsburg seam, lower Freeport
and lower Kittaning seams and with the use of horizontal elutriator and collected over 8 in*10
in membrane filter (Millipore SCW P00010). Each sample was separated into four different
size fractions by Bahco centrifugal classifier. Then various experiments were conducted by
them to calculate the above parameters for each size fractions. Then the difference in
parameters for the size fractions were analysed and discussed. Thus, it is made possible to corelate the advent and seriousness of respirable lung diseases with the physical and chemical
properties of different size fractions of the ARD (Airborne respirable dust), more closely.
Kumari et al. (1995) the study puts a great emphasis on determination of quartz present in the
airborne respirable dust (ARD) known to cause silicosis & cancer. FT-IR spectrometer was
being used in direct on filter method for quartz determination in ARD with quartz doublet peak
at 800 & 700 cm-1. For taking air samples from different locations of mine personal dust
samplers were used and collected over GLA -5000 PVC membrane filters.
Certain dust generating sources were selected where dust samplers may be placed and it was
even attached with different workers engaged in the shifts. The analysis in different coal and
metal mines showed that quartz content in respirable dust is <1% which is less than the
prescribed MEL (Maximum exposure limit) 3mg/m3 except for 2-3 locations in Longwall and
bunker top. It was observed that drilling, haulage, crusher house are main high risk zone of
silicosis and was eventually concluded that wet drilling as well as improved ventilation is
effective to control airborne dust as well as emission of quartz. Frequent rotation of workers is
a must in locations like crusher sites where, even after adoption of dust suppression measures,
dust is not reduced to safe limits.
5
Chaulya (1999) for a period of 1 year, carried out a study for assessment of air quality in
Lakhanpur area. He found out that the annual average of concentrations of TSP & PM 10 were
higher than the prescribed limits given by NAAQS. He took the help of linear regression
analysis to predict the concentrations of one type of particulate matter by knowing the level of
the other, for O/C coal mines with same as conditions. Monitoring stations were placed to
evaluate air quality and plan any control measures. Sampling and analysis were done twice
monthly for residential areas (buffer zone) and six times monthly for industrial areas (core
zone/mining area) during the year from September 1998 to August 1999.
He suggested that effective control measures at the CHP, excavation area & o/b dumps should
be optimised to mitigate the TSP emission at source. Concentrations of carbon monoxide (CO)
and lead (Pb) were below detectable limits or negligible as per the bi-monthly monitoring
report for the area during the study time.
Krupa and Legge (1999) studied the use of passive samplers for gaseous air pollutants. They
evaluated the specificity and linearity of the response of passive samplers; results obtained by
such an approach were initially compared and cross-correlated with co-located active samplers
or continuous monitors for accuracy. It was found that the seasonal influences in any
comparisons of data from passive sampling versus active monitoring, particularly in the cold
climates and associated atmospheric processes of the northern latitudes. They found that the
differences between the two systems can be highly significant during the winter months. Some
pollutants such as NH3 need to be converted to a second compound (NO2) before
quantification. This can lead to technical complications on site with instrument performance.
Finally they concluded that although passive samplers are very desirable from economic and
logistic perspectives, they should be co-located with passive samplers, with continuous
monitors at sampling locations.
Ghose and Majee (2001) observed that In India, coal is mainly mined out from opencast
mines, contributing more than 70% of total coal production and it also has a high share in air
pollution. To keep a track upon the local atmosphere impact, a survey was conducted by them
taking emissions data which were utilised to find out the dust generation due to various mining
activities. They noticed that the air pollutants coming from mines and their seasonal
fluctuations in its quantity had high pollution potential and greater negative impact on human
health. They have given a lot of control measures to deal with this situation and even chalked
out ‘afforestation and tolerating capability of trees’ against the dust particulate matter. They
6
emphasised the need of utilisation of different chemicals to minimize the air pollutants coming
from haul road and stated that a pollution free environment can be achieved by implementing
suitable abatement measures.
Chakraborty et al. (2001) developed empirical formulae with the objective to calculate
emission rate of various opencast mining activities. They selected 7 coal mines and 3 iron ore
mines with the consideration of geographical location, working method, accessibility and
resource availability. 12 Empirical formula for Suspended particulate matter were developed
for many opencast mining activities like drilling, coal loading ,coal handling plant , haul road ,
workshop , etc. but the formula was for the overall mine for NO x and SO2 estimation. To verify
the universal applicability of the empirical formulas, they selected Rajpura opencast coal mine.
A good accuracy was indicated between the calculated value and field measured value which
varied from 77.2% to 80.4%. They concluded that Suspended particulate matter is the main
constituent of emissions while emissions due to NOx & SO2 are negligible. They revealed that
the results of this study is of great importance for mine environmental engineers and scientists
working in the field of air quality monitoring to monitor air quality and its impact from
pollutants generating projects.
Reddy and Ruj (2002) carried out the ambient air quality assessment in the Raniganj –
Asansol area based on sulphur dioxide, oxides of nitrogen and suspended particulate matter
(SPM) at four stations namely – Raniganj girls college (RGC), Searsol raj high school (SRS)
Raniganj, B.B college (BBC) Asansol and B.C college (BCC) Asansol; where a total of 429
samples each were taken from RGC & SRS and 435 each from BBC & BCC locations.
Ambient air monitoring frequency was 3*8 hours per day at each site on every alternate days
for 1 year; along with the recording of other parameters such as temperature, relative humidity,
air speed and its direction. They used high volume samplers to measure SPM & SO 2, and NOx
fumes and were collected by bubbling the sample in a particular absorbing solution. The results
from the above investigations showed that 95 percentile values of SPM & NOx exceeded the
reference limit in most of the stations but 95 percentile values of SO 2 level didn’t cross the
prescribed limit.
Further their seasonal variation was observed by them which highlighted ‘winter’ as the most
polluted season due to high concentration of pollutants, than summer followed by monsoon.
Thus, they concluded that the mining along with other industrial activities are solely
responsible for the high concentration of pollutants in this area.
7
Anastasiadou and Gidarakos (2006) and their team evaluated the environmental quality of
open air asbestos mine over a long period of time by measuring and monitoring the
concentration of asbestos fibres in air. The study was carried out in Asbestos Mine of Northern
Greece (MABE). Air sampling was performed according to the standard method for asbestos
sampling—the NIOSH Method 740 for phase contrast microscopy (PCM)—and according to
the air sampling process described by the EU. Static samples were taken at fixed locations,
1.5m above floor level. The samples were first observed optically and were analyzed
afterwards with X-ray powder diffraction (XRD).
A scanning electronic microscope (SEM) was also used and the suspect fibres were examined
with an energy dispersive X-ray for their composition. Majority of incidents show that asbestos
exposure is attributed to human activities, such as excavations, the treatment of asbestos, the
use of asbestos and the disposal of asbestos products into landfills.
Dahmann et al. (2008) investigated the results of exposure assessment with respect to
nitrogen oxides and carbon monoxide in German hard coal mines. The measurement campaign
was accompanied by an epidemiological study investigating possible health effects on the
airways of the lungs. For this purpose time weighted 8-hour shift values were determined by
them, for typical groups of coalminers according to the European measurement standards.
Based on these measurements and on experts’ assessments of the retrospective exposure
situation, time-dependent cumulative and average NO and NO2 exposure estimates were
derived for an inception cohort of two groups of coalminers. They concluded that Miners
working in blasting crews (no blasting specialists) were estimated by experts to experience 2/3
of the nitrogen oxide exposure of blasting specialists. Especially, for the diesel engine drivers,
exposure can be rather higher than the prescribed value.
Sharma and Siddiqui (2010) carried out a study for the assessment and management of the air
quality around Jayant open cast coal mining situated at Jayant in Sidhi district of Madhya
Pradesh, India. Air monitoring for SO2, NOx and TSP was done for 24 hrs. once every 15 days
at each sites and concentration were expressed as μgm. Mean value for pollutant were
calculated on 24 hours sampling basis. For the sampling of particulate matter HVS (High
Volume Sampler) was used. Samples were collected for two years using glass fibre filter paper
on fort nightly basis.
They also sought upon the observations on ‘spatial and temporal
variations in concentration of gaseous and particulate pollutants’ had done by Chaulya (2004)
during both the year of air monitoring. The study suggested that concentration of particulate
pollutant exceeded the prescribed limit especially during summer and winter season.
8
They finally recommended implementing a plan of regular cleaning of transportation roads,
watering of paved and unpaved roads with chemical binding agents, installation of sprinkler
system at high polluting coal transport roads within the plant premises and effective dust
suppression mechanism at coal handling plant.
Silva et al. (2010) observed that monitoring of light hydrocarbons is extremely critical ,
basically on two aspects; one is due to global climate change and other one for economic &
safety reasons. Due to the difficulty to access and lack of correct procedures of gas sampling in
Brazilian coal mines, they aimed to apply standard gas chromatography procedures of gas
sampling to determine LHCs (light hydrocarbons) levels from their 2 surface mines and 3
underground mines. Samples of gas were collected with the help of sequential sampler and
were placed in polypropylene tedler gas sampling bags. Then the LHCs concentration was
calculated from gas chromatograph equipped with flame ionization detector. The results
indicated higher percentage of LHCs in u/g mines than surface mines with CH 4 levels varying
from 3 ppm to 27% in coal mine atmosphere. They found that the proposed methodology was
very effective in measuring LHCs levels and was finally concluded that sampling of air using
tedler bags and sequential sampler was better than steel canisters.
Chen et al. (2010) dealt with the application of matter-element method in estimation of
ambient air quality in Huizhou opencast coal fields in Fuxin colliery. Study conducted by Fu et
al (2000) described air pollution of Fuxin to be composed of total suspended particulates
(TSP), SO2 and NOx. To verify their studies, dust samples were taken from four different
monitoring stations located in 4 different districts around Fuxin colliery. They applied ‘fuzzy
concept’ to the air quality assessment based on extension of matter-element theory, which
handles the concept of partial truth. Moreover this idea can predict the relative influence of
each dust pollutant on environment based on the upper and lower maximum allowable
exposure limits. They concluded that re-vegetating appropriate sites as well as the initiatives
from government can successfully help in complying ‘air quality’ within the prescribed limits
of CAAQS, 1996. The future work of this study is to develop an integrated & automated
decision support system for air quality assessment with the help of a programming language.
Khan and Bagaria (2011) carried out the study inDhanappa limestone mines, Nagpur with the
main objective to suggest a monitoring programme to evaluate the effectiveness of meditative
measures to suppress air pollutants coming from mining areas. The sites which were selected
for the studies were of three different types of anthropogenic activities i.e. sensitive, residential
9
and commercial and industrial area in around the mining sites. Annual Arithmetic mean of
minimum 104 measurements in a year taken twice a week 24 hourly at uniform interval was
taken for the study. The APM-460 Respirable Dust Sampler that they used was provided with a
cyclone. The cyclone was designed to provide separation of PM10 particulate matters for a
more accurate sampling. Sampling of SO2 and NOx was done through an impinger which was
exposed for 24 hours at an impingement rate of 1 LPM to get one sample in a day. They
analysed SO2 and NOx on spectrophotometer employing West-Geake method and JacobHochheiser method respectively. The results that they obtained suggested that ambient air
quality in the mines zones with respect to SO2 and NOx shows low pollution, while with
respect to RSPM and SPM it is moderate. They also suggested that regular monitoring and
analysing of those parameters will definitely restrict them below prescribed limits.
Mandal et al. (2011) analysed that majority of air pollutants that are contaminating the
atmosphere traces its source from the haul and transport roads in coal mining areas thus
enhancing different health problems. As high as 93.3% of total generated dust comes from haul
roads of South African coal mines, according to the analysis carried out by Amponsah-Dacosta
using USEPA guidelines. Due to the partial failure of the available techniques, the dust doesn’t
get removed from the haul road completely. In this study the qualitative as well as quantitative
aspects of road dusts is being dealt by them. For this, they collected representative road dust
samples from four different coalfields of India.
Determination of PH of dust samples were carried out by Orion ion analyser using glass
electrode; moisture content by oven dry method using Indian standards; Volatile matter by
heating the sample inside a covered crucible in a muffle furnace; ash content using Indian
standards and fixed carbon by deducting the sum total of moisture, volatile matter and ash
content from 100. Their results were quite encouraging in the sense that coal dust from haul
and transport road of mining areas can be effectively used as a domestic fuel. They concluded
that some road dust (comprising powdery coal) could be collected and converted into a solid
form so that it can be used as a domestic fuel vis-à-vis sustenance of a healthy environment
and energy.
10
Khalaji et al. (2011) used the new technique of spark induced breakdown spectroscopy (SIBS)
as a simple, rapid and in situ method for continuous dust monitoring as this method can detect
elemental composition of dust simultaneously and no sample preparation is required. They
formulated an experimental technique using a high voltage and a breakdown is created
between two electrodes. Each element in the plasma between electrodes emits its characteristic
spectral emissions by analysing the spectral emission of plasma, the elemental composition of
dusty air is determined. With this experiment the team showed that SIBS can be used as a
method for dust level monitoring and also can be used to alarm a remarkable increase of dust
in mines.
11
Chapter 3
HEALTH IMPACTS OF AIR POLLUTION IN OPEN CAST METAL
MINES
3. EFFECTS OF AIR POLLUTANTS ON DIFFERENT ORGANS
AND SYSTEMS
PM2.5 and PM10 concentration are the currently accepted criteria of National Ambient Air
Quality Standard (NAAQS) for accessing air quality.
Following are the two reasons discussed:
(i)
Long retention periodof fine particulate matter (diameter<10μ) in ambient airSmall particles have a relatively high surface area per unit mass. A centimetre cube of
quartz particle if broken into particles of 1μm3, there will be1012particles with surface
area of 6m2 in comparison to only 6cm2 area of original quartz cube. Their terminal
velocity being very negligible of the order of cm/hour or even mm/hour remains in air
borne state for a long time.
(ii)
Relative negligible absorption of fine particulate matter(diameter<10μ)in upper
respiratory trackAll dust below 10μm are considered as dangerous because of the fact that they don’t
get trapped in the upper respiratory track, such as trachea, bronchi and thus reach the
alveoli producing toxic effect like dyspnoea, thickening of alveolar walls, etc.
[Image courtesy – U.S. EPA]
Fig 3.1 Size comparison of PM 2.5 and PM10
3.1 EFFECT OF PARTICULATE MATTER ON VARIOUS SYSTEMS OF HUMAN
BODY
3.1.1 Respiratory system
Numerous studies describe that all types of air pollution, at high concentration, can affect the
airways. Nevertheless, same as effects are also observed with long-term exposure to lower
pollutant concentrations. Symptoms such as nose and throat irritation, followed by
bronchoconstriction and dyspnoea, especially in asthmatic individuals, are usually experienced
after exposure to increased levels of sulphur dioxide, nitrogen oxides, and certain heavy metals
13
such as arsenic, nickel or vanadium. In addition particulate matter that penetrates the alveolar
epithelium and ozone start lung inflammation. In patients with lung lesions or lung diseases,
pollutant-initiated inflammation will worsen their condition. Moreover air pollutants such as
nitrogen oxides increase the susceptibility to respiratory infections. Finally chronic exposure to
ozone and certain heavy metals reduces lung function, while the later are also responsible for
asthma, emphysema, and even lung cancer. Emphysema-like lesions have also been observed
in mice exposed to nitrogen dioxide.
3.1.2 Cardiovascular system
Carbon monoxide binds to haemoglobin modifying its conformation and reduces its capacity to
transfer oxygen. This reduced oxygen availability can affect the function of different organs
(and especially high oxygen consuming organs such as the brain and the heart), resulting in
impaired concentration, slow reflexes, and confusion. Apart from lung inflammation, systemic
inflammatory changes are induced by particulate matter, affecting equally blood coagulation.
Air pollution that induces lung irritation and changes in blood clotting can obstruct (cardiac)
blood vessels, leading to angina or even to myocardial infraction. Symptoms such as
tachycardia, increased blood pressure and anaemia due to an inhibitory effect on
haematopoiesis have been observed as a consequence of heavy metal pollution (specifically
mercury, nickel and arsenic). Finally, epidemiologic studies have linked dioxin exposure to
increased mortality caused by ischemic heart disease. While in mice, it was seen that heavy
metals can also increase triglyceride.
3.1.3 Nervous system
The nervous system is mainly affected by heavy metals (lead, mercury and arsenic) and
dioxins. Neurotoxicity leading to neuropathies, with symptoms such as memory disturbances,
Sleep disorders, anger, fatigue, hand tremors, blurred vision, and slurred speech, have been
observed after arsenic, lead and mercury exposure. Especially, lead exposure causes injury to
the dopamine system, glutamate system, and N-methyl-D-Aspartate (NMDA) receptor
complex, which play an critical role in memory functions. Mercury is also responsible for
certain cases of neurological cancer. Dioxins decrease nerve conduction velocity and impaired
mental development of children.
3.1.4 Urinary system
Heavy metals can induce kidney damage such as an initial tubular dysfunction evidenced by an
increased excretion of low molecular weight proteins, which progresses to decreased
14
glomerular filtration rate (GFR). In addition they increase the risk of stone formation or
nephrocalcinosis and renal cancer.
3.1.5 Digestive system
Dioxins induce liver cell damage, as indicated by an increase in levels of certain enzymes in
the blood, as well as gastrointestinal and liver cancer.
3.1.6 Reproductive system
It is rather critical to mention that air pollutants can also affect the developing foetus. Maternal
exposure to heavy metals and especially to lead increases the risks of spontaneous abortion and
reduced foetal growth (preterm delivery, low birth weight). There are also evidences
suggesting that parental lead exposure is also responsible for congenital malformations, and
lesions of the developing nervous system, causing critical impairment in new-born’s motor and
cognitive abilities. Same dioxins were found to be transferred from the mother to the foetus via
the placenta.
3.2 EFFECT OF MINE GASSES ON HUMAN HEALTH
3.2.1 Nitrous Fumes
Nitrous fumes emanates mainly from exhaust of diesel automobiles and blasting of negative
oxygen balance explosives. Nitrous Fumes are rarely found in mine air, and it consists mainly
of nitric oxide and nitrogen dioxide. Nitrous fumes are very poisonous, the maximum tolerable
concentration for long exposure being 0.00025%, as accepted by ACGIH. Concentrations of
0.025 to 0.75 % are rapidly fatal. Man affected by nitrous fumes show immediate symptoms of
nausea cough, choking, perspiration and headache, but later develops serious bronchial trouble
such as bronchitis and bronchopneumonia, which may prove fatal within 48 hours. It has been
claimed by Canadian investigators that small quantities of Nitrous fumes stimulate the
development and growth of silicosis in dusty atmosphere. In Indian mines a tolerable
concentration of Nitrous fumes is taken as 0.0005 %.
3.2.2 Sulphur di-oxide
Sulphur dioxide is also produced from diesel exhaust and blast fumes. Sulphur dioxide is an
irritant gas that is removed by the nasal passages. Moderate activity levels that trigger mouth
breathing, such as a brisk walk, are needed for sulphur dioxide to cause health effects in most
people. People with asthma who are physically active outdoors are most likely to experience
15
the health effects of sulphur dioxide. The main effect, even with very brief exposure (minutes),
is a narrowing of the airways (called bronchoconstriction). This may be accompanied by
wheezing, chest tightness, and shortness of breath, which may require use of medication that
opens the airways.
Symptoms increase as sulphur dioxide levels or breathing rate increases. When exposure to
sulphur dioxide ceases, lung function typically returns to normal within an hour, even without
medication. At very high levels, sulphur dioxide may cause wheezing, chest tightness, and
shortness of breath even in healthy people who do not have asthma.
Long-term exposure to sulphur dioxide may cause respiratory symptoms and illness, and
aggravate asthma. People with asthma are the most susceptible to sulphur dioxide. However,
people with other chronic lung diseases or cardiovascular disease, as well as children and older
adults, may also be susceptible to these effects.
3.2.3 Hydrogen sulphide
Also known as stink damp, it smells like rotten egg and has a sweetish taste. It is poisonous in
nature, even more than CO, and the allowable maximum concentration for prolonged exposure
is 0.001% as recommended by ACGIH, the symptoms being irritation and inflammation of the
eyes and irritation of respiratory tracts. An exposure for an hour to a concentration of 0.02 to
0.03 % causes marked symptoms, while an exposure to a concentration of .05 to .07 % leads to
serious poisoning in 30 minutes to 1 hour. A concentration of 0.1 to 0.3 % causes rapid
paralysis of the respiratory centre leads to asphyxia and death.
3.2.4 Carbon monoxide
CO is produced from blast fumes, diesel exhaust and surface mine fires. Also known as white
damp, it is colourless, odourless gas slightly lighter than air. CO is deadly poisonous gas,
because the haemoglobin in the blood has 250 to 300 times greater affinity to CO than for O2.
Thus if CO is breath in large quantities for sufficiently long time, due to lack of oxygen, the
brain tissues get damaged. After long exposure the blood cells also get damaged, as a result the
patient suffers from headache, nausea, overstraining of the heart, mental disorder, loss of
memory, paralysis, temporary blindness, etc. leading to unconsciousness. A concentration
above 0.01 % for a long time causes a chronic poisoning with a slight headache resulting
exertion, while 0.3 to 0.4% may be fatal in a few minutes.
16
Chapter 4
AIR SAMPLING TECHNIQUES
Basic sampling methods
Air sampling and analysis methods as recommended by CPCB
4. AIR SAMPLING TECHNIQUES
4.1 Basic Sampling methods
Basically there are six air sampling methods which are:
4.1.1 Filter Sampling Inhalable (Total) Dust
Air is drawn through a filter paper, the paper traps the solid particulate e.g. dust, aerosols &
fibres. Gravimetric analysis is usually used to measure results (i.e. by measuring the weight
gained by the filter). Further analysis can be carried out on the filter to identify the specific
chemicals captured.
4.1.2 Sorbent Sampling
Sorbents are normally contained in a small glass tube with sealed ends. Air is drawn through
the sorbent, which captures molecules of the gas or vapour to be sampled. The trapped
contaminants are released using solvent washing or heat to a gas chromatograph (GC) for
analysis. One of the best known sorbents is charcoal.
4.1.3 Sampling Respirable Dust
The I.O.M. Sampler with a foam plug placed in the cassette inlet is capable of sampling
respirable dust. The specific foam separates the respirable fraction, which is collected on the
filter, from other particulate matter sizes.
4.1.4 Bag Sampling
Particularly suitable for ''grab'' or Short Term Samples (STS), the air is passed through the
pump into a special plastic bag. Alternative methods of filling a bag without passing air
through a pump can also be used. The bag, containing a relatively large volume of sampled
atmosphere is then taken to the laboratory for analysis.
4.1.5 Filter Sampling Respirable (Alternative Method)
The Cyclone Sampler uses a filter contained in a cassette, which separates out the respirable
fraction of dust in the sample.
4.1.6 Impinger/Bubble Sampling
Air drawn into the impinger is forced through a nozzle, which is covered with a liquid such as
high purity water. The pollutants dissolve in the liquid media and is subsequently analysed,
usually by colorimetric techniques of detection.
18
4.2GRAVIMETRIC SAMPLING
In this method of sample air is passed through a filter, the filter or other sampling collector is
weighed to determine the amount the particulate matter collected. This is a non-specific
technique. All material collected on the filter is included, although some of them may not be
the contaminant of interest. While most contaminants are determined by other methods that
give quantitative analysis of the compound in the air sample, material such as wood dust, coal
dust, etc. are still measured gravimetric element.
4.2.1 PM10 and PM2.5 Samplers of High volume type
For PM10 assessment, traditional gable roof of the high volume sampler is replaced by an
impactor design size-select inlet. For the impaction design the air sample entering the
symmetrical hood is deflected upward into a buffer chamber. The buffer chamber is evacuated
at a rate of 68 m3 per hour via multiple circular nozzles. The entering particulate matters get
accelerated as they pass through the nozzle to an impaction chamber; this process helps the
particulate matter to gain some momentum and thus particulate matters having diameter larger
then inlet 10μm cut design impact the surface of the impaction chamber. Small particulate
matters rise through the impactor chamber at speeds slow enough to minimise re-entrainment
of the already impacted particles and then pass through multiple bent tubes to high volume
sampler’s filter where they are collected.
The second size select design of PM10 measurement is ‘cyclone inlet’. Here omnidirectional
cyclone is used for fractionation in the inlet allowing particulate matters to enter from all
angles of approach. In the inlet, an angular velocity component is added to the sample air and
the particulate matters contained in it by a series of evenly spaced vanes. Larger particulate
matter removal occurs in the inner collection tube. This tube incorporates a perfect absorber
which is usually an oiled surface to eliminate bouncing of particulate matters. The sample flow
then enters the intermediate tube where the trajectory of the particulate matters is altered to an
upward direction. An additional turn is added to change the flow to a downward direction to
allow the remaining particulate matters to deposit on a filter for subsequent analysis. As with
the impaction inlet control of air velocities in cyclonic inlet, it is critical to maintain the correct
particulate matter size cut point. It is critical to maintain correct design volumetric flow
through the inlet.
19
4.2.2 Personal samplers for PM2.5 and PM10 particulate matter sampling
These versions of air samplers are lightweight type for collecting air borne particulate matters
in the PM2.5 and PM10 size range. These are frequently used to provide a measure of air borne
particulate matters concentration for studying potential health impacts of dust particulate
matters in the ambient environment.
The aerosol sample enters the sampler through multi nozzle single stage impactors to remove
large particulate matters having aerodynamic equivalent diameter larger than 2.5um and 10um.
Particulate matters having diameter smaller than the impactor cut size are collected on a 37mm
diameter filter of choice. The collected particulate matter can be analysed gravimetrically to
get air borne particulate matter’s mass or analysed for specific chemical compounds.
Features:
Light-weight personal samplers with single stage impactors.
Selective impactor cut-point of 2.5 µm or 10 µm.
Can be operated with a personal sampling pump
Applications:
o Personal dust sampling for exposure assessment.
o Ambient air pollution studies.
o Ambient air quality assessment.
o Personal sampling for industrial hygiene applications.
20
Fig 4.1: Photographic view of PM10 sampler
21
4.3 AIR SAMPLING AND ANALYSIS METHODS AS RECOMMENDED BY CPCB
4.3.1 Guidelines for sampling and analysis of particulate matter (PM 10) in ambient air
(gravimetric method)
PM10refers to fine particulate matters that are 10micrometres (μm) or smaller in diameter.
4.3.1.1 Standard
Table 4.1: National ambient air quality standard for Particulate Matter PM 10
Pollutant
Time weighted
Average
Industrial/Residential EcologicallySensitive
Area
Area
PM10 (μgm/m3)
Annual
60
60
24 Hours
100
100
4.3.1.2 Principle of the method
Air is drawn through a size-selective inlet and through a 20.3 X 25.4 cm (8 X 10 in) filter at a
flow rate, which is typically 1132 L/min. Particulate matters with aerodynamic diameter less
than the cut-point of the inlet are collected by the filter. The mass of these particulate matters is
determined by the difference in filter weights prior to and after sampling. The concentration of
PM10 in the difference of the mass divided by the total volumetric flow.
Designated size range is calculated by dividing the weight gain of the filter by the volume of
air sampled.
4.3.1.3 Instrument/Equipment
The following items are necessary to perform the monitoring and analysis of Particulate Matter
PM10 in ambient air:
·
Analytical balance
·
Sampler : High Volume Sampler with size selective inlet for PM10 and
automatic volumetric flow control
·
Calibrated flow-measuring device to control the airflow at 1132 l/min.
·
Top loading orifice kit.
4.3.1.4Sampling
Field Sampling - Tilt back the inlet and secure it according to manufacturer's instructions.
Loosen the faceplate wing nuts and remove the faceplate. Remove the filter from its jacket and
centre it on the support screen with the rough side of the filter facing upwards. Replace the
22
faceplate and tighten the wing nuts to secure the rubber gasket against the filter edge. Gently
lower the inlet. For automatically flow-controlled units, record the designated flow rate on the
data sheet. Record the reading of the elapsed time meter. The specified length of sampling is
commonly 8 hours or 24 hours. During this period, several reading (hourly) of flow rate should
be taken. After the required time of sampling, record the flow meter reading, take out the filter
media from the sampler and put in a container or envelope.
Fig 4.2: Schematic PM10 Sampler (Cyclonic Inlet)
4.3.1.5 Calibration
Periodical calibration of the sampler is being done by Orifice Transfer Standard. The PM10
sampler calibration orifice consists of a 3.175 cm (1.25 inch) diameter hole in the end cap of
7.62 cm (3 inch) diameter by 20.3 cm (8 inch) long hollow metal cylinder. This orifice is
mounted tightly to the filter support in place of the inlet during calibration. A small tap on the
side of the cylinder is provided to measure the pressure drop across the orifice. A flow rate of
1132 L/min through the orifice typically results in a pressure difference of several inches of
water. The relationship between pressure difference and flow rate is established via a
calibration curve derived from measurements against a primary standard such as a Roots meter
at standard temperature and pressure. Flow resistances that simulate filter resistances are
introduced at the end of the calibrator opposite the orifice by a set of perforated circular disks.
23
4.3.1.6 Calculation
PM10 (μgm/m3) = (Wf – Wi) x 106 / V
Where,
o PM10 = Concentration of PM10in μgm/m3
o Wf = Initial weight of filter in gm
o Wi = Initial weight of filter in gm
o 106 = Conversion of gm to μgm
o V = Volume of air sampled in m3
4.3.1.7 Quality Control
Quality Control (QC) is the techniques that are used to fulfil requirements for quality. The QC
procedures for the air sampling and monitoring sections of this protocol include preventative
maintenance of equipment, calibration of equipment, analysis of field blanks and lab blanks.
4.3.2 Guidelines for sampling and analysis of particulate matter (PM 2.5) in ambient air
(gravimetric method)
PM2.5 refers to fine particulate matters that are 2.5 micrometres (μm) or smaller in diameter.
4.3.2.1Standard
Table 4.2: National ambient air quality standards for Particulate Matter PM 2.5
Pollutant
PM2.5 (μgm/m3)
Time weighted
Average
Industrial/Residential
Area
Ecologically
Annual
40
40
24 Hours
60
60
Sensitive Area
4.3.2.2Principle
The electrically powered air sampler draws ambient air at a constant volumetric flow rate (16.7
lpm) maintained by a mass flow / volumetric flow controller coupled to a microprocessor into
specially designed inertial particulate matter-size separator (i.e. cyclones or impactor) where
the suspended particulate matter in the PM2.5 size ranges is separated for collection on a 47 mm
polytetrafluoroethylene (PTFE) filter over a specified sampling period. Each filter is weighed
before and after sample collection to determine the net gain due to the particulate matter. The
mass concentration in the ambient air is computed as the total mass of collected particulate
24
matters in the PM2.5 size ranges divided by the actual volume of air sampled, and is expressed
in μgm/m3. The microprocessor reads averages and stores five-minute averages of ambient
temperature, ambient pressure, filter temperature and volumetric flow rate. In addition, the
microprocessor calculates the average temperatures, pressure, and total volumetric flow for the
entire sample run time and the coefficient of variation of the flow rate.
4.3.2.3 Sitting Requirements
Samplers should be sited to meet the goals of the specific monitoring project. For routine
sampling to determine compliance with the National Ambient Air Quality Standards
(NAAQS), sampler sitting is described in CPCB guidelines shall apply. The monitoring should
be done outside the zone of influence of sources located within the designated zone of
representation for the monitoring site. Height of the inlet must be 3–10 m above the ground
level and at a suitable distance from any direct pollution source including traffic.
Large nearby buildings and trees extending above the height of the monitor may create
barriers or deposition surfaces for PM. Distance of the sampler to any air flow obstacle i.e.
buildings, must be more than two times the height of the obstacle above the sampler. There
should be unrestricted airflow in three of four quadrants. Certain trees may also be sources of
PM in the form of detritus, pollen, or insect parts. These can be avoided by locating samplers
by placing them >20 m from nearby trees. If collocated sampling has to be performed the
minimum distance between two Samplers should be 2 m.
4.3.2.4 Apparatus and Materials
Sampling equipment designated as FRM (Federal Reference Method) or FEM (Federal
Equivalent Method)
Electronic microbalance with a minimum resolution of 0.001 mg and a precision of
±0.001 mg, supplied with a balance pan. The microbalance must be positioned on a
vibration-damping balance support table.
Non-serrated forceps for handling filters. Non-metallic, non-serrated forceps for
handling weights.
47 mm Filter: Teflon membrane, 46.2 mm effective diameter with a polypropylene
support ring or filters.
Filter support cassettes and covers.
Filter equilibration racks.
Impactor oil/grease.
25
4.3.2.5 Procedure
The procedure of the PM2.5sampling is same as that of PM10 sampling.
4.3.2.6Calculation and Reporting of Mass Concentrations
The equation to calculate the mass of fine particulate matter collected on a Teflon filter is as
below:
M2.5 = (Mf – Mi) mg x 103 μgm
Where,
M2.5 = total mass of fine particulate collected during sampling period (μgm)
Mf = final mass of the conditioned filter after sample collection (mg)
Mi = initial mass of the conditioned filter before sample collection (mg)
103 = unit conversion factor for milligrams (mg) to micrograms (μgm)
Field records of PM2.5 samplers are required to provide measurements of the total volume of
ambient air passing through the sampler (V) in cubic meters at the actual temperatures and
pressures measured during sampling.
Use the following formula if V is not available directly from the sampler:
V = Qavg x t x 10-3 m3
Where,
·
V = total sample value (m3)
·
Qavg = average flow rate over the entire duration of the sampling period (L/min)
·
t = duration of sampling period (min)
·
103 = unit conversion factor for litres (L) into cubic meters (m3)
The equation given below can be used to determine PM2.5 mass concentration:
PM2.5 = M2.5 / V
Where,
PM2.5 = mass concentration of PM2.5 particulates (μgm/m3)
M2.5 = total mass of fine particulate collected during samplingperiod (μgm)
V = total volume of air sampled (m3)
26
Chapter 5
AIR QUALITY MODELLING
5. AIR QUALITY MODELLING
It is the mathematical simulation of how air pollutants diffuse in the ambient atmospheric
conditions. Air quality modelling is performed with computer programs that repeat and solve
the mathematical equations and algorithms which simulate the pollutant dispersion. The
dispersion models are used to estimate or to predict the down air concentration of air pollutants
or toxins produced from sources such as industrial plants, mines, vehicular traffic or
inadvertent chemical releases.
The dispersion models vary from each other depending on the mathematical algorithm used to
develop the model, but all require the input of data that may include:
Meteorological conditions such as air speed and direction, the quantity of atmospheric
turbulence (as characterized by what is called the "stability class"), the ambient air
temperature, the height to the bottom of any inversion aloft that may be present, cloud
cover and solar radiation.
Source term (the concentration or quantity of toxins in emission or accidental release
source terms) and temperature of the material.
Emissions or release parameters that influence such as source location and height, type
of source (i.e., fire, pool or vent stack) and exit velocity, exit temperature and mass
flow rate or release rate.
Terrain heights at the source location and at the receptor location(s), such as nearby
homes, schools, businesses and hospitals.
The location, height and width of any obstructions (such as buildings or other
structures) in the path of the released gaseous plume, surface roughness or the use of a
more general parameter “rural” or “city” terrain.
5.1 GAUSSIAN PLUME MODEL
The Gaussian plume model of dust dispersion is a mathematical model that is used in case
point source emitters, such as dust generating sources. Intermittently, this model will be
applied to non-point source emitters, such as dust exhaustion from automobiles in mines.
One of the main assumptions of this model is that over short periods of time (e.g. few hours)
steady state conditions exist with regard to air pollutant emissions and meteorological changes.
Air pollution is characterized as an idealized plume coming from the peak of a stack of some
28
height and diameter. One of the major calculations in this model is the effective stack height.
As the gases are heated in the stack, the hot plume (dust) will be thrust upward some distance
above the top of the stack: the effective stack height. For the model, we need to be able to
determine this vertical displacement, which depends on the stack dusty air exit velocity and
temperature, and the temperature of the neighbouring air.
Once the plume has reached its effective stack height, dispersion of dust will begin in three
dimensions. Dispersion in the downwind direction is a function of the mean wind speed
blowing across the plume in this direction. Dispersion in the cross-wind direction and in the
vertical direction will be according to the Gaussian plume equations of lateral dispersion.
Lateral dispersion relies on a value known as the atmospheric condition. It is the measure of
the relative stability of the neighbouring air. The model assumes that dispersion in these two
dimensions will take the outline of a normal Gaussian curve, with the greatest concentration in
the middle of the plume.
c, concentration
q, emission rate
σ values represent diffusion along the appropriate axes
y, horizontal distance off plume axis
z, height
h, emission height
In order for a plume to be modelled using the Gaussian distribution the subsequent assumption
must be made:
The plume spread has a normal distribution
The emission rate (q) is constant and continuous
Wind speed and direction is uniform
Total reflection of the plume takes place at the surface
The terrain is relatively flat, i.e., no crosswind barriers
29
Fig 5.1: Co-ordinates of a Gaussian plume
Plume Behaviour: The mixing of ambient air into the plume is called entrainment. As the
plume entrains air into it, the plume diameter grows as it travels downwind. A combination of
the gases' momentum and buoyancy causes the gases to rise. This is referred to as plume rise
and allows air pollutants emitted in this gas stream to be lofted higher in the atmosphere.
The final height of the plume, referred to as the effective stack height (H), is the sum of the
physical stack height (H ) and the plume rise (Δh). Plume rise is actually calculated as the
distance to the imaginary centreline of the plume rather than to the upper or lower edge of the
plume.
30
Fig 5.2: Gaussian plume from a stack
The Briggs’ plume rise formula (1969) is as follows:
∆h =
Where:
Δh = plume rise (above stack)
F = Buoyancy Flux
ū = average wind speed
x = downwind distance from the stack
g = acceleration due to gravity (9.8 m/ 2)
V = volumetric flow rate of stack gas
= temperature of stack gas
= temperature of ambient air
[Ref: Briggs, G.A., "Plume Rise", USAEC Critical Review Series, 1969]
Plume Stability:
Shapes of plumes depend upon atmospheric stability conditions which depend on
Environmental Lapse rate (ELR) and Dry Adiabatic Lapse Rate (DALR). If,
ELR > DLR, atmosphere is stable
ELR >> DLR ,very stable atmosphere
ELR = DALR , atmosphere is neutral
ELR < DLR , atmosphere is unstable
31
5.2 METEOROLOGICAL PARAMETERS THAT EFFECTS THE AIR QUALITY
MODELLING
Given below is a list of some meteorological parameters:
5.2.1 Cloud cover: Cloud cover (also known as cloudiness, cloud amount) refers to the portion
of the sky sheltered by the clouds when observed from a precise location. It is articulated in
units of either in oktas (or eighths of the sky) or in tenths. It is because they are calculated with
an okta grid. A value of 0 refers to clear sky, while 8 oktas or 10 on the decimal scale
exemplify total overcast. Each okta characterizes one eighth of the sky covered by cloud as
detected.
5.1.2 Global Horizontal radiation: Total solar radiation; the sum of direct, diffuse, and
ground-reflected radiation; nevertheless, because ground reflected radiation is usually
inconsequential compared to direct and diffuse, for all applied purposes global horizontal
radiation is said to be the sum of direct and diffuse radiation only. Global horizontal radiation
is the sum of both the direct and diffuse components as measured incident on a flat horizontal
plane. It is thus the sum of the direct horizontal and diffuse horizontal values.
5.1.3 Hourly Precipitation: Precipitation is calculated as the deepness to which a flat
horizontal surface would have been enclosed per unit time if no water were lost by runoff,
evaporation, or percolation. Depth is stated in inches or millimetres. Gauging precipitation
covers rain, hail, snow, rime, hoar frost and fog, and is conventionally measured using
numerous types of rain gauges such as the non-recording cylindrical vessel type or the
recording weighing type, float type and tipping-bucket kind.
5.1.4 Ceiling Height: Ceiling height is well-defined as the height-above-ground level of the
lowest broken or overcast layer. If the sky is totally covered, the height of the vertical visibility
(VV) is taken as the ceiling height. The height for the lowest broken or overcast layer is used
as the ceiling height.
5.1.5 Relative humidity: Relative humidity is a term used to describe the amount of water
vapour that exists in a gaseous mixture of air and water vapour.
5.1.6 Dry Bulb Temperature: The dry-bulb temperature is the temperature of air shown by a
thermometer freely unprotected to the air but safeguarded from radiation and moisture.
5.1.7 Wind Speed: It is the speed of wind, the movement of air or other gases in an
atmosphere.
32
5.1.8 Wind Direction: Wind direction is the direction from which a wind initiates. It is
typically described in cardinal directions or in azimuth degrees.
5.3 Preferred and recommended models
AERMOD - An atmospheric dispersion model based on atmospheric boundary layer
turbulence structure and scaling concepts, including treatment of multiple ground-level
and elevated point, area and volume sources. It handles flat or complex, rural or urban
terrain and includes algorithms for building effects and plume penetration of inversions
aloft.
It uses Gaussian dispersion for stable atmospheric conditions (i.e., low turbulence) and
non-Gaussian dispersion for unbalanced conditions (high turbulence). Algorithms for
plume depletion by wet and dry deposition are also included in the model. This air
model was in development for approximately 14 years before being officially accepted
by the U.S. - EPA.
CALPUFF - A non-steady-state puff dispersion model that simulates the effects of time
and space-varying meteorological conditions on pollution transport, transformation,
and removal. CALPUFF can be applied for long-range transport and for complex
terrain.
BLP - A Gaussian plume dispersion model designed to handle unique modelling
problems associated with industrial sources where plume rise and downwash effects
from stationary line sources are critical.
CALINE3 - A steady-state Gaussian dispersion model designed to define pollution
concentrations at receptor locations down air of highways located in relatively
uncomplicated terrain.
33
Chapter 6
AIR QUALITY ANALYSIS
Procedure and observations
Air quality index
AQI of some iron and manganese mines in Keonjhar district In Odisha
6. AIR QUALITY ANALYSIS
WHY KEONJHAR & SUNDARGARH DISTRICT IS SELECTED FOR AMBIENT
AIR ASSESSMENT?
The mineral resources of Orissa are distributed very unevenly. Most of the iron and manganese
ore is found in Sundargarh and Keonjhar district. So, all the large open cast metal mines are
located in this region. Due to the presence of large number of mines, there is a cumulative
impact of particulate matter pollution on the environment. Therefore a detailed study on
ambient air quality needs to be done on that area. Our studies spanned on mines namely, Joda
east iron ore mine, Khondbond iron and manganese mines, Jilling Langalota iron and
manganese mines, Raikela Tantra iron ore mines, Oraghat iron ore mines,etc. The study
included direct sampling in the field, data collection from EIA/EMP reports and SPCB,
Regional office, Rourkela.
6.1 PROCEDURE
The method that was used was according to the CPCB guidelines. The sampling instrument
was set on a stable and levelled ground, without any type of disturbances. In the core zone, the
sampler was located at an approximate distance of 40m from nearby constructions. The
sampler was placed 20 m away from the trees in buffer zone. Three populous locations were
selected lying within 10 km radius from the mine periphery, viz. Village Dengula, Tensa Town
and Village Bahamba.
The filter paper was properly conditioned before placing it on the filter cassette of the sampler.
Initial dry gas meter reading was noted. The suction pump was activated along with the timer.
A total duration of 8 hours was set for sampling. After the stipulated time, the sampling
instrument was stopped and the filter paper was retrieved. It was conditioned and sealed for
further investigation in laboratory.
6.2 OBSERVATIONS
Air quality data from mining areas of Keonjhar district were collected from some EIA/EMP
reports. Data were also collected from SPCB, Rourkela regional office. To verify the status of
air quality in field, measurement of air quality were done at Raikela-Tantra iron ore mines in
the month of December. Particulate matter samplers were used for the above purpose. The
gases collected at the mine sited were subsequently sent to the lab SPCB, Rourkela.
35
The analysis of sampled air quality data of Raikela Tantra iron mines in the Keonjhar district
has been presented in table given below:
Table 6.1: Sampled Air Quality data of ‘Raikela Tantra iron mines’.
LOCATION
Mines office area
Village Dengula
Tesnsa Town
Village Bahamba
PARAMETER
Results
Prescribed standard
UNIT
PM2.5
29
60
μgm/m3
PM10
82
100
μgm/m3
SO2
4
80
μgm/m3
NOx
9
80
μgm/m3
CO
0.1
4
mg/m3
PM2.5
30
60
μgm/m3
PM10
88
100
μgm/m3
SO2
4
80
μgm/m3
NOx
16
80
μgm/m3
CO
0.1
4
mg/m3
PM2.5
41
60
μgm/m3
PM10
97
100
μgm/m3
SO2
4
80
μgm/m3
NOx
9
80
μgm/m3
CO
0.1
4
mg/m3
PM2.5
27
60
μgm/m3
PM10
75
100
μgm/m3
SO2
4
80
μgm/m3
NOx
9
80
μgm/m3
CO
0.1
4
mg/m3
36
120
c 100
o
n
c 80
e
n
t 60
r
a
t 40
i
o
20
n
PM 2.5
PM 10
SO2
Nox
CO
0
Mine office area Village dengula
Tensa town
village bahamba
NAAQS
Fig. 6.1: PM Conc. in Raikela Tantra Iron ore Mine (Mining site)
Note: Concentration of PM10, PM2.5, SO2, and NOxin figure isμgm/m3 and that of CO is mg/m3
The analysis of sampled air quality data of different iron and manganese mines in the Keonjhar
district taken from EIA/EMP reports are presented in tables given below:
Table 6.2: Air quality of Khondbond iron and manganese mines (mining site)
Sampling date
PM2.5
PM10
unit
Oct -2011
28.7
49.2
μgm/m3
Nov-2011
30.6
51.2
μgm/m3
Dec-2011
31
51.3
μgm/m3
Jan-2012
30.9
51.3
μgm/m3
Feb-2012
34
53.9
μgm/m3
Mar-2012
35.3
55.9
μgm/m3
NAAQS
60
100
μgm/m3
37
120
100
80
PM2.5
Concentration 60
PM10
40
20
0
oct 11
Nov-11
Dec-11
Jan-12
Feb-12
Mar-12
NAAQS
Fig. 6.2: PM Conc. in Khondbond Iron & Manganese Mine (Mining site)
Table 6.3: Air quality of Khondbond iron and manganese mines (Near plant area)
Sampling date
PM2.5
PM10
Unit
Oct-11
32.9
54.7
μmg/m3
Nov-11
34.6
55.1
μmg/m3
Dec-11
34
54.9
μmg/m3
Jan-12
33.5
54
μmg/m3
Feb-12
36.2
56.9
μmg/m3
Mar-12
38.5
59
μmg/m3
NAAQS
60
100
μmg/m3
120
100
80
PM2.5
concentration 60
PM10
40
20
0
Oct-11
Nov-11
Dec-11
Jan-12
Feb-12
Mar-12
NAAQS
Fig. 6.3: PM Conc. in Khondbond Iron & Manganese Mine (Near plant area)
38
Table 6.4: Air quality of Joda east Iron ore mine (Mining area)
Sampling date
PM2.5
PM10
Unit
Apr-11
22.6
43.3
μmg/m3
May-11
21.3
41.6
μmg/m3
Jun-11
21.5
42
μmg/m3
Jul-11
22
42.8
μmg/m3
Aug-11
15
35.8
μmg/m3
NAAQS
60
100
μmg/m3
120
100
80
PM2.5
Concentration 60
PM10
40
20
0
Apr-11
May-11
Jun-11
Jul-11
Aug-11
NAAQS
Fig. 6.4: PM Conc. in Joda east Iron ore mine (Mining area)
Table 6.5: Air quality of Joda east Iron ore mine (Residential area)
Sampling date
PM2.5
PM10
Unit
Apr-11
12.4
32.3
μmg/m3
May-11
13.3
33.5
μmg/m3
Jun-11
13.3
33.6
μmg/m3
Jul-11
13.6
32.9
μmg/m3
Aug-11
8.8
29.4
μmg/m3
NAAQS
60
100
μmg/m3
39
120
100
80
PM2.5
Concentration 60
PM10
40
20
0
Apr-11
May-11
Jun-11
Jul-11
Aug-11
NAAQS
Fig. 6.5: PM Conc. in Joda east Iron ore mine (Residential area)
Table 6.6: Air quality of Jilling Langalota iron & manganese mine
Sampling date
05-03-2012
PM2.5
20
PM10
48
Unit
μmg/m3
06-03-2012
22
56
μmg/m3
12-03-2012
23
44
μmg/m3
13-03-2012
18
53
μmg/m3
19-03-2012
17
50
μmg/m3
26-03-2012
14
62
μmg/m3
NAAQS
60
100
μmg/m3
120
100
80
Concentration 60
PM2.5
40
PM10
20
0
Fig. 6.6: PM Conc. in Jilling Langalota iron & manganese mine
40
Table 6.7: Air quality of Bhulbeda iron ore mine
Station
Inside ML Area
PM2.5
42.4
PM10
56.65
Unit
μmg/m3
Within DLC Forest
40.05
52.1
μmg/m3
Bhulbeda village
44.1
57.05
μmg/m3
Hariharpur village
43
57.55
μmg/m3
Jaribahal village
47.3
62.4
μmg/m3
Sargitalia village
45.65
58.3
μmg/m3
Kankada village
42.15
56
μmg/m3
Daduan village
46.35
61
μmg/m3
NAAQS
60
100
μmg/m3
120
100
80
60
PM2.5
40
PM10
20
0
Fig. 6.7: PM Conc. in Bhulbeda iron mines
Table 6.8: Observed Air Quality data of ‘Oraghat Iron ore mines’ during 2009-2012
CORE ZONE
Year
Station Name
PM2.5
(μgm/
m3)
PM10
(μgm/m3)
SO2 (<value)
(μgm/m3)
NOx(μgm/
m3)
CO
(mg/m3)
2009
45
56.5
3.78
34
<0.1
2010
42.5
59
4.5
24
<0.1
22
67.5
5
22
<0.1
32.5
22
7
17
<0.1
2011
2012
Mines office
41
BUFFER ZONE
2009
38.5
20
1.78
25
<0.1
2010
32
29
4
15
<0.1
34
64
5
17
<0.1
38
24
7
13
<0.1
Oraghat village
2011
2012
2009
41
52.5
1.78
15.5
<0.1
2010
42.5
54
4.5
19.5
<0.1
24
71.5
4.5
27.5
<0.1
2012
38.5
20
6
22.5
<0.1
2009
38.5
80.5
3.28
22
<0.1
2010
41
52.5
3.28
15
<0.1
19.5
60
5.5
25.5
<0.1
38.5
25
4
18
<0.1
Malda village
2011
Sanindpur village
2011
2012
2009
51.5
81.5
4
17
<0.1
2010
49.5
-
4
18.5
<0.1
13.5
38.5
5
11.5
<0.1
2012
43
18
4
32.5
<0.1
NAAQS
60
100
80
80
4
Pureibahal
2011
Table 6.9: Recent Air Quality Data of different open cast metal mines obtained from
SPCB, Regional office, Rourkela.
Mine
Location
Parameter
Unit
Result
NAAQS
Near Crusher Area(25m
PM2.5
μgm/m3
49
60
PM2.5
μgm/m3
44
60
PM10
μgm/m3
86
100
PM10
μgm/m3
89
100
PM10
μgm/m3
82
100
from source)
Near Barsua valley(25m
from source)
Barsua iron mines
Near Crusher Area(25m
from source)
Near Barsua valley(25m
from source)
Nadidihi Iron and
Near Active Mining Area
42
Near Weigh Bridge
PM10
μgm/m3
89
100
Oraghat Iron
Near Active mining Area
PM10
μgm/m3
96
100
mines
Near Mining office Area
PM10
μgm/m3
80
100
KantherKoira
Near Active mining Area
PM10
μgm/m3
54
100
Near Main Gate
PM10
μgm/m3
48
100
Near 650 TPH iron ore
PM10
μgm/m3
92
100
Manganese mines
Manganese mines
Narayanaposhi
Iron and
crusher Area
Manganese mines
Near Active mining Area
PM10
μgm/m3
70
100
TRB iron ore
Near iron Crushing Area
PM10
μgm/m3
92
100
mine
Near Active mining Area
PM10
μgm/m3
80
100
Bandhal
Near Weigh Bidge
PM10
μgm/m3
74
100
Manganese Mines
Near Quarry Area
PM10
μgm/m3
86
100
6.3 Air quality index
Air quality index (AQI) is a number used by government agencies to communicate to the
public how polluted the air is currently or how polluted it is forecast to become. As the AQI
increases, an increasingly large percentage of the population is likely to experience
increasingly severe adverse health effects. Different countries have their own air quality
indices which are not all consistent. Different countries also use different names for their
indices such as Air Quality Health Index, Air Pollution Index and Pollutant Standards Index.
The United States Environmental Protection Agency (EPA) has developed an index which they
use to report daily air quality. This AQI is divided into six categories indicating increasing
levels of health concern. An AQI value over 300 represents hazardous air quality whereas if it
is below 50 the air quality is good.
The air quality index is a piecewise linear function of the pollutant concentration. At the
boundary between AQI categories, there is a discontinuous jump of one AQI unit.
43
To convert from concentration to AQI this equation is used.
I=(
where:
= the (Air Quality) index,
= the pollutant concentration,
= the concentration breakpoint that is ≤
,
= the concentration breakpoint that is ≥
,
= the index breakpoint corresponding to
= the index breakpoint corresponding to
,
.
EPA's table of breakpoints for PM2.5 is:
Category
0
15.4
0
50
Good
15.5
40.4
51
100
Moderate
40.5
65.4
101
150
Unhealthy for Sensitive Groups
65.5
150.4
151
200
Unhealthy
150.5
250.4
201
300
Very Unhealthy
250.5
350.4
301
400
Hazardous
350.5
500.4
401
500
Hazardous
44
6.4 Air quality index of some iron and manganese mines
Table 6.10:Joda East iron ore mine, M/s Tata Steel Ltd.
(Half yearly compliance report for the period: April to September’ 11)
(Near Mining Area)
SAMPLING DATE
PM 2.5
AQI
REMARKS
Apr-11
22.6
64.97
Moderate
May-11
21.3
62.41
Moderate
Jun-11
21.5
64.8
Moderate
Jul-11
22
63.79
Moderate
Aug-11
15
48.7
good
Sep-11
13.5
43.83
good
(Near Residential Area)
SAMPLING DATE
PM 2.5
AQI
REMARKS
Apr-11
13.3
43.18
good
May-11
12.6
40.91
good
Jun-11
8.8
28.57
good
Jul-11
7.6
24.67
good
Aug-11
12.4
40.26
good
Sep-11
13.3
43.18
good
Table 6.11 Khondbond iron and manganese mines, M/s Tata Steel Ltd.
(Half yearly compliance report for the period: October 11 to march 12)
SAMPLING DATE
PM 2.5
AQI
REMARKS
Oct-11
32.9
85.24
Moderate
Nov-11
34.6
88.58
Moderate
Dec-11
34
87.4
Moderate
Jan-12
33.5
86.42
Moderate
Feb-12
36.2
91.73
Moderate
Mar-12
38.5
96.26
Moderate
45
Table 6.12: Bhulbeda iron ore mines, M/s Mineral Trading Syndicate
(Executive summary report on EIA/EMP of year 2011)
STATION CODE
SAMPLING DATE
PM2.5
AQI
REMARKS
Inside ML Area
1/9/11 TO 30/11/11
42.4
104.73
Within DLC Forest
1/9/11 TO 30/11/11
40.05
99.31
unhealthy for sensitive
groups
Moderate
Bhulbeda village
1/9/11 TO 30/11/11
44.1
108.08
Hariharpur village
1/9/11 TO 30/11/11
43
105.91
Jaribahal village
1/9/11 TO 30/11/11
47.3
114.38
unhealthy for sensitive
groups
unhealthy for sensitive
groups
unhealthy for sensitive
groups
Table 6.13: Jilling Langalota iron and manganese mines, M/s Essel Mining & Industries
Ltd.
(Executive summary report of draft EIA of year 2012)
MONTH
January
February
SAMPLING DATE
PM2.5
AQI
REMARKS
02-01-2012
39
97.24
Moderate
03-01-2012
25
69.69
Moderate
09-01-2012
21
61.82
Moderate
10-01-2012
23
65.76
Moderate
16-01-2012
24
67.72
Moderate
17-01-2012
25
69.69
Moderate
23-01-2012
29
77.56
Moderate
24-01-2012
31
81.5
Moderate
06-02-2012
22
63.79
Moderate
07-02-2012
23
65.76
Moderate
13-02-2001
25
69.69
Moderate
14-02-2012
26
71.66
Moderate
20-02-2012
21
61.82
Moderate
27-02-2012
19
57.88
Moderate
46
March
05-03-2012
20
59.55
Moderate
06-03-2012
22
63.79
Moderate
12-03-2012
23
65.76
Moderate
13-03-2012
15
55.91
Moderate
19-03-2012
17
53.95
Moderate
26-03-2012
14
48.04
Moderate
47
Chapter 7
DISCUSSION AND CONCLUSION
Measures of Dust Control
7. DISCUSSION AND CONCLUSION
7.1 DISCUSSION
Mining of ore impacts the air quality to a significant extent. Air Quality study was carried out
in some of the metal mining areas of Keonjhar and Sundargarh district. These two districts
have a number of Iron, Manganese, Limestone, Dolomite and Chromite mines. There has been
a large number of complaints from the residents of nearby villages regarding the high level of
particulate matter pollution. This has also been highlighted in different newspaper reports.
Therefore a study of the air quality at some of the locations at these two districts was carried
out. Since the area is too vast, air quality data was collected from the EIA reports and SPCB
Rourkela Regional Office. In addition to this, air sampling was carried out in December 2012
with the help of EnviroTech PM 2.5 and PM10 (model no. APM 460 NL) samplers. In addition,
the air quality index (AQI) of all the locations have been calculated to make a comparison of
air quality in different locations and accordingly recommend suitable remedial measures. The
summary of the findings are presented here.
It was observed that the concentration of gases, viz. CO, SO2 and NOx were negligible in all
cases. Therefore, emphasis has been given on particulate matter concentration in this study.
Raikela Tantra iron ore mines were the site where we went to take air quality observations of
our own. In the four locations where we took sampling data, village Bahamba was found to be
least polluted with PM2.5 and PM10 values lowest among all the locations. This may be due to
distance of the sampling location from the actual mine site and the presence of a surrounding
green belt. It is observed from table 6.1 and fig 6.1 that Tensa town was the most polluted of
the four locations as the particulate matter values are close to the NAAQS standards. The AQI
of Tensa town was unhealthy to sensitive groups due to its high particulate matter content
whereas for other three locations the AQI was Moderate suggesting that the air quality is just
acceptable.
In the Khondbond iron and manganese mines, from table 6.2 and fig 6.2, it can be observed
that from October to march -2011, the particulate matter concentration is slightly increasing
with lowest value in October and highest value in March for both PM 10 and PM2.5. These
phenomena can be attributed to seasonal variation of PM concentration. The overall air quality
index was moderate which is depicted in table 6.11.
49
In both mining and residential areas of Joda east iron ore mine, the PM2.5 and PM10
concentration has a decreasing trend throughout the sampling period from April-11 to August11 depicted in Table 6.4, 6.5 and fig 6.4 and 6.5. The concentration of dust particles were
much below the NAAQS standard indicating AQI (table 6.10) of the mine is good for both the
sampling areas. In rainy months, the PM concentration was found to be least.
In Jilling Langalota iron and manganese mines, sampling was done throughout the month of
March by SPCB. It was found that the concentration of PM2.5 decreased during the sampling
period but PM10 concentration showed no specific trend of change as depicted in figure 6.6.
AQI of the mine area was found to be moderate as shown in table 6.13
For the air quality assessment in Bhulbeda iron ore mines, air sampling was done in eight
nearby locations and the result is shown in table 6.7 and figure 6.7. The PM2.5 and PM10
concentration are constant but are relatively higher than any other mines. Village Daduan has
the highest value of both PM2.5 and PM10 concentration. Hence the AQI in table 6.12 depicts
that the air quality is unhealthy to sensitive groups.
The yearly air quality data (2009-2012) of ‘Oraghat iron ore mines’ is shown in Table 1. Here
we observe that PM2.5 concentration is remaining constant for the whole period. PM10
concentration is at its peak in the year 2009-2011 but it reduced drastically to around half the
previous values. CO concentration is remaining below 0.1 mg/m3 in the whole time frame. The
NOx and SO2 concentration is well within the NAAQS prescribed limits and there is no pattern
of change.
The recent air quality data collected from a group of iron and manganese mines taken from
SPCB, Regional office, Rourkela is given in the table 6.9. It can be observed that in all mines,
PM concentration is alarmingly high near crusher areas ranging from 80-92µgm which is just
below NAAQS standard. Therefore it can be suggested that appropriate dust suppression
measures need to be implemented near the crusher areas such as application of foaming and
wetting agents and formation of green belt.
The observed decrease in the concentration of particulate matter and other toxic gasses is due
to the successful application of modern dust control methods which include dry and wet
methods, and adoption of newer technology for reducing gas emission. The most common one
that is used in those mines is the fixed and mobile water sprinkler system. Regular dust
cleaning practises are being adopted for better air quality management.
50
7.1.1 Measures of Dust Control
From the above discussion it is clear that air pollution due to different gases is not a serious
concern in the study area. However, particulate matter is a matter of concern, even though
they are within prescribed limits at the moment. Since, there are a number of mines in cluster,
the cumulative impact could be serious and is yet to be studied. It is noticed that majority of
the concern is the particulate matter pollution caused by transportation, crushing and grinding
operations. Some of the latest technologies which could be utilised to mitigate such challenges
in mines are:
Housekeeping: Bad road conditions and overloading of vehicles lead to spillage, and the
material spilled is subject to re-entrainment which leads to production of dust. Overloading of
trucks/dumpers should be strictly prohibited to prevent spillage and regular clearing of roads
should be carried out. If possible the trucks/dumpers should be covered to avoid spillage. The
spilled material should be removed periodically. Further dust suppression can be carried out by
spraying water using fixed or mobile sprinklers.
Fig 7.1: Static water sprinkling system in an Australian opencast mine
(http://australianminingreview.com.au/central-control-system-making-dust-controleasy/)
51
With frequent watering, newly spilled material is moistened at close intervals. When chemicals
are applied with infrequent watering, newly spilled material could go for long periods before
being moistened. Therefore, in mines where spillage cannot be controlled, watering alone is
better for dust control.
Black topping of permanent roads: Haul roads and light vehicle roads having a reasonably
long life (say 10 to 15 years) can be metalled and topped with asphalt or bitumen to provide a
better road surface and to reduce the generation of fugitive dust.
Binding and agglomerating agents: Binding agents are used when dust control by water is
not feasible. They are classified as humectants and adhesive formulations. Humectants,
maintains surface moisture to keep the dust wet, like calcium and magnesium chloride.
Adhesives, maintain fine dust particle agglomerate in absence of surface moisture, like oils and
polymers. The performance of binding agent depends on physical and chemical properties of
substrate, the application technique and storage and handling conditions (Rosbury and Zimmer,
1983). For example, EK35, is synthetic resin binder which captures fines and keep them locked
in surface, it works effectively on all types of soil and aggregates and are biodegradable in
nature (Midwest Industrial Supply Inc., 2010).
Wetting agents: Wetting agents are surfactant formulations that improve the ability of water
to adhere and spread on dust particles thereby increasing the bulk density of particle and leads
to agglomeration. These are mainly useful in unloading and conveying operations.
Considerable research has been done on the use of wetting agents and has found to have
increased dust control effectiveness ranging from 0-25% (Chander et al., 1991).For Example3M Dust suppressant LSP-1000C is water soluble, alcohol free formulation. It penetrates and
agglomerates fine dust particles; dries to form a thin, flexible film that suppresses dust for
extended periods.
Surfactants are sometimes used in wet spray applications because they lower the surface
tension of the water solution, which has the following effects:
Reduced droplet diameter.
An increase in the number of droplets for a given volume of water; and
A decrease in the contact angle defined as the angle at which a liquid meets a solid surface.
Despite the effectiveness of chemical additives, it must be noted that they are not often
used in the metal/non-metal mining industry based upon several limitations.
52
Surfactants are significantly more expensive than a typical water application. They can
alter the properties of the mineral or material being processed. Surfactants have limited
usefulness in the metal/non-metal mining industry, as opposed to in the coal industry, since
ore or stone are much easier to wet than is coal due to its hydrophobic nature.
The effectiveness of chemical additives depends on:
1. the type of wetting agent
2. hydrophobic nature of the mineral particles
3. dust particle size
4. dust concentration
5. water pH
6. minerals present in the water used
Examples:
3M™ SDS4 Polymeric Dust Suppression
3M™ SDS-2 Surfactant Based Dust Suppression
Enviroseal LDC PLUS 12™
Foam suppression: Foaming agents are high foaming surfactants containing wetting and
binding agents which convert water and compressed air mixture into foam. The foam
suppression technology, gives a heavy spray of foam which blankets the dust before a dust
cloud can rise. It works by reducing the surface tension of dust particles. This minimizes the
amount of water used. Foams used for dust control are dry, stable, small-bubbled and
consistent. Use of foam has better efficiency as compared to water as the foam liquid wets and
agglomerates fine dust particle, it can reduce 20-60% more dust as compared to water. These
dust particles penetrate the foam bubble, causing the bubble to break and wet the particles.
Large particles are not a problem, as the small micro-foam bubbles wet the larger particles
without affecting the bubble. Micro-foam can be injected at material transfer points in order to
obtain optimum dust control, requiring approximately 0.4 gallons of water for each ton of bulk
material treated for dust control.
It is effective as it use lesser water as compared to that used in water sprays. Use of foam has
increased dust reduction (Mukherjee and Singh, 1984). They can be used at transfer points and
crushing operations. It provides best way of suppressing dust with minimum addition of
moisture. The major drawback in use of this system is its high cost.
53
Fig 7.2: Application of foam near crusher area
(Ref: http://www.envirofloeng.com/foamexample.html)
Micro-foam is another method for controlling dust from fugitive dust sources, particularly
load-out stockpiles. Typical foams used in fire fighting (large 5-mm bubbles) are not effective
at dust control, unlike micro-foam (small <100-µm bubbles). Micro-foam is stated to be better
than water for dust suppression, because the water droplets, to be effective for dust control,
must be similar in size to the dust particles which micro-foam can replicate. In addition, the
velocity of the water must be high to break its surface tension upon contact with the dust
particle. Highly concentrated foam dust control agents are formulated to produce resilient, low
surface tension foam for the control of fugitive dust throughout the plant material handling
system. The most cost-effective performance generally occurs in waters containing total
hardness between 100 to 1000 ppm (mg/L).
Dust hood/collectors: Dust collection hoods and flanges capture dust at the source and
provide easy connection to the duct system. Most Dust Hoods and Flanges can be double faced
taped to a machine cabinet or drilled and mounted as need. Dry collection can be performed
most efficiently by maintaining an appropriate dust collector to bailing airflow ratio.
Dust collection systems work on the basic formula of capture, convey and collect.
First, the dust must be captured. This is accomplished with devices such as capture hoods
to catch dust at its source of origin. Many times, the machine producing the dust will have
a port to which a duct can be directly attached.
Second, the dust must be conveyed. This is done via a ducting system, properly sized and
manifold to maintain a consistent minimum air velocity required to keep the dust in
suspension for conveyance to the collection device. A duct of the wrong size can lead to
material settling in the duct system and clogging it.
54
Finally, the dust is collected. This is done via a variety of means, depending on the
application and the dust being handled. It can be as simple as a basic pass-through filter, a
cyclonic separator, or an impingement baffle. It can also be as complex as an electrostatic
precipitator, a multistage bag house, or a chemically treated wet scrubber or stripping
tower.
Green belt: Plantation of trees is one of the best measures for controlling air pollution. Trees
act as wind breaks and the leaves as dust filter. Much of the dust produced in permanent roads
in and around mines can be trapped by having trees with dense foliage planted on both sides of
the roads. Maiti and Banerjee (1992) found that a 8m wide green belt between roads and
buildings can reduce dust-fall by two to three times, and conifers reduce dust-fall by up to 42%
in temperate urban areas. They also indicated that evergreen plants with shiny leaves like
Alstoniascholaris, Ficuslunea, F. Benghalensisand Magniferaindicaare the best dust catchers.
Therefore, major dust producing areas such as stockyard, transfer points, material handling
plants should be surrounded by a green belt. At least 30-40 meter green belt should be created
on either side of the transportation road passing through populated areas.
Table 7.1: Comparison between different particulate matter control measures
Particulate Matter control methods
Effectiveness
Cost and Drawbacks
Dilution ventilation
Moderate
High- more air may not be feasible
Displacement ventilation
Moderate to
high
Moderate - can be difficult to
implement
Wetting by sprays
Moderate
Low - too much water can be a
problem
Airborne capture by sprays
low to
Moderate
Low - too much water can be a
problem
Airborne capture by high pressure
sprays
Moderate
moderate- can only be used in
enclosed spaces
Foam
Moderate
High
Wetting agents
Zero to low
Moderate
Dust collectors
Moderate to
high
Moderate to High - possible noise
problems
Reducing generated dusts
low to
Moderate
Moderate
Enclosure with sprays
low to
Moderate
Moderate
Dust avoidance
Moderate
Low to Moderate
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7.2 CONCLUSION
Mining, because of the very nature of operations involves disturbing the ground, removing and
handling soil and rock, and the subsequent transport, dumping, crushing and processing of this
material. At all stages there is some potential to produce particulate matter. It has become more
serious and alarming due to increased production and mechanization in opencast as well as
underground mines. It is seen that in mining industry, right from the soil handling to the final
transportation, dust is generated resulting in air pollution.
In the present study, it was found that the AQI values for Joda East Iron ore mines ranges from
0 to 50, which lies in the ‘Good’ category. The AQI value of Bhulbeda Iron ore mines varied
from 100 to 150, indicating that it belongs to ‘Unhealthy to sensitive group’ category. Rest of
the mines, viz. Khondbond Iron and Manganese mines, Jilling Langalota Iron and Manganese
mines have their AQI value within ‘Moderate’ category.
The PM10values of most of the mines under observation were found to be close to the
standards prescribed by NAAQS, whereas PM2.5 values are well within NAAQS. The
concentration of gaseous pollutants e.g. NOx, SO2, CO were found to be negligible with
respect to NAAQS limits.
Several suggested mitigation measures which has been suggested, if followed, can bring down
the level of particulate matter concentration considerably. These days, a number of dust
dispersion modelling software’s are also available to predict the dust concentration, which can
be utilized to plan for precautionary measures in advance. Best practice dust management can
be achieved by appropriate planning in the case of new or expanding mining operations and by
identifying and controlling dust sources during the active phases of all mining operations.
56
Chapter 8
REFERENCES
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