Interactive comment on “ Chemical mass balance estimation of arsenic in atmospheric dust fall out in an urban residential area , Raipur , Central India ”

The manuscripts shows a good attempt at measuring the flux of dust depositing in an industrial city with the main focus on Arsenic. The manuscript can be improved with some editing for grammar and language. However, several key things were missing: detail meteorological information, explanationof wind channels, data for other chemical species measured, particle size distribution information, error bugdet and details about accuracy and method detection values for the chemical analyses.


Introduction
Atmospheric particulate pollutants, specifically heavy metals and trace elements derived from different anthropogenic sources, induce a variety of health effects which are currently considered as major problems in the highly urbanized regions of the world.Among the trace elements of airborne particulate matter, arsenic is the commonly known toxic element which causes adverse effects on human health (Deb and Thakur, 2002).Arsenic occurs naturally in a wide range of minerals, but its distribution in the environment is due to emission of fossil fuel combustion, industrial activities, Figures widespread use of pigments, pesticides and other human activities reported in recent years (Deb and Thakur, 2002;Tsai et al., 2003).Arsenic concentration in urban environment varies considerably in roadside soils (Chirenje et al., 2001).Urban soils are significantly more heterogeneous than undisturbed soils and also human activity plays a dominant role in the changing of these soils (Chirenje et al., 2003, Davis et al., 1987).Urban particulates can be emitted directly to the atmosphere through combustion processes and it is considered that traffic is one of the main sources of particulate pollution (Pandey and Patel, 1998;Pio et al., 1998;Kleeman and Cass, 1998).Studies on urban atmospheric particulate matter and on street sediments were carried out in some Chinese cities (Shu et al., 2001;Li et al., 2001).These results highlight the need to investigate the near-ground deposition of particulate matter with regard to impact on humans and plants.One recent study based on treated laterite (TL) as an arsenic adsorbent has been demonstrated to have competitive adsorption of As(V) and As(III) species and effects of arsenic adsorption in the presence of phosphate, carbonate, and silicate ions (Maiti et al., 2010).The arsenic species is in the form of arsenite, which is the most prevalent form of arsenic in some ground waters the dermal uptake for arsenite during one bath could increase to 1.1 µg arsenite (Ngugen et al., 2009).Inorganic arsenic is a recognized cause of cancer.Inhalation of high levels of airborne arsenic causes lung cancer, observed primarily among workers exposed in cadmium, lead, and copper smelters (Lubin et al., 2000;Enterline and Marsh, 1982;Lundstrom et al., 2006).Ingestion of high concentrations of arsenic causes cancer of the skin, lung, and urinary bladder and is a suspected cause of kidney and other malignancies (International Agency for Research on Cancer, 2004;Cantor et al., 2006).Arsenic ingestion has also been implicated in many other adverse health effects, including skin lesions, diabetes mellitus, chronic bronchitis, cardiovascular disease, peripheral neuropathy, adverse reproductive outcomes, and hematological effects (National Research Council: Subcommittee on Arsenic in Drinking Water, 1999; National Research Council: Subcommittee to Update the 1999 Arsenic in Drinking Water Report, 2001).Introduction

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Full During the last 10 years, the widespread nature of human exposure to arsenic in drinking water has become apparent in many countries.Potential health risks, in particular, cancer risks are very high (Chen et al., 1992;Smith et al., 1992;NRC, 1999NRC, , 2001)).At the same time, regulating arsenic concentrations in drinking water has been a controversial and protracted process (Smith et al., 2002).
Increasing severity of dispersion and fallout of fugitive dusts in urban areas of India has shown spontaneous linkage with higher degree of health disorders especially bronchial ailments (Saxena et al., 2008;Quraishi and Pandey, 1995;Sharma andPervez, 2003, 2005;Bohm and Saldiva, 2000;Goel and Trivedi, 1998).Due to higher settling tendency of bigger particles of dust fallout fraction near emission sources on a regional scale, researchers have made classification of its reception pattern as ambientoutdoor, street-outdoor and indoors dust fallout (Dubey and Pervez, 2008;Quraishi and Pandey, 1993;Sharma and Pervez, 2004;Gadkari and Pervez 2007).
The presented work has been focused on source apportionment of arsenic in dust fallout in selected classified urban receptor of Raipur City, India which located in global scale of: 21 • 14 22.7 N latitude and 81 • 38 30.1 E longitudes.Regression analysis between various longitudinal measurements of selected and defined deposit regions has been utilized to identify possible sources/routes of dust transport to a receptor region.Chemical mass balance (CMB8) has been executed to investigate source contribution estimates of dust fallout in relation to source signature of arsenic in a specific ambientoutdoor receptor located in a residential area.
2 Materials and method (study design, sampling plan and data analysis)

Study design
The study was undertaken in an urban area.The goal of the study is to evaluate relative source contribution estimates of various routes of arsenic in dust fallout in urban residential environment.The objectives here are: (1) To measure and characterize Introduction

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Full dust fallout and arsenic at identified sources (2) to analyze statistically, the relationship between dust fallout measurements of source-routes and residential-receptors and (3) to carryout apportionment of arsenic in dust fall at classified residential-receptors, taking identified atmospheric routes as possible sources using Chemical mass balance Model (CMB8).A residential area (Birgaon) located in close proximity to a major industrial area (Siltara) has been selected for the study.Apart from two major industrial sources of dusts emission, local soils, paved road dusts and automobile exhaust emissions along with construction activities have also been identified to cluster of source profiles for source apportionment.The details of location of residential colony (receptor), major industrial complexes, wind rose and wind channel has been shown in Fig. 1a,b.

Sampling design
A comprehensive study about source contribution estimates of major possible and observable sources of dusts emission to dust fallout of urban areas (residential, commercial and sensitive regions) was started from yr 2007.Source apportionment study of arsenic in dust fallout of a specific urban-residential region has been presented here.A non-probability based longitudinal stratified random sampling design in spacetime frame work has been chosen to achieve the objectives (Gilbert, 1987).Ambientoutdoor atmospheric level has been decided for measurement of dust fallout at identified sources of dust emissions.In case of residential-receptor, three most susceptible atmospheric levels have been chosen, namely ambient-outdoors, house-indoors and local street-outdoors (Table 1).

Sampling method of dust fallout
Dust emission sources were identified using layout map, anthropogenic activity patterns and urban-industrial development plan of the study area.The identified sources (Table 1) were classified in point, line and regional sources of dust emission (Goel and Introduction

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Full Trivedi , 1998).Dust collection Jars (Dimension: dia-23 ht-45 ) with standard specifications (Katz, 1977;Thakur and Deb, 1999) has been placed for a month at a height of 10 ft (ambient-outdoor), at both source and receptor sites, 5 ft (local street-outdoor) and 1 ft (indoor-house) at receptor sites.Sampling at local-outdoor (5 ft height) has been chosen for measurement at construction activity site.In case of sampling at paved road source (S-3), sampler was installed at the height of 5 ft at major cross road passing near to the residential colony.About a liter of double distilled water was placed in each Jar and a net sheet (size: 20 mesh) was placed on mouth of the Jars.Water soluble and insoluble fraction of dust fallout has been measured separately and by adding them, total dust fallout was measured.Five replicate measurements were done to minimize weighing error (Table 2).
As far as soil chemical profile (S-6) is concern, samples of soils (1 kg) have been collected from open land of residential colony.Soil samples were collected after removing surface soils up to 6 cm depth and sent to laboratory.Soil has been smashed in a milling machine and blown in a closed glass chamber (size 1.5 m 3 ) using a pressure fan.The dust collecting jars has been placed in the chamber and collected dust during dispersion of soil dusts in the chamber (Gadkari and Pervez, 2008).Black smoky dust emitted and deposited in automobile exhaust silencers of diesel fuel based heavy duty trucks and petrol based cars have been collected and scum were mixed together for development of chemical profile of automobile source (S-5).Vehicles have been selected randomly which mostly passes through that road junction.About 5-10 g of exhaust emitted black smoky dust has been collected.Frequency of sampling was 12 (one in each month) at each source-receptor site throughout the sampling period (December 2007 to November 2008).
The dust fall rate was calculated for each site using the following equation (Kikuo, 1977): fall-out in the collecting container (g); D -the diameter of the dust collecting container (cm); N -the number of days of collection of sample.

Chemical analysis of dust fallout
Dried samples of soils and automobile exhaust scum have been powdered using a milling machine.Powder and dust samples were digested in Teflon digestion bomb and nitric acid (HNO 3 ) and hydrogen peroxide (H 2 O 2 ) (3:1).Teflon bomb was then kept in an electric oven at 80 • C for 8 h, cooled, and contents filtered in a volumetric flask and washed with dilute HNO 3 .Final volume of digested sample was made up to 25 ml using distilled water.Digested samples and soluble fraction of dust fallout measured during field sampling were analyzed for total As content using inductive coupled plasma-atomic emission spectrophotometer (ICP-AES) (JOBIN-YVON HORIBA ICP Spectrometer Version 3.0).Arsenic analysis was carried out at a wavelength of 189.042 nm to avoid spectral and chemical interferences.Calibration of instrument was done using Merck standard ICP solution of concentration range 0.1-10 ppm.The power used for analysis is 1200 W; plasma gas flow rate is 12 L/min.

Data analysis
Measurement data of dust fallout and particulate arsenic has been documented as geometrical mean and standard deviation of longitudinal measurements of each monitoring site and presented in Table 2. Regression analysis between annual mean of dust fallout measured at defined receptor site (local-outdoor, indoor and street of Birgaon residential region) and selected source sites (Siltara Industrial complex, Urla Industrial complex, paved road and construction sites) has been conducted and presented in (3) estimation of the fraction of each of the chemical species which is contained in each source type (source profile); (4) estimation of the uncertainty in both receptor concentrations and source profiles; and (5) solution of the chemical mass balance equations.The CMB is implicit in all factor analysis and multiple linear regression models that intend to quantitatively estimate source contributions.The chemical mass balance consists of a least squares solution to a set of linear equations which expresses each receptor concentration of a chemical species as a linear sum of products of source profile species and source contribution.Exact knowledge of dispersion factor of emissions is not necessary in receptor models.Geometric mean and standard deviation values of chemical parameters have been utilized for the concentration and uncertainties of corresponding species of specific site for development of source/receptor profiles.All prepared source and receptor profiles has been introduced in CMB model using an INFRA control file to execute source apportionment program (Watson et al., 1997(Watson et al., , 1998)).Results of CMB execution have been presented in Figs.3-5.(Ferrari, 2000).
The monthly dust fall rate were found to be in the range 67.71-391.01mt km −2 month −1 for all six source sites and the receptor site has shown the range 51.78-119.64 mt km −2 month −1 at ambient-outdoor level, 61.56-143.56mt km −2 month −1 at outdoor-street and 12.34-18.92mt km −2 month −1 in houseindoors of residential area during the sampling period of 12 month.The lowest rate of dust fall in source sites was found at construction (S-4) in summer and the highest at Siltara industrial area (S-1) in spring and at receptor area (Birgaon) (R-1), the lowest rate found in post-rainy and the highest in winter at ambient-outdoor level.In streetoutdoor level, lowest rate was found in post-rainy and the highest in winter season.
Indoor-house has shown lowest dust fall in summer and the highest winter season.
The geometric mean of dust fallout rate (mt km −2 month −1 ) of 12 sampling months at different sampling sites were found to be: 181.19±77.97(S-1), 217.43±24.41(S-2), 141.44±18.31(S-3), 87.85±25.49(S-4) and for receptor site (R-1), ambientoutdoor level have shown 77.59±25.49,street-outdoor 84.29±22.35and house-indoor 14.31±2.39.On the basis of monthwise dust fall rate, the highest total flux was observed to be measured at S-2 with an amount of 2624.78 mt km −2 yr −1 .The values of annual flux in the other sources, viz.S-1, S-3 and S-4 were 2313.91,1709.1 and 1070.29 mt km −2 yr −1 , respectively.Linear regression analyses have shown that receptor site (Birgaon) is best correlated with Road dust fall (S-4) compared to other sources at ambient, street and indoor level (Fig. 2).This has been proved by the CMB model out put results for dust fallout.

Arsenic levels in airborne dust fallout
The analyses on month wise and site wise, arsenic concentration in mt km −2 month −1 has been calculated, and annual site wise flux of As in mt km −2 yr −1 at different sites for the whole study period have also been evaluated and presented in Table 2.
Month wise variation of flux of Arsenic in the airborne dust fall (mt km −2 month −1 ) for 12 sampling months at different sampling sites were observed to be in the range: 0.0089±0.001 in S-1, 0.0041±0.0037 in S-2, 0.0014±0.0038 in S-3, 0.0006±0.002Introduction

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Full in S-4, 0.0043±0.002 in S-5 and 0.0017±0.001 in S-6.For receptor site, the arsenic concentrations have been found as: 0.0641±0.033at ambient-outdoor level, 0.0309±0.0324at street-outdoor, and 0.0442±0.0284at house-indoor levels.It has been found that indoor arsenic level (R-2) is high in compared to street out door (R-3).This may due to house hold fuel burning.The concentration of arsenic at S-1 (Siltara industrial area) ranges between 0.007-0.019mt km −2 month −1 and at S-2 (Urla industrial area) it ranges between 0.002-0.016mt km −2 month −1 dust falls.
These are higher than the arsenic concentrations found in other sources viz.S-3, S-4, S-5 and S-6.The arsenic concentrations for other sources were in the range 0.0009-0.002mt km −2 month −1 at S-3, 0.0005-0.0009mt km −2 month −1 at S-4, 0.003-0.013mt km −2 month −1 at S-5 and 0.0005-0.001mt km −2 month −1 at S-6 of dust matrix.Simultaneously, residential receptor have shown reception of 0.0414-0.0957at ambient level, 0.013-0.112at street and 0.029-0.082mt km −2 month −1 arsenic at house indoor level in dust fall.Due to the maximum precipitation of airborne particulates, as well as highest concentration of arsenic in industrial areas, the flux of arsenic is also maximum in ambient-outdoor level.The next highest flux of dust fall-arsenic has been found at heavy traffic-outdoors.House-indoors of R-1 has shown the least quantum of arsenic.

Preliminary assessment using regression analysis
The statistical evaluation of contribution of independent source sites to dependent receptors has been reported to given clear agreement with experimental data in earlier studies.Industrial source (S-1) and construction activities (S-4) have shown significant contribution of 39.29% and 90%, respectively to dust fallout at ambient-outdoor level (R-1) of residential receptors.Other two sources (S-2 and S-3) have not shown any contribution in dust fallout at ambient level.In case of street-outdoor level, (S-1) has shown 17% contribution effect while other selected sources have not shown sig-Introduction

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Full As far as house-indoor levels is concern, paved road (S-3) and construction activities (S-4) have shown significant contribution effect of 90% and 62%, respectively.Inadequate contribution of major industrial site (S-2) might be due to unfavorable prevailing wind channels to residential receptors.

Source signatures of dust fallout and arsenic content using receptor model
Source profiles have shown that mean level of arsenic is projected above than 50th percentile in all sources except S-1.In case of S-3, it has been projected above than 75th percentile.Arsenic has shown significant level in all source sites.CMB results have shown multiple source contribution with dominance of paved road in dust fall at all classified atmospheric levels of defined receptor.As far as source contribution assessment of dust fallout is concern, paved road (S-3) has shown major contribution in dust fall at all stages i.e. 31% at R-1, 53% at R-3 and 31% at R-2 of Birgaon residential area.Siltara industrial area (S-1) has shown significant contribution at all stages than Urla industrial area (S-2) with 20% contribution at R-1. Arsenic source apportionment values have shown different pattern source contribution at different level compared to source signatures of dust fallout.Siltara industrial area (S-1) has shown major contribution (39%) at ambient level (R-1).Vehicle exhaust (S-5) has expressed major contribution (44% and 37%) at both R-2 and R-3.Lower contribution of Urla Industrial (S-2) source compared to Siltara Industrial (S-1) source has been observed and variation in contribution could be assessed using windrose of the study region.In contrast to international scenario, vehicle exhaust has shown significant contribution.
The results of source apportionment of arsenic content of dust fallout have shown that coal combustion activities (S-1) was came out as a significant contributor with 39% (R-1), 23% at R-3 and 29% at receptor sites (R-3).Vehicle exhaust (S-5) and industrial location of Urla (S-2) have also shown significant contribution in arsenic content of dust fall in all atmospheric levels of residential receptor (R-1, 2, 3).Overall, contrast 26421 Introduction

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Full result of source apportionment of dust fallout and arsenic content of dust fall has been observed.In this complete study arsenic levels at receptor site are comparatively high than source sites, this is due to the multiple source contribution at receptor site.

Conclusions
Profuse and highly skewed dust fallout at outdoor and indoor environment of residential receptor site (Birgaon) has been observed.It has been observed that geometrical mean level of dust fallout at residential outdoor receptor is thousand times higher than maximum permissible limits (0.01 mt km −2 m −1 ) developed in Australia (Ferrari, 2000) and justify the need to develop India standards of dust fallout.On comparison to previous reported data of dust fallout in this region, present levels have shown about 1.2 fold higher concentration.On comparison to fine particulate matter, coarser particle size of dust fallout has played an important role in decreasing the deviation pattern of annul average from geometric mean.Road borne dusts (S-3) have shown major contribution to dust fallout at residential receptors.Siltara industrial area (S-1), construction activities (S-4) and vehicle exhaust (S-5) sources have also shown significant contribution.Siltara industrial area (S-1) has shown significant contribution at all levels of residential receptor (R-1, 2 and 3) compared to Urla industrial area (S-2) due to unfavorable prevailing wind direction.The annual flux of arsenic in the urban city is an alarming amount of 3.896 mt.On comparison to source apportionment of dust fallout, a different pattern of dominance among selected sources to relative source contributions of arsenic content in dust fallout has been observed.Vehicle exhaust and Urla Industrial area along with Siltara industrial site have shown strong contribution in arsenic levels measured in dust fallout of residential receptors.Overall multisource contribution and strong variation in relative source contribution to dust fallout and its arsenic content in urban-residential environment has been obtained.Introduction

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Fig. 2 .
The source profile abundances (mass fraction of chemicals in the emissions from each source type) and the receptor concentrations, with appropriate uncertainty estimates, serve as input data to the CMB model.The output consists of the amount Discussion Paper | Discussion Paper | Discussion Paper |contributed by each source type represented by a profile to the total mass and each chemical species.The CMB calculates values for the contributions from each source and the uncertainties of those values.The CMB is applicable to multi-species data sets.The CMB modeling procedure requires: (1) identification of the contributing source type; (2) selection of chemical species or other properties to be included in the calculation; flux and rate of dust fallout The total annual flux of airborne dust particulate has been calculated on the basis of month wise measurements of dust fall rate at different sources and receptor during December 2007-November 2008.All the sites have shown thousand times higher annual dust fall rate compared to prescribed standard of 0.01 mt km −2 month Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | nificant contribution.Paved road(S-3) has shown major contribution in dust fallout of local Street-outdoor (R-1).
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Acknowledgement.I am thankful to Caf é U No (Raipur) and its staff who make help in my sampling and Chemical analysis.Discussion Paper | Discussion Paper | Discussion Paper |

Fig: 1 Fig. 2 .
Figures & TablesFig:1Local map of source and receptor sites in Raipur City along with windrose of the region

Table 3 .
Good fit parameters of CMB execution output results for selected receptors.