ISCST3 Model Research Articles

Air Quality Predictions through Mathematical Modeling for Iron Ore Mine Project

Mathematical modeling was deployed to predict air quality during the construction and operation phases of an iron ore mine project in Maharashtra, India. A survey of different models revealed that the ISCST3 model was the most applicable one to predict the air quality parameters, particularly the suspended particulate matter (SPM) and coarse particulate matter (PM10). Baseline air quality data, emission rates, local meteorology, and terrain information were used to simulate the ground-level concentrations. The simulation predicted SPM and PM10 peaks of 172 µg/m3 and 44 µg/m3, respectively. The prediction was within the prescribed limits of the national standards of 200 µg/m3 and 100 µg/m3, respectively, near the source, with minor exceedances in total SPM in two nearby villages and an impact on air quality due to proposed mining. Accordingly, mitigation strategies towards such villages were recommended and implemented. Later, the monitoring in the operation phase revealed that particulate matter could be controlled effectively with mitigation strategies and ensured compliance with air quality standards. The analysis also revealed strong correlations between the particulate matter and the distance of the localities and SPM and PM10. Continuous monitoring and adaptive mitigation based on real-time data were thus emphasized for long-term sustainability and responsible mining practices.

Comparison of Application of AERMOD and ISCST3 Models for Simulating the Dispersion of Emitted Pollutant from the Stack of an Industrial Plant in Different Time Scales

Background: One of the main parts of air quality management is known as modeling of atmospheric pollutants. In this regards, simultaneous application of several models in a project and comparing the results obtained from these models could have been a considerable contribution to air quality managers for taking a more efficient decision. Methods: In this study, the stack of an industrial plant in the southwest of Isfahan was selected as the emission source and the total suspended particles emitted from this stack was simulated by applying AERMOD and ISCST3 view models (version 8.2). In this vein, the modeling process was conducted using MM5 meteorological data in a 50 50 km extent with 2000 m network distance for each of the models in 1-h, 24-h term averages (short term averages) and monthly and annual periods (long term averages) at ground level concentrations (GLC). Results: Results indicated that the highest simulated concentration for both models occurred in a 2000 meters’ distance in the east of the stack. Moreover, the highest simulated concentration applying AERMOD was lower than that of applying ISCST3 in all term averages which is due to existing differences between applied algorithms in these two models. Conclusion: Consequently, applying AERMOD due to the use of more advanced and up-to-date algorithms have priority over ISCST3 model. Applying ISCST3 can also be useful for small projects that require less input data compared to the AERMOD.

Air Pollution Dispersion Modeling for Diesel Generators at Jamia University Campus, New Delhi, India

The study is conducted in order to assess the contribution of pollutants from the Diesel generators running in the Jamia Millia Islamia University Campus. In this work, ISCST3 air dispersion model was applied to simulate the air quality for 24 hourly average ground level concentrations of SOx, NOx, PM10 and 8 hourly average for CO at various receptor locations. Based on surveys and questionnaires, an inventory was formulated for different Gensets and their characteristics. The ISCST3 model is based on a steady-state Gaussian plume algorithm. It has been developed by USEPA for assessing air quality impact from point, area, and volume sources. Emission rates for different pollutants have been computed using empirical formulas for Gensets based on their capacity. Pollutant emitting potential has also been computed. The predicted values given by ISCST3 model are 11.33μg/m3 for PM10, 58.4 μg/m3 for SOx, 176.50 μg/m3 for NOx, 57.02 μg/m3 for CO. Both monitored and simulated values have been compared with NAAQS 2009. A possible solution for minimizing the pollutant load in the area via Diesel Gensets has been suggested in this research which will further help in managing the air quality scenario at the study area.

The Study of AERMOD and ISCST3 for Area Source Simulation in Taiwan

This research compared the performance of ISCST3 model with the AERMOD simulated for six selected environmental impact assessment (EIA) cases which belongs four kinds of area in Taiwan (hotel, industrial area, road, reservoir). The influence of different terrain (complex or flat) and land use (countryside or urban) was then determined for the two air dispersion models.The results of the cross analysis indicated that there is no significant difference between of the complex terrain and flat terrain on the incremental concentration ratio. However, the biggest difference of incremental concentration of particulate matter (PM) is in the simulation for case in urban (ISCST3 is 1.96 times higher than AERMOD), and the gas pollutants in ISCST3 of incremental concentration simulation results ratio reach to 65.38% more than others. The highest incremental concentration of ISCST3 is 2.67 times to AERMOD. The concentration in AERMOD higher than that in ISTSC3 was 20% in the total 40 simulation values, due to the difference between their vertical diffusion simulations. The ratio of maximum incremental concentration in AERMOD was higher than ISCST3 by 42.5%. By the cross match of these incremental concentration, the ratio that maximum incremental concentration in AERMOD being less than ISCST3 was 22.5% after diffusion, which shows that the sinking rate in AERMOD is faster than ISCST3.The simulation of AERMOD considers more in complex terrain and surface characteristics. It uses the stratified flow over complex terrain and considers the effect in characteristics of the Earth’s surface. Thus, the theoretical basis of AERMOD is solider than ISCST3, and its simulation has more reliability.

Spatial distribution of SO2 concentration and population exposure in the tropical city of Villahermosa, Mexico

A hybrid system to compute a fine-resolution spatial distribution of population exposure to SO2 concentration due to mobile and area sources in the tropical city of Villahermosa is described, which consists of an air dispersion model, GIS analysis techniques, and a static exposure model. A methodology to spatially allocate SO2 emissions has been applied, which is adapted to the characteristics of a typical medium-sized city in a developing country. It was estimated that 363.2 tons of SO2 was emitted in the Villahermosa Metropolitan Zone, 21.3 % of which was produced by area sources and 78.7 % by mobile sources. The highest spatially allocated emissions were located in main road intersections, where they reached a maximum value of 39,804 μg s−1, and, in a lesser measure, in the most populated areas of Villahermosa. Performance of the ISCST3 model to simulate hourly SO2 concentrations was similar to that of other studies. The highest SO2 concentrations were located at intersections of main roads in the south-central and southwestern Villahermosa. On the other hand, the lowest SO2 concentrations were found in its north-central district. The highest population exposure to SO2 concentrations was located in areas with high population density like southwestern, south-central, and northeastern Villahermosa. On the other hand, its north-central zone had the lowest exposure due to a low SO2 concentration and low population density.

Uncertainty in Health Impact Assessment of Organic Air Toxics from Refinery – A Case Study in Taiwan

Background Petroleum refinery is one of major sources of NMOGs in Taiwan which contributed 2.3% emissions among all stationary sources. Estimation of the toxic may affect significantly on health risk assessment due to the different emission factor selection. Aims This study investigates the procedure for health impact assessment organic air toxics released from a refinery in Taiwan. Six emission source categories, including stack, equipment component, storage tank, flare, loading/unloading, and wastewater treatment plant, in refinery were discussed. Methods NMOG emissions from each category were calculated by applying WebFIRE and SPECIATE 4.0. Facility priority for target air toxics was evaluated. The ISCST3 model was used to simulate the ambient concentration. Result Total of 31 VOC species were identified by using emission factors in WebFIRE and SPECIATE 4.0. The results show that the top air toxic is benzene. The results of facility priority of carcinogenic effect showed the highest score is flare. The scores of flare, equipment component, wastewater treatment plant, and storage tank are higher than 10 and will be classified as high priority facility. The ambient concentrations of four selected organic air toxics were simulated. The maximum annual concentration of benzene was 183 ?g/m3. The maximum total cancer risk for target air toxics is 7,120×10-6. Benzene is most important compound ( 6.91×10-3) and followed by ethylbenzene (2.10×10-4 ). Conclusions The case study in Taiwan indicates that air toxic emission profile selection causes the greatest variation on health impact assessment among those relevant factors in a refinery. .

On the possibility of estimating the volume of NO2 emissions in cities using zenith spectral observations of diffuse solar radiation near 450 nm

Methodological questions are considered for using the measurements of the integral content of NO2 in the atmospheric boundary layer, carried out at a fixed station, to analyze NO2 sources in a city. These measurements are carried out regularly at the IAP RAS network in Moscow. The experimental estimates of NO2 content are compared with calculations of pollutant transport by the ISCST3 model on the basis of the emission inventory, which shows a good agreement between these two approaches. We suggested a technique for estimating NO2 emissions in the urban environment with the use of the NO2 integral content measurements by the zenith spectral method. During the observation period of 2010–2011, vehicular emissions of NO2 in Moscow amounted to 88 kt/year.

Daily and Seasonal Changes of Air Pollution in Kuwait

This paper focuses on assessment of air pollution i n Umm-Alhyman, Kuwait, which is located south to oil refineries, power station, oil field, and highways. The measure ments were made over a period of four days in March and July in 200 1, 2004, and 2008. The measured pollutants included methanated and non- methanated hydrocarbons (MHC, NMHC), CO, CO2, SO2, NOX, O3, and PM10. Also, meteorological parameters were measured, which includes temperature, wind speed and direction, and solar radiation. Over the study period, data analysis showed increas e in measured SO2, NOX and CO by factors of 1.2, 5.5 and 2, respectively. This is explained in terms of increase in industrial activi ties, motor vehicle density, and power generation. Predictions of the m easured data were made by the ISC-AERMOD software package and by using the ISCST3 model option. Finally, comparison was made between measured data against international standards. Keywords—Air pollution, Emission inventory, ISCST3 model, Modeling

Air quality modelling study to analyse the impact of the World Bank emission guidelines for thermal power plants in Delhi

Recent strategies for air pollution control in Delhi have largely neglected the emission reduction measures from thermal power plants (TPPs), which are the second most polluting sources. The present study investigates how the ambient air quality of Delhi would improve if the World Bank emission guidelines (WBEG) for the TPPs were to be implemented. To accomplish this, a comprehensive inventory of point, area, and line sources was conducted in the selected study area, primarily aiming to estimate the sectoral emission contributions to ambient air quality. The Industrial Source Complex Short–Term Model, Version 3 (ISCST3) was used to predict the ambient concentrations of total suspended particulates (TSP), sulphur dioxide (SO2), and nitrogen dioxide (NO2) at seven monitoring sites (receptor locations) operated by the Central Pollution Control Board (CPCB) for the period from July 2004 to June 2005. The ISCST3 model predictions for TSP and NO2 were satisfactory at all receptor locations. However, for SO2, the model predictions were satisfactory at only two receptor locations. The vehicles contributed 58% of the total ambient air pollution, followed by TPPs contributing 30%. The study estimates that adoption of WBEG may reduce the ambient air pollution due to TPPs emissions by 56% to 82%, bringing it within the National Ambient Air Quality Standards (NAAQS) set for industrial areas in India, except at one location where TPP’s contribution to ambient air pollution is negligible compared to vehicular emissions.

GIS-Based Emission Inventory, Dispersion Modeling, and Assessment for Source Contributions of Particulate Matter in an Urban Environment

The Industrial Source Complex Short Term (ISCST3) model was used to discern the sources responsible for high PM10 levels in Kanpur City, a typical urban area in the Ganga basin, India. A systematic geographic information system-based emission inventory was developed for PM10 in each of 85 grids of 2 × 2 km. The total emission of PM10 was estimated at 11 t day−1 with an overall breakup as follows: (a) industrial point sources, 2.9 t day−1 (26%); (b) vehicles, 2.3 t day−1 (21%); (c) domestic fuel burning, 2.1 t day−1 (19%); (d) paved and unpaved road dust, 1.6 t day−1 (15%); and the rest as other sources. To validate the ISCST3 model and to assess air-quality status, sampling was done in summer and winter at seven sampling sites for over 85 days; PM10 levels were very high (89–632 μg m−3). The results show that the model-predicted concentrations are in good agreement with observed values, and the model performance was found satisfactory. The validated model was run for each source on each day of sampling. The overall source contribution to ambient air pollution was as follows: vehicular traffic (16%), domestic fuel uses (16%), paved and unpaved road dust (14%), and industries (7%). Interestingly, the largest point source (coal-based power plant) did not contribute significantly to ambient air pollution. The reason might be due to release of pollutant at high stack height. The ISCST3 model was shown to produce source apportionment results like receptor modeling that could generate source apportionment results at any desired time and space resolution.

Prediction of Ground-Level Concentration of Sulfur Dioxide Downwind of an Industrial Estate in Mauritius Using the ISCST3 Model and Selection of Air Pollution Control Systems

Industries on the island of Mauritius are under increasing pressure from the regulatory authority and from the general public to control the air pollution from their boilers and particularly that of sulfur dioxide emissions from fuel oil combustion. The measures taken by industry are usually “ad hoc” in nature, and there has been yet no proper scientific methodology to justify the nature of the pollution control interventions. Air modeling as a planning tool provides a scientific methodology to industries and to the regulatory authority to select the optimum option(s) among various scenarios such as raising stack heights, changing fuels, implementing cleaner production opportunities or installation of wet scrubbers. The aim of this project was to use an air dispersion model for the selection of air pollution control systems for industrial boilers in an industrial estate. Given a number of constraints on small island developing states like Mauritius, it is recommended to start using established and simple modeling methods, as the complexity of the more refined models requires a relatively long learning curve to be able to use the model correctly. The Industrial Source Complex Short Term (ISCST3) is recommended for that purpose. The application of the ISCST3 model to the multiple-source case study helped in the identification of the most cost-effective options.

Potential Impacts of Integrated Oil and Gas Plant on Ambient Air Quality

The ISCST-3 model has been used to study the ground level concentrations of carbon monoxide (CO), oxides of nitrogen (NOX), particulate matter less than 10.0 microns in diameter (PM10) and sulphur dioxide (SO2). The purpose was to predict air quality effects from an integrated oil and gas project (IOGP) proposed for the Niger Delta, Nigeria. The emissions of 12 elevated point sources for criteria air pollutants were considered with eight different scenarios. Both natural gas-fired and diesel (AGO) fired equipment were considered for the identified emission sources. Five years of hourly meteorological observations were used in the prediction of the ground level concentration of the pollutants. The model outputs show a general maximum ground level concentration between 0.5 – 3.5 km, with easterly and north-easterly receptors having the greatest concentration. The pollutants emitted in the greatest concentration in their order of magnitude were CO, NOx and PM10. Maximum ground level concentration for 1, 8 and 24 – hr periods for CO were below regulatory standards (less than 10 %) for scenarios 1 – 4 when the fuel is natural gas. The 8 – hr ground level concentrations were about 1.3 folds of the World Bank Standard in scenarios 5 – 8 when the fuel sources are switched to AGO. However in these scenarios, the Nigerian environment and petroleum ministries' emission limits were not breached for all the averaging periods. Modelled NOX concentrations were significant in all the scenarios except 3 and 4. Though NOX concentrations were within the standards for all the averaging periods in scenarios 1 – 4, except the 1 – hr limit that was breached in scenarios 1 and 2, these concentrations were about 1.1 – 2.8 folds in all the averaging periods of all the standards in scenarios 5 – 8. The predicted PM10 and SO2 concentrations are all below the guideline limits. If the use of AGO is completely avoided in the entire life of the proposed IOGP, the air quality of its immediate vicinity can be protected. Furthermore, the declaration of a radius 1.75 km natural forest buffer around the plant and continuous monitoring of ground level concentrations of CO, NOX, PM10, and SO2 may further assist in guaranteeing the safety of people in terms of air quality. The study shows the need for policy formulation that will integrate comprehensive cumulative impacts assessment of air quality in the environmental laws regulating the gas development projects in Nigeria.

Using a Simulation Tool to Model the Ground Level Concentrations of Green House Gases Emitted by Flaring in Petroleum Production in Kuwait Oilfields

Air pollution and its effects on the ecosystem has been a source of concern for many environmental pollution organizations in the world. In particular climatologists who are not directly involved in petroleum industry sometimes express concerns about the environmental impacts of gas emissions from flaring at well heads. For environmental and resource conservation reasons, flaring should always be minimized as much as practicable and consistent with safety considerations. However, any level of flaring has a local environmental impact, as well as producing emissions which have the potential to contribute to the global warming. In the present research the Industrial Source Complex (ISCST3) Dispersion Model is used to calculate the ground level concentrations of two selected primary pollutants (i.e. methane and non-methane hydrocarbons) emitted due to flaring in all of Kuwait Oilfields. In additional, the performance of the ISCST3 model is assessed, by comparing the model prediction with the observed concentration of methane and non-methane hydrocarbons obtained from the monitoring sites. The described model evaluation is based on the comparison of 50 highest daily measured and predicted concentrations of methane and non-methane hydrocarbons. The overall conclusion of this comparison is that the model predictions are in good agreement with the observed data (accuracy range of 60-95%) from the monitoring stations maintained by the Kuwait Environmental Public Authority (EPA). A specific important conclusion of this study is that, there is a need for a proper emission inventory strategy for Kuwait Oil Company (KOC) as means of monitoring and minimizing the impact of methane and non-methane hydrocarbons released because of flaring activities.

Soil Suspension/Dispersion Modeling Methods for Estimating Health-Based Soil Cleanup Levels of Hexavalent Chromium at Chromite Ore Processing Residue Sites

The primary health concern associated with exposures to chromite ore processing residue (COPR)-affected soils is inhalation of hexavalent chromium [Cr(VI)] particulates. Site-specific soil alternative remediation standards (ARSs) are set using soil suspension and dispersion models to be protective of the theoretical excess cancer risk associated with inhalation of soil suspended by vehicle traffic and wind. The purpose of this study was to update a previous model comparison study that identified the 1995 AP-42 particulate emission model for vehicle traffic over un-paved roads and the Fugitive Dust Model (FDM) as the most appropriate model combination for estimating site-specific ARSs. Because the AP-42 model has been revised, we have updated our past evaluation. Specifically, the 2006 AP-42 particulate emissions model; the Industrial Source Complex–Short Term model, version 3 (ISCST3); and the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) air dispersion models were evaluated, and the results were compared with those from the previously used modeling approaches. Two sites with and two sites without vehicle traffic were evaluated to determine if wind erosion is a significant source of emissions. For the two sites with vehicle traffic, both FDM and ISCST3 produced total suspended particulate (TSP) estimates that were, on average, within a factor of 2 of measured; whereas AERMOD produced estimates that were as much as 5-fold higher than measured. In general, the estimated TSP concentrations for FDM were higher than those for ISCST3. For airborne Cr(VI), the ISCST3 model produced estimates that were only 2- to 8-fold of the measured concentrations, and both FDM and AERMOD estimated airborne Cr(VI) concentrations that were approximately 4- to 14-fold higher than measured. Results using the 1995 AP-42 model were closer to measured than those from the 2006 AP-42 model. Wind erosion was an insignificant contributor to particulate emissions at COPR sites.

Simulation of Air Quality using an ISCST3 Dispersion Model

AbstractUrban air quality is an issue of major concern across many cities in India. In particular, high levels of particulate matter (both SPM and RSPM) are responsible for noncompliance to air quality standards. Air quality modeling is an effective tool to simulate the air quality of a region and to predict air quality concentrations under different scenarios. Kanpur city which is a top‐ten urban conglomerate in India (based on population) is chosen for the application of the ISCST3 model and simulation of air quality. Sectored emission loads are estimated for transport, industrial, power, and domestic sectors, which provide an estimate of the major contributors to air pollution with specific reference to particulate matter, which is a major pollutant of concern. A detailed scenario analysis is carried out to estimate the changes in emissions that would take place due to various interventions. Dispersion modeling is carried out using the ISCST3 model, to estimate the concentrations of SPM all over the city under different scenarios. Emission inventory and meteorological data served as input to the model, and the air quality is predicted for various seasons and intervention scenarios. The modeled values for the scenario without intervention results in an underestimation of 48%, which is due to unaccountable or unidentified sources, trans‐boundary movement of SPM, and model calibration errors. To overcome the error, the model is calibrated with the observed values and results are obtained for other scenarios using the calibration factor. The paper demonstrates only the research direction currently used to simulate air quality in Indian cities. However, further refinement and research is required before it could be used for more accurate predictions.

Hydrogen cyanide in ambient air near a gold heap leach field: Measured vs. modeled concentrations

To extract gold from low-grade ores, a solution of sodium cyanide is trickled over pads of crushed ore. During this operation, small quantities of hydrogen cyanide gas may escape to the ambient air. To assess these emissions, we collected air samples at monitoring stations located on opposite sides of a gold heap leach field at distances ranging from 1100 to 1500 ft from the center of the field. Hydrogen cyanide was detected in 6 of 18 ambient air samples at concentrations ranging from 0.26 to 1.86 parts per billion (ppb). Ambient air samples collected at residential properties located within 2600 ft of the leach field did not contain detectable concentrations of cyanide (detection level of 0.2 ppb). We used site-specific data and two steady-state air dispersion models, ISCST3 and AERMOD, to predict ambient air concentrations of cyanide at the sampling points. The ISCST3 model over-predicted the measured 8-h concentrations of hydrogen cyanide by a factor of 2.4, on average, and the AERMOD model under-predicted the air concentrations of hydrogen cyanide by a factor of 0.76, on average. The major sources of uncertainty in the model predictions were the complex terrain of the area and the uncertainty in the emission rates of cyanide from the leach field. The measured and predicted concentrations of cyanide in the air samples were not at levels that would pose a human health hazard for acute or chronic exposures.

AIR DISPERSION MODELING OF VOCs EMITTED FROM MSW LANDFILLS

In Turkey, landfilling is the most preferred method of municipal solid waste management strategy since it is still considered to be the most cost-effective method of waste disposal. Landfills are very complex systems in which various interactive processes proceed simultaneously. Following waste deposition, a landfill gas mainly comprised of methane and carbon dioxide is generated due to the microbial decomposition. Various trace volatile organic compounds (VOCs) besides main components of landfill gas are also produced. The main components and the trace gases from landfills contribute to the greenhouse effect and influence the ozone layer. In addition, adverse effects of landfill gas on human health and vegetation as well as complaints due to unpleasant odor at landfills have been also reported in the literature. Particularly, during landfill operations and after landfill closure, VOCs emitted from landfills should be determined and evaluated due to their probable carcinogenicity. In this study, the dispersion of VOCs emitted at the IZAYDAS landfill (Kocaeli, Turkey) was modeled. The landfill has been in use since 1998, and covers an area of 363,000 m2 with a total capacity of 3,163,000 m3. First, USEPA`s Landfill Gas Emissions Model (LandGEM V3.2) was used to determine the concentrations of the VOCs emitted from the landfill. Then, USEPA s ISCST3 model (ISC-AERMOD V5.3) was employed for the air dispersion modeling. Following the model inputs such as meteorological parameters, VOC concentrations, digital maps, etc., the wind rose for a five year (2000 2004) period and the concentration gradients were obtained.

Estimation of Enhancing Improvement for Ambient Air-Quality during Street Flushing and Sweeping

This investigation addressed the source apportionment of aerosol particles using both the receptor and dispersion models. Factor analysis and chemical mass balance (CMB) models were two receptor modeling techniques employed to categorize the possible sources in Kaohsiung district. The ISCST3 dispersion model was also used to evaluate improvements in ambient-air quality. Factor analysis revealed that road sweeping resulted in a variation of approximately 10% in the compositions of TSP and PM10. The mass fractions of TSP explained by the CMB model were 60-70% before flushing, 35-37% after flushing, 71-83% before sweeping, and 80-120% after sweeping. The CMB method identified six possible sources of TSP as: combustion sources (53.2 ± 11.1%), street dust (12.4 ± 9.3%), nitrate (4.9 ± 1.2%), sulfate (2.9 ± 0.8%), sea salt (1.0 ± 0.3%), and gasoline cars (0.4 ± 0.6%). The simulation results of ISCST3 model showed that road flushing improved annual PM10 from 1.5-2.1% at the 11 monitoring stations operated around Kaohsiung City. After road flushing, the ratios and concentrations of TSP for street dust and combustion sources were reduced. For TSP, road sweeping increased the concentrations of street dust within 30 m downwind of the sampling sites (both sites located downwind at 5 and 30 meters); but reduced it at 200 m downwind. Factor analysis showed rates of street dust for TSP were lower than 28% before street sweeping; lower than 17% after street sweeping. The CMB model revealed that contributed rates of street dust for TSP were lower than 22% before street sweeping, and lower than 34% after street sweeping. The ISCST3 model showed air quality improvements for PM10 in urban areas were greater than in industrial areas. Moreover, the maximum improvement in the annual mean PM10 was around 2 μg/m3.

Assessment of contribution of SO 2 and NO 2 from different sources in Jamshedpur region, India

Contribution of pollution from different types of sources in Jamshedpur, the steel city of India, has been estimated in winter 1993 using two approaches in order to delineate and prioritize air quality management strategies for the development of region in an environmental friendly manner. The first approach mainly aims at preparation of a comprehensive emission inventory and estimation of spatial distribution of pollution loads in terms of SO 2 and NO 2 from different types of industrial, domestic and vehicular sources in the region. The results indicate that industrial sources account for 77% and 68% of the total emissions of SO 2 and NO 2, respectively, in the region, whereas vehicular emissions contributed to about 28% of the total NO 2 emissions. In the second approach, contribution of these sources to ambient air quality levels to which the people are exposed to, was assessed through air pollution dispersion modelling. Ambient concentration levels of SO 2 and NO 2 have been predicted in winter season using the ISCST3 model. The analysis indicates that emissions from industrial sources are responsible for more than 50% of the total SO 2 and NO 2 concentration levels. Vehicular activities contributed to about 40% of NO 2 pollution and domestic fuel combustion contributed to about 38% of SO 2 pollution. Predicted 24-h concentrations were compared with measured concentrations at 11 ambient air monitoring stations and good agreement was noted between the two values. In-depth zone-wise analysis of the above indicates that for effective air quality management, industrial source emissions should be given highest priority, followed by vehicular and domestic sources in Jamshedpur region.

입력변수의 조건에 따른 대기확산모델의 민감도 분석

In order to how well predict ISCST3(lndustrial Source Complex Short Term version 3) model dispersion of air pollutant at point source, sensitivity was analysed necessary parameters change. ISCST3 model is Gaussian plume model. Model calculation was performed with change of the wind speed, atmospheric stability and mixing height while the wind direction and ambient temperature are fixed. Fixed factors are wind direction as the south wind(l80") and temperature as 298 K(25 "C). Model's sensitivity is analyzed as wind speed, atmospheric stability and mixing height change. Data of stack are input by inner diameter of 2m, stack height of 30m, emission temperature of 40 "C, outlet velocity of 10m/s. On the whole, main factor which affects in atmospheric dispersion is wind speed and atmospheric stability at ISCST3 model. However it is effect of atmospheric stability rather than effect of distance downwind. Factor that exert big influence in determining point of maximum concentration is wind speed. Meanwhile, influence of mixing height is a little or almost not.