Mapping the spatial distribution of primary and secondary PM2.5 in a multi-industrial city by combining monitoring and modeling results

Industrial cities are strongly influenced by primary emissions of PM2.5 from local industries. In addition, gaseous precursors, such as sulfur oxides (SOX), nitrogen oxides (NOX), and volatile organic compounds (VOCs), emitted from industrial sources, undergo conversion into secondary inorganic and organic aerosols (SIAs and SOAs). In this study, the spatial distributions of primary and secondary PM2.5 in Ulsan, the largest industrial city in South Korea, were visualized. PM2.5 components (ions, carbons, and metals) and PM2.5 precursors (SO2, NO2, NH3, and VOCs) were measured to estimate the concentrations of secondary inorganic ions (SO42-, NO3-, and NH4+) and secondary organic aerosol formation potential (SOAFP). The spatial distributions of SIAs and SOAs were then plotted by combining atmospheric dispersion modeling, receptor modeling, and monitoring data. Spatial distribution maps of primary and secondary PM2.5 provide fundamental insights for formulating management policies in different districts of Ulsan. For instance, among the five districts in Ulsan, Nam-gu exhibited the highest levels of primary PM2.5 and secondary nitrate. Consequently, controlling both PM2.5 and NO2 emissions becomes essential in this district. The methodology developed in this study successfully identified areas with dominant contributions from both primary emissions and secondary formation. This approach can be further applied to prioritize control measures during periods of elevated PM levels in other industrial cities.

Space-specific flux estimation of atmospheric chemicals from point sources to soil

Predicting chemical flux to soil from industrial point sources accurately at a regional scale has been a significant challenge due to high uncertainty in spatial heterogeneity and quantification. To address this challenge, we developed an innovative approach by combining California Air Resources Board Puff (CALPUFF) and mass balance models, leveraging their complementary strengths in quantitative accuracy and spatial precision. Specifically, CALPUFF was used to predict the polycyclic aromatic hydrocarbons (PAHs) flux to soil due to industrial sources. Additionally, the spatial distribution coefficient of PAHs flux (e.g., si for spatial unit i) was calculated by neural network and combined with the mass balance model to obtain the results of total PAHs fluxes, which were then combined with the results predicted by CALPUFF to effectively estimate the contribution of industrial sources to soil PAHs flux. Taking a petrochemical industry region located in Zhejiang province, China as a case study, results showed the input Phenanthrene (Phe) and Benzo(a)pyrene (BaP) fluxes predicted by CALPUFF were generally lower than those by the mass balance model, with slightly different distribution patterns. CALPUFF results, based on 36 industrial sources, partially represent those of the mass balance model, which includes all sources and pathways. It was suggested that industrial sources contributed 49%-89% and 65%-100% of soil Phe and BaP, respectively across the study area. The average Phe flux from point sources by deposition averaged 2.68 mg m-2∙a-1 in 2021, accounting for approximately 60% of the total Phe flux to soil. The average BaP flux from point sources by deposition averaged 0.0755 mg m-2∙a-1, accounting for only 0.1%-3.65% of the total BaP flux to soil. Thereby, our approach fills up a gap between the relevance to point sources and the accuracy of deposition quantification in estimating chemical flux from specific point sources to soil at a regional scale.

Towards quantifying atmospheric dispersion of pesticide spray drift in Yuma County Arizona

While pesticide vapor and particles from agricultural spray drift have been reported to pose a risk to public health, limited baseline ambient measurements exist to warrant an accurate assessment of their impacts at community-to-county-wide scale. Here, we present an initial modeling investigation of the transport and deposition of applied pesticides in an agricultural county in Arizona (Yuma County), to provide initial estimates on the corresponding enhancements in ambient levels of these spray drifts downwind of application sites. With a 50 × 50 km domain, we use the dispersion model CALPUFF with meteorology from the Weather Research and Forecasting (WRF) to investigate the spatiotemporal distribution of pesticide abundance due to spray drift from a representative sample of nine application sites. Data records for nine application days in September and October 2011, which are the peak months of pesticide application, were retroactively simulated for 48-h for all nine application sites using an active ingredient lambda-cyhalothrin, which is a commonly-used pesticide in the county. Twenty-one WRF/CALPUFF simulations were conducted with varying emissions, chemical lifetime, deposition rate, application height, and meteorology inputs, allowing for an ensemble-based analysis on the possible ranges in modeled abundance. Our results show that dispersion of vapors released at time of application heavily depends on prevailing meteorology, particularly wind speed and direction. Dispersion is limited to thin plumes that are easily transported out of the domain. The ensemble-mean vapor concentrations of the 48-h average (> 90 percentile domain-wide) range from 0.2 nanograms (ng)/m3 to 200 ng/m3, and the peak can be as high as 1000 ng/m3 near the application sites. Pesticide particles are mainly deposited within 1-2 km from the application sites at an average rate of 106 ng/km2/h but vary with particle mean diameter and standard deviation. While these findings are generally consistent with reported ambient levels in the literature, the associated ensemble-spread on these estimates are in the same order of magnitude as their ensemble-mean. At the two nearby communities downwind of these sites, we find that peak vapor concentrations are less than 50 ng/m3 with exposure times of less than an hour, as approximately 99.4% of the vapors are advected out and 99.5% of the particles deposit within the domain. Results of this study indicate pesticide spray drift from a sample of application sites and representative days in Fall may have a limited impact on neighboring communities. However, we strongly suggest that field measurements should be collected for model validation and more rigorous investigation of the actual scale of these impacts when the bulk of pesticide applications across the county, variation in active pesticide ingredients, and potential resuspension of deposited particles are considered.

Contributions of the oil sands sources to the ambient concentrations and deposition of particulate elements in the Canadian Athabasca oil sands region

In this study, model sensitivity tests were conducted to investigate the relative contributions between emission sources of oil sands (OS) activities and other sources to the ambient concentrations and deposition of 29 particulate elements in the Athabasca oil sands region (AOSR) of Canada. Element emission sources from a recently developed emission database were grouped into three source sectors for elements in PM2.5 (OS-Industrial, OS-Dust, and Non-OS) and two source sectors for elements in PM2.5-10 (OS-All and Non-OS). The OS-Dust and OS-Industrial sectors (combined as one sector for PM2.5-10; OS-All) included element sources linked to dust and other industrial activities from the OS activities, respectively, whereas the Non-OS sector included remaining sources in the region, unrelated to the OS activities. The OS-Industrial, OS-Dust, and Non-OS emissions (tonnes/year) of all elements in PM2.5 were 326, 1430, and 562, respectively. The OS-All and Non-OS emissions (tonnes/year) of all elements in PM2.5-10 were 5890 and 2900, respectively. The element concentrations were simulated by the CALPUFF dispersion model. The sum of the domain averaged annual mean concentrations of all elements in PM2.5 and PM2.5-10 from all sources were 57.3 ng/m3 and 30.4 ng/m3, respectively. Except for Co (PM2.5 and PM2.5-10), Sb (PM2.5-10), and Sn (PM2.5-10), major proportions (≥ 59 %) of the ambient concentrations of the individual elements were linked to the OS source sector. Overall, the OS sector was responsible for 78 % and 68 % of the sum of the mean ambient concentrations of all elements in PM2.5 and PM2.5-10, respectively, which are close to the corresponding emission contributions (76 % and 67 %, respectively). Likewise, the bulk proportion (∼74 %) of the sum of the total atmospheric deposition of all elements was also associated with the OS sources. Carcinogenic and non-carcinogenic risks associated with inhalation exposure to airborne elements were below the recommended threshold risk levels.

Regional Transport of PM2.5 from Coal-Fired Power Plants in the Fenwei Plain, China

The Fenwei Plain (FWP) remains one of the worst PM2.5-polluted regions in China, although its air quality has improved in recent years. To evaluate the regional transport characteristics of PM2.5 emitted by coal-fired power plants in the FWP in wintertime, the primary PM2.5, SO2, and NOx emissions from coal-fired power plants with large units (≥300 MW) in 11 cities of the area in January 2019 were collected based on the Continuous Emission Monitoring System (CEMS). The spatial distribution and source contribution of primary and secondary PM2.5 concentrations were investigated using the Weather Research and Forecast (WRF) model and the California Puff (CALPUFF) model. The results showed that secondary PM2.5 was transported over a larger range than primary PM2.5 and that secondary nitrate was the main component of the total PM2.5 concentration, accounting for more than 70%. High concentrations of primary, secondary, and total PM2.5 mainly occurred in the Shaanxi region of the FWP, especially in Xianyang, where the PM2.5 concentrations were the highest among the 11 cities, even though its pollutant emissions were at moderate levels. The PM2.5 concentrations in Sanmenxia and Yuncheng primarily came from regional transport, accounting for 64% and 68%, respectively, while those in other cities were dominated by local emissions, accounting for more than 63%. The results may help to understand the regional transport characteristics of pollutants emitted from elevated point sources over a complex terrain.

Assessment of meteorological settings on air quality modeling system-a proposal for UN-SDG and regulatory studies in non-homogeneous regions in Brazil

Air quality models are essential tools to meet the United Nations Sustainable Development Goals (UN-SDG) because they are effective in guiding public policies for the management of air pollutant emissions and their impacts on the environment and human health. Despite its importance, Brazil still lacks a guide for choosing and setting air quality models for regulatory purposes. Based on this, the current research aims to assess the combined WRF/CALMET/CALPUFF models for representing SO₂ dispersion over non-homogeneous regions as a regulatory model for policies in Brazilian Metropolitan Regions to satisfy the UN-SDG. The combined system was applied to the Rio de Janeiro Metropolitan Area (RJMA), which is known for its physiographic complexity. In the first step, the WRF model was evaluated against surface-observed data. The local circulation was underestimated, while the prevailing observational winds were well represented. In the second step, it was verified that all CALMET three meteorological configurations performed better for the most frequent wind speed classes so that the largest SO₂ concentrations errors occurred during light winds. Among the meteorological settings in WRF/CALMET/CALPUFF, the joined use of observed and modeled meteorological data yielded the best results for the dispersion of pollutants. This result emphasizes the relevance of meteorological data composition in complex regions with unsatisfactory monitoring given the inherent limitations of prognostic models and the excessive extrapolation of observed data that can generate distortions of reality. This research concludes with the proposal of the WRF/CALMET/CALPUFF air quality regulatory system as a supporting tool for policies in the Brazilian Metropolitan Regions in the framework of the UN-SDG, particularly in non-homogeneous regions where steady-state Gaussian models are not applicable.

Application and validation of the fugitive dust source emission inventory compilation method in Xiong'an New Area, China

The development of a refined fugitive dust emission inventory is vital for prevention and control of air pollution. In this study, a fugitive dust emission inventory of soil dust (SD), road dust (RD), and construction dust (CD) in Xiong'an New Area (XANA) for 2020 was developed by collecting activity data and combining remote sensing and field investigation data based on a popular compilation technology in China. The CALPUFF model was used to elucidate the contribution characteristics of dust sources to ambient particulate matter (PM), and the accuracy of the dust emission inventory compilation method was verified. The results show that the total emissions of PM₁₀ and PM_2.5 were 43,081.14 tons and 9701.69 tons, respectively. Meanwhile, RD and CD were the main emission sources, accounting for over 98.49% of the total emissions. The total contribution from the different types of dust sources to the ambient PM₁₀ was 42.59 μg/m³ (29.38%), with the contribution of RD (32.63 μg/m³, 22.51%) being approximately three times that of CD (9.78 μg/m³, 6.74%). Roads were the main source of fugitive dust, but large-scale infrastructure construction was the main cause of the high emission and high contribution of RD. The results show that the emission inventory compilation method can be used to estimate the emissions of dust sources, while the method used to calculate the emission of SD may be more suitable for dry and semi-dry areas with less rainfall. It was also found that when the dust emissions stay stable, the contribution of dust sources to the ambient PM₁₀ in different seasons can vary by 3-4 times. Therefore, under adverse meteorological conditions, it is necessary to strengthen the control of various dust sources and reduce the influence of human factors on them.

Mercury atmospheric emission, deposition and isotopic fingerprinting from major coal-fired power plants in Australia: Insights from palaeo-environmental analysis from sediment cores

Despite Australia's high reliance on coal for electricity generation, no study has addressed the extent to which mercury (Hg) deposition has increased since the commissioning of coal-fired power plants. We present stratigraphic data from lake sediments in the Hunter Valley (New South Wales) and Latrobe Valley (Victoria), where a significant proportion of Australia's electricity is generated via coal combustion. Mercury deposition in lake sediments increased in the 1970s with the commissioning of coal-fired power plants, by a factor of 2.9-times in sediments of Lake Glenbawn (Hunter Valley) and 14-times in Traralgon Reservoir (Latrobe Valley). Sediments deposited after the commissioning of power plants have distinct Hg isotope compositions, similar to those of combusted coals. Mercury emission, estimated using an atmospheric model (CALPUFF), was higher in the Latrobe Valley than in the Hunter Valley. This is a result of higher Hg concentrations in lignite coal, lax regulation and older pollution-control technologies adopted by coal-fired power plants in the Latrobe Valley. Near-source deposition of Hg in Australia is significantly higher than North America and Europe, where better emission controls (e.g. wet flue gas desulfurization) have been in effect for decades. The challenge for Australia in years to come will be to ratify the Minamata Convention and develop better regulation policies to reduce Hg emissions.

Inter-city air pollutant transport in The Beijing-Tianjin-Hebei urban agglomeration: Comparison between the winters of 2012 and 2016

In recent years, with the continual urbanization of China, regional atmospheric environmental problems have become increasingly prominent. Although local emissions are an important cause of local pollution, the cross-boundary transmission of pollutants between cities also has an inevitable impact on regional pollution. In this study, the Weather Research and Forecasting (WRF) model coupled with the California Puff (CALPUFF) air quality model was used to study the transmission characteristics of four major air pollutants (SO₂, NO_x, PM_2.5 and PM₁₀) in the Beijing-Tianjin-Hebei urban agglomeration in China in winter, which is the season characterized by the highest levels of pollution. This urban agglomeration is the most polluted area in China. We compared the emission and transmission of pollutants at the city level based on data for January 2012 and 2016. We found that the emissions of most cities had declined since the implementation, in 2013, of the "Action Plan for the Prevention and Control of Air Pollution". However, the emissions of three cities, Zhangjiakou, Chengde and Baoding, had significantly increased. Furthermore, the "receptor cities" and "source cities" also showed some changes. For example, in 2016, Chengde and Zhangjiakou changed from receptor to source cities, while Tangshan and Tianjin showed the opposite change in status. The likely reason for these changes was that some industries in heavily polluted cities had moved due to stringent atmospheric pollution policies. Moreover, the transmission range of source cities (e.g., Shijiazhuang) in 2016 was significantly smaller than that in 2012, and the transmission intensity also decreased. This case study aids our understanding of how inter-city air pollution transmission has been affected by environmental policy.

Use of dispersion model and satellite SO2 retrievals for environmental impact assessment of coal-fired power plants

The aim of this study is to investigate the impact of ten proposed plants along with three operating plants in Çanakkale province of Turkey where the proposed plants are within very close proximity. The province has the highest capacity of the planned plants and the region is also of interest due to its history, tourism and agriculture potential. Current SO₂ pollution was assessed using ground observations and satellite retrievals where the impact of plants was better captured by satellite retrievals. Individual and cumulative impact from proposed and operating plants was simulated by CALPUFF for 2014. The study domain was 150 × 150 km², with 1 × 1 km² cell size. The effect of changing meteorological inputs and domain size were investigated with simulations. Three cases were performed using meteorological inputs: from one surface and one radiosonde station (Case 1), 22 surface and one radiosonde station (Case 2), and 22 surface and two radiosonde stations (Case 3). Case 2 and 3 resulted in higher concentrations and showed larger affected regions than case 1 in all simulations. The cumulative impact of proposed plants indicated national annual and daily limit values were exceeded in Case 2 and 3. Hourly limit values were exceeded in all three cases. Simulations for two selected proposed plants were assessed for plant impact area given in environmental impact area reports. Results indicated the plant impact areas cannot be sufficient to determine the maximum SO₂ concentrations in some cases and using single meteorology station data cannot represent the study area, especially regions with complex terrain and land-sea interactions such as Çanakkale province. Cumulative impact can be underestimated due to small size of plant impact areas not including other plants. Lastly satellite retrievals are better capturing the pollution than air quality monitoring stations which are strongly affected by meteorology.

Co-benefits analysis of energy cascade utilization in an industrial park in China

As an important role in economic development in China, industrial parks have consumed plenty of energy, while emitting enormous air pollutants and discharging large quantities of waste heat. Energy cascade utilization is an effective way to improve the energy efficiency of industrial parks. The objective of this study was to assess the co-benefits of energy cascade utilization, including the energy savings potential, reduction potential of air pollutants, and air quality improvements, in an industrial park in China. Through an energy flow analysis of steam at different pressures and residual gas among various enterprises, this study identified the existing energy cascade utilization network in a baseline scenario and proposed an enhanced scenario. To evaluate the co-benefits of these two scenarios, the CALPUFF model was used to integrate energy savings and air pollutant mitigation for the park in 2017. The results show that energy cascade utilization can result in considerable co-benefits related to energy conservation, air pollutant emission reductions, and air quality improvements. In the enhanced scenario, the total energy savings potential is 11,425 TJ, with emission reductions of 859 tons of SO₂ and 910 tons of NO_x. Based on the CALPUFF simulations of SO₂ and NO_x diffusion in the four seasons, the concentrations of SO₂ and NO_x in the study area considerably decreased in the enhanced scenario compared with those in the baseline scenario. This study demonstrates that the park should focus on the cascade utilization of waste heat and residual gas to improve the energy utilization efficiency and reduce atmospheric pollutant emissions.

Use of CALPUFF to predict airborne Mn levels at schools in an urban area impacted by a nearby manganese alloy plant

Children are susceptible to the health effects derived from elevated manganese (Mn) environmental exposure; residents living in urban areas where ferromanganese alloy plants are located are usually exposed to high Mn levels. In this work, a dispersion model developed by the USEPA, CALPUFF, has been used to estimate the airborne Mn levels near educational centers located in Santander bay, Northern Spain, an urban area where high Mn levels have been measured in the last decade. The CALPUFF model was validated in a previous work from a multi-site one-year observation dataset. Air manganese levels in 96 primary, secondary and high schools located in Santander bay were estimated using the CALPUFF model for two months corresponding to warm and cold periods using real meteorological data and Mn emission rates corresponding to different emission scenarios. Results show that when the emission scenario that best represented the observations dataset is used, the air Mn levels exceed the WHO guideline (i.e. 150 ng Mn/m³) in 24% and 11% of the studied schools in the cold and warm periods respectively. These exceedances depend on the distance from the FeMn alloy plant and the direction of the prevailing winds. Additional emission scenarios based on the implementation of preventive and corrective measures are simulated and analysed in terms of the number of exceedances of the WHO guideline. The age range of children has been also considered in the analysis.

Estimation of PM10-bound manganese concentration near a ferromanganese alloy plant by atmospheric dispersion modelling

Numerous studies have associated air manganese (Mn) exposure with negative health effects, primarily neurotoxic disorders. This work presents a description of the emission and dispersion of PM₁₀-bound Mn from industrial sources in the Santander bay area, Northern Spain. A detailed day-specific emission estimation was made and assessed for the main Mn source, a manganese alloy production plant under 8 different scenarios. Dispersion analysis of PM₁₀-bound Mn was performed using the CALPUFF model. The model was validated from an observation dataset including 101 daily samples from four sites located in the vicinities of the manganese alloy plant. Model results were in reasonable agreement with observations (r = 0.37; NMSE = 2.08; Fractional Bias = 0.44 and Modelled/Observed ratio = 1.57). Simulated and observed Mn concentrations in the study area were much higher than the guidelines proposed by the World Health Organization (WHO) and the U.S. Environmental Protection Agency (USEPA), highlighting the need to reduce the Mn concentrations in the area. Based on the analysis of the Mn source contribution from the ferromanganese alloy plant, some preventive and corrective measures are discussed at the end of the paper. This work shows that CALPUFF dispersion model can be used to predict PM₁₀-bound Mn concentrations with reasonable accuracy in the vicinities of industrial facilities allowing the exposure assessment of the nearby population, which can be used in future epidemiological studies.

Dust emission and dispersion from mineral storage piles

Dust pollution is a complex problem of growing interest because of its environmental, health, economic and political impact. Environmental impact assessment methods for dust pollution management are often based on the simulation of dust dispersion, which requires a precise characterization of the source term and of the source parameters. The source term model should be as simple and as accurate as possible and requires low time consumption in order to be easily connected to a more complex algorithm for the dispersion calculations. This work focuses on dust emissions from mineral storage piles, which are usually modelled as source terms by means of the algorithm proposed in the AP-42 US EPA standard. Unfortunately, this algorithm tends to overestimate emissions, and when coupled with a Gaussian dispersion model, it leads to inaccurate results in terms of estimation of both concentration and spatial distribution. This paper proposes a new methodology drawn from the original standard US EPA AP-42 https://www3.epa.gov/ttnchie1/ap42/ch13/ scheme with the purpose to account for the actual dynamics of erosion and to enhance the accuracy of the concentration and the pollutant spatial distribution assessment, thereby considering the effects of the wind interactions. The standard EPA methodology and the new one were compared by means of the AERMOD and CALPUFF dispersion models. Results are superimposable in terms of concentration values, leading to a quantification of the same order of magnitude, although with a different and more variable spatial distribution.

Atmospheric dispersion of radon around uranium mill tailings of the former Pridneprovsky Chemical Plant in Ukraine

Simulations of atmospheric dispersion of radon around the uranium mill tailings of the former Pridneprovsky Chemical Plant (PChP) in Ukraine were carried out with the aid of two atmospheric dispersion models: the Airviro Grid Model and the CALMET/CALPUFF model chain. The available measurement data of radon emission rates taken in the territories and the close vicinity of tailings were used in simulations. The results of simulations were compared to the yearly averaged measurements of concentration data. Both models were able to reasonably reproduce average radon concentration at the Sukhachivske site using averaged measured emission rates as input together with the measured meteorological data. At the same time, both models significantly underestimated concentrations as compared to measurements collected at the PChP industrial site. According to the results of both dispersion models, it was shown that only addition of significant radon emission rate from the whole territory of PChP in addition to emission rates from the tailings could explain the observed concentration measurements. With the aid of the uncertainty analysis, the radon emission rate from the whole territory of PChP was estimated to be between 1.5 and 3.5 Bq·m^-2s^-1.

The modelling of odour dispersion as a support tool for the improvements of high odours impact plants

Two scenarios in terms of odour impact assessment were studied during the phase of upgrading of an existing waste treatment plant: CALPUFF was used for the simulation of odour dispersion. Olfactometric measures, carried out over different periods and different positions in the plant, were used for model calibration. Results from simulations were reported in terms of statistics of odour concentrations and isopleths maps of the 98th percentile of the hourly peak concentrations, as requested from the European legislation and standards. The excess perception thresholds and emissions were utilized to address the plant upgrade options. The hourly evaluation of odours was performed to determine the most impacting period of the day. An inverse application of the numerical simulation starting from defining the odour threshold at the receptor was made to allow the definition of the required abatement efficiency at the odours source location. Results from the proposed approach confirmed the likelihood to adopt odour dispersion modelling, not only in the authorization phase, but also as a tool for driving technical and managing actions in plant upgrade so to reduce impacts and improve the public acceptance. The upgrade actions in order to achieve the expected efficiency are reported as well.

Comparison of AERMOD and CALPUFF models for simulating SO2 concentrations in a gas refinery

In this study, concentration of SO2 from a gas refinery located in complex terrain was calculated by the steady-state, AERMOD model, and nonsteady-state CALPUFF model. First, in four seasons, SO2 concentrations emitted from 16 refinery stacks, in nine receptors, were obtained by field measurements, and then the performance of both models was evaluated. Then, the simulated results for SO2 ambient concentrations made by each model were compared with the results of the observed concentrations, and model results were compared among themselves. The evaluation of the two models to simulate SO2 concentrations was based on the statistical analysis and Q-Q plots. Review of statistical parameters and Q-Q plots has shown that, according to the evaluation of estimations made, performance of both models to simulate the concentration of SO2 in the region can be considered acceptable. The results showed the AERMOD composite ratio between simulated values made by models and the observed values in various receptors for all four average times is 0.72, whereas CALPUFF's ratio is 0.89. However, in the complex conditions of topography, CALPUFF offers better agreement with the observed concentrations.

Dispersion of TSP and PM(10) emissions from quarries in complex terrain

This study evaluates AERMOD and CALPUFF dispersion calculations of particulate matter emissions from stone quarries in two mountainous regions against TSP and PM10 measurements, using both observational and WRF-modeled meteorological data. Due to different model parameterization, AERMOD dispersion predictions were in better agreement with the measured concentrations than those obtained by CALPUFF. As expected, the smaller the distance between the meteorological station, the source (quarry) and the receptors, the better the predictions of both AERMOD and CALPUFF. In contrast, using in-situ wind field obtained by runs of the WRF meteorological model for the complex terrain study area provided, in general, less accurate dispersion estimates than when using (even remote) meteorological observations. In particular, using the three-dimensional WRF-modeled wind field within CALPUFF did not provide any advantage over using the two-dimensional wind field, which is the common procedure of AERMOD and CALPUFF. Dry deposition was more significant for ambient concentration estimation in AERMOD than in CALPUFF.

Quantification of emissions from domestic heating in residential areas of İzmir, Turkey and assessment of the impact on local/regional air-quality

Air pollution in cities is a major environmental problem principally in the developing countries. The quantification of emissions is a basic requirement to assess the human influence to the atmosphere. The air quality generally shows decreases with the major contribution residential emissions and meteorology in the winter season in the big cities. Poor meteorological conditions especially inversion events for the efficient mixing of air pollutants occurred during the winter months in İzmir. With this work we quantify the amount of domestic heating emissions for particulate matter (PM10), sulfur dioxides (SO2), nitrogen dioxides (NO2), volatile organic compounds (VOC) and carbon monoxide (CO) together with greenhouse gases which are carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) in İzmir for 2008-2009 winter season. The results showed that the most affected residential areas were central districts in the city center from domestic heating emissions due to meteorological condition and demographic reasons. Air quality modeling is a great tool for assisting policy makers how to decrease emissions and improve air quality. At the second part of the study, calculated emissions were modeled by using CALMET/CALPUFF dispersion modeling system and plotted in the form of air pollution maps by using geographical information system to determine the locations and estimate the effects of the new residential areas that will be established in the future in İzmir.