Respirable particulate matter at an urban and nearby industrial location: concentrations and variability and synoptic weather conditions during high pollution episodes

Continuous data of the concentration measurements of respirable suspended particulates (PM10, particles with aerodynamic diameter smaller than or equal to 10 pm) were analyzed. These measurements were carried out at an urban and nearby industrial location in northern Greece for the 5-year period 1996-2000. The time series concentration trend was examined, the seasonal and diurnal variations were identified, and the lognormality of the daily mean concentration data sets was tested. Over the 5-year data-gathering period, the days on which the U.S. Environmental Protection Agency (EPA) 24-hr PM10 standard was exceeded (episode days) were identified and their relation to prevailing synoptic-scale meteorological conditions was studied. The analysis led to useful information concerning the air quality levels, the contribution of the main pollution sources in this area, as well as some of the mechanisms that influence the PM10 concentrations. It also was proved that the measured PM10 concentrations are a result of a combination of processes including local anthropogenic sources, mesoscale transport, and resuspension. A complex system of sources and meteorological conditions modulate the heavy particulate pollution in the area of interest.     

Evaluation of human exposure to ambient PM10 in the metropolitan area of Mexico City using a GIS-based methodology.

The main goal of this study was to evaluate the magnitude of outdoor exposure to fine particulate matter (PM10) potentially experienced by the population of metropolitan Mexico City. With the use of a geographic information system (GIS), spatially resolved PM10 distributions were generated and linked to the local population. The PM10 concentration exceeded the 24-hr air quality standard of 150 microg/m3 on 16% of the days, and the annual air quality standard of 50 microg/m3 was exceeded by almost twice its value in some places. The basic methodology described in this paper integrates spatial demographic and air quality databases, allowing the evaluation of various air pollution reduction scenarios. Achieving the annual air quality standard would represent a reduction in the annual arithmetic average concentration of 14 microg/m3 for the typical inhabitant. Human exposure to particulate matter (PM) has been associated with mortality and morbidity in Mexico City; reducing the concentration levels of this pollutant would represent a reduction in mortality and morbidity and the associated cost of such impacts. This methodology is critical to assessing the potential benefits of the current initiative to improve air quality implemented by the Environmental Metropolitan Commission of Mexico City.     

Estimation of ambient PM2.5 concentrations in Maryland and verification by measured values

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 microm in aerodynamic diameter (PM23), but did have annual ambient data for PM smaller than 10 microm (PM10) at 24 sites. The PM10 data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM2.5 concentrations at the 24 PM10 monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM2.5 NAAQS of 15 microg/m3, but Maryland's air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM2.5 across central Maryland.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

An enhanced PM_2.5 air quality forecast model based on nonlinear regression (NLR) and back-trajectory concentrations has been developed for use in the Louisville, Kentucky metropolitan area. The PM_2.5 air quality forecast model is designed for use in the warm season, from May through September, when PM_2.5 air quality is more likely to be critical for human health. The enhanced PM_2.5 model consists of a basic NLR model, developed for use with an automated air quality forecast system, and an additional parameter based on upwind PM_2.5 concentration, called PM24. The PM24 parameter is designed to be determined manually, by synthesizing backward air trajectory and regional air quality information to compute 24-h back-trajectory concentrations. The PM24 parameter may be used by air quality forecasters to adjust the forecast provided by the automated forecast system. In this study of the 2007 and 2008 forecast seasons, the enhanced model performed well using forecasted meteorological data and PM24 as input. The enhanced PM_2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24. The two models that included PM24 were of comparable accuracy. The two models incorporating back-trajectory concentrations had lower mean absolute errors and higher rates of detecting unhealthy PM2.5 concentrations compared to the other models.     

Long-term assessment of particulate matter using CHIMERE model

Particulate matter (PM) and aerosols have became a critical pollutant and object of several research applications, due to their increasing levels, especially in urban areas, causing air pollution problems and thus effects on human health. The main purpose of this study is to perform a first long-term air quality assessment for Portugal, regarding aerosols and PM pollution. The CHIMERE chemistry-transport model, forced by the MM5 meteorological fields, was applied over Portugal for 2001 year, with 10 km horizontal resolution, using an emission inventory obtained from a spatial top-down disaggregation of the 2001 national inventory database. The evaluation model exercise shows a model trend to overestimate particulate pollution episodes (peaks) at urban sites, especially in winter season. This could be due to an underprediction of the winter model vertical mixing and also to an overestimation of PM emissions. Simulated inorganic components (ammonium and sulfate) and secondary organic aerosols (SOA) were compared to measurements taken at Aveiro (northwest coast of Portugal). An underestimation of the three components was verified. However, the model is able to predict their seasonal variation. Nevertheless, as a first approach, and despite the complex topography and coastal location of Portugal affected by sea salt natural aerosols emissions, the results obtained show that the model reproduces the PM levels, temporal evolution, and spatial patterns. The concentration maps reveal that the areas with high PM values are covered by the air quality monitoring network.     

Estimating the emission source reduction of PM10 in central Taiwan

Three theoretical parent frequency distributions; lognormal, Weibull and gamma were used to fit the complete set of PM10 data in central Taiwan. The gamma distribution is the best one to represent the performance of high PM10 concentrations. However, the parent distribution sometimes diverges in predicting the high PM10 concentrations. Therefore, two predicting methods, Method I: two-parameter exponential distribution and Method II: asymptotic distribution of extreme value, were used to fit the high PM10 concentration distributions more correctly. The results fitted by the two-parameter exponential distribution are better matched with the actual high PM10 data than that by the parent distributions. Both of the predicting methods can successfully predict the return period and exceedances over a critical concentration in the future year. Moreover, the estimated emission source reductions of PM10 required to meet the air quality standard by Method I and Method II are very close. The estimated emission source reductions of PM10 range from 34% to 48% in central Taiwan.     

Carbon monoxide concentration forecasting in Santiago, Chile

In the city of Santiago, Chile, air quality is defined in terms of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) concentrations. An air quality forecasting model based on past concentrations of PM10 and meteorological conditions currently is used by the metropolitan agency for the environment, which allows restrictions to emissions to be imposed in advance. This model, however, fails to forecast between 40 and 50% of the days considered to be harmful for the inhabitants every year. Given that a high correlation between particulate matter and carbon monoxide (CO) concentrations is observed at monitoring stations in the city, a model for CO concentration forecasting would be a useful tool to complement information about expected air quality in the city. Here, the results of a neural network-based model aimed to forecast maximum values of the 8-hr moving average of CO concentrations for the next day are presented. Forecasts from the neural network model are compared with those produced with linear regressions. The neural network model seems to leave more room to adjust free parameters with 1-yr data to predict the following year's values. We have worked with 3 yr of data measured at the monitoring station located in the zone with the worst air quality in the city of Santiago, Chile.     

Comparisons of statistical characteristic of air pollutants in Taiwan by frequency distribution

The lognormal, Weibull, and type V Pearson distributions were selected to fit the concentration frequency distributions of particulate matter with an aerodynamic diameter of < or = 10 microm (PM10) and SO2 in the Taiwan area. Air quality data from three stations, Hsin-Chu, Shalu, and Gain-Jin, were fitted with three distributions and compared with the measured data. The parameters of unimodal and bimodal fitted distributions were obtained by the methods of maximum likelihood and nonlinear least squares, respectively. Moreover, the root mean square error (RMSE), index of agreement (d), and Kolmogorov-Smirnov (K-S) test were used as criteria to judge the goodness-of-fit of these three distributions. These results show that the frequency distributions of PM10 concentration at the Hsin-Chu and Shalu stations are unimodal, but the distribution at Gain-Jin is bimodal. The distribution type of PM10 concentration varied greatly in different areas and could be influenced by local meteorological conditions. For SO2 concentration distribution, the distributions were all unimodal. The results also show that the lognormal distribution is the more appropriate to represent the PM10 distribution, while the Weibull and lognormal distributions are more suitable to represent the SO2 distribution. Moreover, the days exceeding the air quality standard (AQS) (PM10 > 125 microg/ m3) for the Hsin-Chu, Shalu, and Gain-Jin stations in the coming year are successfully predicted by the theoretic distributions.     

First assessment of the PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript> particulate level in the ambient air of belgrade city

INTENTION, GOAL, SCOPE, BACKGROUND: As the strong negative health effect of exposure to the inhalable particulate matter PM10 in the urban environment has been confirmed, the study of the mass concentrations, physico-chemical characteristics, sources, as well as spatial and temporal variation of atmospheric aerosol particles becomes very important. OBJECTIVE: This work is a pilot study to assess the concentration level of ambient suspended particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade central urban area. Average daily concentrations of PM10 and PM2.5 have been measured at three representative points in the city between June 2002 and December 2002. The influence of meteorological parameters on PM10 and PM2.5 concentrations was analyzed, and possible pollution sources were identified. METHODS: Suspended particles were collected on Pure Teflon filters by using a Mini-Vol low-volume air sampler (Airmetrics Co., Inc.; 5 l min(-1) flow rate). Particle mass was determined gravimetrically after 48 h of conditioning in a desiccator, in a Class 100 clean room at the temperature T = 20 degrees C and at about 50% constant relative humidity (RH). RESULTS AND DISCUSSION: Analysis of the PM10 data indicated a marked difference between season without heating--(summer; mean value 56 microg m(-3)) and heating season--(winter; mean value 96 microg m3); 62% of samples exceeded the level of 50 microg m(-3). The impact of meteorological factors on PM concentrations was not immediately apparent, but there was a significant negative correlation with the wind speed. CONCLUSIONS: The PM10 and PM2.5 mass concentrations in the Belgrade urban area had high average values (77 microg m(-3) and 61 microg m(-3)) in comparison with other European cities. The main sources of particulate matter were traffic emission, road dust resuspension, and individual heating emissions. When the air masses are coming from the SW direction, the contribution from the Obrenovac power plants is evident. During days of exceptionally severe pollution, in both summer and winter periods, high production of secondary aerosols occurred, as can be seen from an increase in PM2.5 in respect to PM10 mass concentration. RECOMMENDATION AND OUTLOOK: The results obtained gave us the first impression of the concentration level of particulate matter, with an aerodynamic diameter of less than 10 microm, in the Belgrade ambient air. Due to measured high PM mass concentrations, it is obvious that it would be very difficult to meet the EU standards (EEC 1999) by 2010. It is necessary to continue with PM10 and PM2.5 sampling; and after comprehensive analysis which includes the results of chemical and physical characterization of particles, we will be able to recommend effective control measures in order to improve air quality in Belgrade.     

Statistical characterization of atmospheric PM10 and PM2.5 concentrations at a non-impacted suburban site of Istanbul, Turkey

Inhalable particulate matter (PM10) has been monitored at several stations by Istanbul Municipality. On the other hand, information about fine fraction aerosols (PM2.5) in Istanbul atmosphere was not reported. In this study, 86 daily aerosol samples were collected between July 2002 and July 2003. The PM10 annual arithmetic mean value of 47.1 microg m(-3), was lower than the Turkish air quality standard of 60 microg m(-3). On the other hand, this value was found higher than the annual European Union air quality PM(10) standard of 40 microg m(-3). Furthermore, the annual mean concentration of PM2.5 20.8 microg m(-3) was found higher than The United States EPA standard of 15 microg m(-3). The statistics and relationships of fine, coarse, and inhalable particles were studied. Cyclic behavior of the monthly average concentrations of PM10 and PM2.5 data were investigated. Several frequency distribution functions were used to fit the measured data. According to Chi-squared and Kolmogorov-Smirnov tests, the frequency distributions of PM2.5 and PM10 data were found to fit Log-logistic functions.     

Patterns and Concentrations of PM10 in a Mountainous Basin Region

ABSTRACT

In this study, continuous data of PM₁₀ (particles with aerodynamic diameter <10 u,m) concentration measurements for a 4-yr period were analyzed. These measurements have been carried out in the Eordea Basin, an industrial area in the northwestern mountainous region of Greece. The annual, monthly, and diurnal patterns are presented and investigated regarding the prevailing meteorological conditions and atmospheric processes that affect the ambient concentrations of PM₁₀. The effect of wind on controlling PM₁₀ concentration is also discussed. Based on the data analysis, an attempt is made to provide useful information about air quality levels, taking into account U.S. Environmental Protection Agency air quality standards.     

Aerosol load study in urban area by Lidar and numerical model

Vertical profiles of particle mass concentration in the urban canopy above the city of Lyon have been obtained from Lidar measurements of atmospheric backscattering, over a period of three days. The concentrations measured at 50 m above the ground have been compared with the mass concentration of PM10 measured by a ground-based sampler located near the Lidar site. At certain times during the measurement campaign, the Lidar concentration measurements at 50 m agree reasonably well with the concentrations at ground level but at other times the differences between the two sets of measurements are so great that they cannot be explained by possible uncertainties in the data processing. Even when the Lidar and ground-based measurements coincide, there are significant differences between the two signals. To explain these differences we have computed the trajectories of the air parcels that pass over the Lidar, using a numerical model for the wind field that takes into account surface features such as relief and changes in roughness. This analysis showed that the differences can be explained by the meteorological conditions (wind speed and direction, vertical profiles of temperature) and the positions of the different sources of particulate matter relative to the measurement site. The combination of Lidar, ground-based sampler and air mass trajectory calculations is shown to be a powerful tool for discriminating between different sources of pollution, which could be useful in enforcing an urban air quality policy.     

Time-resolved measurements of aerosol elemental concentrations in indoor working environments

We have measured the elemental concentrations in aerosols with a 2-h time resolution in two different types of working environment: a chemistry laboratory dealing with the processing of advanced nanoparticulate materials and a medium-sized machine workshop. Non-stop 10-day and 12-day samplings were performed at each location in order to determine the concentration trends during the non-working/working and weekday/weekend periods. Supplementary measurements of PM10 aerosols with a 2-day sample collection time were performed with a standard Gent PM10 sampler to compare the elemental concentrations with the time-averaged concentrations detected by the 2D step-sampler. The concentrations were determined a posteriori by analyzing the x-ray spectra of aerosol samples emitted after 3-MeV proton bombardment. The PM10 samples collected in the chemistry laboratory were additionally inspected by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) to determine the chemical compositions of the individual particles. In the workshop, a total PM10 mass sampling was performed simultaneously with a minute resolution to compare the signal with typical outdoor PM10 concentration levels. A factor analysis of the time-resolved dataset points to six and eight factors in the chemistry laboratory and the machine workshop, respectively. These factors describe most of the data variance, and their composition in terms of different elements can be related to specific indoor activities and conditions. We were able to demonstrate that the elemental concentration sampling with hourly resolution is an excellent tool for studying the indoor air pollution. While sampling the total PM10 mass concentration with a minute resolution may lack the potential to identify the emission sources in a “noisy” environment, the time averaging on a day time scale is too coarse to cope with the working dynamics, even if elemental sensitivity is an option.     

多孔喷嘴PM10-PM2.5串级冲击式大气采样器的研制及应用

多孔喷嘴冲击式大气采样器广泛应用于大气环境监测,相对于单孔喷嘴采样器,它具有压差小、相同空气雷诺数下采样流量大等特点.利用Marple的冲击理论,设计了一种中流量PM10-PM2.5串级冲击式大气采样器,采样流量为100L/min.用该采样器进行实地测量,通过PM2.5/PM10的比值分析,该采样器测量的PM2.5/PM10数据基本与文献报道一致.     

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales,Sonora, Mexico

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States–Mexico border. During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14–30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM₃ concentrations in the range of 134 to 157 μg m^?3 and biomass stoves 163 to 504 μg m^?3. Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM₃: 130 to 770 μg m^?3). The former is evident in the median and range of daytime PM values (median PM₃: 250 μg m^?3, maximum: 9411 μg m^?3), while the meteorological influences appear to be dominant during nighttime periods (median PM₃: 251 μg m^?3, maximum: 10,846 μg m^?3). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 μg m^?3).

Implications:Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States–Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.     

Contribution of residential wood combustion to PM10 levels in Portugal

Wood is commonly used in residential combustion for heating purposes; however, it can be a major source of air pollutants, namely fine particles, volatile organic compounds and carbon monoxide. Since 2004, the PM10 daily limit value has been surpassed in Portugal, and the European Commission has stated that plans and programs must be designed in order to reduce these levels. In Portugal, 18% of PM10 emissions are due to residential wood combustion, which may deeply impact the PM10 levels in the atmosphere. The main aim of this study is to investigate the impact of residential wood combustion on the air quality in Portugal. The air quality modelling system MM5/CHIMERE was applied over Portugal for a winter month, for the following three scenarios: the reference scenario, considering the actual emissions of PM10; scenario 1, where residential wood combustion emissions are not considered; and scenario 2, which takes into account a complete conversion from traditional fireplaces to certified appliances (with a 90% reduction in PM emissions). The residential wood combustion contribution to PM10 air quality concentration values during January 2007 ranges from 0 to 14 μg m^?3, with a mean contribution of 10 μg m^?3 in the Lisboa area and 6 μg m^?3 in the Porto region. Concerning the legislated values, the area where the daily average limit value (50 μg m^?3) is exceeded decreases by 46% in the simulation when residential combustion is not considered. The modelling results for scenario 2 are not significantly different from those for scenario 1. In summary, the regulation of the residential wood combustion sector is as an effective way to reduce the PM10 levels in the atmosphere as regards air quality plans and programs.     

Defining the photochemical contribution to particulate matter in urban areas using time-series analysis

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O3 (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM10 (PM with less than 10 microm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O3, NO or NO2, CO, and SO2. Approximately 3 years of daily average PM10, daily maximum 8-hr average O3 and CO, daily 24-hr average SO2 and NO2, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O3, PM10, NO, NO2, CO, and SO2 series. Cross correlations between PM10 (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM10 and that O3 is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM10 is defined for an urban location, the effect of an O3-control strategy on PM concentrations is estimated by calculating daily PM10 concentrations with reduced O3 concentrations. Forecasted summertime PM10 reductions resulting from a 5 percent decrease in ambient O3 range from 1.2 microg/m3 (3.03%) in Chicago to 3.9 microg/m3 (7.65%) in Phoenix.     

Analysis of temporal and spatial dichotomous PM air samples in the El Paso-Cd. Juarez air quality basin.

This paper presents and discusses the results obtained from the gravimetric and chemical analyses of the 24-hr average dichotomous samples collected from five sites in the El Paso-Cd. Juarez air quality basin between August 1999 and March 2000. Gravimetric analysis was performed to determine the temporal and spatial variations of PM2.5 (particulate matter less than 2.5 microm in diameter) and PM25-10 (particulate matter less than 10 pm but greater than 2.5 microm in diameter) mass concentrations. The results indicate that approximately 25% of the PM10 (i.e., PM25 + PM25-10) concentration is composed of PM2.5. Concurrent measurements of hourly PM concentrations and wind speed showed strong diurnal patterns of the regional PM pollution. Results of X-ray fluorescence (XRF) elemental analyses were compared to similar but limited studies performed by the Texas Natural Resource Conservation Commission (TNRCC) in 1990 and 1997. Major elements from geologic sources-Al, Si, Ca, Na, K, Fe, and Ti-accounted for 35% of the total mass concentrations in the PM2.5-10 fraction, indicating that geologic sources in the area are the dominant PM sources. Levels of toxic trace elements, mainly considered as products of anthropogenic activities, have decreased significantly from those observed in 1990 and 1997.     

冬季沈阳市典型源排放PM10浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月～2007年2月的PM10排放浓度资料,利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明：冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时,污染物扩散范围大,污染物浓度小;地势不平、风速小时,污染物扩散范围小,污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份,污染物分布主要集中在市区的北部、东部和南部地区,东部地区大气污染最为严重。