CityDelta: A model intercomparison study to explore the impact of emission reductions in European cities in 2010

This paper gives an overview of the set up, methodology and the obtained results of the CityDelta (phase 1 and 2) project. In the context of the Clean Air For Europe programme of the European Commission, the CityDelta project was designed to evaluate the impact of emission-reduction strategies on air quality at the European continental scale and in European cities. Ozone and particulate matter (PM) are the main components that have been studied. To achieve this goal, a model intercomparison study was organized with the participation of more than 20 modelling groups with a large number of modelling configurations. Two following main topics can be identified in the project. First, in order to evaluate their strengths and weaknesses, the participating models were evaluated against observations in a control year (1999). An accompanying paper will discuss in detail this evaluation aspect for four European cities. The second topic is the actual evaluation of the impact of emission reductions on levels of ozone and PM, with particular attention to the differences between large-scale and fine-scale models. An accompanying paper will discuss this point in detail. In this overview paper the main input to the intercomparison is described as well as the use of the ensemble approach. Finally, attention is given to the policy relevant issue on how to implement the urban air quality signal into large-scale air quality models through the use of functional relationships.     

Implications of high altitude desert dust transport from Western Sahara to Nile Delta during biomass burning season

The air over major cities and rural regions of the Nile Delta is highly polluted during autumn which is the biomass burning season, locally known as black cloud. Previous studies have attributed the increased pollution levels during the black cloud season to the biomass or open burning of agricultural waste, vehicular, industrial emissions, and secondary aerosols. However, new multi-sensor observations (column and vertical profiles) from satellites, dust transport models and associated meteorology present a different picture of the autumn pollution. Here we show, for the first time, the evidence of long range transport of dust at high altitude (2.5-6 km) from Western Sahara and its deposition over the Nile Delta region unlike current Models. The desert dust is found to be a major contributor to the local air quality which was previously considered to be due to pollution from biomass burning enhanced by the dominant northerly winds coming from Europe.     

Analysis of model responses to emission-reduction scenarios within the CityDelta project

This paper investigates how air quality models applied at different scales (50 and 5 km horizontal resolutions) can predict pollution levels in response to emission control strategies in various cities in Europe. This study, involving five modelling teams and focused on four European cities, has been conducted within the CityDelta project (http://aqm.jrc.it/citydelta). The CityDelta models generally agree, on the O₃ changes expected from scenarios representative of the current legislation on air pollution in 2010, named CLE. They also agree about less scope for further improvements from emission controls beyond CLE. For PM₁₀, more significant differences between the models are observed, especially between models with different spatial resolutions. However, these differences are city-dependent and are larger in complex geographical areas such as Milan in the Pô Valley than in the Paris area.Fine scale models generally capture important urban scale effects, which are not represented by regional scale models. For instance, they improve the simulation of potential O₃ increase caused by NO_x emissions reduction in NMVOC-limited regime situations. Large scale models generally underpredict PM mean concentrations in city areas. A series of emission scenarios to address the question of the efficiency of local emission controls designed independently from regional measures is analyzed. The analysis of the CityDelta results contributes to the quantification of the impact of grid resolution in air quality modelling, and its application to emission control scenarios.     

An assessment of the impact of California's Phase 2 Reformulated Gasoline on ozone air quality

California's Phase 2 Reformulated Gasoline (CaRFG), introduced early in 1996, represents an important step toward attainment of ozone standards. Studies of vehicle emissions and ambient air quality data have reported substantial reductions of ozone precursors due to CaRFG. This study uses daily measurements of regional ozone and meteorology to estimate the effect of CaRFG on ozone concentrations in three areas of California. In each area, a regression model was used to partially account for the daily effects of meteorology on area-wide ozone maxima for May-October. The statistical models are based on combinations of air temperature aloft (approximately 5000 ft), surface air temperatures, and surface wind speeds. Estimated ozone benefits were attributed to CaRFG after accounting for meteorology, which improved the precision of the estimates by approximately 37-57% based on a resampling analysis. The ozone benefits were calculated as the difference in ozone times the proportion of the reductions of hydrocarbons and nitrogen oxides attributed to CaRFG by the best available emission inventories. Ozone benefits attributed to CaRFG (with approximately 90% confidence) are 8-13% in the Los Angeles area, -2-6% in the San Francisco Bay area overall with greater benefits in two major subregions, and 3-15% in the Sacramento area.     

Verification of a source-oriented externally mixed air quality model during a severe photochemical smog episode

The CIT/UCD three-dimensional source-oriented externally mixed air quality model is tested during a severe photochemical smog episode (Los Angeles, 7–9 September 1993) using two different chemical mechanisms that describe the formation of ozone and secondary reaction products. The first chemical mechanism is the secondary organic aerosol mechanism (SOAM) that is based on SAPRC90 with extensions to describe the formation of condensable organic products. The second chemical mechanism is the caltech atmospheric chemistry mechanism (CACM) that is based on SAPRC99 with more detailed treatment of organic oxidation products.The predicted ozone concentrations from the CIT/UCD/SOAM and the CIT/UCD/CACM models agree well with the observations made at most monitoring sites with a mean normalized error of approximately 0.4–0.5. Good agreement is generally found between the predicted and measured NO_x concentrations except during morning rush hours of 6–10 am when NO_x concentrations are under-predicted at most locations. Total VOC concentrations predicted by the two chemical mechanisms agree reasonably well with the observations at three of the four sites where measurements were made. Gas-phase concentrations of phenolic compounds and benzaldehyde predicted by the UCD/CIT/CACM model are higher than the measured concentrations whereas the predicted concentrations of other aromatic compounds approximately agree with the measured values.The fine airborne particulate matter mass concentrations (PM_2.5) predicted by the UCD/CIT/SOAM and UCD/CIT/CACM models are slightly greater than the observed values during evening hours and lower than observed values during morning rush hours. The evening over-predictions are driven by an excess of nitrate, ammonium ion and sulfate. The UCD/CIT/CACM model predicts higher nighttime concentrations of gaseous precursors leading to the formation of particulate nitrate than the UCD/CIT/SOAM model. Elemental carbon and total organic mass are under-predicted by both models during morning rush hour periods. When this latter finding is combined with the NO_x under-predictions that occur at the same time, it suggests a systematic bias in the diesel engine emissions inventory. The mass of particulate total organic carbon is under-predicted by both the UCD/CIT/SOAM and UCD/CIT/CACM models during afternoon hours. Elemental carbon concentrations generally agree with the observations at this time. Both the UCD/CIT/SOAM and UCD/CIT/CACM models predict low concentrations of secondary organic aerosol (SOA) (<3.5 μg m⁻³) indicating that both models could be missing SOA formation pathways. The representation of the aerosol as an internal mixture vs. a source-oriented external mixture did not significantly affect the predicted concentrations during the current study.     

Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains. Part I: Hourly and Seasonal Ozone

Abstract

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI’s assessment.     

Testing the capability of the chemistry transport model LOTOS-EUROS to forecast PM10 levels in the Netherlands

Since particulate matter has a direct and adverse impact on public health, a good air quality forecast is important. Several European countries presently use statistical forecasting models, which have their limitations, especially for PM10. An alternative approach is to use a chemistry transport model. Here, the ability of the chemical transport model LOTOS-EUROS to forecast PM10 concentrations in the Netherlands was investigated. LOTOS-EUROS models several PM10 components individually. For sulphate, nitrate and ammonium aerosol the evaluation against observations shows that the modelled annual mean concentrations are within 20% of the measured concentration and that the temporal correlation is reasonably good (R > 0.6). For sea salt the model tended to overestimate the measured concentrations. For elemental carbon the correspondence with black smoke observations was reasonable. However, total PM10 is seriously underestimated, due to unmodelled components (secondary organic aerosols, mineral dust) and missing sources. Therefore, a simple bias correction for four seasons was derived based on the years 2004–2006. The model was compared with the Dutch operational statistical model PROPART and ground-level observations. With bias correction, LOTOS-EUROS performed better than PROPART regarding the timing of events. The major flaw of LOTOS-EUROS was that high values (>50 μg m^?3) were still underestimated. Another advantage of LOTOS-EUROS over the statistical model was the more detailed information in space and time, which facilitates communication of the forecast to the general public.     

Urban emissions measured with aircraft

Detailed knowledge of the quantity and composition of urban emissions is a prerequisite for successful application of atmospheric models to predict transport and distribution of primary and secondary air pollutants in the troposphere. We investigate the prospects and limitations of aircraft measurements in the determination of emission fluxes from urban areas. Our analysis focuses on data collected in September 1994 in and around Athens, Greece. Generally, emission fluxes from cities can be quantified with aircraft and with the minimum acceptable precision (uncertainty better than a factor of 2) only under very favorable meteorological conditions, namely in a homogeneous flow field in a well-mixed boundary layer. Better accuracy can be achieved only through ensemble averaging of repeated measurements. From our measurements in the Athens area, we deduced relative emission ratios of pollutant gases. With the support of ground-based measurements in a street canyon, the emission ratios NOx/CO, SO2/CO, and volatile organic compounds/CO (34 individual VOCs) could be determined with high precision. These results are very useful in analyzing differences between various existing emission inventories. Our data for VOCs reveal that the non-traffic emissions are of the same magnitude as the emissions originating from traffic.     

Simulating industrial emissions using atmospheric dispersion modeling system: model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM10) and sulfur dioxide (SO2)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement 'd' values reaching 0.58, fractional bias 'FB' and geometric mean bias 'MG' values approaching 0 and 1, respectively, and normalized mean square error 'NMSE' values as low as 2.17. However, median ratios of predicted to observed concentrations 'Cp/Co' at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NOx, CO, PM10 and SO2, respectively, and the fraction of predictions within a factor of two of observations 'FAC2' values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.     

Ozone predictions in Atlanta, Georgia: analysis of the 1999 ozone season

Ozone prediction has become an important activity in many U.S. ozone nonattainment areas. In this study, we describe the ozone prediction program in the Atlanta metropolitan area and analyze the performance of this program during the 1999 ozone-forecasting season. From May to September, a team of 10 air quality regulators, meteorologists, and atmospheric scientists made a daily prediction of the next-day maximum 8-hr average ozone concentration. The daily forecast was made aided by two linear regression models, a 3-dimensional air quality model, and the no-skill ozone persistence model. The team's performance is compared with the numerical models using several numerical indicators. Our analysis indicated that (1) the team correctly predicted next-day peak ozone concentrations 84% of the time, (2) the two linear regression models had a better performance than a 3-dimensional air quality model, (3) persistence was a strong predictor of ozone concentrations with a performance of 78%, and (4) about half of the team's wrong predictions could be prevented with improved meteorological predictions.     

Spatial variance in multimedia mass balance models: comparison of LOTOS-EUROS and SimpleBox for PCB-153

The aim of this study was to determine whether nested generic box models can be used to predict spatial variance. An inter-comparison study was performed for the nested box model SimpleBox, and the spatially resolved model LOTOS-EUROS, using PCB-153 emissions in Europe as an example. We compared the two models concerning (1) average environmental concentrations, (2) spatial concentration variances, (3) spatial concentration patterns (maps), and (4) agreement with measured concentrations for the air and soil compartments. In SimpleBox, the spatial concentration variances and patterns were calculated subsequently for each separate grid cell surrounded by a regional and a continental shell with homogeneous, averaged circumstances. Average European PCB-153 concentrations calculated by LOTOS-EUROS and SimpleBox for the period 1981-2000 agree well for the air and soil compartments. Moreover, the predicted concentrations of both models are in line with the measured PCB-153 concentrations in Europe during that period. For PCB-153, the prediction of spatial concentration variances with the nested multimedia fate model SimpleBox performs adequately in most cases, except for the lower concentration boundary in the air compartment. It is concluded that SimpleBox can be used to predict the spatial maximum and average concentrations of PCB-153 in the air and soil compartments. The proposed method has to be tested systematically for different types of compounds, emission scenarios, environmental compartments and spatial scales in order to allow conclusions about the general applicability of the method.     

Low emission zones reduce PM10 mass concentrations and diesel soot in German cities

In many European cities mass concentrations of PM₁₀ (particles less than 10 μm in size) are still exceeding air quality standards as set by the European Commission in 1999. As a consequence, many cities introduced low emission zones (LEZs) to improve air quality and to meet the limit values. In Germany currently 48 LEZs are in operation. By means of dispersion modeling, PM₁₀ concentrations were estimated to decrease up to 10%. Analysis of PM₁₀ levels conducted for Cologne, Berlin, and Munich some time after the LEZs were introduced showed reduction of PM₁₀ mass concentration in the estimated range. The PM₁₀ particle fraction is, however, composed of particles with varying toxicity, of which diesel soot is highly health relevant. An evaluation of air quality data conducted in Berlin showed that in 2010 traffic-related soot concentrations measured along major roads decreased by 52% compared to 2007. Diesel particle emissions in Berlin were reduced in 2012 by 63% compared to a business-as-usual scenario (reference year 2007). A strong reduction of the traffic-related particle fraction of PM_2.5 was also reported for Munich. Therefore, it is likely that the effects of LEZs are considerably more significant to human health than was anticipated when only considering the reduction of PM₁₀ mass concentrations.

Implications: The implementation of low emission zones in German cities might result in a reduction of PM₁₀ levels concentrations by up to 10%. However, it is difficult to show a reduction of PM₁₀ annual averages in this order of magnitude as meteorology has a large impact on the year-to-year variation of PM mass concentrations. Monitoring of other PM metrics such as black smoke (BS) or elemental carbon (EC) might be a better strategy for evaluating LEZs effects. The benefit of low emission zones on human health is far greater than is presently visible from routine measurements of PM₁₀.     

A Pilot Indoor-Outdoor Study of Organic Particulate Matter and Particulate Mutagenicity

Abstract

Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season”. Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for input into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been widely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear—especially for ozone—properties that might be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.     

Ozone pollution and ozone biomonitoring in European cities. Part I: Ozone concentrations and cumulative exposure indices at urban and suburban sites

In the frame of a European research project on air quality in urban agglomerations, data on ozone concentrations from 23 automated urban and suburban monitoring stations in 11 cities from seven countries were analysed and evaluated. Daily and summer mean and maximum concentrations were computed based on hourly mean values, and cumulative ozone exposure indices (Accumulated exposure Over a Threshold of 40 ppb (AOT40), AOT20) were calculated. The diurnal profiles showed a characteristic pattern in most city centres, with minimum values in the early morning hours, a strong rise during the morning, peak concentrations in the afternoon, and a decline during the night. The widest amplitudes between minimum and maximum values were found in central and southern European cities such as Düsseldorf, Verona, Klagenfurt, Lyon or Barcelona. In the northern European cities of Edinburgh and Copenhagen, by contrast, maximum values were lower and diurnal variation was much smaller. Based on ozone concentrations as well as on cumulative exposure indices, a clear north–south gradient in ozone pollution, with increasing levels from northern and northwestern sites to central and southern European sites, was observed. Only the Spanish cities did not fit this pattern; there, ozone levels were again lower than in central European cities, probably due to the direct influence of strong car traffic emissions. In general, ozone concentrations and cumulative exposure were significantly higher at suburban sites than at urban and traffic-exposed sites. When applying the newly established European Union (EU) Directive on ozone pollution in ambient air, it was demonstrated that the target value for the protection of human health was regularly surpassed at urban as well as suburban sites, particularly in cities in Austria, France, northern Italy and southern Germany. European target values and long-term objectives for the protection of vegetation expressed as AOT40 were also exceeded at many monitoring sites.     

Total human exposure: basic concepts, EPA field studies, and future research needs

Historically, environmental regulatory programs designed to protect public health have monitored pollutants only in geophysical carrier media (for example, outdoor air, streams, soil). Field studies have identified a gap between the levels observed in geophysical carrier media and the concentrations with which people actually come into contact: their daily exposures. A new approach--Total Human Exposure (THE)--has evolved to fill this gap and provide the critical data needed for accurately assessing public health risk. The THE approach considers a three-dimensional "bubble" around each person and measures the concentrations of all pollutants contacting that bubble, either through the air, food, water, or skin. Two basic THE approaches have emerged: (1) the direct approach using probability samples of populations and measuring pollutant concentrations in the food eaten, air breathed, water drunk, and skin contacted; and (2) the indirect approach using human activity pattern-exposure models to predict population exposure distributions. Using the direct approach, EPA has conducted over 20 field studies for pollutants representing four groups--volatile organic compounds, carbon monoxide, pesticides, and particles--in 15 cities in 12 states. The indirect modeling approach has been applied to several of these pollutants. Additional research is needed in a great variety of areas. Even from the few projects completed thus far, the THE approach has yielded a rich new data base for risk assessments and has provided many surprises about the relative contribution of various pollutant sources to public health risk.     

Simulating industrial emissions using Atmospheric Dispersion Modeling System: Model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NO_X), carbon monoxide (CO), fine particulate matter (PM₁₀) and sulfur dioxide (SO₂)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement d values reaching 0.58, fractional bias “FB” and geometric mean bias “MG” values approaching 0 and 1, respectively, and normalized mean square error “NMSE” values as low as 2.17. However, median ratios of predicted to observed concentrations “Cp/Co” at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NO_X, CO, PM₁₀ and SO₂, respectively, and the fraction of predictions within a factor of two of observations “FAC2” values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.

Implications In the absence of site-specific source emission factors, the use of internationally reported emission factors without testing their validity may generate significant errors. Instead, recorded field measurements and meteorological data may be combined with atmospheric transport and dispersion models to better estimate source emissions, particularly in regulatory compliance studies. In this context, lower model performance is expected at higher wind speeds for most indicators such as CO, PM₁₀, and SO₂.     

Receptor modeling application framework for particle source apportionment

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.     

Simulation of boundary layer trajectory dispersion sensitivity to soil moisture conditions: MM5 and Noah-based investigation

In this study, the sensitivity of trajectory paths to anomalous soil moisture was analyzed during three different synoptic episodes in June 2006. The MM5 and Noah land surface models were used to simulate the response of the planetary boundary layer. The HYSPLIT model was used for trajectory analysis. It was found that the response in horizontal lower-level wind field was larger at regions where vertical wind velocity changes were also large. In addition, the sensitivity to soil moisture changes was significant and localized where convective activity was well developed and synoptic effects did not dominate. A non-local effect was felt over the rest of the domain where convection was not present since the model atmosphere reacted as a whole to compensate for induced changes in vertical velocity. This finding was supported by the fact that domain averaged vertical velocities changes were of the order of 0.2 cm s^?1 or less at about 650 hPa and about 200 times smaller than modeled local vertical velocity changes. The largest change in horizontal wind field near the surface was found for weak synoptic events on June 11–12 and June 22–23 while the stronger synoptic event of June 17–18 showed smaller differences. These changes in wind field conditions impacted the transport and dispersion of pollutants. To quantify the sensitivity of air quality estimates to soil moisture uncertainty, we have used three well known measures of trajectory differences: the absolute horizontal transport deviation (AHTD), the relative horizontal transport deviation (RHTD) and the absolute vertical transport deviation (AVTD) for an ensemble of 98 trajectories departing from a region well within the computational domain. For the June 11–12 event it was found that for wet and dry soil moisture experiments, AHTD, RHTD, and AVGTD can reach values in the range 60–100 km, 10–20% and 500–900 m at 24 h run time, respectively. For the June 17–18 and June 22–23 events these values of trajectory differences were reduced more than half. These differences in behavior between time periods are largely attributed to the combined effects of synoptic forcing and the sensitivity of planetary boundary layer to soil moisture changes during well developed convection. The implication for air quality studies is that the soil moisture anomaly and related uncertainty in planetary boundary layer response needs to be incorporated in order to construct an ensemble of the most probable scenarios in which pollutants are released and transported throughout a given target region.     

大气污染物扩散模式的应用研究综述

应用大气污染物扩散模式可以模拟不同尺度、气象、地形条件下工业污染物在大气中的输送与扩散特征,为大气监测、城市环境规划和空气质量预报等工作提供科学依据.归纳了目前广泛应用于模拟工业污染物扩散的模式,着重介绍了近年来国内外对这些模式的主要应用研究进展,比较了各模式在应用上的优缺点,并对大气污染物扩散模式的应用研究前景进行了讨论.