Adjoint inverse modeling of NOx emissions over eastern China using satellite observations of NO2 vertical column densities

A four-dimensional variational data assimilation system for optimization of NO_x emissions (RC4-NO_x) was developed. A parameterized NO_x chemistry scheme was introduced into the RC4-NO_x system, and key parameters such as chemical production and loss terms of NO_x were calculated in advance using the Community Multiscale Air Quality (CMAQ) modeling system. RC4-NO_x was applied to optimize NO_x emissions over eastern China (EC) in July 1996, 1999, and 2002 using Global Ozone Monitoring Experiment (GOME) satellite observations of NO₂ vertical column densities (VCDs) and a priori emissions from the Regional Emission Inventory in Asia (REAS). After assimilation, RC4-NO_x generally reproduced the spatial distribution, regional averaged values, and time evolution of GOME NO₂ VCDs. Over EC, a priori emissions were reduced by 20% in 1996 and by 8% in 1999, whereas a posteriori emissions were almost the same as a priori emissions in 2002. A priori emissions in the Beijing region were reduced by optimization over the whole simulation period. A posteriori emissions over the Yangtze Delta were larger than a priori emissions in 2002, although they were smaller in both 1996 and 1999. As in other areas, a priori emissions over the North China Plain were reduced in 1996; but those over the eastern part of the plain were increased in 1999, and the area of increased emissions moved slightly westward in 2002. In each region, the growth rates of a posteriori emissions during both 1996–1999 and 1999–2002 became generally larger than those of a priori emissions, and the trends of a posteriori emissions became similar to those of GOME NO₂ VCDs. Our inverse modeling analysis indicates that the rate of increase of NO_x emissions over EC from 1996 to 2002 was much larger for a posteriori emissions (49%) than for a priori emissions (19%).     

Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode

Abstract

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29–July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O₃), particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM₁₀) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O₃ and PM than CMAQ. Both models tend to predict O₃ values that are higher than those observed. For observed O₃ values above 60 ppb, O₃ performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O₃ values above 40 ppb.

Both models predict similar amounts of sulfate (SO₄ ^2?) and organic matter, and both predict SO₄ ^2? to be the largest contributor to PM_2.5. PMCAMx generally predicts higher amounts of ammonium (NH₄ ⁺), nitrate (NO₃ ^?), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO₃ ^?,NH₄ ⁺, and BC than observed, which degrades its performance. For PM₁₀ and PM_2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37–43% and –33–4% for CMAQ and 50–59% and 7–30% for PMCAMx. Both models predict the largest MNGEs for NO₃ ^? (98–104% for CMAQ, 138–338% for PMCAMx). The inaccurate NO₃ ^? predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

Variations of the increasing trend of tropospheric NO2 over central east China during the past decade

A numerical analysis using a regional chemical transport model (CTM) is presented in comparison with Global Ozone Monitoring Experiment (GOME) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) satellite NO₂ measurements over East Asia from 1996 to 2005 from a climatological perspective. Modeling results agree well with satellite retrievals in geographical distribution patterns, with systematic underestimation of the absolute values. The sharp increase in NO₂ vertical column densities (VCDs) over central east China (CEC) after the year 2000 (14.1–20.5% yr⁻¹ for the satellite observations and 10.8% yr⁻¹ for model simulations) is analyzed quantitatively over different megacity clusters. The distinct emission increase patterns are responsible for the different increase trends observed over the Beijing megacity cluster (BJ), the Yangtze Delta (YD) and other CEC regions. The growth rate of satellite measured and CMAQ-modeled NO₂ VCDs for the YD is much higher than that in other regions, with no clear seasonal variation. Apart from BJ and YD, NO₂ emissions from other regions in CEC also expand considerably.     

Influence of boundary conditions on CMAQ simulations over the Iberian Peninsula

The influence of chemical boundary conditions (BC) on the response of the Community Multiscale Air Quality (CMAQ) model over the Iberian Peninsula was investigated in this study. Three strategies to supply boundary conditions in the context of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) were tested. Alternative methods consist in providing BC from (1) fixed, time-independent, concentration profiles, (2) concentrations predicted in a CMAQ mother domain (48 km, 1 h resolution) and (3) concentration values from the GEOS-Chem chemical-transport global model (2 × 2.5°, 3 h resolution). High resolution (3 km) simulated concentrations of the main pollutants (NO₂, NO, SO₂, O₃, PM₁₀ and PM_2.5) were compared through a comprehensive statistical analysis including observational data from 165 monitoring stations all over the Iberian Peninsula. It was found that model sensitivity to BC for nitrogen and sulphur oxides was limited, being restricted to the vicinity of model boundaries. However, significant domain-wide differences were found when modelling ozone and PM depending on the BC provided to run the tests. Although model performance was affected by spatial and seasonal factors, the results indicate that model-derived, dynamic BC improved CMAQ predictions when compared to those based on static concentrations prescribed in the boundaries. Aggregated statistics suggest that the GEOS-Chem produced the best results for O₃ and PM_2.5 while NO₂ and PM₁₀ were slightly better predicted under the CMAQ nesting approach. Besides the statistical evaluation some other relevant issues in the context of Integrated Assessment Modelling (IAM) are discussed to gain a better insight into the suitability of the methods analyzed and limitations of downscaling methods. Despite being useful to get a better understanding of the role of BC in SIMCA, this study contributed to highlight model deficiencies and therefore to point out future research needs to improve IAM activities in the Iberian Peninsula.     

Evaluation of a CMAQ simulation at high resolution over the UK for the calendar year 2003

A comprehensive ‘operational’ evaluation of the performance of the Community Multiscale Air Quality (CMAQ) modelling system version 4.6 was conducted in support of pollution assessment in the UK for the calendar year 2003. The model was run on multiple grids using one-way nests down to a horizontal resolution as fine as 5 km over the whole of the UK. The model performance was evaluated for pollutants with standards and limit values (e.g. O₃, PM₁₀) and species contributing to acidic and nitrogenous deposition (e.g. NH₃, SO₄^2–, NO₃^–, NH₄⁺) against data from operational national monitoring networks. The key performance characteristics of the modelling system were found to be variable according to acceptance criteria and to depend on the type (e.g. urban, rural) and location of the sites, as well as on the time of the year. As regards the techniques that were used for ‘operational’ evaluation, performance generally complied with expected levels and ranged from good (e.g. O₃, SO₄^2–) to moderate (e.g. PM₁₀, NO₃^–). At a few sites low correlations and large standard deviations for some species (e.g. SO₂) suggest that these sites are subject to local factors (e.g. topography, emission sources) that are not well described in the model. Overall, the model tends to over predict O₃ and under predict aerosol species (except SO₄^2–). Discrepancies between predicted and observed concentrations may be due to a variety of intertwined factors, which include inaccuracies in meteorological predictions, chemical boundary conditions, temporal variability in emissions, and uncertainties in the treatment of gas and aerosol chemistry. Further work is thus required to investigate the respective contributions of such factors on the predicted concentrations.     

The sensitivity of modeled ozone to the temporal distribution of point, area, and mobile source emissions in the eastern United States

Ozone remains one of the most recalcitrant air pollution problems in the US. Hourly emissions fields used in air quality models (AQMs) generally show less temporal variability than corresponding measurements from continuous emissions monitors (CEM) and field campaigns would imply. If emissions control scenarios to reduce emissions at peak ozone forming hours are to be assessed with AQMs, the effect of emissions' daily variability on modeled ozone must be understood. We analyzed the effects of altering all anthropogenic emissions' temporal distributions by source group on 2002 summer-long simulations of ozone using the Community Multiscale Air Quality Model (CMAQ) v4.5 and the Carbon Bond IV (CBIV) chemical mechanism with 12 km resolution. We find that when mobile source emissions were made constant over the course of a day, 8-h maximum ozone predictions changed by ±7 parts per billion by volume (ppbv) in many urban areas on days when ozone concentrations greater than 80 ppbv were simulated in the base case. Increasing the temporal variation of point sources resulted in ozone changes of +6 and −6 ppbv, but only for small areas near sources. Changing the daily cycle of mobile source emissions produces substantial changes in simulated ozone, especially in urban areas at night; results suggest that shifting the emissions of NO_x from day to night, for example in electric powered vehicles recharged at night, could have beneficial impacts on air quality.     

Assessment of air quality benefits from national air pollution control policies in China. Part I: Background,emission scenarios and evaluation of meteorological predictions

Under the 11th Five Year Plan (FYP, 2006–2010) for national environmental protection by the Chinese government, the overarching goal for sulfur dioxide (SO₂) controls is to achieve a total national emissions level of SO₂ in 2010 10% lower than the level in 2005. A similar nitrogen oxides (NO_x) emissions control plan is currently under development and could be enforced during the 12th FYP (2011–2015). In this study, the U.S. Environmental Protection Agency (U.S.EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) modeling system was applied to assess the air quality improvement that would result from the targeted SO₂ and NO_x emission controls in China. Four emission scenarios — the base year 2005, the 2010 Business-As-Usual (BAU) scenario, the 2010 SO₂ control scenario, and the 2010 NO_x control scenario—were constructed and simulated to assess the air quality change from the national control plan. The Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) was applied to generate the meteorological fields for the CMAQ simulations. In this Part I paper, the model performance for the simulated meteorology was evaluated against observations for the base case in terms of temperature, wind speed, wind direction, and precipitation. It is shown that MM5 model gives an overall good performance for these meteorological variables. The generated meteorological fields are acceptable for using in the CMAQ modeling.     

Spatial PM2.5 mobile source impacts using a calibrated indicator method

Motor vehicles are major sources of fine particulate matter (PM_2.5), and the PM_2.5 from mobile vehicles is associated with adverse health effects. Traditional methods for estimating source impacts that employ receptor models are limited by the availability of observational data. To better estimate temporally and spatially resolved mobile source impacts on PM_2.5, we developed an approach based on a method that uses elemental carbon (EC), carbon monoxide (CO), and nitrogen oxide (NO_x) measurements as an indicator of mobile source impacts. We extended the original integrated mobile source indicator (IMSI) method in three aspects. First, we generated spatially resolved indicators using 24-hr average concentrations of EC, CO, and NO_x estimated at 4 km resolution by applying a method developed to fuse chemical transport model (Community Multiscale Air Quality Model [CMAQ]) simulations and observations. Second, we used spatially resolved emissions instead of county-level emissions in the IMSI formulation. Third, we spatially calibrated the unitless indicators to annually-averaged mobile source impacts estimated by the receptor model Chemical Mass Balance (CMB). Daily total mobile source impacts on PM_2.5, as well as separate gasoline and diesel vehicle impacts, were estimated at 12 km resolution from 2002 to 2008 and 4 km resolution from 2008 to 2010 for Georgia. The total mobile and separate vehicle source impacts compared well with daily CMB results, with high temporal correlation (e.g., R ranges from 0.59 to 0.88 for total mobile sources with 4 km resolution at nine locations). The total mobile source impacts had higher correlation and lower error than the separate gasoline and diesel sources when compared with observation-based CMB estimates. Overall, the enhanced approach provides spatially resolved mobile source impacts that are similar to observation-based estimates and can be used to improve assessment of health effects.

Implications: An approach is developed based on an integrated mobile source indicator method to estimate spatiotemporal PM_2.5 mobile source impacts. The approach employs three air pollutant concentration fields that are readily simulated at 4 and 12 km resolutions, and is calibrated using PM_2.5 source apportionment modeling results to generate daily mobile source impacts in the state of Georgia. The estimated source impacts can be used in investigations of traffic pollution and health.     

Dynamic evaluation of a regional air quality model: Assessing the emissions-induced weekly ozone cycle

Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system for the “weekend ozone effect” to determine if observed changes in ozone due to weekday-to-weekend (WDWE) reductions in precursor emissions can be accurately simulated. The weekend ozone effect offers a unique opportunity for dynamic evaluation, as it is a widely documented phenomenon that has persisted since the 1970s. In many urban areas of the Unites States, higher ozone has been observed on weekends than weekdays, despite dramatically reduced emissions of ozone precursors (nitrogen oxides [NO_x] and volatile organic compounds [VOCs]) on weekends. More recent measurements, however, suggest shifts in the spatial extent or reductions in WDWE ozone differences. Using 18 years (1988–2005) of observed and modeled ozone and temperature data across the northeastern United States, we re-examine the long-term trends in the weekend effect and confounding factors that may be complicating the interpretation of this trend and explore whether CMAQ can replicate the temporal features of the observed weekend effect. The amplitudes of the weekly ozone cycle have decreased during the 18-year period in our study domain, but the year-to-year variability in weekend minus weekday (WEWD) ozone amplitudes is quite large. Inter-annual variability in meteorology appears to influence WEWD differences in ozone, as well as WEWD differences in VOC and NO_x emissions. Because of the large inter-annual variability, modeling strategies using a single episode lasting a few days or a few episodes in a given year may not capture the WEWD signal that exists over longer time periods. The CMAQ model showed skill in predicting the absolute values of ozone concentrations during the daytime. However, early morning NO_x concentrations were underestimated and ozone levels were overestimated. Also, the modeled response of ozone to WEWD differences in emissions was somewhat less than that observed. This study reveals that model performance may be improved by (1) properly estimating mobile source NO_x emissions and their temporal distributions, especially for diesel vehicles; (2) reducing the grid cell size in the lowest layer of CMAQ; and, (3) using time-dependent and more realistic boundary conditions for the CMAQ simulations.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM_2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO₂) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality.The air quality improvement that would result from the targeted sulfur dioxide (SO₂) and nitrogen oxides (NO_x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO₂ concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30–60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM_2.5 can also decline by 3–15 μg m^?3 (4–25%) due to the lower SO₂ and sulfate concentrations. If similar controls are implemented for NO_x emissions, NO_x concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM_2.5 concentrations will also decline by 2–14 μg m^?3 (3–12%). In addition, the number of ozone (O₃) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O₃ concentrations in the summer reduced by 8–30 ppb.     

Study of a winter PM episode in Istanbul using the high resolution WRF/CMAQ modeling system

High winter-time PM₁₀, sulfate, nitrate and ammonium levels in Istanbul were investigated using a high resolution WRF/CMAQ mesoscale model system. A model-ready anthropogenic emission inventory on 2 km spatial resolution was developed for the area and the present study is the first attempt to test these emissions. The results suggested that the system was capable of producing the magnitudes. PM₁₀ levels calculated by the model underestimated the observations with an average of 10 per cent at Bogazici University sampling station, whereas an overestimation of 12 per cent is calculated for all stations. High uncertainties, particularly in traffic and coal combustion, led to over estimations around emission hot spots. Base case results together with the sensitivity studies pointed significant contribution of local sources, pointing to the need of control strategies focusing on primary particulate emissions.     

Evaluation of the community multiscale air quality (CMAQ) model version 4.5: Sensitivities impacting model performance; Part II—particulate matter

This paper is Part II in a pair of papers that examines the results of the Community Multiscale Air Quality (CMAQ) model version 4.5 (v4.5) and discusses the potential explanations for the model performance characteristics seen. The focus of this paper is on fine particulate matter (PM_2.5) and its chemical composition. Improvements made to the dry deposition velocity and cloud treatment in CMAQ v4.5 addressing compensating errors in 36-km simulations improved particulate sulfate (SO₄²⁻) predictions. Large overpredictions of particulate nitrate (NO₃⁻) and ammonium (NH₄⁺) in the fall are likely due to a gross overestimation of seasonal ammonia (NH₃) emissions. Carbonaceous aerosol concentrations are substantially underpredicted during the late spring and summer months, most likely due, in part, to a lack of some secondary organic aerosol (SOA) formation pathways in the model. Comparisons of CMAQ PM_2.5 predictions with observed PM_2.5 mass show mixed seasonal performance. Spring and summer show the best overall performance, while performance in the winter and fall is relatively poor, with significant overpredictions of total PM_2.5 mass in those seasons. The model biases in PM_2.5 mass cannot be explained by summing the model biases for the major inorganic ions plus carbon. Errors in the prediction of other unspeciated PM_2.5 (PM_Other) are largely to blame for the errors in total PM_2.5 mass predictions, and efforts are underway to identify the cause of these errors.     

Long-range transport of acidifying substances in East Asia—Part II: Source–receptor relationships

Region-to-grid source–receptor (S/R) relationships are established for sulfur and reactive nitrogen deposition in East Asia, using the Eulerian-type Community Multiscale Air Quality (CMAQ) model with emission and meteorology data for 2001. We proposed a source region attribution methodology by analyzing the non-linear responses of the CMAQ model to emission changes. Sensitivity simulations were conducted where emissions of SO₂, NO_x, and primary particles from a source region were reduced by 25%. The difference between the base and sensitivity simulations was multiplied by a factor of four, and then defined as the contribution from that source region. The transboundary influence exhibits strong seasonal variation and generally peaks during the dry seasons. Long-range transport from eastern China contributes a significant percentage (>20%) of anthropogenic reactive nitrogen as well as sulfur deposition in East Asia. At the same time, northwestern China receives approximately 35% of its sulfur load and 45% of its nitrogen load from foreign emissions. Sulfur emissions from Miyakejima and other volcanoes contribute approximately 50% of the sulfur load in Japan in 2001. Sulfur inflows from regions outside the study domain, which is attributed by using boundary conditions derived from the MOZART global atmospheric chemistry model, are pronounced (10–40%) over most parts of Asia. Compared with previous studies using simple Lagrangian models, our results indicate higher influence from long-range transport. The estimated S/R relationships are believed to be more realistic since they include global influence as well as internal interactions among different parts of China.     

Implementation and application of sub-grid-scale plume treatment in the latest version of EPA’s third-generation air quality model,CMAQ 5.01

The Community Multiscale Air Quality (CMAQ) modeling system Version 5.0 (CMAQv5.0) was released by the U.S. Environmental Protection Agency (EPA) in February 2012, with an interim release (v5.01) in July 2012. Because CMAQ is a community model, the EPA encourages the development of proven alternative science treatments by external scientists and developers that can be incorporated as part of an official CMAQ release. This paper describes the implementation, evaluation, and testing of a plume-in-grid (PinG) module in CMAQ 5.01. The PinG module, also referred to as Advanced Plume Treatment (APT), provides the capability of resolving sub-grid-scale processes, such as the transport and chemistry of point-source plumes, in a grid model. The new PinG module in CMAQ 5.01 is applied and evaluated for two 15-day summer and winter periods in 2005 to the eastern United States, and the results are compared with those from the base CMAQ 5.01. Eighteen large point sources of NOx in the eastern United States were selected for explicit plume treatment with APT in the PinG simulation. The results show that overall model performance is negligibly affected when PinG treatment is included. However, the PinG model predicts significantly different contributions of the 18 sources to pollutant concentrations and deposition downwind of the point sources compared to the base model.

Implications: This study describes the incorporation of a plume-in-grid (PinG) capability within the latest version of the EPA grid model, CMAQ. The capability addresses the inherent limitation of the grid model to resolve processes, such as the evolution of point-source plumes, which occur at scales much smaller than the grid resolution. The base grid model and the PinG version predict different source contributions to ozone and PM_2.5 concentrations that need to be considered when source attribution studies are conducted to determine the impacts of large point sources on downwind concentrations and deposition of primary and secondary pollutants.     

Testing model accuracy measures according to the EU directives—examples using the chemical transport model REM-CALGRID

The paper presents a comprehensive model evaluation focusing on the meaning and shortcomings of accuracy measures used to determine model quality according to European Union (EU) directives on air quality. European wide simulations employing the chemical transport model REM-CALGRID for the year 2002 were compared with O₃, NO₂, SO₂ and PM₁₀ observations of the German measurement network.The EU model quality objective, which is based on maximum relative errors, tends to penalise (i) the overestimation of very low measured concentrations in the case of annual averages and (ii) the underestimation of extremely high measured concentrations in the case of short-term values. As a more robust alternative, a model accuracy measure is presented, which corresponds to the allowed number of exceedances of the corresponding short-term air quality limit values.The influence of the spatial heterogeneity of the observations in relation to the spatial resolution of the model is investigated by spatial averaging of observation data. Because of this heterogeneity, any model with a 25 km resolution would fail to simulate about 20% of all NO₂ and SO₂ stations and 5–10% of all O₃ and PM₁₀ stations in Germany according to the EU model quality objectives for short-term averages.     

Examination of the impact of photoexcited NO2 chemistry on regional air quality

Impact of the excited nitrogen dioxide (NO₂¹) chemistry on air quality in the U.S. is examined using the Community Multiscale Air Quality (CMAQ) model for a summer month. Model simulations were conducted with and without the NO₂¹ chemistry. The largest impact of the NO₂¹ chemistry in the eastern U.S. occurred in the northeast and in the western U.S. occurred in Los Angeles. While the single largest daily maximum 8-h ozone (O₃) increased by 9 ppbv in eastern U.S. and 6 ppbv in western U.S., increases on most days were much lower. No appreciable change in model performance statistics for surface-level O₃ predictions relative to measurements is noted between simulations with and without the NO₂¹ chemistry. Based on model calculations using current estimates of tropospheric emission burden, the NO₂¹ chemistry can increase the monthly mean daytime hydroxyl radicals (OH) and nitrous acid (HONO) by a maximum of 28% and 100 pptv, respectively.     

Modeling Analyses of the Effects of Changes in Nitrogen Oxides Emissions from the Electric Power Sector on Ozone Levels in the Eastern United States

Abstract

In this paper, we examine the changes in ambient ozone concentrations simulated by the Community Multiscale Air Quality (CMAQ) model for summer 2002 under three different nitrogen oxides (NO_x) emission scenarios. Two emission scenarios represent best estimates of 2002 and 2004 emissions; they allow assessment of the impact of the NO_x emissions reductions imposed on the utility sector by the NO_x State Implementation Plan (SIP) Call. The third scenario represents a hypothetical rendering of what NO_x emissions would have been in 2002 if no emission controls had been imposed on the utility sector. Examination of the modeled median and 95th percentile daily maximum 8-hr average ozone concentrations reveals that median ozone levels estimated for the 2004 emission scenario were less than those modeled for 2002 in the region most affected by the NO_x SIP Call. Comparison of the “no-control” with the “2002” scenario revealed that ozone concentrations would have been much higher in much of the eastern United States if the utility sector had not implemented NO_x emission controls; exceptions occurred in the immediate vicinity of major point sources where increased NO titration tends to lower ozone levels.     

Process analysis of a regional air pollution episode over Pearl River Delta Region,China, using the MM5-CMAQ model

This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October 10–12, 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD. MM5 shows reasonable performance for major meteorological variables (i.e., temperature, relative humidity, wind direction) with normalized mean biases (NMB) of 4.5–38.8% and for their time series. CMAQ can capture one peak of all air pollutant concentrations on October 11, but misses other peaks. The CMAQ model systematically underpredicts the mass concentrations of all air pollutants. Compared with chemical observations, SO₂ and O₃ are predicted well with a correlation coefficient of 0.70 and 0.65. PM_2.5 and NO are significantly underpredicted with an NMB of 43% and 90%, respectively. The process analysis results show that the emission, dry deposition, horizontal transport, and vertical transport are four main processes affecting air pollutants. The contributions of each physical process are different for the various pollutants. The most important process for PM₁₀ is dry deposition, and for NO_x it is transport. The contributions of horizontal and vertical transport processes vary during the period, but these two processes mostly contribute to the removal of air pollutants at Guangzhou city, whose emissions are high. For this high-pressure case, the contributions of the various processes show high correlations in cities with the similar geographical attributes. According to the statistical results, cities in the PRD region are divided into four groups with different features. The contributions from local and nonlocal emission sources are discussed in different groups.

Implications: The characteristics of aerosol pollution episodes are intensively studied in this work using the high-resolution modeling system MM5/SMOKE/CMAQ, with special efforts on examining the contributions of different physical and chemical processes to air concentrations for each city over the PRD region by a process analysis method, so as to provide a scientific basis for understanding the formation mechanism of regional aerosol pollution under the high-pressure system over PRD.     

Comparison of satellite observed tropospheric NO2 over India with model simulations

Nitrogen dioxide (NO₂) plays a key role in the chemistry of the atmosphere and is emitted mainly by combustion processes. These emissions have been increasing over India over the past few years due to rapid economic growth and yet there are very few systematic ground based observations of NO₂ over this region. We thus take recourse to satellite data and compare tropospheric NO₂ column abundances simulated by a chemical transport model, MOZART, with data from the Global Ozone Monitoring Experiment (GOME) for a few locations in India that have seen a rapid economic growth in the last decade. The model generally simulates higher columnar abundances of NO₂ compared to GOME observations and does not reproduce the features of the observed seasonal behaviour. The combined uncertainties of the emission inventory and retrieval of the satellite data could be contributing factors to the discrepancies. It may be thus worthwhile to develop emission inventories for India at a higher resolution to include local level activity data. The ten year data (1996–2006) from GOME and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) show increasing trends for Indian cities where rapid industrial and vehicular traffic growth has been observed during this period.