Responses of future air quality to emission controls over North Carolina,Part II: Analyses of future-year predictions and their policy implications

The MM5/CMAQ system evaluated in Part I paper is applied to study the impact of emission control on future air quality over North Carolina (NC). Simulations are conducted at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August 2009 and 2018. Simulated PM_2.5 in 2009 and 2018 show distribution patterns similar to those in 2002. PM_2.5 concentrations over the whole domain in January and July reduced by 5.8% and 23.3% in 2009 and 12.0% and 35.6% in 2018, respectively, indicating that the planned emission control strategy has noticeable effects on PM_2.5 reduction in this region, particularly in summer. More than 10% and 20% of 1-h and 8-h O₃ mixing ratios are reduced in July 2009 and 2018, respectively, demonstrating the effectiveness of emission control for O₃ reduction in summer. However, O₃ mixing ratios in January 2009 and 2018 increase by more than 5% because O₃ chemistry is VOC-limited in winter and the effect of NO_x reduction dominates over that of VOC reduction under such a condition. The projected emission control simulated at 4-km will reduce the number of sites in non-attainment for max 8-h O₃ from 49 to 23 in 2009 and to 1 in 2018 and for 24-h average PM_2.5 from 1 to 0 in 2009 and 2018 based on the latest 2008 O₃ and 2006 PM_2.5 standards. The variability in model predictions at different grid resolutions contributes to 1–3.8 ppb and 1–7.9 μg m^?3 differences in the projected future-year design values for max 8-h O₃ and 24-h average PM_2.5, respectively.     

A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems

A harmonized comparative performance evaluation of A Unified Regional Air-quality Modelling System (AURAMS) v1.3.1b and Community Multiscale Air Quality (CMAQ) v4.6 air-quality modelling systems was conducted on the same North American grid for July 2002 using the same emission inventories, emissions processor, and input meteorology.Comparison of AURAMS- and CMAQ-predicted O₃ concentrations against hourly surface measurement data showed a lower normalized mean bias (NMB) of 20.7% for AURAMS versus 46.4% for CMAQ. However, AURAMS and CMAQ had more similar normalized mean errors (NMEs) of 46.9% and 54.2%, respectively. Both models did similarly well in predicting daily 1-h O₃ maximums; however, AURAMS performed better in calculating daily minimums. CMAQ's poorer performance for O₃ is partly due to its inability to correctly predict nighttime lows.Total PM_2.5 hourly surface concentration was under-predicted by both AURAMS and CMAQ with NMBs of ?10.4% and ?65.2%, respectively. However, as with O₃, both models had similar NMEs of 68.0% and 70.6%, respectively. In general, AURAMS performance was better than CMAQ for all major PM_2.5 species except nitrate and elemental carbon. Both models significantly under-predicted total organic aerosols (TOAs), although the mean AURAMS concentration was over four times larger than CMAQ's. The under-prediction of TOA was partly due to the exclusion of forest-fire emissions. Sea-salt aerosol made up approximately 50.2% of the AURAMS total PM_2.5 surface concentration versus only 6.2% in CMAQ when averaged over all grid cells. When averaged over land cells only, sea-salt still contributed 13.9% to the total PM_2.5 mass in AURAMS versus 2.0% in CMAQ.     

Improving ozone modeling in complex terrain at a fine grid resolution – Part II: Influence of schemes in MM5 on daily maximum 8-h ozone concentrations and RRFs (Relative Reduction Factors) for SIPs in the non-attainment areas

Part II presents a comprehensive evaluation of CMAQ for August of 2002 on twenty-one sensitivity simulations (detailed in Part I) in MM5 to investigate the model performance for O₃ SIPs (State Implementation Plans) in the complex terrain. CMAQ performance was quite consistent with the results of MM5, meaning that accurate meteorological fields predicted in MM5 as an input resulted in good model performance of CMAQ. In this study, PBL scheme plays a more important role than its land surface models (LSMs) for the model performance of CMAQ. Our results have shown that the outputs of CMAQ on eighteen sensitivity simulations using two different nudging coefficients for winds (2.5 and 4.5 × 10^?4 s^?1, respectively) tend to under predict daily maximum 8-h ozone concentrations at valley areas except the TKE PBL sensitivity simulations (ETA M-Y PBL scheme with Noah LSMs and 5-layer soil model and Gayno-Seaman PBL) using 6.0 × 10^?4 s^?1 with positive MB (Mean Bias). At mountain areas, none of the sensitivity simulations has presented over predictions for 8-h O₃, due to relatively poor meteorological model performance. When comparing 12-km and 4-km grid resolutions for the PX simulation in CMAQ statistics analysis, the CMAQ results at 12-km grid resolution consistently show under predictions of 8-h O₃ at both of valley and mountain areas and particularly, it shows relatively poor model performance with a 15.1% of NMB (Normalized Mean Bias). Based on our sensitivity simulations, the TKE PBL sensitivity simulations using a maximum value (6 × 10^?4) among other sensitivity simulations yielded better model performance of CMAQ at all areas in the complex terrain. As a result, the sensitivity of RRFs to the PBL scheme may be considerably significant with about 1–3 ppb in difference in determining whether the attainment test is passed or failed. Furthermore, we found that the result of CMAQ model performance depending on meteorological variations is affected on estimating RRFs for attainment demonstration, indicating that it is necessary to improve model performance. Overall, G_c (Gayo-Seaman PBL scheme) using the coefficient for winds, 6 × 10^?4 s^?1, sensitivity simulation predicts daily maximum 8-h ozone concentration closer to observations during a typical summer period from May to September and provides generally low future design values (DVFs) at valley and mountain areas compared to other simulations.     

An integrated MM5–CMAQ modeling approach for assessing trans-boundary PM10 contribution to the host city of 2008 Olympic summer games—Beijing,China

In this paper, an integrated MM5–CMAQ modeling approach was employed to investigate the PM₁₀ air pollution issue in Beijing, China, with a focus on assessing pollution contributions from surrounding provinces. A 2-level-nested grid domain with spatial resolutions of 36 and 12 km was designed for the study region. Seven monitoring stations across Beijing municipality were selected to provide hourly PM₁₀ measurement data. The months of January, April, July and October in 2002 were taken as target periods for model performance evaluation. Five emission scenarios were designed and run in order to quantitatively assess the trans-boundary PM₁₀ contributions. The results show that, while Beijing needs to take positive steps to reduce its own pollution emissions, much effort should also be placed on demanding more pollution reduction and better environmental performance from surrounding provinces.     

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.     

A combined model–observation approach to estimate historic gridded fields of PM2.5 mass and species concentrations

This paper introduces a methodology for estimating gridded fields of total and speciated fine particulate matter (PM_2.5) concentrations for time periods and regions not covered by observational data. The methodology is based on performing long-term regional scale meteorological and air quality simulations and then integrating these simulations with available observational data. To illustrate this methodology, we present an application in which year-round simulations with a meteorological model (the National Center for Atmospheric Research/Penn State Mesoscale Model, hereafter referred to as MM5) and a photochemical air quality model (the Community Multiscale Air Quality Model, hereafter referred to as CMAQ) have been performed over the northeastern United States for 1988–2005. Model evaluation results for total PM_2.5 mass and individual species for the time period from 2000 to 2005 show that model performance varies by species, season, and location. Therefore, an approach is developed to adjust CMAQ output with factors based on these three variables. The adjusted model values for total PM_2.5 mass for 2000–2005 are compared against independent measurements not utilized for the adjustment approach. This comparison reveals that the adjusted model values have a lower root mean square error (RMSE) and higher correlation coefficients than the original model values. Furthermore, the PM_2.5 estimates from these adjusted model values are compared against an alternate method for estimating historic PM_2.5 values that is based on PM_2.5/PM₁₀ ratios calculated at co-located monitors. Results reveal that both methods yield estimates of historic PM_2.5 mass that are broadly consistent; however, the adjusted CMAQ values provide greater spatial coverage and information for PM_2.5 species in addition to total PM_2.5 mass. Finally, strengths and limitations of the proposed approach are discussed in the context of potential uses of this method.     

Improving ozone modeling in complex terrain at a fine grid resolution: Part I – examination of analysis nudging and all PBL schemes associated with LSMs in meteorological model

Meteorological variables such as temperature, wind speed, wind directions, and Planetary Boundary Layer (PBL) heights have critical implications for air quality simulations. Sensitivity simulations with five different PBL schemes associated with three different Land Surface Models (LSMs) were conducted to examine the impact of meteorological variables on the predicted ozone concentrations using the Community Multiscale Air Quality (CMAQ) version 4.5 with local perspective. Additionally, the nudging analysis for winds was adopted with three different coefficients to improve the wind fields in the complex terrain at 4-km grid resolution. The simulations focus on complex terrain having valley and mountain areas at 4-km grid resolution. The ETA M–Y (Mellor–Yamada) and G–S (Gayno–Seaman) PBL schemes are identified as favorite options and promote O₃ formation causing the higher temperature, slower winds, and lower mixing height among sensitivity simulations in the area of study. It is found that PX (Pleim–Xiu) simulation does not always give optimal meteorological model performance. We also note that the PBL scheme plays a more important role in predicting daily maximum 8-h O₃ than land surface models. The results of nudging analysis for winds with three different increased coefficients' values (2.5, 4.5, and 6.0 × 10^?4 s^?1) over seven sensitivity simulations show that the meteorological model performance was enhanced due to improved wind fields, indicating the FDDA nudging analysis can improve model performance considerably at 4-km grid resolution. Specifically, the sensitivity simulations with the coefficient value (6.0 × 10^?4) yielded more substantial improvements than with the other values (2.5 and 4.5 × 10^?4). Hence, choosing the nudging coefficient of 6.0 × 10^?4 s^?1 for winds in MM5 may be the best choice to improve wind fields as an input, as well as, better model performance of CMAQ in the complex terrain area. As a result, a finer grid resolution is necessary to evaluate and access of CMAQ results for giving a detailed representation of meteorological and chemical processes in the regulatory modeling. A recommendation of optimal scheme options for simulating meteorological variables in the complex terrain area is made.     

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.     

Understanding of regional air pollution over China using CMAQ,part I performance evaluation and seasonal variation

The U.S. EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system with the process analysis tool is applied to China to study the seasonal variations and formation mechanisms of major air pollutants. Simulations show distinct seasonal variations, with higher surface concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM₁₀), column mass of carbon monoxide (CO) and NO₂, and aerosol optical depth (AOD) in winter and fall than other seasons, and higher 1-h O₃ and troposphere ozone residual (TOR) in spring and summer than other seasons. Higher concentrations of most species occur over the eastern China, where the air pollutant emissions are the highest in China. Compared with surface observations, the simulated SO₂, NO₂, and PM₁₀ concentrations are underpredicted throughout the year with NMBs of up to ?51.8%, ?32.0%, and ?54.2%, respectively. Such large discrepancies can be attributed to the uncertainties in emissions, simulated meteorology, and deviation of observations based on air pollution index. Max. 1-h O₃ concentrations in Jan. and Jul. at 36-km are overpredicted with NMBs of 12.0% and 19.3% and agree well in Apr. and Oct. Simulated column variables can capture the high concentrations over the eastern China and low values in the central and western China. Underpredictions occur over the northeastern China for column CO in Apr., TOR in Jul., and AODs in both Apr. and Jul.; and overpredictions occur over the eastern China for column CO in Oct., NO₂ in Jan. and Oct., and AODs in Jan. and Oct. The simulations at 12-km show a finer structure in simulated concentrations than that at 36-km over higher polluted areas, but do not always give better performance than 36-km. Surface concentrations are more sensitive to grid resolution than column variables except for column NO₂, with higher sensitivity over mountain and coastal areas than other regions.     

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.     

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.     

Real-time bias-adjusted O3 and PM2.5 air quality index forecasts and their performance evaluations over the continental United States

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA’s North American Mesoscale (NAM) meteorological model with EPA’s Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2.5) forecasts over the continental United States (CONUS) during 2008. This paper describes the implementation of a real-time Kalman Filter (KF) bias-adjustment technique to improve the accuracy of O₃ and PM_2.5 forecasts at discrete monitoring locations. The operational surface-level O₃ and PM_2.5 forecasts from the NAQFC system were post-processed by the KF bias-adjusted technique using near real-time hourly O₃ and PM_2.5 observations obtained from EPA’s AIRNow measurement network. The KF bias-adjusted forecasts were created daily, providing 24-h hourly bias-adjusted forecasts for O₃ and PM_2.5 at all AIRNow monitoring sites within the CONUS domain. The bias-adjustment post-processing implemented in this study requires minimal computational cost; requiring less than 10 min of CPU on a single processor Linux machine to generate 24-h hourly bias-adjusted forecasts over the entire CONUS domain.The results show that the real-time KF bias-adjusted forecasts for both O₃ and PM_2.5 have performed as well as or even better than the previous studies when the same technique was applied to the historical O₃ and PM_2.5 time series from archived AQF in earlier years. Compared to the raw forecasts, the KF forecasts displayed significant improvement in the daily maximum 8-h O₃ and daily mean PM_2.5 forecasts in terms of both discrete (i.e., reduced errors, increased correlation coefficients, and index of agreement) and categorical (increased hit rate and decreased false alarm ratio) evaluation metrics at almost all locations during the study period in 2008.     

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.     

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.     

Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside

The 24-h average coarse (PM₁₀) and fine (PM_2.5) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM₁₀ and PM_2.5 concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM₁₀ concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM_2.5 concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM₁₀ and PM_2.5 masses showed a high concentration in winter followed by monsoon and summer seasons.The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM₁₀ and PM_2.5 concentrations at the study area. Results indicated that marine aerosol (40.4% in PM₁₀ and 21.5% in PM_2.5) and secondary PM (22.9% in PM₁₀ and 42.1% in PM_2.5) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM₁₀ and 6% in PM_2.5), biomass burning (0.7% in PM₁₀ and 14% in PM_2.5), tire and brake wear (4.1% in PM₁₀ and 5.4% in PM_2.5), soil (3.4% in PM₁₀ and 4.3% in PM_2.5) and other sources (12.7% in PM₁₀ and 6.8% in PM_2.5).     

Air quality during the 2008 Beijing Olympic Games

China is taking major steps to improve Beijing's air quality for the 2008 Olympic Games. However, concentrations of fine particulate matter and ozone in Beijing often exceed healthful levels in the summertime. Based on the US EPA's Models-3/CMAQ model simulation over the Beijing region, we estimate that about 34% of PM_2.5 on average and 35–60% of ozone during high ozone episodes at the Olympic Stadium site can be attributed to sources outside Beijing. Neighboring Hebei and Shandong Provinces and the Tianjin Municipality all exert significant influence on Beijing's air quality. During sustained wind flow from the south, Hebei Province can contribute 50–70% of Beijing's PM_2.5 concentrations and 20–30% of ozone. Controlling only local sources in Beijing will not be sufficient to attain the air quality goal set for the Beijing Olympics. There is an urgent need for regional air quality management studies and new emission control strategies to ensure that the air quality goals for 2008 are met.     

Aerosol transport model evaluation of an extreme smoke episode in Southeast Asia

Biomass burning is one of many sources of particulate pollution in Southeast Asia, but its irregular spatial and temporal patterns mean that large episodes can cause acute air quality problems in urban areas. Fires in Sumatra and Borneo during September and October 2006 contributed to 24-h mean PM₁₀ concentrations above 150 μg m^?3 at multiple locations in Singapore and Malaysia over several days. We use the FLAMBE model of biomass burning emissions and the NAAPS model of aerosol transport and evolution to simulate these events, and compare our simulation results to 24-h average PM₁₀ measurements from 54 stations in Singapore and Malaysia. The model simulation, including the FLAMBE smoke source as well as dust, sulfate, and sea salt aerosol species, was able to explain 50% or more of the variance in 24-h PM₁₀ observations at 29 of 54 sites. Simulation results indicated that biomass burning smoke contributed to nearly all of the extreme PM₁₀ observations during September–November 2006, but the exact contribution of smoke was unclear because the model severely underestimated total smoke emissions. Using regression analysis at each site, the bias in the smoke aerosol flux was determined to be a factor of between 2.5 and 10, and an overall factor of 3.5 was estimated. After application of this factor, the simulated smoke aerosol concentration averaged 20% of observed PM₁₀, and 40% of PM₁₀ for days with 24-h average concentrations above 150 μg m^?3. These results suggest that aerosol transport models can aid analysis of severe pollution events in Southeast Asia, but that improvements are needed in models of biomass burning smoke emissions.     

Particulate matter emissions from on-road vehicles in a freeway tunnel study

Particulate matter, including coarse particles (PM_2.5–10, aerodynamic diameter of particle between 2.5 and 10 μm) and fine particles (PM_2.5, aerodynamic diameter of particle lower than 2.5 μm) and their compositions, including elemental carbon, organic carbon, and 11 water-soluble ionic species, and elements, were measured in a tunnel study. A comparison of the six-hour average of light-duty vehicle (LDV) flow of the two sampling periods showed that the peak hours over the weekend were higher than those on weekdays. However, the flow of heavy-duty vehicles (HDVs) on the weekdays was significant higher than that during the weekend in this study. EC and OC content were 49% for PM_2.5–10 and 47% for PM_2.5 in the tunnel center. EC content was higher than OC content in PM_2.5–10, but EC was about 2.3 times OC for PM_2.5. Sulfate, nitrate, ammonium were the main species for PM_2.5–10 and PM_2.5. The element contents of Na, Al, Ca, Fe and K were over 0.8 μg m^?3 in PM_2.5–10 and PM_2.5. In addition, the concentrations of S, Ba, Pb, and Zn were higher than 0.1 μg m^?3 for PM_2.5–10 and PM_2.5. The emission factors of PM_2.5–10 and PM_2.5 were 18 ± 6.5 and 39 ± 11 mg km^?1-vehicle, respectively. The emission factors of EC/OC were 3.6/2.7 mg km^?1-vehicle for PM_2.5–10 and 15/4.7 mg km^?1-vehicle for PM_2.5 Furthermore, the emission factors of water-soluble ions were 0.028(Mg²⁺)–0.81(SO₄^2?) and 0.027(NO₂^?)–0.97(SO₄^2?) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively. Elemental emission factors were 0.003(V)–1.6(Fe) and 0.001(Cd)–1.05(Na) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively.     

Comparisons of ambient air particulates concentrations (TSP,PM2.5) and dry depositions during smog and non-smog periods at Luliao,Shalu District sampling site

The concentrations of ambient total suspended particulates (TSP) and PM_2.5, and the dry depositions at a sample site at Luliao Junior High School (Luliao) in central Taiwan were measured during smog and non-smog days between December 2017 and July 2018. The results are compared to those obtained during non-smog periods in the years 2015–2017. The mean TSP and PM_2.5 concentrations and dry deposition flux were 72.41?±?26.40, 41.88?±?23.51?μg/m³, and 797.57?±?731.46?μg/m² min, respectively, on the smog days. The mean TSP and PM_2.5 concentrations and dry deposition flux on the non-smog days were 56.39?±?18.08, 34.81?±?12.59?μg/m³ and 468.93?±?600.57?μg/m² min, respectively. The mean TSP concentration in the smog period was 28% greater than that in the non-smog period, and the mean PM_2.5 concentration was 20% higher. The mean dry deposition flux in the smog period was 70% higher than that in the non-smog period at Luliao. The PM_2.5 concentrations exceeded the standards set by the Taiwan EPA (35?μg/m³ daily, and 15?μg/m³ annually). Therefore, the TSP and PM_2.5 concentrations and dry deposition must be reduced in central Taiwan on smog days. In addition, atmospheric TSP and PM_2.5 concentrations at various sampling sites were compared, and those herein were not higher than those measured in other countries. Finally, apart from the local traffic emissions, during smog periods, the other pollution source originated from the transportation process of traffic pollutants emitted in the northwest side of Taiwan.