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This study integrates data from regional model simulations, reanalysis data set, radiosonde observations, lidar measurements, and satellite products to evaluate the direct radiative forcing effect of biomass burning and dust over East Asia. During March and April, we find an overall cooling effect of the dust of −5 to −9 W/m2. Biomass burning aerosols from Peninsular Southeast Asia exhibit a warming effect of 5–10 W/m2 over the source area, lower than that over the downwind area of 10–20 W/m2 because of significantly higher cloud coverage in South China. Dust and biomass burning aerosols are found to cool the near surface layer (0–1 km) by −0.5 and −0.3 K, respectively, and warm the upper air (1–5 km) by +0.1 and +0.2 K, respectively. In Taipei, simultaneous presences of dust and biomass burning lead to cooling of near‐surface air by −1.5 K and warming of upper air by +1 K. Plain Language Summary: Biomass burning and dust are the largest natural emission sources of atmospheric aerosol. However, no solid consensus exists regarding whether biomass burning or dust contributes to a net warming or cooling effect. This study integrates data from regional climate model simulations, reanalysis data, radiosonde observations, lidar measurements, and satellite products to evaluate the climate effects of biomass burning and dust at a regional scale over East Asia. We find prominent warming effects by biomass burning in Peninsular Southeast Asia, which is more significant over the downwind area in South China than over the emission source area. Dust exhibits cooling effects, with a few exceptions over areas covered by semipersistent snow or ice. We also reveal that under conditions in which both biomass burning and dust aerosols are present, they exhibit an overall slight warming effect. Key Points: Peninsular Southeast Asia biomass burning shows larger warming effect (10‐20 W/m2) over downwind region than over the source area (5‐10 W/m2)Dust shows a cooling effect of up to ‐9 W/m2 with a few exceptions along north and east edges of Tibet Plateau due to snow or ice coverDust and biomass burning cool the near surface air and warm the upper air, and their radiative efficiencies decrease during transport [ABSTRACT FROM AUTHOR]

A synergy of numerical simulation, ground-based measurement and satellite observation was applied to evaluate the impact of biomass burning originating from Southeast Asia (SE Asia) within the framework of NASA's 2006 Biomass burning Aerosols in Southeast Asia: Smoke Impact Assessment (BASE-ASIA). Biomass burning emissions in the spring of 2006 peaked in March–April when most intense biomass burning occurred in Myanmar, northern Thailand, Laos, and parts of Vietnam and Cambodia. Model performances were reasonably validated by comparing to both satellite and ground-based observations despite overestimation or underestimation occurring in specific regions due to high uncertainties of biomass burning emission. Chemical tracers of particulate K+, OC concentrations, and OC/EC ratios showed distinct regional characteristics, suggesting biomass burning and local emission dominated the aerosol chemistry. CMAQ modeled aerosol chemical components were underestimated at most circumstances and the converted AOD values from CMAQ were biased low at about a factor of 2, probably due to the underestimation of biomass emissions. Scenario simulation indicated that the impact of biomass burning to the downwind regions spread over a large area via the Asian spring monsoon, which included Southern China, South China Sea, and Taiwan Strait. Comparison of AERONET aerosol optical properties with simulation at multi-sites clearly demonstrated the biomass burning impact via long-range transport. In the source region, the contribution from biomass burning to AOD was estimated to be over 56%. While in the downwind regions, the contribution was still significant within the range of 26%–62%. [ABSTRACT FROM AUTHOR]

BACKGROUND: The Yangtze River Delta (YRD) in China is a densely populated region with recent dramatic increases in energy consumption and atmospheric emissions. OBJECTIVES: We studied how different emission sectors influence population exposures and the corresponding health risks, to inform air pollution control strategy design. METHODS: We applied the Community Multiscale Air Quality (CMAQ) Modeling System to model the marginal contribution to baseline concentrations from different sectors. We focused on nitrogen oxide (NOx) control while considering other pollutants that affect fine particulate matter [aerodynamic diameter ≤ 2.5 µm (PM2.5)] and ozone concentrations. We developed concentration--response (C-R) functions for PM2.5 and ozone mortality for China to evaluate the anticipated health benefits. RESULTS: In the YRD, health benefits per ton of emission reductions varied significantly across pollutants, with reductions of primary PM2.5 from the industry sector and mobile sources showing the greatest benefits of 0.1 fewer deaths per year per ton of emission reduction. Combining estimates of health benefits per ton with potential emission reductions, the greatest mortality reduction of 12,000 fewer deaths per year [95% confidence interval (CI), 1,200-24,000] was associated with controlling primary PM2.5 emissions from the industry sector and reducing sulfur dioxide (SO2) from the power sector, respectively. Benefits were lower for reducing NOx emissions given lower consequent reductions in the formation of secondary PM2.5 (compared with SO2) and increases in ozone concentrations that would result in the YRD. CONCLUSIONS: Although uncertainties related to C-R functions are significant, the estimated health benefits of emission reductions in the YRD are substantial, especially for sectors and pollutants with both higher health benefits per unit emission reductions and large potential for emission reductions. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Aerosol is frequently transported by a southward high-pressure system from the Asian Continent to Taiwan and had been recorded a 100% increase in mass level compared to non-event days from 2002 to 2005. During this time period, PM2.5 sulfate was found to increase as high as 155% on event days as compared to non-event days. In this study, Asian emission estimations, Taiwan Emission Database System (TEDS), and meteorological simulation results from the fifth-generation Mesoscale Model (MM5) were used as inputs for the Community Multiscale Air Quality (CMAQ) model to simulate a long-range transport of PM2.5 event in a southward high-pressure system from the Asian Continent to Taiwan. The simulation on aerosol mass level and the associated aerosol components were found within a reasonable accuracy. During the transport process, the percentage of semi-volatile PM2.5 organic carbon in PM2.5 plume only slightly decreased from 22–24% in Shanghai to 21% near Taiwan. However, the percentage of PM2.5 nitrate in PM2.5 decreased from 16–25% to 1%. In contrast, the percentage of PM2.5 sulfate in PM2.5 increased from 16–19% to 35%. It is interesting to note that the percentage of PM2.5 ammonium and PM2.5elemental carbon in PM2.5 remained nearly constant. Simulation results revealed that transported pollutants dominate the air quality in Taipei when the southward high-pressure system moved to Taiwan. Such condition demonstrates the dynamic chemical transformation of pollutants during the transport process from continental origin over the sea area and to the downwind land. [Copyright &y& Elsevier]

An advanced modeling system with a “one-atmosphere” perspective, Models-3/Community Multi-scale Air Quality (CMAQ) modeling system, driven by MM5/NCEP reanalysis data as the meteorology, and GEOS-Chem outputs as boundary values was applied to simulate the O3, and other gaseous pollutants (SO2 and NO2) evolution among other atmospheric chemicals for July 2001. Comparisons had been made with other models in the MICS-II exercise for the same period. Statistics of both monthly and daily means show that the model skill is very good in reproducing O3 and SO2 with small to moderate RMSE. The model species capture the day-to-day and spatial variability of the observations. The same O3 model concentrations that overpredict most of the EANET observations in the MICS-II study may have underpredicted ones from monitoring networks in Beijing area that is not included in this paper. Vertical O3 profiles at 4 ozonesonde sites are well predicted in July 2001. In fact, our model is among the best of those MICS-II models within the 2-km surface layer. The meteorology near surface and lower troposphere is well reproduced. Compared to SO2 and O3, the NO2 gas concentrations are simulated less well, but the correlation coefficient is still significant. The choice of reanalysis meteorological fields and different boundary conditions generated by different global models may result in diverse spatial patterns exhibited by MICS-II models and ours. Our spatial distributions of O3 shows a high concentration patch covering Beijing, a moderate to high pattern across Korea and Japan Sea, and a low but extensive pattern enclosing southern China, Taiwan, and East Sea. Extension of the pattern to southern China coincides with the existence of pollution problems in Guangdong and Taiwan, but overprediction of O3 over the region deserves further improvement by various factors. One of them can be the grid resolution to resolve the complex orography in or close to the ocean. Another factor can be the refinement of local land use data that changes the micro-meteorology in favor of more air pollution events. [Copyright &y& Elsevier]

Background: The Yangtze River Delta (YRD) in China is a densely populated region with recent dramatic increases in energy consumption and atmospheric emissions. Objectives: We studied how different emission sectors influence population exposures and the corresponding health risks, to inform air pollution control strategy design. Methods: We applied the Community Multiscale Air Quality (CMAQ) Modeling System to model the marginal contribution to baseline concentrations from different sectors. We focused on nitrogen oxide (NOx) control while considering other pollutants that affect fine particulate matter [aerodynamic diameter \(\leq 2.5 \mu m (PM_{2.5})\)] and ozone concentrations. We developed concentration–response (C-R) functions for \(PM_{2.5}\) and ozone mortality for China to evaluate the anticipated health benefits. Results: In the YRD, health benefits per ton of emission reductions varied significantly across pollutants, with reductions of primary \(PM_{2.5}\) from the industry sector and mobile sources showing the greatest benefits of 0.1 fewer deaths per year per ton of emission reduction. Combining estimates of health benefits per ton with potential emission reductions, the greatest mortality reduction of 12,000 fewer deaths per year [95% confidence interval (CI), 1,200–24,000] was associated with controlling primary \(PM_{2.5}\) emissions from the industry sector and reducing sulfur dioxide \((SO_2)\) from the power sector, respectively. Benefits were lower for reducing \(NO_x\) emissions given lower consequent reductions in the formation of secondary \(PM_{2.5}\) (compared with \(SO_2\)) and increases in ozone concentrations that would result in the YRD. Conclusions: Although uncertainties related to C-R functions are significant, the estimated health benefits of emission reductions in the YRD are substantial, especially for sectors and pollutants with both higher health benefits per unit emission reductions and large potential for emission reductions.

Abstract: On February 29th 2012, China published its new National Ambient Air Quality Standard (CH-NAAQS) aiming at revising the standards and measurements for both gaseous pollutants including ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2), and also particle pollutants including PM10 and PM2.5. In order to understand the air pollution status regarding this new standard, the integrated MM5/CMAQ modeling system was applied over Yangtze River Delta (YRD) within this study to examine the criteria gaseous pollutants listed in the new CH-NAAQS. Sensitivity simulations were also conducted to assess the responses of gaseous pollutants under 8 different sector-dependent emission reduction scenarios in order to evaluate the potential control strategies. 2006 was selected as the simulation year in order to review the air quality condition at the beginning of China's 11th Five-Year-Plan (FYP, from 2006 to 2010), and also compared with air quality status in 2010 as the end of 11th FYP to probe into the effectiveness of the national emission control efforts. Base case simulation showed distinct seasonal variation for gaseous pollutants: SO2, and NO2 were found to have higher surface concentrations in winter while O3 was found to have higher concentrations in spring and summer than other seasons. According to the analyses focused on 3 megacities within YRD, Shanghai, Nanjing, and Hangzhou, we found different air quality conditions among the cities: NO2 was the primary pollutant that having the largest number of days exceeding the CH-NAAQS daily standard (80 μg m−3) in Shanghai (59 days) and Nanjing (27 days); SO2 was the primary pollutant with maximum number of days exceeding daily air quality standard (150 μg m−3) in Hangzhou (28 days), while O3 exceeding the daily maximum 8-h standard (160 μg m−3) for relatively fewer days in all the three cities (9 days in Shanghai, 14 days in Nanjing, and 11 days in Hangzhou). Simulation results from predefined potential applicable emission control scenarios suggested significant air quality improvements from emission reduction: 90% of SO2 emission removed from power plant in YRD would be able to reduce more than 85% of SO2 pollution, 85% NO x emission reduction from power plant would reduce more than 60% of NO2 pollution, in terms of reducing the number of days exceeding daily air quality standard. NO x emission reduction from transportation and industry were also found to effectively reduce NO2 pollution but less efficient than emission control from power plants. We also found that multi-pollutants emission control including both NO x and VOC would be a better strategy than independent NO x control over YRD which is China's 12th Five-Year-Plan (from 2011 to 2015), because O3 pollution would be increased as a side effect of NO x control and counteract NO2 pollution reduction benefit. [Copyright &y& Elsevier]

Abstract: We estimated PM2.5-related public health impacts/ton emitted of primary PM2.5, SO2, and NOx for a set of power plants in the Mid-Atlantic and Lower Great Lakes regions of the United States, selected to include varying emission profiles and broad geographic representation. We then developed a regression model explaining variability in impacts per ton emitted using the population distributions around each plant. We linked outputs from the Community Multiscale Air Quality (CMAQ) model v 4.7.1 with census data and concentration–response functions for PM2.5-related mortality, and monetized health estimates using the value-of-statistical-life. The median impacts for the final set of plants were $130,000/ton for primary PM2.5 (range: $22,000–230,000), $28,000/ton for SO2 (range: $19,000–33,000), and $16,000/ton for NOx (range: $7100–26,000). Impacts of NOx were a median of 34% (range: 20%–75%) from ammonium nitrate and 66% (range: 25%–79%) from ammonium sulfate. The latter pathway is likely from NOx enhancing atmospheric oxidative capacity and amplifying sulfate formation, and is often excluded. Our regression models explained most of the variation in impact/ton estimates using basic population covariates, and can aid in estimating impacts averted from interventions such as pollution controls, alternative energy installations, or demand-side management. [Copyright &y& Elsevier]

Abstract: We used the regional air quality model CMAQ to simulate organic aerosol (OA) concentrations over the Pearl River Delta region (PRD) and compared model results to measurements. Our goals were (1) to evaluate the potential contribution of the aqueous reactive uptake of dicarbonyls (glyoxal and methylglyoxal) as a source of secondary organic aerosol (SOA) in an urban environment, and (2) to quantify the sources of SOA in the PRD in fall. We improved the representation of dicarbonyl gas phase chemistry in CMAQ, as well as added SOA formation via the irreversible uptake of dicarbonyls by aqueous aerosols and cloud droplets, characterized by a reactive uptake coefficient γ = 2.9 × 10−3 based on laboratory studies. Our model results were compared to aerosol mass spectrometry (AMS) measurements in Shenzhen during a photochemical smog event in fall 2009. Including the new dicarbonyl SOA source in CMAQ led to an increase in the simulated mean SOA concentration at the sampling site from 4.1 μg m−3 to 9.0 μg m−3 during the smog event, in better agreement with the mean observed oxygenated OA (OOA) concentration (8.0 μg m−3). The simulated SOA reproduced the variability of observed OOA (r = 0.89). Moreover, simulated dicarbonyl SOA was highly correlated with simulated sulfate (r = 0.72), consistent with the observed high correlation between OOA and sulfate (r = 0.84). Including the dicarbonyl SOA source also increased the mean simulated concentrations of total OA from 8.2 μg m−3 to 13.1 μg m−3, closer to the mean observed OA concentration (16.5 μg m−3). The remaining difference between the observed and simulated OA was largely due to impacts from episodic biomass burning emissions, but the model did not capture this variability. We concluded that, for the PRD in fall and outside of major biomass burning events, 75% of the total SOA was biogenic. Isoprene was the most important precursor, accounting for 41% of the total SOA. Aromatics accounted for 13% of the total SOA. Our results show that the aqueous chemistry of dicarbonyls can be an important SOA source, potentially accounting for 53% of the total surface SOA in the PRD in fall. [Copyright &y& Elsevier]

Purpose of this study is to discuss the electric vehicle policy's effects on air pollution reduction in Taiwan. Since PM 2.5 is one of Taiwan's major air-pollution issues, Environmental Protection Administration of Taiwan (TEPA) promoted a policy that the sale of cars powered by fossil fuels would be banned in 2040, which means all the pollutants emitted by petrol-engine vehicles will be reduced. But at the same time the electric vehicles require additional power consumption, therefore, it is important to investigate the effect of air quality and health benefit when mobile emission reduces but power plant emission increases. To evaluate this clean air policy, Weather Research and Forecasting model (WRF) - Community Multi-scale Air Quality model (CMAQ) and Benefits Mapping and Analysis Program (BenMAP) were applied in scenarios discussion. The location of power plants to generate additional electric power and the seasonal variation were adapted in scenarios for considering the atmospheric transportation effects. The results showed if additional power supply was generated in northern, central, or southern Taiwan, the average annual PM 2.5 concentration would be reduced by 2.88, 2.90, and 2.92 μg/m3, respectively. The associated health benefits would be 43.35 billion, 43.40 billion, and 43.54 billion USD. This evaluation presents adopting electric vehicles would improve the air quality of Taiwan significantly. The analysis of seasonal scenarios also indicates the location to generate additional electric power is important when adopting electric vehicles policy. The prevailing wind of different season will transport the air pollutant to diverse downwind area. The additional electricity demand generated by northern power plants in summer and autumn but switched to southern power plants in spring and winter would reduce 2.95 μg/m3 PM 2.5 and lead to the best air quality and health benefits across Taiwan among the considered options. Image 1 • Electric vehicles related air quality policy needs to examine additional power generation and pollution emissions. • WRF-CMAQ-BenMAP models are used to investigate air quality and health co-benefits. • Population distribution, seasonal wind, and emission locations are important in policy making. [ABSTRACT FROM AUTHOR]