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Photochemical air quality models (AQMs) are a vital tool for atmospheric pollution research and have been widely used in various applications, such as air quality prediction and evaluation of pollution control strategies. Before using these models for further studies, it is essential to thoroughly evaluate their reliability and accuracy. While previous guidelines and benchmarks have primarily focused on fine particulate matter (PM 2.5) and ozone (O 3), there is still a lack of benchmarks for evaluating the model performance on primary criteria pollutants such as sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM 10). The use of air quality models in China has increased significantly in the past decades. However, there is still a lack of standardized benchmarks for the performance evaluation of these models. Building upon our previous work on PM 2.5 and its chemical species, we propose a set of benchmarks for evaluating the performance of the aforementioned four air pollutants. Initially, we identified a total of 475 papers published during 2007–2019 that utilized at least one of the five commonly used AQMs in China. From these papers, we selected 164 articles that provided model performance evaluation (MPE) results of the four primary air pollutants. The three most frequently used Model Performance Evaluation (MPE) metrics were selected to analyse the impact of different model configurations on the reported statistics, including modelling region, season, and emission inventory. Lastly, three commonly used statistical indicators, including normalized mean bias (NMB), normalized mean error (NME), and correlation coefficient (R), were proposed for the validation of simulated NO 2 , SO 2 , CO, and PM 10. Two sets of benchmarks are given, including the "goal" and "criteria". The "goal" represents the best range of performance that a model can be expected to achieve, and the "criteria" represents performance that the majority of studies have achieved. We recommend R values above 0.50, 0.35, 0.45, and 0.40 for NO 2 , SO 2 , PM 10 , and CO, respectively, in order to meet the "criteria" benchmark. If the "goal" benchmark is to be achieved, the corresponding R values are 0.60, 0.55, 0.60, and 0.60. The "goal" benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are within ±20%, ±25%, ±20%, and ±25%, respectively; while the "goal" benchmarks of NME for the four pollutants are less than 40%, 45%, 45%, and 60%, respectively. These benchmarks supplement our previous benchmarks for PM 2.5 and its components and provide a more comprehensive guideline for the air quality modelling community in China. • A set of benchmarks for evaluation of the NO 2 , SO 2 , CO and PM 10 simulation over China are proposed. • Three commonly used statistical indicators (NMB, NME, and R) were proposed for the validation of the four pollutants. • The goal benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are <20%, <25%, <20% and <25%, respectively. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports findings of a recent field study that characterized the on-road emissions of individual diesel vehicles in and around Beijing, China during November and December of 2009. We successfully sampled 230 individual trucks on 4 major expressways around the city as well as 57 individual buses in the city using refined mobile chasing techniques and fast response instruments. Emission factors (EF) for carbon monoxide (CO), black carbon (BC) and particulate matter with diameters less than 0.5 μm (PM0.5) are derived from the measurements, which are consistent with the results from laboratory dynamometer tests. The PM0.5 number emission factor distributions demonstrate consistent bimodal modes with peaks around 10 nm and 80 nm, while the mass emission factor distributions demonstrate a unimodal maximum around 110 nm for a majority of the trucks. The BC emissions are shown to be highly correlated with the mass emission of particles with 100–250 nm diameters, which are in good agreement with the results from previous studies. A number of important policy implications are discussed based on the results from this study. First, we identified “heavy emitters” in the on-road fleet we encountered, finding that 5% of diesel trucks in this sample are responsible for 50% of total BC emissions, and 20% of the trucks are responsible for 50% CO and PM0.5 number emissions, 60% PM0.5 mass emissions and over 70% of BC emissions. This suggests that emissions control programs should include identifying and removing heavy emitters from the road or improving their emissions. Second, the BC and PM0.5 number emission factors of trucks registered in regions outside Beijing are significantly higher than those of Beijing-registered trucks, suggesting that improving engine and fuel standards in Beijing alone is not sufficient in reducing the traffic-related air pollution in Beijing. Third, the significantly lower emissions from Euro IV and CNG buses compared to the Euro II and Euro III buses support that introducing clean-burning buses is an effective way to reduce the overall vehicle emissions for the pollutants studied. Fourth, our refined chasing method demonstrates a cost-effective approach to characterize the emissions from a large number of on-road diesel vehicles. Further studies with large sample sizes are critical to constructing more accurate mobile emission inventories to represent the on-road vehicle population. [Copyright &y& Elsevier]

Abstract: 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 (PM2.5, particles with aerodiameter less than or equal to 2.5μm) 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 (NOx) 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 PM2.5 can also decline by 3–15μgm−3 (4–25%) due to the lower SO2 and sulfate concentrations. If similar controls are implemented for NOx emissions, NOx concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM2.5 concentrations will also decline by 2–14μgm−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 8–30ppb. [Copyright &y& Elsevier]

Abstract: Valuation of health effects of air pollution is becoming a critical component of the performance of cost–benefit analysis of pollution control measures, which provides a basis for setting priorities for action. Beijing has focused on control of transport emission as vehicular emissions have recently become an important source of air pollution, particularly during Olympic games and Post-games. In this paper, we conducted an estimation of health effects and economic cost caused by road transport-related air pollution using an integrated assessment approach which utilizes air quality model, engineering, epidemiology, and economics. The results show that the total economic cost of health impacts due to air pollution contributed from transport in Beijing during 2004–2008 was 272, 297, 310, 323, 298 million US$ (mean value), respectively. The economic costs of road transport accounted for 0.52, 0.57, 0.60, 0.62, and 0.58% of annual Beijing GDP from 2004 to 2008. Average cost per vehicle and per ton of PM10 emission from road transport can also be estimated as 106 US $/number and 3584 US $ t−1, respectively. These findings illustrate that the impact of road transport contributed particulate air pollution on human health could be substantial in Beijing, whether in physical and economic terms. Therefore, some control measures to reduce transport emissions could lead to considerable economic benefit. [Copyright &y& Elsevier]

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 12km 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. [Copyright &y& Elsevier]

The air pollution in China has presented remarkable regional and complex characteristics, and particle explosive growth events happened frequently. In view of the domestic situation, a new synergistic approach, which could detect particle pollution over large area rapidly, is urgently needed. A rapid detection approach based on multiple mobile vehicle-based lidar systems is proposed to meet the needs of regional particle pollution observation in this paper. Take the Jing-Jin-Ji (the abbreviation of Beijing-Tianjin-Hebei) area for example, the methodology and practice of the rapid synergistic approaches with three sets of mobile vehicle-based lidars are presented. On the premise of synergistic observation scheme design and data quality control, we conducted a synergistic observation of aerosol in Jing-Jin-Ji area on 4 November 2017. Then the spatial distribution and transport characteristics of particle pollution in this area are discussed. The synergistic observation results show that high aerosol extinction was observed on the southwest pathway in this case. Furthermore, the spatial distribution characteristics of aerosol optical depth and boundary layer height were analyzed in this study. The comprehensive analysis of synergistic observation results, backward trajectories, and near-surface concentration of PM 2.5 based on in situ instrument further illustrated the transport from the southwest pathway strongly affects air quality. The synergistic approach based on multiple mobile vehicle-based lidars provides an effective approach on regional pollution tracking and characterizing within hours. • A synergistic approach for regional pollution tracking based on multiple mobile vehicle-based lidars was presented. • Characteristics of the regional distribution of aerosol particles in Jing-Jin-Ji were observed. • The significant AOD and BLH was found together on the southwest pathway in the early stage of haze development. [ABSTRACT FROM AUTHOR]