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The contribution of various emission sources to the vertical structure of the PM2.5 concentration and the modeling of emission reduction strategies are emphasized in this study. Analysis of vertical distribution of PM2.5 concentration in the planetary boundary layer (PBL) reveals that strong diurnal cycle exists during the pollution episodes, with heavier surface pollution in nocturnal periods. Contributions from transportation and agriculture are mainly restricted to the surface, while contributions from industry and power are distributed in a relatively higher layer. In the northerly-controlled episodes, the contribution of local emissions mainly accumulates below 300 m and the impact of the emissions from surrounding cities can reach 500–600 m during nocturnal periods. The contributions outside of Guangdong are uniformly distributed within 1000 m altitude. In the daytime, the contribution of emissions is basically uniform throughout the PBL. In the southerly-controlled episodes, the contribution of local emission mainly concentrates below 400 m during the nocturnal periods. Emissions from surrounding cities can exert the influence below 1000 m height, and the contribution outside of Guangdong reaches even 1500 m. In the daytime, the contribution of emissions in the PBL is distributed evenly. The highest altitude of the contribution from different subdomains that can reach is closely related to the physical property of the PBL. The industrial and agricultural emissions are the most important contributors for the surface PM2.5 concentration. Results from emission reduction experiments show that PM2.5 reduces significantly near the pollution center. Although control efficiency decreases with the increasing reduction ratio, the efficiency differences between 30% and 50% reduction is limited. In particular, 10% reduction in industrial emission causes PM2.5 concentration to be slightly higher in the afternoon. Furthermore, below 200-m height, emission reduction experiments perform the effective reduction in PM2.5 concentration, and higher reduction ratio results in larger reduced PM2.5 concentration on almost all layers in the PBL.

This article uses the WRF-CMAQ model to systematically study the source apportionment of PM2.5 under typical meteorological conditions in the dry season (November 2010) in the Pearl River Delta (PRD). According to the geographical location and the relative magnitude of pollutant emission, Guangdong Province is divided into eight subdomains for source apportionment study. The Brute-Force Method (BFM) method was implemented to simulate the contribution from different regions to the PM2.5 pollution in the PRD. Results show that the industrial sources accounted for the largest proportion. For emission species, the total amount of NOx and VOC in Guangdong Province, and NH3 and VOC in Hunan Province are relatively larger. In Guangdong Province, the emission of SO2, NOx and VOC in the PRD are relatively larger, and the NH3 emissions are higher outside the PRD. In northerly-controlled episodes, model simulations demonstrate that local emissions are important for PM2.5 pollution in Guangzhou and Foshan. Meanwhile, emissions from Dongguan and Huizhou (DH), and out of Guangdong Province (SW) are important contributors for PM2.5 pollution in Guangzhou. For PM2.5 pollution in Foshan, emissions in Guangzhou and DH are the major contributors. In addition, high contribution ratio from DH only occurs in severe pollution periods. In southerly-controlled episode, contribution from the southern PRD increases. Local emissions and emissions from Shenzhen, DH, Zhuhai-Jiangmen-Zhongshan (ZJZ) are the major contributors. Regional contribution to the chemical compositions of PM2.5 indicates that the sources of chemical components are similar to those of PM2.5. In particular, SO42- is mainly sourced from emissions out of Guangdong Province, while the NO3- and NH4+ are more linked to agricultural emissions.

Up to now, a nation-wide scale study of surface ozone (O3) concentrations in China was limited due to scarce observation. Thanks to the establishment of national air quality monitoring network in 2013, surface O3 data from 1402 stations during 2014–2017 were collected to investigate O3 seasonality. Our analysis reveals that the variations of monthly O3 averaged from daily mean concentration during a year show different temporal profiles depending on latitude. A unimodal structure (UMS) is generally found for latitudes over 35°N, whereas a bimodal structure (BMS) is in most of the cases identified south of 35°N. The peak of UMS is found in the period of May to July, whereas the first and second peaks of BMS are found from April to June, and from July to October, respectively. In addition, the seasonality of O3 presents a strong dependence on pseudo-equivalent potential temperature and monsoonal clouds. The onset and retreat of warm and wet air are correlated to the summer minimum in BMS cases and to the sharp decrease of UMS in July. As far as the relationships between O3 and carbon monoxide are concerned, the effects of clean maritime air masses on the summer trough of O3 are not significant for inland sites. Overall, summer monsoon bringing warm and moist air and subsequent clouds leads to the suppression of photochemical production, thereby contributing directly to the geographical distribution of O3 seasonality.

To evaluate the impact of emission control measures on the air quality in the Pearl River Delta (PRD) region of South China, statistic data including atmospheric observations, emissions and energy consumptions during 2006-2014 were analyzed, and a Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model was used for various scenario simulations. Although energy consumption doubled from 2004 to 2014 and vehicle number significantly increased from 2006 to 2014, ambient SO2, NO2 and PM10 were reduced by 66%, 20% and 24%, respectively, mainly due to emissions control efforts. In contrast, O3 increased by 19%. Model simulations of three emission control scenarios, including a baseline (a case in 2010), a CAP (a case in 2020 assuming control strength followed past control tendency) and a REF (a case in 2020 referring to the strict control measures based on recent policy/plans) were conducted to investigate the variations of air pollutants to the changes in NOx, VOCs and NH3 emissions. Although the area mean concentrations of NOx, nitrate and PM2.5 decreased under both NOx CAP (reduced by 1.8%, 0.7% and 0.2%, respectively) and NOx REF (reduced by 7.2%, 1.8% and 0.3%, respectively), a rising of PM2.5 was found in certain areas as reducing NOx emissions elevated the atmospheric oxidizability. Furthermore, scenarios with NH3 emission reductions showed that nitrate was sensitive to NH3 emissions, with decreasing percentages of 0-10.6% and 0-48% under CAP and REF, respectively. Controlling emissions of VOCs reduced PM2.5 in the southwestern PRD where severe photochemical pollution frequently occurred. It was also found that O3 formation in PRD was generally VOCs-limited while turned to be NOx-limited in the afternoon (13:00-17:00), suggesting that cutting VOCs emissions would reduce the overall O3 concentrations while mitigating NOx emissions in the afternoon could reduce the peak O3 levels.