Study on aerosol optical properties and radiative effect in cloudy weather in the Guangzhou region

Characteristics of boundary layer ozone and its effect on surface ozone concentration in Shenzhen, China: A case study

In late September 2019, the longest and most extensive ozone (O₃) pollution process occurred at Pearl River Delta. Base on the observational data, surface-level O₃, vertical distribution characteristics boundary layer O₃ as well as its effect on surface-level O₃ are thoroughly analyzed. The O₃ lidar results showed similar vertical O₃ profiles both in pollution episodes and clean periods, from which a high O₃ concentration layer between 300 and 500 m and a sub-high O₃ concentration layer between 1300 and 1700 m (near the top of the mixing layer) can be found. Besides, the downward O₃ transport paths from the high/sub-high O₃ concentration layers could be observed along with the boundary layer evolution: At nighttime, large amounts of O₃ were effectively stored into the residual layer (RL). Due to the upward development of Mixing layer (ML) in early morning, atmospheric vertical mixing carried the O₃ inside the RL down to the surface, which led to a rapid increase in the surface-level O₃. The sub-high O₃ layer began the downward mixing at noon, and became well-mixed after the boundary layer was fully developed in the afternoon, by which the near surface O₃ pollution deteriorated again. Further analysis of the heavy O₃ pollution episodes show that, the high O₃ concentration inside the RL contributed 54% ± 6% of the surface-level O₃ at 9:00 LT and the average contribution of O₃ in the sub-high concentration layer to the surface-level O₃ at 14:00 LT was 26% ± 9%. Based on the quantitative analysis of the observational data, this paper focus to reveal the importance of the contribution of O₃ inside the RL and near the top of the ML to the surface O₃.

Combined use of satellite and surface observations to study aerosol optical depth in different regions of China

Aerosol optical depth (AOD) is one of essential atmosphere parameters for climate change assessment as well as for total ecological situation study. This study presents long-term data (2000-2017) on time-space distribution and trends in AOD over various ecological regions of China, received from Moderate Resolution Imaging Spectroradiometer (MODIS) (combined Dark Target and Deep Blue) and Multi-angle Imaging Spectroradiometer (MISR), based on satellite Terra. Ground-based stations Aerosol Robotic Network (AERONET) were used to validate the data obtained. AOD data, obtained from two spectroradiometers, demonstrate the significant positive correlation relationships (r = 0.747), indicating that 55% of all data illustrate relationship among the parameters under study. Comparison of results, obtained with MODIS/MISR Terra and AERONET, demonstrate high relation (r = 0.869 - 0.905), while over 60% of the entire sampling fall within the range of the expected tolerance, established by MODIS and MISR over earth (±0.05 ± 0.15 × AODAERONET and 0.05 ± 0.2 × AODAERONET) with root-mean-square error (RMSE) of 0.097-0.302 and 0.067-0.149, as well as low mean absolute error (MAE) of 0.068-0.18 and 0.067-0.149, respectively. The MODIS search results were overestimated for AERONET stations with an average overestimation ranging from 14 to 17%, while there was an underestimate of the search results using MISR from 8 to 22%.

Numerical simulations for the sources apportionment and control strategies of PM2.5 over Pearl River Delta, China, part I: Inventory and PM2.5 sources apportionment

This article uses the WRF-CMAQ model to systematically study the source apportionment of PM_2.5 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 PM_2.5 pollution in the PRD. Results show that the industrial sources accounted for the largest proportion. For emission species, the total amount of NO_x and VOC in Guangdong Province, and NH₃ and VOC in Hunan Province are relatively larger. In Guangdong Province, the emission of SO₂, NO_x 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 PM_2.5 pollution in Guangzhou and Foshan. Meanwhile, emissions from Dongguan and Huizhou (DH), and out of Guangdong Province (SW) are important contributors for PM_2.5 pollution in Guangzhou. For PM_2.5 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 PM_2.5 indicates that the sources of chemical components are similar to those of PM_2.5. In particular, SO₄^2- is mainly sourced from emissions out of Guangdong Province, while the NO^3- and NH⁴⁺ are more linked to agricultural emissions.

Numerical simulations for the sources apportionment and control strategies of PM2.5 over Pearl River Delta, China, part II: Vertical distribution and emission reduction strategies

The contribution of various emission sources to the vertical structure of the PM_2.5 concentration and the modeling of emission reduction strategies are emphasized in this study. Analysis of vertical distribution of PM_2.5 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 PM_2.5 concentration. Results from emission reduction experiments show that PM_2.5 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 PM_2.5 concentration to be slightly higher in the afternoon. Furthermore, below 200-m height, emission reduction experiments perform the effective reduction in PM_2.5 concentration, and higher reduction ratio results in larger reduced PM_2.5 concentration on almost all layers in the PBL.