Direct and indirect effects and feedbacks of biomass burning aerosols over Mainland Southeast Asia and South China in springtime.

Southeast Asia is one of the largest biomass burning (BB) source regions in the world. In order to promote our understanding of BB aerosol characteristics and environmental impacts, this study investigated the emission, composition, evolution, radiative effects, and feedbacks of BB aerosols from Mainland Southeast Asia during 15 March to 15 April 2019 by using an online-coupled regional chemistry/aerosol-climate model RIEMS-Chem. Model results are compared against a variety of ground and vertical observations, indicating a generally good model performance for meteorology, aerosol chemical compositions, and aerosol optical properties. It is found that BB aerosols contributed significantly to regional particulate matter (PM), accounting for up to 90 % of the near-surface PM2.5, BC, and OC concentrations over the BB source regions of north Mainland Southeast Asia and for approximately 30-70 % over wide downwind areas including most areas of southwest China and portions of south China. At the top of atmosphere (TOA), BB aerosols exerted a positive all-sky radiative effect (DREBB) up to 25 W/m2 over north Vietnam and south China, a negative DREBB up to -10 W/m2 over Myanmar, western Thailand, and southwest China. Meanwhile, the indirect radiative effect (IREBB) was consistently negative, with the maximum of -10 W/m2 over downwind areas with cloud coverage, e.g., from north Vietnam to most of south China. The subregional (95-125°E and 10-30°N) and period mean DREBB and IREBB at TOA were estimated to be 0.69 W/m2 and - 0.63 W/m2, respectively, leading a total radiative effect (TREBB) of 0.06 W/m2 at TOA. The radiative effects of BB aerosols led to decreases in sensible and latent heat fluxes, near-surface temperature, PBL height, and wind speed of 6.0 Wm-2, 9.0 Wm-2, 0.26 °C, 38.7 m, and 0.1 m/s, respectively, accompanied with an increase in RH of 1.9 %, averaged over the subregion and the study period. The accumulated precipitation during the study period was apparently reduced by BB aerosols from east Thailand to south China, with the maximum reduction up to 14 cm (exceeding 40 %) over north Vietnam and south China. TREBB tended to increase mean near-surface PM2.5 and its component concentrations, with the maximum percentage increase up to 24 % over the BB source regions of north Mainland Southeast Asia, resulting from the combined effects of dynamic and chemical feedbacks. DREBB generally dominated over IREBB in the feedback-induced PM2.5 concentration changes.

Impact of dynamical and microphysical schemes on black carbon prediction in a regional climate model over India.

Aerosol concentrations and their properties strongly depend on dynamics of atmosphere. Effects of physical and dynamical parameterizations on meteorology and black carbon (BC) mass in Weather Research and Forecasting model coupled with Chemistry (WRF-CHEM) are investigated over India. Simulations are performed in ten experiments considering two boundary layer, three cumulus parameterization, and five microphysics schemes during winter and monsoon of 2008. Morrison double-moment physical parameterization, Yonsei University boundary layer parameterization with Kain-Fritsch and Grell-Freitas cumulus parameterization schemes are found suitable to simulate meteorology and BC mass over India. BC mass is found to be underestimated in almost all experiments during winter; while, BC mass is overestimated in monsoon over Ahmedabad, Delhi, and Kanpur, which suggests inefficient wet scavenging of BC in monsoon, while lower emission rate may cause differences in winter. The results will be useful in understanding parameterizations and their impact on aerosols.

Investigation of PM2.5 mass concentration over India using a regional climate model.

Seasonal variation of PM2.5 (Particulate Matter <2.5 µm) mass concentration simulated from WRF-Chem (Weather Research and Forecasting coupled with Chemistry) over Indian sub-continent are studied. The simulated PM2.5 are also compared with the observations during winter, pre-monsoon, monsoon and post-monsoon seasons of 2008. Higher value of simulated PM2.5 is observed during winter followed by post-monsoon, while lower values are found during monsoon. Indo-Gangetic Basin (IGB) exhibits high amount of PM2.5 (60- 200 µg m-3) throughout the year. The percentage differences between model simulated and observed PM2.5 are found higher (40- 60%) during winter, while lower (< 30%) during pre-monsoon and monsoon over most of the study locations. The weighted correlation coefficient between model simulated and observed PM2.5 is 0.81 at the significance of 98%. Associated RMSE (Root Mean Square Error) is 0.91 µg m-3. Large variability in vertically distributed PM2.5 are also found during pre-monsoon and monsoon. The study reveals that, model is able to capture the variabilities in spatial, seasonal and vertical distributions of PM2.5 over Indian region, however significant bias is observed in the model. PM2.5 mass concentrations are highest over West Bengal (82± 33 µg m-3) and the lowest in Jammu & Kashmir (14± 11 µg m-3). Annual mean of simulated PM2.5 mass over the Indian region is found to be 35± 9 µg m-3. Higher values of PM2.5 are found over the states, where the reported respiratory disorders are high. WRF-Chem simulated PM2.5 mass concentration gives a clear perspective of seasonal and spatial distribution of fine aerosols over the Indian region. The outcomes of the study have significant impacts on environment, human health and climate.