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Biogenic volatile organic compounds (BVOCs) simulated by current air quality and climate models still have large uncertainties, which can influence atmospheric chemistry and secondary pollutant formation. These modeling sensitivities are primarily due to two sources. One originates from different treatments in the physical and chemical processes associated with the emission rates of BVOCs. The other is errors in the specification of vegetation types and their distribution over a specific region. In this study, the version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) updated by the University of Science and Technology of China (USTC version of WRF-Chem) from the public WRF-Chem(v3.6) is used. The modeling results over eastern China with different versions (v1.0, v2.0, v3.0) of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in WRF-Chem are examined or documented. Sensitivity experiments with these three versions of MEGAN and two vegetation datasets are conducted to investigate the difference of three MEGAN versions in modeling BVOCs and its dependence on the vegetation distributions. The experiments are also conducted for spring (April) and summer (July) to examine the seasonality of the modeling results. The results indicate that MEGAN v3.0 simulates the largest amount of biogenic isoprene emissions over eastern China. The different performance among MEGAN versions is primarily due to their different treatments of applying emission factors and vegetation types. In particular, the results highlight the importance of considering the sub-grid vegetation fraction in estimating BVOC emissions over eastern China, which has a large area of urbanization. Among all activity factors, the temperature-dependent factor dominates the seasonal change of activity factor in all three versions of MEGAN, while the different response to the leaf area index (LAI) change determines the difference among the three versions in seasonal variation of BVOC emissions. The simulated surface ozone concentration due to BVOCs can be significantly different (ranging from 1 to more than 10 ppbv in some regions) among the experiments with three versions of MEGAN, which is mainly due to their impacts on surface VOCs and NO x concentrations. Theoretically MEGAN v3.0 that is coupled with the land surface scheme and considers the sub-grid vegetation effect should overcome previous versions of MEGAN in WRF-Chem. However, considering uncertainties of retrievals and anthropogenic emissions over eastern China, it is still difficult to apply satellite retrievals of formaldehyde and/or limited sparse in situ observations to constrain the uncertain parameters or functions in BVOC emission schemes and their impacts on photochemistry and ozone production. More accurate vegetation distribution and measurements of biogenic emission fluxes and species concentrations are still needed to better evaluate and optimize models. [ABSTRACT FROM AUTHOR]

Air quality is strongly influenced by both local emissions and regional transport. Atmospheric chemical transport models can distinguish between emissions and regional transport sources in air pollutant concentrations. However, quantifying model inventories is challenging due to emission changes caused by the recent strict control measures taken by the Chinese government. In this study, we use NO2 column observations from the Tropospheric Monitoring Instrument to retrieve top-down nitrogen oxide (NOX) emissions and quantify the contributions of local emissions and regional transport to NOx in Beijing (BJ), from 1 November 2018 to 28 February 2019 (W_2018) and 1 November 2019 to 29 February 2020 (W_2019). In W_2018 and W_2019, the BJ bottom-up NOX emissions from the multi-resolution emission inventory for China in 2017 were overestimated by 11.8% and 40.5%, respectively, and the input of NOX from other cities to BJ was overestimated by 10.9% and 51.6%, respectively. The simulation using our adjusted inventory exhibited a much higher spatial agreement (slope = 1.0, R2 = 0.79) and reduced a mean relative error by 45% compared to those of bottom-up NOX emissions. The top-down inventory indicated that (1) city boundary transport contributes approximately 40% of the NOX concentration in BJ; (2) in W_2019, NOX emissions and transport in BJ decreased by 20.4% and 17.2%, respectively, compared to those of W_2018; (3) in W_2019, NOX influx substantially decreased (−699 g/s) in BJ compared to that of W_2018 despite negative meteorological conditions that should have increased NOx influx by +503 g/s. Overall, the contribution of intercity input to NOx in BJ has declined with decreasing emissions in the surrounding cities due to regional cooperative control measures, and the role of local emissions in BJ NOx levels was more prominent. Our findings indicate that local emissions may play vital roles in regional center city air quality. [ABSTRACT FROM AUTHOR]

In this study, the spatiotemporal distribution of the NO 2 and SO 2 Vertical Columns Densities (VCDs) in the North China Plain (NCP) region was measured by long-distance mobile measurements using a mobile Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. The mobile observations were performed in both summer (July 2017) and winter (January and February 2018) and the total driving mileage exceeded 3000 km. The concentrations of NO 2 and SO 2 in different seasons and areas were significantly different. During winter, serious NO 2 and SO 2 pollution was observed in northern Anhui Province, central Shandong Province, and the Beijing-Tianjin-Hebei Region. The evolution and transportation processes of three typical heavy pollution cases were discussed in detail. Combined with the Weather Research and Forecasting with Chemistry model simulated wind field information, the NO 2 transportation flux from northern Jiangsu Province to northern Anhui Province is quantified as 7.12 kg s−1. Finally, we estimated the NO 2 and SO 2 emissions from the Dezhou and Hengshui power plants by plume cross section scanning and encircled observations, respectively. The NO 2 and SO 2 emission fluxes of the Dezhou Power Plant are 0.79 kg s−1 and 1.11 kg s−1, respectively, while the NO 2 and SO 2 emission fluxes of the Hengshui Power Plant are 0.12 kg s−1 and 0.36 kg s−1, respectively. This study quantitatively analyzed the transportation of atmospheric pollutants and power plant emissions, which is helpful for understanding the occurrence and evolution of pollution and is also useful for the government to introduce policies to protect and control the atmospheric environment. • Large-scale and long-distance mobile MAX-DOAS measurements were performed. • The spatiotemporal patterns of the NO 2 and SO 2 VCDs in NCP was measured. • A transportation calculation method was used to estimate the pollutant transportation. • Pollutant emission reduction measures significantly reduce emissions of power plants. [ABSTRACT FROM AUTHOR]