[Impacts of Anthropogenic Emission Reduction on Urban Atmospheric Oxidizing Capacity During the COVID-19 Lockdown].

In recent years， regional compound air pollution events caused by fine particles （PM2.5） and ozone （O3） have occurred frequently in economically developed areas of China， in which atmospheric oxidizing capacity （AOC） has played an important role. In this study， the WRF-CMAQ model was used to study the impacts of anthropogenic emission reduction on AOC during the COVID-19 lockdown period. Three representative cities in eastern China （Shijiazhuang， Nanjing， and Guangzhou） were selected for an in-depth analysis to quantify the contribution of meteorology and emissions to the changes in AOC and oxidants and to discuss the impact of AOC changes on the formation of secondary pollutants. The results showed that， compared with that in the same period in 2019， the urban average AOC in Shijiazhuang， Nanjing， and Guangzhou in 2020 increased by 60%， 48.7%， and 12.6%， respectively. The concentrations of O3， hydroxyl radical （·OH）， and nitrogen trioxide （NO3·ï¼‰ increased by 1.6%-26.4%， 14.8%-73.3%， and 37.9%-180%， respectively. The AOC in the three cities increased by 0.06×10-4， 0.12×10-4， and 0.33×10-4 min-1， respectively， due to emission reduction. The meteorological change increased AOC in Shijiazhuang and Nanjing by 20% and 17.9%， respectively， but decreased AOC in Guangzhou by -9.3%. Enhanced AOC led to an increase in the nitrogen oxidation ratio （NOR） and VOCs oxidation ratio （VOR） and promoted the transformation of primary pollutants to secondary pollutants. This offset the effects of primary emission reduction and resulted in a nonlinear decline in secondary pollutants compared to emissions during the COVID-19 lockdown.

[Differences of Three Methods in Determining Ozone Sensitivity in Nanjing].

In recent years， ozone （O3） has become an increasingly important air pollutant in China. Identifying the sensitivity of O3 to the precursors volatile organic compounds （VOCs） and nitrogen oxides （NOx） can help make effective abatement strategies. This study compared three methods for determining O3-VOCs-NOx sensitivity： simulated photochemical indicator values and sensitivity coefficients derived from a three-dimensional air quality model and an observation-based model （OBM）， with a case study involving an O3 pollution event that occurred in Nanjing in late July 2017. The results showed that O3 sensitivity based on the photochemical indicator and sensitivity coefficients demonstrated similar spatial variations （over 50% of the grid cells of Nanjing exhibiting identical O3 sensitivity）. However， sensitivity coefficients identified a larger number of areas within a transitional O3 sensitivity regime， as opposed to the VOCs- or NOx-limited regime identified by the photochemical indicator. The determination of the latter was affected by the adopted threshold values. The OBM relied on the quality of the observational data. For example， positive biases in observed NO2 could lead to an underestimation of O3 sensitivity to NOx with the OBM. During the high pollution period， the three methods exhibited significant disparities. The photochemical indicator tended to suggest the VOCs-limited condition， whereas the OBM and sensitivity coefficients indicated the NOx-limited or transitional regimes.

[Elucidating the Impacts of Meteorology and Emission Changes on Concentrations of Major Air Pollutants in Major Cities in the Yangtze River Delta Region Using a Machine Learning De-weather Method].

This study applied a de-weather method based on a machine learning technique to quantify the contribution of meteorology and emission changes to air quality from 2015 to 2021 in four cities in the Yangtze River Delta Region. The results showed that the significant reductions in PM2.5, NO2, and SO2 emissions(57.2%-68.2%, 80.7%-94.6%, and 81.6%-96.1%, respectively) offset the adverse effects of meteorological conditions, resulting in lower pollutant concentrations. The meteorological contribution of maximum daily 8-h average O3(MDA8_O3) showed a stronger effect than that of others(23.5%-42.1%), and meteorological factors promoted the increase in MDA8_O3 concentrations(4.7%); however, emission changes overall resulted in a decrease in MDA8_O3 concentrations(-3.2%). NO2 and MDA8_O3 decreased more rapidly from 2019 to 2021, mainly because the emissions played a stronger role in reducing pollutant concentrations than from 2015 to 2018. However, emissions changes had weaker reduction effects on PM2.5 and SO2 from 2019 to 2021 than from 2015 to 2018. De-weather methods could effectively seperate the effects of meteorology and emission changes on pollutant trends, which helps to evaluate the real effects of emission control policies on pollutant concentrations.