[Response of PM_2.5 and O₃ to Emission Reductions in Nanjing Based on Random Forest Algorithm]

High levels of fine particulate matter (PM_2.5) and ozone (O₃) in ambient air affect climate change and also endanger human health and ecosystems. Air pollution in Nanjing has been improving since the implementation of the "Air Pollution Prevention and Control Action Plan" in 2013. However, Nanjing still faces PM_2.5 and O₃ pollution. Evaluating the response of pollutant concentrations to the reductions in precursor emissions is helpful to obtain effective strategies of emission reduction to improve pollution levels. The sensitive simulations of emission perturbation in atmospheric chemistry models directly demonstrate the response of pollution to the reductions in emissions. Nevertheless, these sensitive simulations are limited in computing time and resources. The random forest algorithm was trained by using the simulation results of the atmospheric chemical transport model (GEOS-Chem) in 2015. The changes in daily PM_2.5 and daily maximum eight-hour O₃ (MDA8 O₃) concentrations in Nanjing in 2019 were efficiently predicted under different reduction scenarios of anthropogenic emissions. The simulations showed that the seasonal average of ρ(PM_2.5) in Nanjing would decrease by 2-4 μg·m^-3 with the reduction in anthropogenic emissions of 10% in 2019 in China. In the case of controlling only local emissions in Nanjing, the concentrations of PM_2.5 in Nanjing decreased significantly without local anthropogenic emissions. Additionally, the simulations showed that the annual average of ρ(PM_2.5) in Nanjing could be lower than the national secondary limit (35 μg·m^-3) when the anthropogenic emission reduction in China was higher than 20% in 2019. For ozone, the equal proportional emission reductions in nitrogen oxides (NO) and volatile organic pollutants (VOCs) of O₃ precursors in China likely led to the increase in seasonal average concentrations of O₃ in Nanjing. For the proportional reduction of anthropogenic emissions by 10%-50% in China, the seasonal average of ρ(MDA8 O₃) in Nanjing in 2019 would increase by 1-3 μg·m^-3 in spring, 1-4 μg·m^-3 in autumn, and 3-11 μg·m^-3 in winter, respectively, compared with that in the base simulation. With the reduction in anthropogenic NO emission by 10% and VOCs by 20%, the seasonal average of ρ(MDA8 O₃) in Nanjing would decrease by 3-6 μg·m^-3. On this basis, further increasing the proportion (30%) of VOCs emission reduction could reduce the annual average of ρ(MDA8 O₃) in Nanjing by 7 μg·m^-3. However, the annual average of ρ(MDA8 O₃) of Nanjing in 2019 increased by 1 μg·m^-3, with the local emission reduction of NO by 10% and VOCs by 30%. Therefore, this showed that the key to alleviate ozone pollution in Nanjing is a reasonable control ratio of ozone precursor emissions and the implementation of regional joint prevention and control. In order to effectively reduce the O₃ pollution in Nanjing, the emission reduction ratio of NO and VOCs in China should be less than 1:2. The response of pollutant concentrations to reductions in precursor emissions were efficiently obtained by the random forest algorithm and GEOS-Chem model. The simulations would provide the scientific basis for the emission control strategy to alleviate air pollution.