As the two important ambient air pollutants , particulate matter (PM 2.5 ) and ozone (O 3 ) can both originate from gas nitrogen oxides . In this study, applied by theoretical analysis and machine learning method, we examined the effects of atmospheric reactive nitrogen on PM 2.5 -O 3 pollution, in which nitric oxide (NO), nitrogen dioxide (NO 2 ), gaseous nitric acid (HNO 3 ) and particle nitrate (pNO 3 − ) conversion process has the co-directional and contra-directional effects on PM 2.5 -O 3 pollution. Of which, HNO 3 and SO 2 are the co-directional driving factors resulting in PM 2.5 and O 3 growing or decreasing simultaneously; while NO, NO 2 , and temperature represent the contra-directional factors, which can promote the growth of one pollutant and reduce another one. Our findings suggest that designing the suitable co-controlling strategies for PM 2.5 -O 3 sustainable reduction should target at driving factors by considering the contra-directional and co-directional effects under suitable sensitivity regions. For co-directional driving factors, the design of suitable mitigation strategies will jointly achieve effective reduction in PM 2.5 and O 3 ; while for contra-directional driving factors, it should be more patient, otherwise, it is possible to reduce one item but increase another one at the same time.
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Wang et al. (2024) studied this question.
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