Spatial and temporal distribution of PM2.5 and O3 in north China from 2011 to 2020: Patterns and influence mechanisms

Liu, Jingya; Ding, Weifu

doi:10.1016/j.apr.2023.101906

Cited by 7 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The emissions of CO 2 and air pollutants will undergo fundamental changes, and the changes in energy layout, industrial layout, and emissions will further have a positive effect on the ecological environment [67]. Special management for different air pollutants not only should to be implemented, but also should to reduce production of their pollutant precursors, minimize the internal transformation of pollutants, and avoid the situation where O 3 concentration will continue to rise while PM 2.5 concentration will decrease significantly [26]. Hence, it is meaningful to follow the general direction of carbon and pollution reduction in the YRB [50].…”

Section: Heterogeneity Analysis From Different Sub-watershedsmentioning

confidence: 99%

“…Ground-level O 3 is also affected by weather conditions, such as rainfall [25]. Existing studies on synergistic mechanisms have confirmed that PM 2.5 and O 3 are homologous pollutants, while NO x and VOCs are common precursors of both [26]. Meanwhile, there is a complex chemical coupling mechanism between the two pollutants, whose relationship will change significantly with the rapid evolution of pollution [27].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Synergistic Evolution of PM2.5 and O3 Concentrations: Evidence from Environmental Kuznets Curve Tests in the Yellow River Basin

Qi,

Miao,

Xie

et al. 2024

Sustainability

View full text Add to dashboard Cite

Air pollution, especially the synergistic pollution of PM2.5 and O3, poses a severe threat to human life and production. The synergistic formation mechanism of PM2.5 and O3 pollution is relatively confirmed, while research on their spatiotemporal synergy is urgent. Based on remotely sensed interpretation data from 90 cities in the Yellow River Basin, we analyzed the synergistic evolution of PM2.5 and O3 concentrations during 2013–2020. Combined with the environmental Kuznets curve, we performed factor analysis using a panel regression model. The synergistic evolution pattern shows a gradual decrease in PM2.5 concentration and a gradual increase in O3 concentration. There is a strong spatial auto-correlation in the two pollutants’ concentrations. The relationship between economy and PM2.5 concentration shows an “N-shaped” curve, while that between O3 concentration and economic development presents an inverse “N-shaped” curve. The environmental Kuznets curve shows that the deterioration of O3 pollution takes place later than the mitigation of PM2.5 pollution. Various factors have obvious heterogeneous effects on PM2.5 and O3 concentrations. Meanwhile, the sensitivity effect of per capita GDP on PM2.5 concentration in the midstream region is stronger than that in the upstream region, while the sensitivity effect of per capita GDP on O3 concentration is strongest in the midstream region than that in upstream and downstream region.

show abstract

Section: Heterogeneity Analysis From Different Sub-watershedsmentioning

confidence: 99%