Interaction Patterns between Climate Action and Air Cleaning in China: A Two-Way Evaluation Based on an Ensemble Learning Approach.

China will attempt to achieve its simultaneous goals in 2060, whereby carbon neutrality will be accomplished and the PM2.5 (fine particulate matter) level is expected to remain below 10 µg/m3. Identifying interaction patterns between air cleaning and climate action represents an important step to obtain cobenefits. Here, we used a random sampling strategy through the combination of chemical transport modeling and machine learning approach to capture the interaction effects from two perspectives in which the driving forces of both climate action and air cleaning measures were compared. We revealed that climate action where carbon emissions were decreased to 1.9 Bt (billion tons) could lead to a PM2.5 level of 12.4 µg/m3 (95% CI (confidence interval): 10.2-14.6 µg/m3) in 2060, while air cleaning could force carbon emissions to reach 1.93 Bt (95% CI: 0.79-3.19 Bt) to achieve net carbon neutrality based on the potential carbon sinks in 2060. Additional controls targeting primary PM2.5, ammonia, and volatile organic compounds were required as supplements to overcome the partial lack of climate action. Our study provides novel insights into the cobenefits of air-quality improvement and climate change mitigation, indicating that the effect of air cleaning on the simultaneous goals might have been underestimated before.

Identification method and application of critical load contribution areas based on river retention effect.

For the entire watershed, the critical source areas (CSAs) and the critical load contribution areas (CLCAs) are two completely different concepts. The CLCAs can reflect the impact of river retention effects on pollutant transmission. In this study, an integrated modelling approach was developed for those complex watersheds by combining two models: MECM (modified export coefficient model) and SWAT (Soil and Water Assessment Tool). A case study was performed in a typical rural area-Miyun Reservoir watershed, China. The simulated results indicated that anthropogenic pollution is the main source of pollutants in most townships, including livestock breeding, rural activities, and crop cultivation. It spreads upstream with the outlet of the basin as the center, and the transport efficiency decays regularly, so the location of the pollution source is closely related to its transport efficiency. The river retention effect has a significant retardation effect on the transportation of pollutants, more than half of the pollutant load will be deposited in the river network. Generally, the CLCAs are concentrated in the area where the transport efficiency and pollutant load are relatively high, which is quite different from the spatial distribution of the CSAs. The research results fully excavated the transmission path and process of pollutants, especially the process of river migration, which helps to improve the scientific configuration of management practices.