
PM2.5-O3 composite pollution is a pressing atmospheric challenge in China, necessitating an assessment of territorial spatial landscape patterns’ impact for atmospheric governance and spatial planning. This study reclassifies territorial space within the Yangtze River Delta urban agglomeration into an agricultural-urban-ecological space system and calculates landscape metrics. Variables are screened using a random forest model and collinearity test. The geographically and temporally weighted regression (GTWR) model explores the spatiotemporally heterogeneous impact of selected landscape metrics on PM2.5 and O3 concentrations. A tradeoff-synergy analysis is conducted to propose planning strategies. Findings indicate that PM2.5 and O3 concentrations are numerically and spatially correlated, with increasing temporal stability but significant spatial heterogeneity in their responses to metrics. Agricultural production space aggregation index (AP_AI) and forest area percentage (FO_PLAND) are identified as trade-off and synergy factors for coordinated control, respectively. Grassland largest patch index (GR_LPI) and other ecological spaces patch density (OT_PD) are individual factors for PM2.5 reduction. The study advocates for spatial zoning with intra- and inter-zonal cooperation policies and coordinated control guidelines centered on agricultural production space utilization.
PM2.5-O3复合污染已成为中国面临的严峻大气环境挑战,为大气治理和空间规划提供依据,需要评估区域空间格局对PM2.5和O3浓度的影响。本研究将长江三角洲城市群的国土空间划分为农业-城市-生态空间系统,并计算景观指数。通过随机森林模型和共线性检验筛选变量,然后利用地理和时空加权回归(GTWR)模型探究选定景观指数对PM2.5和O3浓度的时空异质性影响,并进行权衡-协同分析提出规划策略。研究发现,PM2.5和O3浓度在数值和空间上均呈正相关,污染物浓度对指标的响应时间稳定性增加,空间异质性显著。农业生产空间集聚指数(AP_AI)和森林覆盖率(FO_PLAND)分别是协调控制的权衡和协同因素。草地最大斑块指数(GR_LPI)和其他生态空间斑块密度(OT_PD)是PM2.5减排的独立因素。研究提倡进行空间分区,并辅以区域内和区域间合作政策,以及以农业生产空间利用为中心的协调控制指南。
PM2.5-O3 composite pollution is a pressing atmospheric challenge in China, necessitating an assessment of territorial spatial landscape patterns’ impact for atmospheric governance and spatial planning. This study reclassifies territorial space within the Yangtze River Delta urban agglomeration into an agricultural-urban-ecological space system and calculates landscape metrics. Variables are screened using a random forest model and collinearity test. The geographically and temporally weighted regression (GTWR) model explores the spatiotemporally heterogeneous impact of selected landscape metrics on PM2.5 and O3 concentrations. A tradeoff-synergy analysis is conducted to propose planning strategies. Findings indicate that PM2.5 and O3 concentrations are numerically and spatially correlated, with increasing temporal stability but significant spatial heterogeneity in their responses to metrics. Agricultural production space aggregation index (AP_AI) and forest area percentage (FO_PLAND) are identified as trade-off and synergy factors for coordinated control, respectively. Grassland largest patch index (GR_LPI) and other ecological spaces patch density (OT_PD) are individual factors for PM2.5 reduction. The study advocates for spatial zoning with intra- and inter-zonal cooperation policies and coordinated control guidelines centered on agricultural production space utilization.
@article{2024_jcp_pm25_o3,
title={Impact of territorial spatial landscape pattern on PM2.5 and O3 concentrations in the Yangtze River delta urban agglomeration: Exploration and planning strategies},
author={Xin Chen and 蔚芳},
journal={Journal of Cleaner Production},
year={2024},
doi={10.1016/j.jclepro.2024.142172}
}