Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China.
Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China.
Int J Environ Res Public Health. 2023 Jan 27;20(3):2282. doi: 10.3390/ijerph20032282.
As the threat to human life and health from fine particulate matter (PM) increases globally, the life and health problems caused by environmental pollution are also of increasing concern. Understanding past trends in PM and exploring the drivers of PM are important tools for addressing the life-threatening health problems caused by PM. In this study, we calculated the change in annual average global PM concentrations from 2000 to 2020 using the Theil-Sen median trend analysis method and reveal spatial and temporal trends in PM concentrations over twenty-one years. The qualitative and quantitative effects of different drivers on PM concentrations in 2020 were explored from natural and socioeconomic perspectives using a multi-scale geographically weighted regression model. The results show that there is significant spatial heterogeneity in trends in PM concentration, with significant decreases in PM concentrations mainly in developed regions, such as the United States, Canada, Japan and the European Union countries, and conversely, significant increases in PM in developing regions, such as Africa, the Middle East and India. In addition, in regions with more advanced science and technology and urban management, PM concentrations are more evenly influenced by various factors, with a more negative influence. In contrast, regions at the rapid development stage usually continue their economic development at the cost of the environment, and under a high intensity of human activity. Increased temperature is known as the most important factor for the increase in PM concentration, while an increase in NDVI can play an important role in the reduction in PM concentration. This suggests that countries can achieve good air quality goals by setting a reasonable development path.
随着细颗粒物 (PM) 对人类生命和健康的威胁在全球范围内不断增加，环境污染所导致的生命和健康问题也越来越受到关注。了解 PM 的过去趋势并探索 PM 的驱动因素是解决由 PM 引起的威胁生命的健康问题的重要工具。在本研究中，我们使用 Theil-Sen 中位数趋势分析方法计算了 2000 年至 2020 年期间全球年平均 PM 浓度的变化，并揭示了二十一年来 PM 浓度的时空变化趋势。从自然和社会经济角度出发，利用多尺度地理加权回归模型，探讨了不同驱动因素对 2020 年 PM 浓度的定性和定量影响。结果表明，PM 浓度趋势存在显著的空间异质性，发达地区如美国、加拿大、日本和欧盟国家的 PM 浓度显著下降，而发展中地区如非洲、中东和印度的 PM 浓度则显著上升。此外，在科学技术和城市管理更为先进的地区，PM 浓度受各种因素的影响更为均衡，负面影响也更大。相比之下，处于快速发展阶段的地区通常以牺牲环境为代价来维持经济发展，在高强度的人类活动下，气温升高被认为是 PM 浓度增加的最重要因素，而 NDVI 的增加可以在降低 PM 浓度方面发挥重要作用。这表明各国可以通过设定合理的发展路径来实现良好的空气质量目标。
