College of Geography and Environment, Shandong Normal University, Jinan, Shandong, China.
Inspur Software Technology Co., Ltd., Jinan, Shandong, China.
PLoS One. 2024 Oct 3;19(10):e0310190. doi: 10.1371/journal.pone.0310190. eCollection 2024.
In the rapid development of air pollution over the past two decades in Shandong Province, it has played a detrimental role, causing severe damage to regional ecological security and public health. There has been little research at the county scale to explore the spatiotemporal causes and heterogeneity of PM2.5 pollution. This study utilizes a Geographically and Temporally Weighted Regression Model (GTWR) to environmentally model meteorological elements and socioeconomic conditions in Shandong Province from 2000 to 2020, aiming to identify the key driving factors of PM2.5 concentration changes across 136 counties. The results show that PM2.5 pollution in Shandong Province peaked in 2013, followed by a rapid decline in pollution levels. Geographically, counties in the western plains of Shandong generally exhibit higher pollution levels, while most counties in the central hills of Shandong and the Jiaodong Peninsula are in low pollution areas. Strong winds positively influence air quality in the southeast of Shandong; high temperatures can ameliorate air pollution in areas outside the southeast, whereas air pressure exhibits the opposite effect. Precipitation shows a significant negative correlation in the Laizhou Bay and central Shandong regions, while relative humidity primarily exerts a negative effect in coastal areas. The impact of fractional vegetation cover is relatively mild, with positive effects observed in southern Shandong and negative effects in other regions. Population density shows a significant positive correlation in the western plains of Shandong. Economic factors exhibit predominantly positive relationships, particularly in the northwest and the Jiaodong Peninsula. Electricity consumption in southern Shandong correlates positively, while industrial factors show positive effects province-wide. PM2.5 pollution in Shandong Province demonstrates significant spatiotemporal heterogeneity, aligning with governmental expectations for the effectiveness of air pollution control measures. The conclusions of this study can be utilized to assess the efficiency of air pollution abatement at the county level and provide quantitative data support for the revision of regional emission reduction policies.
在过去二十年山东省空气污染的快速发展中，它起到了不利的作用，对区域生态安全和公众健康造成了严重的破坏。在县级尺度上，很少有研究探索 PM2.5 污染的时空成因和异质性。本研究利用地理时空加权回归模型（GTWR）对 2000 年至 2020 年山东省的气象要素和社会经济条件进行环境建模，旨在识别 136 个县 PM2.5 浓度变化的关键驱动因素。结果表明，山东省的 PM2.5 污染在 2013 年达到峰值，随后污染水平迅速下降。从地理上看，山东省西部平原的各县普遍污染水平较高，而山东省中部山区和胶东半岛的大多数县则处于低污染区。强风对山东省东南部的空气质量有积极影响；高温可以改善东南部以外地区的空气污染，而气压则产生相反的影响。降水在莱州湾和山东省中部地区呈显著负相关，而相对湿度主要在沿海地区产生负效应。植被覆盖分数的影响相对温和，在山东南部呈正效应，在其他地区呈负效应。人口密度在山东省西部平原呈显著正相关。经济因素表现出明显的正相关，特别是在西北部和胶东半岛。山东省南部的电力消耗呈正相关，而工业因素则在全省范围内呈正效应。山东省的 PM2.5 污染表现出显著的时空异质性，与政府对空气污染控制措施有效性的期望一致。本研究的结论可用于评估县级空气污染减排的效率，并为区域减排政策的修订提供定量数据支持。
