使用景观模式数据高分辨率地平面臭氧度的变化趋势预测
Yingying Mei1, Xueqi Xiang2, Zhenwei Wang1
1School of Public Administration, Hubei University, Wuhan, China.
PloS one
|November 16, 2023
概括
在深,特别是西部地区,地面层臭氧度 (GOCs) 正在上升. 景观的多样性增加了中国政府,而主导性和传染性减少了它们,指导了污染控制战略.
科学领域:
- 环境科学 环境科学
- 大气化学 大气化学
- 空间分析 空间分析
背景情况:
- 地平面臭氧污染对环境和健康构成重大风险.
- 了解景观模式与地面层臭氧度 (GOCs) 之间的关系对于有效控制污染至关重要.
- 预测中国政府现有的方法可能缺乏空间分辨率或预测准确度.
研究的目的:
- 开发和验证一种混合模型,用于预测地面层臭氧度 (GOC) 变化趋势.
- 分析深中华人民共和国政府的时空空间模式及其与景观特征的相关性.
- 为优化景观提供见解,以减轻地面层臭氧污染.
主要方法:
- 开发了一种混合模型,结合了通用线性模型 (GLM) 和后勤回归模型 (LRM).
- 该模型使用正确预测的样本百分比 (PCP) 和接收器操作特征曲线 (AUC) 下的面积来评估.
- 每个像素增加年平均中国政府的概率在深的1公里空间分辨率下生成.
主要成果:
- 在深,中国政府的年平均度从2015年到2020年呈现上升趋势,西部度较高,东部度较低.
- 中国政府的变化趋势与景观异质性 (HET) 有显著的正相关,与主导性 (DMG) 和传染性 (CON) 有负相关.
- 在特定的地区确定了增加中国政府的高风险:广明,平山,长江,罗湖和安.
结论:
- 混合模型在预测中国政府变化趋势方面表现令人满意.
- 景观异质性是影响中国政府增加的关键因素,而景观配置起到了缓解作用.
- 这些发现为中国政府在没有监测数据的情况下进行趋势估计提供了初步指数,并为臭氧污染控制提供了景观设计指南.
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