PM<sub>2.5</sub>与土地利用类型关系的四季差异分析:以潍坊市为例

张阔; 张永彬; 李成名; 戴昭鑫

doi:10.13205/j.hjgc.202104012

PM_2.5与土地利用类型关系的四季差异分析:以潍坊市为例

doi: 10.13205/j.hjgc.202104012

张阔^1,2,
张永彬^1, ,,
李成名²,
戴昭鑫²

1. 华北理工大学矿业工程学院, 河北唐山 063210;
2. 中国测绘科学研究院, 北京 100830

基金项目:

国家重点研发计划（2018YFD1100300）；国家自然科学基金项目（41907389）；中国测绘科学研究院基本科研业务费（AR2010）。

详细信息

作者简介:
张阔(1995-),男,硕士,主要从事3S技术在资源与环境中的应用。zk934729803@163.com

通讯作者:
张永彬(1969-),男,博士,教授,主要研究方向为3S技术在资源与环境中的应用,地理国情监测。zyb063009@yeah.net

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出版历程
- 收稿日期: 2020-05-27
- 网络出版日期: 2021-07-21

SEASONAL DIFFERENCE ANALYSIS OF THE RELATIONSHIP BETWEEN PM_2.5 AND LAND USE: A CASE STUDY OF WEIFANG

1. School of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China;
2. China Academy of Surveying and Mapping, Beijing 100830, China

摘要

摘要: 土地利用类型可显著影响PM_2.5的污染浓度，研究两者间的关系，对于大气污染治理具有重要意义。目前现有研究大多基于回归模型分析土地利用类型，在年尺度上对PM_2.5的固定影响，而土地利用类型与PM_2.5之间关系复杂，且在不同季节影响力度也不尽相同。基于此，利用增强回归树定量化探讨了不同季节土地利用类型对PM_2.5浓度影响的贡献率，结果表明：土地利用类型在不同季节中对PM_2.5浓度影响存在显著差异，春、夏、秋、冬四季的主导因素分别为支路（27.37%）、次干路（19.17%）、植被覆盖面（37.23%）、建设用地（86.37%）。此外，根据不同季节各土地利用类型对PM_2.5的影响力变化曲线，提供了在优化绿化建设布局和加强交通管控力度两方面的量化指标，可为潍坊市PM_2.5污染治理提供规划参考。
- 土地利用 /
- 增强回归树模型 /
- PM_2.5 /
- 贡献率 /
- 季节
Abstract: With the acceleration of industrialization and urbanization, China's frequent occurrence of haze weather has seriously affected People's daily life and health. As an important part of haze, PM_2.5 has become a hot issue. The type of land use can significantly affect the pollution concentration of PM_2.5, and the study of the relationship between the type of land use and PM_2.5 pollution is of great significance for air pollution control. At present, most of the existing researches are based on regression model to analyze the fixed influence of land use type on PM_2.5 on an annual scale. However, the relationship between land use type and PM_2.5 is complex, and the influence intensity is not the same in different seasons. Based on this, the contribution rate of land use type to PM_2.5 concentration in different seasons was quantitatively discussed by using the method of boosted regression tree. The results showed that the land use type had significant difference in the influence of PM_2.5 concentration in different seasons, and the dominant factors in spring, summer, autumn and winter were branch road (27.37%), secondary trunk road (19.17%), vegetation coverage (37.23%) and construction land (86.37%). In addition, according to the influence curve of different land use types on PM_2.5 in different seasons, specific and quantitative planning indicators of optimizing the layout of greening construction and strengthening traffic control were provided for the control of PM_2.5 pollution in Weifang.
- land use /
- boosted regression tree model /
- PM_2.5 /
- contribution rate /
- season

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