Three-Dimensional Landscape Pattern Characteristics of Land Function Zones and Their Influence on PM2.5 Based on LUR Model in the Central Urban Area of Nanchang City, China

Int J Environ Res Public Health. 2022 Sep 16;19(18):11696. doi: 10.3390/ijerph191811696.

Abstract

China's rapid urbanization and industrialization process has triggered serious air pollution. As a main air pollutant, PM2.5 is affected not only by meteorological conditions, but also by land use in urban area. The impacts of urban landscape on PM2.5 become more complicated from a three-dimensional (3D) and land function zone point of view. Taking the urban area of Nanchang city, China, as a case and, on the basis of the identification of urban land function zones, this study firstly constructed a three-dimensional landscape index system to express the characteristics of 3D landscape pattern. Then, the land-use regression (LUR) model was applied to simulate PM2.5 distribution with high precision, and a geographically weighted regression model was established. The results are as follows: (1) the constructed 3D landscape indices could reflect the 3D characteristics of urban landscape, and the overall 3D landscape indices of different urban land function zones were significantly different; (2) the effects of 3D landscape spatial pattern on PM2.5 varied significantly with land function zone type; (3) the effects of 3D characteristics of landscapes on PM2.5 in different land function zones are expressed in different ways and exhibit a significant spatial heterogeneity. This study provides a new idea for reducing air pollution by optimizing the urban landscape pattern.

Keywords: PM2.5; land function zone; landscape pattern; three-dimensional landscape.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • China
  • Cities
  • Environmental Monitoring / methods
  • Particulate Matter / analysis
  • Urbanization

Substances

  • Air Pollutants
  • Particulate Matter

Grants and funding

The National Natural Science Foundation of China (No. 42261021, No. 41961036, and No. 41901130).