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ORIGINAL RESEARCH
Spatial and Temporal Heterogeneity of Human-
Air-Ground Coupling Relationships at Fine Scale
1
College of Landscape Architecture, Central South University of Forestry Technology, Changsha 410004, China
2
Engineering Technology Research Centre of Big Data for Landscape Resources in Nature Protected Areas of Hunan
Province, Changsha 410004, China
3
Management Committee of Hangzhou Campus of Zhejiang Normal University, Hangzhou, 321004, China
4
General Design and Research Institute, China Construction Fifth Engineering Bureau Co
5
School of Education and Foreign Languages, Wuhan Donghu University, Wuhan 430212, China
6
College of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, China
Submission date: 2024-10-05
Final revision date: 2024-11-25
Acceptance date: 2024-12-08
Online publication date: 2025-01-21
Publication date: 2026-01-30
Corresponding author
Maomao Zhang
College of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, China
College of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, China
Pol. J. Environ. Stud. 2026;35(1):777-794
KEYWORDS
PM2.5 concentrationpopulation exposure risklandscape pattern indexspatial heterogeneityspatiotemporal evolution
TOPICS
ABSTRACT
The study of the spatial and temporal evolution of annual mean PM2.5 concentration and population
exposure risk in Hunan Province can further analyze the influence of the landscape pattern index on
the changes in annual mean PM2.5 concentration and population exposure risk. The spatial and temporal
evolution of the coupling relationship between people, air, and land at a fine scale and its spatial
heterogeneity were investigated by the population exposure risk model, the moving window method,
the spatial auto correlation model, and correlation analysis. The results show that: (1) from 2000 to
2020, the annual average PM2.5 concentration in Hunan Province showed a slow increase and then a
significant decrease, and its spatial distribution was high in the northeast and low in the southwest.
(2) From 2000 to 2016, the average proportion of the population exposed to high annual average PM2.5
concentrations (>45 μg/m3) in Hunan Province reached 74.24%, and from 2016 to 2020, the proportion
of the population exposed to low annual average PM2.5 concentrations (<35 μg/m3) increased year by
year. In 2020, there were regions with annual average concentrations of 15-25 μg/m3, and the regional
concentrations were all less than 45 μg/m3. The spatial distribution is dominated by low-risk areas, with
an overall scattered distribution, and high-risk areas are concentrated in the Chang - Zhu - Tan urban
agglomeration. (3) Cultivated land and forested land, as the main land types, have relatively obvious
characteristics of changes in dynamics and attitudes; water bodies and impervious surfaces are second;
cultivated land has a high degree of patch aggregation, high edge density and low fragmentation, which
increases the risk of annual average PM2.5 concentration and population exposure; forested land has
a high degree of patch aggregation, low edge density and low fragmentation, which is conducive to
reducing the risk of annual average PM2.5 concentration and population exposure; and water bodies and impervious surfaces have a high degree of aggregation, low edge density, and low fragmentation,
which is conducive to reducing the risk of annual average PM2.5 concentration and population exposure.
The higher the degree of aggregation, the higher the edge density, the more complex the degree of
fragmentation of water bodies and impervious surfaces, and the higher the risk of annual average PM2.5
concentration and population exposure. The results of this study can provide a theoretical basis for
mitigating air pollution, improving the human environment, optimizing the landscape pattern, and
promoting ecologically sustainable development.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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