Geospatial Analytics for Healthy Cities: Exploring Air Pollution and Socio-Spatial Inequality in Urban Environments

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality and Health".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 831

Special Issue Editors

School of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), Shenzhen, China
Interests: GIS; environmental health; spatial accessibility; healthy cities; socio-spatial inequality
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Guest Editor
Department of Geography, Sustainability, Community, and Urban Studies, University of Connecticut, Storrs, CT 06269, USA
Interests: GIS; public health; crime prevention; spatial analysis; human-environment dynamics
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Guest Editor
Department of Geography, Sustainability, Community, and Urban Studies, University of Connecticut, Storrs, CT 06269, USA
Interests: environmental health; health disparities; exposure to air pollution; GIS; geospatial data analytics

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Guest Editor
Yale School of the Environment, Yale University, New Haven, CT 06511, USA
Interests: GIS; environmental health; spatial accessibility; healthy cities; socio-spatial inequality GIScience; Environmental Health; GeoAI
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Guest Editor
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: coupling mechanisms between urbanization and the ecological environment; urban system evolution and assessment; intelligent technologies and urban sustainable development; urban climate resilience; urban and regional planning and governance
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Special Issue Information

Dear Colleagues,

Rapid urbanization amplifies disparities in environmental health burdens. Air pollution acts both as a primary driver of disease and a marker of socio-spatial inequality. Achieving the global vision of healthy cities requires actionable insights into how pollution interacts with urban infrastructure, mobility patterns, and social vulnerability. Geospatial analytics – including Geographic Information System (GIS), remote sensing, Geospatial Artificial Intelligence (GeoAI), and spatial statistics – provide essential tools to quantify these complex dynamics. How to effectively integrate these tools to better address these challenges remains an area that requires further research and innovation.

We invite innovative research that leverages geospatial analytics to investigate the interplay between air pollution exposure, urban health outcomes, and socio-spatial inequality. Contributions should bridge theoretical frameworks with applied solutions, advancing healthier and more equitable cities.

Example topics include, but are not limited to:

  • GeoAI for exploring air pollution mapping and disparities;
  • Mobility-based exposure modeling and dynamic air pollution risk assessment;
  • Spatial epidemiology of pollution-linked diseases in vulnerable populations;
  • Green infrastructure planning for equitable air quality improvement;
  • Urban mobility transitions and health co-benefits;
  • Policy simulations for reducing air pollution injustice;
  • Coupled dynamics of urbanization, air quality, and public health;
  • Low-cost sensor networks for community-driven air quality monitoring;
  • Climate resilience strategies targeting pollution-health inequities;
  • Remote sensing of urban heat islands and pollution synergies;
  • Spatial optimization of healthcare accessibility in polluted areas.

This Special Issue aims to bridge disciplinary silos between atmospheric science, urban planning, and public health by synthesizing cutting-edge geospatial approaches. Positioning socio-spatial inequality as a core determinant of urban environments and health, the issue seeks to advance methodologies for quantifying place-based disparities, identify scalable solutions that prioritize marginalized communities, and equip policymakers with actionable spatial evidence for equitable climate action. Submissions should emphasize real-world applicability to support cities in meeting the WHO air quality guidelines and the UN Sustainable Development Goals (SDG 3: Good Health and Well-being, SDG 11: Sustainable Cities and Communities, SDG 13: Climate Action).

Dr. Dong Liu
Dr. Hanlin Zhou
Dr. Yoo Min Park
Dr. Yimeng Song
Dr. Haimeng Liu
Guest Editors

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Keywords

  • air pollution exposure
  • geospatial analytics
  • urban health inequalities
  • environmental justice
  • spatial epidemiology
  • sustainable urban planning

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Published Papers (1 paper)

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Research

20 pages, 7905 KB  
Article
The Differential Impact of PM2.5 on the Health of Vulnerable Groups in the Context of Rapid Urbanization: An Empirical Analysis Based on Jiangsu Province (2010–2020)
by Hui Wang, Ziyu Zhang, Zhouzhou Qiu, Shuyuan Ma, Wei Zhou, Zhitao Tong, Chun Yin and Dong Liu
Atmosphere 2026, 17(5), 469; https://doi.org/10.3390/atmos17050469 - 30 Apr 2026
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Abstract
The impact of PM2.5 pollution on the health inequality of vulnerable groups is a core issue in environmental justice research. However, existing studies in China mostly focus on severely polluted areas in northern China. They lack comparative cases in economically developed eastern [...] Read more.
The impact of PM2.5 pollution on the health inequality of vulnerable groups is a core issue in environmental justice research. However, existing studies in China mostly focus on severely polluted areas in northern China. They lack comparative cases in economically developed eastern regions. They also rarely consider changes in the impact of air pollution on residents’ health amid rapid urbanization. Based on multi-source data, this study employed spatial visualization, spatial autocorrelation analysis and spatial regression models. It investigated the impact of PM2.5 pollution on the health inequality of vulnerable elderly groups in 92 districts and counties of Jiangsu Province from 2010 to 2020. The results show that: first, the regional pattern of health inequality between PM2.5 pollution and vulnerable elderly groups in Jiangsu has continuously evolved, with a “lower in the south and higher in the north” pollution pattern and high overlap between high-pollution areas and high elderly health risk areas in northern Jiangsu. Second, the spatial coupling between PM2.5 and elderly health risks has gradually strengthened, showing significant positive spatial agglomeration in 2020, confirming obvious spatial agglomeration characteristics of air pollution’s health impact. Third, the adverse health impact of PM2.5 on vulnerable elderly groups became significant in 2020, exhibiting cumulative and lagged characteristics; urbanization and regional coordinated development have played a positive role in alleviating regional health inequality, while a lagging energy structure further exacerbates the health vulnerability of the elderly. This study fills the gap of insufficient research on economically developed eastern regions and provides targeted empirical references for urban refined governance and precise prevention and control of environmental health inequality. Full article
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