GIS-Based Spatial Analysis and Strategic Placement of Fine Dust Alert Systems for Vulnerable Populations in Gangseo District

Air pollution, particularly fine particulate matter (PM), poses significant health risks to vulnerable populations such as children, older adults, and individuals with chronic illnesses. Understanding the spatial distribution of these populations and their access to air quality information is crucial for effective interventions. In urban areas like Gangseo District, the distribution of essential facilities and accessibility varies greatly. While studies have highlighted the health impacts of PM, research on optimizing air quality monitoring for at-risk groups remains limited. This study aims to identify optimal locations for air quality monitoring by analyzing the spatial distribution of vulnerable populations and facility accessibility. Using Geographic Information Systems (GIS) and isochrone maps, we identified areas with high concentrations of vulnerable groups and poor access to healthcare facilities. Our findings revealed significant disparities in access to air quality information, with some high-risk areas underserved by current monitoring systems. This study integrated demographic data and spatial analysis to propose strategic monitoring placements. The methodology can be applied to other urban settings and offers a framework for improving air quality management. This study underscores the importance of targeted air quality monitoring to protect vulnerable populations and suggests practical steps for policymakers to enhance public health.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2024-11-18
DOI
https://doi.org/10.3390/app142210610
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GIS-Based Spatial Analysis and Strategic Placement of Fine Dust Alert Systems for Vulnerable Populations in Gangseo District

Jae‐Kil Jang, Jaewook Lee, Junhyuck Im
Applied Sciences
Air Quality Monitoring and Forecasting
article

GIS-Based Spatial Analysis and Strategic Placement of Fine Dust Alert Systems for Vulnerable Populations in Gangseo District

Jae‐Kil Jang, Jaewook Lee, Junhyuck Im
article en

Abstract

Air pollution, particularly fine particulate matter (PM), poses significant health risks to vulnerable populations such as children, older adults, and individuals with chronic illnesses. Understanding the spatial distribution of these populations and their access to air quality information is crucial for effective interventions. In urban areas like Gangseo District, the distribution of essential facilities and accessibility varies greatly. While studies have highlighted the health impacts of PM, research on optimizing air quality monitoring for at-risk groups remains limited. This study aims to identify optimal locations for air quality monitoring by analyzing the spatial distribution of vulnerable populations and facility accessibility. Using Geographic Information Systems (GIS) and isochrone maps, we identified areas with high concentrations of vulnerable groups and poor access to healthcare facilities. Our findings revealed significant disparities in access to air quality information, with some high-risk areas underserved by current monitoring systems. This study integrated demographic data and spatial analysis to propose strategic monitoring placements. The methodology can be applied to other urban settings and offers a framework for improving air quality management. This study underscores the importance of targeted air quality monitoring to protect vulnerable populations and suggests practical steps for policymakers to enhance public health.

Applied SciencesVol. 14(22)
Gachon University (KR)
Gachon University
Openalex Percentile: Top 82%
Air Quality Monitoring and Forecasting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.