Spatial Relationships between Urban Structures and Air Pollution in Korea

Meen Jung,Jaewoo Park,Sunghwan Kim

doi:10.3390/su11020476

Meen Jung, Jaewoo Park + Show 1 more

Open Access

https://doi.org/10.3390/su11020476

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Abstract

Urban structures facilitate human activities and interactions but are also a main source of air pollutants; hence, investigating the relationship between urban structures and air pollution is crucial. The lack of an acceptable general model poses significant challenges to investigations on the underlying mechanisms, and this gap fuels our motivation to analyze the relationships between urban structures and the emissions of four air pollutants, including nitrogen oxides, sulfur oxides, and two types of particulate matter, in Korea. We first conduct exploratory data analysis to detect the global and local spatial dependencies of air pollutants and apply Bayesian spatial regression models to examine the spatial relationship between each air pollutant and urban structure covariates. In particular, we use population, commercial area, industrial area, park area, road length, total land surface, and gross regional domestic product per person as spatial covariates of interest. Except for park area and road length, most covariates have significant positive relationships with air pollutants ranging from 0 to 1, which indicates that urbanization does not result in a one-to-one negative influence on air pollution. Findings suggest that the government should consider the degree of urban structures and air pollutants by region to achieve sustainable development.

Highlights

Urban structures have become increasingly complicated due to economic factors, such as agglomeration economies and externalities [1,2,3,4]
We focus on emissions of nitrogen oxides (NOX), sulfur oxides (SOX), and two types of particulate matter (PM10 and PM2.5), all of which are meaningful criteria for air pollution
Spatial models for underlying mechanisms are critical for estimating emissions of air pollutants from urban structures and for accounting for regional characteristics

Summary

Introduction

Urban structures have become increasingly complicated due to economic factors, such as agglomeration economies and externalities [1,2,3,4]. Direct application of the sprawl-and-compact development approach to Korean cities is challenging because previous theories are based on North American cities These gaps between the existing hypotheses and empirical analyses fuel our motivation to investigate the administrative area in Korea by using multiple urban land-use covariates and air pollutant variables simultaneously. On the basis of these results, we fit the spatial regression models to investigate the relationship between the structural components of cities and air pollutant emissions In this analysis, four air pollutants and several urban structure variables are used as response variables and covariates, respectively. To the best of our knowledge, no existing approach provides a general spatial model framework for quantifying the relationships between different types of air pollutants and urban structure covariates in Korea.

Study Area

Exploratory Spatial Data Analysis

Spatial Linear Regression Model

Results

Discussion and Conclusions