Abstract

Fine particulate matter (PM2.5) pollution has become one of the greatest urban issues in China. Studies have shown that PM2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM2.5 pollution in urban areas.

Highlights

  • In recent years, the air pollution problem generated by unprecedented urbanization and economic growth in China has become one of the greatest urban issues, fine particulate matter (PM2.5 ) pollution [1]

  • Land use factors including industrial land proportion and ecological land proportion greatly impacted the PM2.5 concentrations, since they were entered into three land use regression (LUR) models (p < 0.1)

  • We can conclude that the urban functional zones which are characterized by a dominant land use type had a great impact on PM2.5 pollution and the impact did not change as the seasons changed

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Summary

Introduction

The air pollution problem generated by unprecedented urbanization and economic growth in China has become one of the greatest urban issues, fine particulate matter (PM2.5 ) pollution [1]. Some epidemiological studies have confirmed that a long exposure to PM2.5 will greatly increase rates of cardiopulmonary morbidity and mortality [3,4]. Gaining a better and clearer understanding of PM2.5 pollution is of vital significance in preventing pollution and protecting public health. Numerous studies have been conducted on PM2.5 , mainly focused on the spatial and temporal distribution [5,6,7,8,9,10], source apportionment [11,12,13,14], health effects [15,16,17,18], and estimation [19,20,21,22]. Res. Public Health 2017, 14, 462; doi:10.3390/ijerph14050462 www.mdpi.com/journal/ijerph

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