Abstract
Due to the frequent urban air pollution episodes worldwide recently, decision-makers and government agencies are struggling for sustainable strategies to optimize urban land use/cover change (LUCC) and improve the air quality. This study, thus, aims to identify the underlying relationships between PM10 concentration variations and LUCC based on the simulated PM10 surfaces in 2006 and 2013 in the Changsha-Zhuzhou-Xiangtan agglomeration (CZT), using a regression modeling approach. LUCC variables and associated landscape indexes are developed and correlated with PM10 concentration variations at grid level. Results reveal that the overall mean PM10 concentrations in the CZT declined from 106.74 μg/m3 to 94.37 μg/m3 between 2006 and 2013. Generally, variations of PM10 concentrations are positively correlated with the increasing built-up area, and negatively correlated with the increase in forests. In newly-developed built-up areas, PM10 concentrations declined with the increment of the landscape shape index and the Shannon diversity index and increased with the growing Aggregation index and Contagion index. In other areas, however, the reverse happens. These results suggest that LUCC caused by urban sprawl might be an important factor for the PM10 concentration variation in the CZT. The influence of the landscape pattern on PM10 concentration may vary in different stages of urban development.
Highlights
Urban sprawl, one of the most significant causes of the increasingly severe air pollution in the world [1,2,3], has made recent headlines in peer-reviewed journals of economics, urban planning, and public health [4,5,6,7]
These results suggest that land use/cover changes (LUCC) caused by urban sprawl might be an important factor for the PM10 concentration variation in the Changsha-Zhuzhou-Xiangtan agglomeration (CZT)
Based on the data of consumption proportions of raw coal, petroleum, natural gas, clean energy and other sources in 2006 (68.51%, 12.87%, 0.66%, 14.87%, 3.09%, respectively) and 2013 (62.23%, 11.66%, 1.55%, 14.04%, 10.52%, respectively) of the CZT are [43] and given the efficient and conservative use of energy has been promoted by the ‘Two Oriented Society’ policy, we assume the change of energy production and consumption structure in the study region has been stable
Summary
One of the most significant causes of the increasingly severe air pollution in the world [1,2,3], has made recent headlines in peer-reviewed journals of economics, urban planning, and public health [4,5,6,7]. Using urban landscape metrics framework, McCarty and Kaza found the mix of different land cover types identifies important correlations between pollutant levels and air quality [19] Their effectiveness is limited since the formation mechanisms of air pollution are generally overlooked in these studies. The LUR uses monitored pollutant concentrations as the dependent variable, and takes surrounding land use, transportation and other variables obtained through GIS as predictors [24,25] It offers a rough, yet helpful, perspective on the analysis of the relationship between the urban LUCC and air pollution variation and attaches certain positive significance to the rational evaluation of city planning and land use strategies. TThheeCChhaannggsshhaa--ZZhhuuzzhhoouu--XXiiaannggttaann aagggglloommeerraattiioonn ((CCZZTT))iiss llooccaatteeddiinntthheennoorrtthheeaassttooffHHuunnaann pprorovvinincceeininCChhininaa,,ccoommpprriissiinngg tthhee cciittiieess ooff CChhaannggsshhaa,, ZZhhuuzzhhoouu aanndd XXiiaannggttaann((FFiigguurree11))..TThheeCCZZTT ccoovveerrssaannaarreeaaooff2288,0,08877kkmm22,, aanndd hhaass aa ppooppuullaattiioonn ooff 1133..7788 mmiilllliioonn. Sustainability 2016, 8, 677 into 1 km 1 km resolution to compare with the spatial patterns of PM10 concentrations simulated by the LUR model
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