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Detecting urban land-use configuration effects on NO2 and NO variations using geographically weighted land use regression.
- Source :
-
Atmospheric Environment . Jan2019, Vol. 197, p166-176. 11p. - Publication Year :
- 2019
-
Abstract
- Abstract Land use regression (LUR) has been used to predict NO 2 and NO distribution. However, previous studies overlooked the possibility that the effect of land-use configuration on NO 2 and NO may not always be constant across the study domain. The objective of this study was to depict the spatially varying effect so as to better predict NO 2 and NO. First, a LUR model was adopted to screen the land-use factors for NO 2 and NO predictions. Then, a geographically weighted regression (GWR) model was developed to delineate the spatial non-stationarity in the relationship. The results show that the GWR model improved NO 2 and NO prediction accuracy, with increases of 29.3% and 6.9%, respectively. The road ERSD (i.e., shortest distance to express road) factor had a negative effect on NO 2. The impervious AWMSI (i.e., area-weighted mean shape index) factor had a larger effect on NO in the northwest of Foshan, due to more uneven and dense distribution of impervious patches. NO had a steeper distribution gradient than NO 2 , which implies that NO is more localized. The relationships between land-use configuration, NO 2 and NO concentrations are not constant in space. This means that the predictive abilities of land-use factors for NO 2 and NO are different across Foshan. Overall, our approach can obtain a higher estimation accuracy than the LUR at city scale. It could also be applied easily for other air pollutants and in cities worldwide. Highlights • Landscape metrics depict the spatial disparity of urban land-use configuration. • Discrepant influences of land-use configuration on NO 2 and NO were revealed. • GWR increased NO 2 and NO prediction accuracy by 29.3% and 6.9%, respectively. • NO had a steeper spatial distribution gradient than NO 2. • The findings benefit optimal regulation of the urban land-use configuration. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13522310
- Volume :
- 197
- Database :
- Academic Search Index
- Journal :
- Atmospheric Environment
- Publication Type :
- Academic Journal
- Accession number :
- 133011945
- Full Text :
- https://doi.org/10.1016/j.atmosenv.2018.10.031