Ma, J, Liu, B, Mitchell, G orcid.org/0000-0003-0093-4519 et al. (1 more author) (2019) A spatial analysis of air pollution and environmental inequality in Beijing, 2000–2010. Journal of Environmental Planning and Management, 62 (14). pp. 2437-2458. ISSN 0964-0568
Abstract
Whilst air pollution is a major problem in China, little is known about how it is distributed socially and how such distributions are changing over time. We use a fine-grained population census and air quality data for 2000 and 2010 to explore socio-spatial and temporal inequalities in air pollution for Beijing, using distributional analyses and spatial regression models. We find that environmental inequalities exist with respect to measures of social disadvantage, such as hukou migrant status, very young children (0–4 years), and the elderly (≥65 years). Our temporal analysis reveals that environmental inequality increases for migrants and the elderly, who bear a disproportionate and increasing share of declining air quality from 2000 to 2010. Regression results emphasise the spatial and temporal variations in environmental inequality, as the associations between air pollution and social demographics differ between different urban zones of Beijing; and their geographic patterns change significantly over time.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Newcastle University. This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Environmental Planning and Management on 01 Feb 2019, available online: http://www.tandfonline.com/10.1080/09640568.2018.1560003. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | air pollution; environmental justice; spatial regression model; China |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Dec 2018 10:43 |
Last Modified: | 01 Feb 2020 01:38 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/09640568.2018.1560003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:140030 |