Correlation between land-use change and greenhouse gas emissions in urban areas
Journal
International Journal of Environmental Science and Technology
Journal Volume
10
Journal Issue
6
Pages
1275-1286
Date Issued
2013
Author(s)
Abstract
Urban areas are the main sources of greenhouse gas (GHG) emissions. Previous studies have identified the effectiveness of better urban design on mitigating climate change and land-use patterns in cities as important factors in reducing GHG by local governments. However, studies documenting the link between land-use and GHG emissions are scant. Therefore, this study explores the driving forces of land-use change and GHG emission increments in urban areas and investigates their correlations. The study area, Xinzhuang, is a satellite city of Taipei that has rapidly urbanized in the past few decades. Twenty-one potential variables were selected to determine the driving forces of land-use change and GHG emission increments by binomial logistic regression based on the investigation data of national land use in 1996 and 2007. The correlation of land-use change and GHG increments was examined by Spearman rank-order analysis. Results of logistic regression analysis identified that population and its increasing density rate are main driving forces on both land-use change and GHG increments. The Spearman rank correlation matrix indicates that fluctuating urbanization level is significantly correlated with the increase of total GHG emissions, the emissions of residence, commerce, and transportation sectors in neighborhoods; and the emissions of residence and transportation sectors seem closely connected to current urbanization level. The findings suggest that relationships among land-use, urbanization, and GHG emissions in urban areas vary greatly according to residence and transportation characteristics. Land-based mitigation may provide the most viable mechanism for reducing GHG emissions through residence and transportation sectors. © 2013 Islamic Azad University (IAU).
Subjects
Binominal logistic regression; Driving force analysis; Greenhouse gas inventory; Land-use classification; Spearman rank-order correlation
Other Subjects
Climate change; Gas emissions; Land use; Logistic regression; Motor transportation; Urban transportation; Binomial logistic regressions; Driving force analysis; Greenhouse gas inventory; Landuse classifications; Spearman rank; Spearman rank correlation; Transportation sector; Urbanization levels; Greenhouse gases; correlation; emission inventory; greenhouse gas; land use change; neighborhood; satellite data; state role; urban area; China; Henan; Taipei; Taiwan; Xinzhuang
Publisher
Center for Environmental and Energy Research and Studies
Type
journal article