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Allocating and mapping carbon footprint at the township scale by correlating industry sectors to land uses

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成果类型:
期刊论文
作者:
Liu, Chengliang*;Wang, Tao;Lin, Xiao;Zhao, Rui
通讯作者:
Liu, Chengliang
作者机构:
[Wang, Tao] Cent China Normal Univ, Hubei Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.
[Liu, Chengliang] East China Normal Univ, Sch Urban & Reg Sci, Shanghai 200062, Peoples R China.
[Liu, Chengliang] Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA.
[Zhao, Rui] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Peoples R China.
[Lin, Xiao] East China Normal Univ, Shanghai, Peoples R China.
通讯机构:
[Liu, Chengliang] East China Normal Univ, Sch Urban & Reg Sci, Shanghai 200062, Peoples R China.
Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA.
语种:
英文
关键词:
carbon footprint;spatiotemporal variations;regional allocation;township scale;cointegration test
期刊:
Geographical Review
ISSN:
1931-0846
年:
2016
卷:
106
期:
3
页码:
441-464
文献类别:
WOS:Article
所属学科:
ESI学科类别:社会科学,概论;WOS学科类别:Geography
入藏号:
基金类别:
National Natural Science Foundation of China [41571123, 41201130, 41571520, 41301639]; Social Science Planning Project of Shanghai [2015BCK001]
机构署名:
本校为其他机构
院系归属:
城市与环境科学学院
摘要:
A key part of reducing CO2 emissions is exploring scientific methods for calculating carbon footprints and allocating their sources. Several limitations in current approaches exist at smaller scales due to shortcomings and uncertainty in data collection. This article implements an improved approach to allocate carbon footprints at the local, neighborhood scale, taking land uses as a criteria, after verifying the correlation between industry sectors and land uses through cointegration test. A case study of the Wuhan Metropolitan Area (WhMA) is provided to examine the method's applicability and effectiveness. Some related spatiotemporal variations in carbon‐footprint values at the township scale are depicted as a spatial tendency from zonal agglomeration to radial diffusion in a core‐periphery structure, which relates to such human‐driven factors as population, transportation, and urban (built‐up) area. The findings provide insight for policymakers to generate appropriate allocative strategies for low‐carbon development.
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