[County scale characteristics of CO2 emission's spatial-temporal evolution in the Beijing-Tianjin-Hebei Metropolitan Region].
CO2 emission spatial distribution is characterized by stages. The study on regional distribution characteristics and evolution can supply important evidence for CO2 emission reduction. Based on CO2 emission data of 128 county areas in the Beijing-Tianjin-Hebei Metropolitan Region (BTHMR) from 1990 to 2009, the spatial pattern and spatial dependence of CO2 emission were discussed by using cartogram and spatial autocorrelation analysis methods. The results show that the total emission of CO2 increased year by year. Average annual growth of CO2 emission after 2002 was 3.7 times higher than before. Different cities have different emission growth trends which can be categorized into three types. The spatial pattern of CO2 emission appeared to be the layered cluster. The Global Moran'I decreased from 1.44 in 1990 to 0.09 in 1998 and then increased slowly to 0.10 in 2009. The spatial distribution of high CO2 emission area changed from 'Double Centers' into 'Four Centers' and the spatial distribution of low CO2 emission area changed less. There were four different change types of local spatial autocorrelation: remaining unchanged or weakening in most regions, enhancing in some regions of Tangshan, transforming in some regions of Tianjin and Xuanhua county. Since the spatial pattern and autocorrelation in low/high CO2 emission area bear different evolution process, the local conditions and interactions with perimeter zones should be considered when formulating emission reduction plan. The discussion of spatial pattern and autocorrelation is very important for understanding spatial evolution pattern of CO2 emission and developing strategic emission reduction planning, and also provides a base for the study on low carbon development in metropolitan area.
Hao
H
Wang
Cao-Cao
CC
Chen
Tao
T
Pan
Chun-Lan
CL
Liu
Long
L
Chen
Li
L
Sun
D000393:Air Pollutants / Q000032:analysis*; D002245:Carbon Dioxide / Q000032:analysis*; D002681:China; D002947:Cities; D004784:Environmental Monitoring; D062211:Spatio-Temporal Analysis
D000393:Air Pollutants; D002245:Carbon Dioxide