Household CO2 emissions were increasing due to rapid economic growth and different household lifestyle. We assessed per capita household CO2 emissions（PHCEs） based on different household consuming demands（including...Household CO2 emissions were increasing due to rapid economic growth and different household lifestyle. We assessed per capita household CO2 emissions（PHCEs） based on different household consuming demands（including clothing, food, residence, transportation and service） by using provincial capital city level survey data in China. The results showed that：（1） there was a declining trend moving from eastward to westward as well as moving from northward to southward in the distribution of PHCEs.（2） PHCEs from residence demand were the largest which accounted for 44% of the total.（3） Correlation analysis and spatial analysis（Spatial Lag Model（SLM） and Spatial Error Model（SEM）） were used to evaluate the complex determinants of PHCEs. Per capita income（PI） and household size（HS） were analyzed as the key influencing factors. We concluded that PHCEs would increase by 0.2951% and decrease by 0.5114% for every 1% increase in PI and HS, respectively. According to the results, policy-makers should consider household consuming demand, income disparity and household size on the variations of PHCEs. The urgency was to improve technology and change household consuming lifestyle to reduce PHCEs.展开更多
基金National Key Research and Development Program,No.2016YFA0602803National Natural Science Foundation of China,No.41371537+1 种基金The Fundamental Research Funds for the Central Universities,No.lzujbky-2016-257The Fundamental Research Funds for the Central Universities,No.lzu-jbky-2017-it106
文摘Household CO2 emissions were increasing due to rapid economic growth and different household lifestyle. We assessed per capita household CO2 emissions（PHCEs） based on different household consuming demands（including clothing, food, residence, transportation and service） by using provincial capital city level survey data in China. The results showed that：（1） there was a declining trend moving from eastward to westward as well as moving from northward to southward in the distribution of PHCEs.（2） PHCEs from residence demand were the largest which accounted for 44% of the total.（3） Correlation analysis and spatial analysis（Spatial Lag Model（SLM） and Spatial Error Model（SEM）） were used to evaluate the complex determinants of PHCEs. Per capita income（PI） and household size（HS） were analyzed as the key influencing factors. We concluded that PHCEs would increase by 0.2951% and decrease by 0.5114% for every 1% increase in PI and HS, respectively. According to the results, policy-makers should consider household consuming demand, income disparity and household size on the variations of PHCEs. The urgency was to improve technology and change household consuming lifestyle to reduce PHCEs.
