为识别和量化导致用水量变化的主要影响因素及其驱动作用,准确把握用水变化趋势,将全国总用水量分为生活、工业和农业用水量,通过构建多层次对数均值迪氏指数(logarithmic mean Divisia index,LMDI)分解模型,在生活、工业及农业用水量...为识别和量化导致用水量变化的主要影响因素及其驱动作用,准确把握用水变化趋势,将全国总用水量分为生活、工业和农业用水量,通过构建多层次对数均值迪氏指数(logarithmic mean Divisia index,LMDI)分解模型,在生活、工业及农业用水量变化的驱动因素分解的基础上,对全国总用水量驱动效应进行测度,并进一步量化研究用水驱动效应在时间和空间尺度上的分异特征。结果表明:2020年用水总量几乎与20年前持平,但各驱动要素的相对作用发生了显著变化,与此同时,用水量变化驱动效应存在较强的空间分异性,并且在“十三五”时期表现出了新的变化态势。结果可为我国水资源的高效利用和水资源管理政策的科学制定提供技术支撑与决策依据。展开更多
Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilizatio...Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilization to achieve the sustainable economic development. In this study, the logarithmic mean Divisia index(LMDI) decomposition method was used to explore the influence factors of CO2 emissions in Central Asia(including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan) during the period 1992–2014. Moreover, decoupling elasticity and decoupling index based on the LMDI decomposition results were employed to explore the relationship between economic growth and CO2 emissions during the study period. Our results show that the total CO2 emissions decreased during the period 1992–1998, influenced by the collapse of the Soviet Union in 1991 and the subsequent financial crisis. After 1998, the total CO2 emissions started to increase slowly along with the economic growth after the market economic reform. Energy-related CO2 emissions increased in Central Asia, mainly driven by economic activity effect and population effect, while energy intensity effect and energy carbon structure effect were the primary factors inhibiting CO2 emissions. The contribution percentages of these four factors(economic activity effect, population effect, energy intensity effect and energy carbon structure effect) to the total CO2 emissions were 11.80%, 39.08%, –44.82% and –4.32%, respectively, during the study period. Kazakhstan, Uzbekistan and Turkmenistan released great quantities of CO2 with the annual average emissions of 189.69×106, 45.55×106 and 115.38×106 t, respectively. In fact, their economic developments depended on high-carbon energies. The decoupling indices clarified the relationship between CO2 emissions and economic growth, highlighting the occurrence of a ’’weak decoupling’’ between these two variables in Central Asia. In conclusion, our results indicate that CO2 emissions are still not com展开更多
文摘为识别和量化导致用水量变化的主要影响因素及其驱动作用,准确把握用水变化趋势,将全国总用水量分为生活、工业和农业用水量,通过构建多层次对数均值迪氏指数(logarithmic mean Divisia index,LMDI)分解模型,在生活、工业及农业用水量变化的驱动因素分解的基础上,对全国总用水量驱动效应进行测度,并进一步量化研究用水驱动效应在时间和空间尺度上的分异特征。结果表明:2020年用水总量几乎与20年前持平,但各驱动要素的相对作用发生了显著变化,与此同时,用水量变化驱动效应存在较强的空间分异性,并且在“十三五”时期表现出了新的变化态势。结果可为我国水资源的高效利用和水资源管理政策的科学制定提供技术支撑与决策依据。
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19030204)the West Light Foundation of the Chinese Academy of Sciences (2015-XBQN-17)
文摘Low-carbon economic development is a strategy that is emerging in response to global climate change. Being the third-largest energy base in the world, Central Asia should adopt rational and efficient energy utilization to achieve the sustainable economic development. In this study, the logarithmic mean Divisia index(LMDI) decomposition method was used to explore the influence factors of CO2 emissions in Central Asia(including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan and Turkmenistan) during the period 1992–2014. Moreover, decoupling elasticity and decoupling index based on the LMDI decomposition results were employed to explore the relationship between economic growth and CO2 emissions during the study period. Our results show that the total CO2 emissions decreased during the period 1992–1998, influenced by the collapse of the Soviet Union in 1991 and the subsequent financial crisis. After 1998, the total CO2 emissions started to increase slowly along with the economic growth after the market economic reform. Energy-related CO2 emissions increased in Central Asia, mainly driven by economic activity effect and population effect, while energy intensity effect and energy carbon structure effect were the primary factors inhibiting CO2 emissions. The contribution percentages of these four factors(economic activity effect, population effect, energy intensity effect and energy carbon structure effect) to the total CO2 emissions were 11.80%, 39.08%, –44.82% and –4.32%, respectively, during the study period. Kazakhstan, Uzbekistan and Turkmenistan released great quantities of CO2 with the annual average emissions of 189.69×106, 45.55×106 and 115.38×106 t, respectively. In fact, their economic developments depended on high-carbon energies. The decoupling indices clarified the relationship between CO2 emissions and economic growth, highlighting the occurrence of a ’’weak decoupling’’ between these two variables in Central Asia. In conclusion, our results indicate that CO2 emissions are still not com
