Droughts are major, large-scale, weather-driven natural disasters, on the rise in the changing climate. We project changing population exposure to drought in two vulnerable, adjacent, basins of large rivers, the Tarim River Basin (TRB) and the Indus River Basin (IRB), for the future horizon 2021-2065. Drought events are assessed based on the outputs of multiple Global Climate Models, by applying the Standardized Precipitation Evapotranspiration Index (SPEI) and the Intensity-Area-Duration method (IAD). Future population exposure to droughts is evaluated by combining the drought events under three RCP scenarios (RCP2.6, RCP4.5, and RCP8.5) with the projected population from Shared Socioeconomic Pathways (SSPs), acknowledging the recent two-child policy in China. Results show that frequency of drought events in both river basins could increase in the future, while increase in the TRB is stronger than in the IRB. The areal coverage of drought events in both river basins is projected to be greater in 2021-2065 than in 1961-2005. Increase of frequency and areal coverage in both basins is especially strong for the class of extreme drought events. According to the ensemble mean of multi-GCMs, population exposure to droughts was 25.0% and 20.9% of the total population in the TRB and the IRB, respectively, in 1961-2005, and it is projected to increase by over 60% for the TRB and to increase by over 30% for the IRB, in 2021-2065.Plain Language Summary As a major, large-scale, weather-driven natural disaster, drought may occur in all climatic zones and cause significant losses in human and natural systems. Both the Tarim River Basin and the Indus River Basin are vulnerable to drought, but changing characteristics of population exposure to drought is unknown for the two basins under the climate and population dynamics scenarios. We analyze the changing frequency and areal coverage of drought events in 2021-2065 relative to 1961-2005 and then quantify the population exposure to drought in both two river basins. It was found that frequency and areal coverage of drought in both river basins could increase in the future. Increase of frequency and areal coverage in both basins is especially strong for extreme drought events. Population exposure to droughts was 25.0% and 20.9% of the total population in the Tarim and the Indus River Basin, respectively, in 1961-2005, and it is projected to increase by over 60% for the Tarim River Basin and by over 30% for the Indus River Basin in 2021-2065.

Analyzing the driving factors of regional carbon emissions is important for achieving emissions reduction. Based on the Kaya identity and Logarithmic Mean Divisia Index method, we analyzed the effect of population, economic development, energy intensity, renewable energy penetration, and coefficient on carbon emissions during 1990–2016. Afterwards, we analyzed the contribution rate of sectors’ energy intensity effect and sectors’ economic structure effect to the entire energy intensity. The results showed that the influencing factors have different effects on carbon emissions under different stages. During 1990–2000, economic development and population were the main factors contributing to the increase in carbon emissions, and energy intensity was an important factor to curb the carbon emissions increase. The energy intensity of industry and the economic structure of agriculture were the main factors to promote the decline of entire energy intensity. During 2001–2010, economic growth and emission coefficient were the main drivers to escalate the carbon emissions, and energy intensity was the key factor to offset the carbon emissions growth. The economic structure of transportation, and the energy intensity of industry and service were the main factors contributing to the decline of the entire energy intensity. During 2011–2016, economic growth and energy intensity were the main drivers of enhancing carbon emissions, while the coefficient was the key factor in curbing the growth of carbon emissions. The industry’s economic structure and transportation’s energy intensity were the main factors to promote the decline of the entire energy intensity. Finally, the suggestions of emissions reductions are put forward from the aspects of improving energy efficiency, optimizing energy structure and adjusting industrial structure etc.

Aridity index reflects the exchanges of energy and water between the land surface and the atmosphere, and its variation can be used to forecast drought and flood patterns, which makes it of great significance for agricultural production. The ratio of potential evapotranspiration and precipitation is applied to analyse the spatial and temporal distributions of the aridity index in the Belt and Road region under the 1.5℃ and 2.0℃ global warming scenarios on the basis of outputs from four downscaled global climate models. The results show that: (1) Under the 1.5℃ warming scenario, the area-averaged aridity index will be similar to that in 1986-2005 (around 1.58), but the changes vary spatially. The aridity index will increase by more than 5% in Central-Eastern Europe, north of West Asia, the monsoon region of East Asia and northwest of Southeast Asia, while it is projected to decrease obviously in the southeast of West Asia. Regarding the seasonal scale, spring and winter will be more arid in South Asia, and the monsoon region of East Asia will be slightly drier in summer compared with the reference period. While, West Asia will be wetter in all seasons, except winter. (2) Relative to 1986-2005, both areal averaged annual potential evapotranspiration and precipitation are projected to increase, and the spatial variation of aridity index will become more obvious as well at the 2.0℃ warming level. Although the aridity index over the entire region will be maintained at approximately 1.57 as that in 1.5℃, the index in Central-Eastern Europe, north of West Asia and Central Asia will grow rapidly at a rate of more 38 Journal of Geographical Sciences than 20%, while that in West Siberia, northwest of China, the southern part of South Asia and West Asia will show a declining trend. At the seasonal scale, the increase of the aridity index in Central-Eastern Europe, Central Asia, West Asia, South Asia and the northern part of Siberia in winter will be obvious, and the monsoon region in East Asia will be drier in both summer and autumn. (3) Under the scenario of an additional 0.5℃ increase in global temperature from 1.5℃ to 2.0℃, the aridity index will increase significantly in Central Asia and north of West Asia but decrease in Southeast Asia and Central Siberia. Seasonally, the aridity index in the Belt and Road region will slightly increase in all other seasons except spring. Central Asia will become drier annually at a rate of more than 20%. The aridity index in South Asia will increase in spring and winter, and that in East Asia will increase in autumn and winter. (4) To changes of the aridity index, the attribution of precipitation and potential evapotranspiration will vary regionally. Precipitation will be the major influencing factor over southern

No abstract

The realization of carbon emissions peak is important in the energy base area of China for the sustainable development of the socio-economic sector. The STIRPAT model was employed to analyze the elasticity of influencing factors of carbon emissions during 1990-2010 in the Xinjiang autonomous region, China. The results display that population growth is the key driving factor for carbon emissions, while energy intensity is the key restraining factor. With 1% change in population, gross domestic product (GDP) per capita, energy intensity, energy structure, urbanization level, and industrial structure, the change in carbon emissions was 0.80%, 0.48%, 0.20%, 0.07%, 0.58%, and 0.47%, respectively. Based on the results from regression analysis, scenario analysis was employed in this study, and it was found that Xinjiang would be difficult to realize carbon emissions peak early around 2030. Under the condition of the medium-high change rates in energy intensity, energy structure, industrial structure, and with the low-medium change rates in population, GDP per capita, and urbanization level, Xinjiang will achieve carbon emissions peak at of 626.21, 636.24, 459.53, and 662.25 million tons in the year of 2030626.21, 636.24, 459.53, and 662.25 million tons in the year of , 2030626.21, 636.24, 459.53, and 662.25 million tons in the year of , 2040626.21, 636.24, 459.53, and 662.25 million tons in the year of , and 2040 the background of Chinese carbon emissions peak around 2030, this paper puts forward relevant policies and suggestions to the sustainable socio-economic development for the energy base area, Xinjiang autonomous region.Sustainability 2019, 11, 4220 2 of 18 in order to mitigate the risks of global warming, the international community has made great efforts to reduce carbon emissions [4]. As an emerging market, though simultaneous development and accelerating industrialization, informatization, agricultural modernization, and urbanization, due to its long-term growth mode of high consumption, high pollution and low output, China has become the country with the largest carbon emissions [5]. In 2006, Chinese carbon emissions surpassed the United States of America (USA) and became the world's largest emitter [4]. In 2015, China accounted for 28.65% of the world's total carbon emissions, exceeding the sum of the USA (14.93%) and the European Union (9.68%), which was ranked second and third in the world, respectively (Global Carbon Project. http://www.globalcarbonatlas.org/en/ CO 2 emissions). With this, China has incurred huge attention from the world, which posed great international political pressures on China. In face of this situation, China pledged at the Copenhagen Climate Summit to increase the percentage of renewable energy in energy consumption structure to 15%, and to cut 40-45% of the energy intensity in 2020 when compared to the 2005 levels. Moreover, China promised at the Paris Agreement to increase the percentage of renewable energy in energy consumption structure to 20% and to cut 60-65% of the e...

No abstract

No abstract

China faces a difficult choice of maintaining socioeconomic development and carbon emissions mitigation. Analyzing the decoupling relationship between economic development and carbon emissions and its driving factors from a regional perspective is the key for the Chinese government to achieve the 2030 emission reduction target. This study adopted the logarithmic mean Divisia index (LMDI) method and Tapio index, decomposed the driving forces of the decoupling, and measured the sector’s decoupling states from carbon emissions in Xinjiang province, China. The results found that: (1) Xinjiang’s carbon emissions increased from 93.34 Mt in 2000 to 468.12 Mt in 2017. Energy-intensive industries were the key body of carbon emissions in Xinjiang. (2) The economic activity effect played the decisive factor to carbon emissions increase, which account for 93.58%, 81.51%, and 58.62% in Xinjiang during 2000–2005, 2005–2010, and 2010–2017, respectively. The energy intensity effect proved the dominant influence for carbon emissions mitigation, which accounted for −22.39% of carbon emissions increase during 2000–2010. (3) Weak decoupling (WD), expansive coupling (EC), expansive negative decoupling (END) and strong negative decoupling (SND) were identified in Xinjiang during 2001 to 2017. Gross domestic product (GDP) per capita elasticity has a major inhibitory effect on the carbon emissions decoupling. Energy intensity elasticity played a major driver to the decoupling in Xinjiang. Most industries have not reached the decoupling state in Xinjiang. Fuel processing, power generation, chemicals, non-ferrous, iron and steel industries mainly shown states of END and EC. On this basis, it is suggested that local governments should adjust the industrial structure, optimize energy consumption structure, and promote energy conservation and emission reduction to tap the potential of carbon emissions mitigation in key sectors.