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Climate change significantly affects the environmental and socioeconomic conditions in northwest China. Here we evaluate the ability of five general circulation models (GCMs) from 6th phase of the Coupled Model Inter-comparison Project (CMIP6) to reproduce regional temperature and precipitation over northwest China from 1961 to 2014, and project the future temperature and precipitation during 2021 to 2100 under SSPs-RCPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5). The results show that the CMIP6 models can simulate temperature better than precipitation. Projections show that the annual mean temperature will further increase under different SSPs-RCPs scenarios in the 21st century. Future climate changes in the near-term (2021–2040), mid-term (2041–2060) and long-term (2081–2100) are analyzed relative to the reference period (1995–2014). In the long term, warming will be significantly higher than the near and mid-terms. In the long term, annual mean temperature will increase by 1.4°C, 1.9°C, 3.3°C, 5.5°C, 2.7°C, 3.8°C and 6.0°C under SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5, respectively. Spatially, warming in the Junggar Basin will be higher than those in the Tarim Basin. Seasonally, the maximum warming zone will be in the mountainous areas of Tarim Basin during spring and autumn, in the southern basin during winter, and in the east during summer. Precipitation shows an increasing trend under different SSPs-RCPs in the 21st century. In the long term, increase in precipitation will be significantly higher than in the near and mid-terms. Increase in annual precipitation in the long term will be 4.1% under SSP1-1.9, 13.9% under SSP1-2.6, 28.4% under SSP2-4.5, 35.2% under SSP3-7.0, 6.9% under SSP4-3.4, 8.9% under SSP4-6.0, and 27.3% under SSP5-8.5 relative to the reference period of 1995–2014. Spatially, precipitation increase will be higher in the south than the north, especially higher in mountainous regions than the basin under SSP2-4.5, SSP3-7.0, and SSP5-8.5. Seasonally, highest increase can be expected for winter, followed by spring, with significant increase in mountainous regions of southern Tarim Basin. Summer precipitation will reduce in Tian Shan and basins but will significantly increase in the northern margin of the Kunlun Mountain.

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°C and 2.0°C global warming scenarios on the basis of outputs from four downscaled global climate models. The results show that: (1) Under the 1.5°C 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°C warming level. Although the aridity index over the entire region will be maintained at approximately 1.57 as that in 1.5°C, the index in Central- Eastern Europe, north of West Asia and Central Asia will grow rapidly at a rate of more 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°C increase in global temperature from 1.5°C to 2.0°C, 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 West Asia, southern South Asia, Central-Eastern Siberia, the non-monsoon region of East Asia and the border between West Asia and Central Asia, while potential evapotranspiration will exert greater effects over Central-Eastern Europe, West Siberia, Central Asia and the monsoon region of East Asia.

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&ndash, 2016. Afterwards, we analyzed the contribution rate of sectors&rsquo, energy intensity effect and sectors&rsquo, 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&ndash, 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&ndash, 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&ndash, 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&rsquo, s economic structure and transportation&rsquo, 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.

Understanding the patterns of dryness/wetness in the warming context is important for stakeholders to formulate adaptation strategies to minimize the impacts of floods and droughts. Spatial and temporal characteristics of regional temperature, precipitation, potential evapotranspiration (PET) and dryness/wetness variation were investigated for the period from 2015 to 2100 under SSPs-RCPs in Northwest China. Results show that annual mean temperature, precipitation and PET are projected to increase during 2015–2100, with increases higher in the long-term (2081–2100) than the near-term (2021–2040) and mid-term (2041–2060). Increase rate under SSP5–8.5 and SSP3–7.0 will significantly higher than other scenarios. Relative to the reference period (1995–2014), annual SPEI12 is projected to show a decreasing trend during 2015–2100. Trend will decrease highest under SSP5–8.5 scenario whereas the lowest under SSP1–1.9 and SSP1–2.6 scenarios. The state of drought in Northwest China is near normal during the reference period, drought will significantly escalate and moderate and severe drought will dominate the most of Northwest China with the increase of radiative forcing under SSPs-RCPs during 2015–2100. SSP5–8.5 will have the largest drought area than other scenarios. Observation shows Northwest China characterized a warmer and humid trend during 1961–2014, while GCMs projected that Northwest China will experience significant dryness trend during 2015–2100 under SSPs-RCPs, and SSP3–7.0, SSP4–3.4, SSP4–6.0 and SSP5–8.5 scenarios will be much drier than SSP1–1.9, SSP1–2.6 and SSP2–4.5 scenarios.

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&ndash, 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 2030, 2030, 2040, and 2040, respectively. At last, under 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.