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PM2.5 is closely linked to both air quality and public health. Many studies have used models combined with remote sensing and auxiliary data to inverse a large range of PM2.5 concentrations. However, the data's spatial resolution is limited. and better results might have been obtained if higher resolution data had been used. Therefore, this paper establishes a geographical and temporal weighted regression model (GTWR) and estimates the PM2.5 concentration in Xinjiang from 2015 to 2020 using 1 km resolution MCD19A2 (MODIS/Terra+Aqua Land Aerosol Optical Thickness Daily L2G Global 1km SIN Grid V006) data and 9 auxiliary variables. The findings indicate that the GTWR model performs better than the simple linear regression (SLR) and geographically weighted regression (GWR) models in terms of accuracy and feasibility in retrieving PM2.5 concentrations in Xinjiang. Simultaneously, by combining the GTWR model with MCD19A2 data, a spatial distribution map of PM2.5 with better spatial resolution can be obtained. Next, the regional distribution of annual PM2.5 concentrations in Xinjiang is consistent with the terrain from 2015 to 2020. The low value area is primarily found in the mountainous area with higher terrain, while the high value area is primarily in the basin with lower terrain. Overall, the southwest is high and the northeast is low. In terms of time change, the six-year PM2.5 shows a single peak distribution with 2016 as the inflection point. Lastly, from 2015 to 2020, the seasonal average PM2.5 concentration in Xinjiang has a significant difference, thereby showing winter (66.15μg/m3)>spring (52.28μg/m3)>autumn (40.51μg/m3)>summer (38.63μg/m3). The research shows that the combination of MCD19A2 data and GTWR model has good applicability in retrieving PM2.5 concentration. [ABSTRACT FROM AUTHOR]

• After 2005, the production space, living space, and ecological space (PLES) in Xinjiang began to undergo significant changes. • Land Desertification is the main reason for space conflict in Xinjiang. • Natural condition, socio-economic, and policy factors collectively influence the evolution of the pattern of PLES in Xinjiang. Xinjiang is located in the northwest of China, with a vast territory and abundant resources, which holds an important strategic position for China. However, the climate in the region is arid and the ecological environment is fragile. In recent years, with the growth of population and the improvement of economic development level, construction and agricultural land in Xinjiang have gradually expanded, and ecological land has been extensively occupied. The competition between land resources is becoming increasingly fierce, leading to some ecological and environmental problems in the region. In this context, understanding the spatiotemporal changes and driving factors of Xinjiang's production space, living space and ecological space (PLES) is of great practical significance for promoting sustainable development in the region, and can also provide reference for the research of PLES in other arid areas at home and abroad. At present, most of the research on PLES is focused on small-scale areas such as urban agglomerations, rural areas, and watersheds, or non arid areas with relatively superior natural conditions, with less research on large-scale arid areas. In this study, the transfer matrix, the center of gravity movement trajectory, Moran's I and the spatial conflict measurement model were used to illustrate the spatial–temporal evolution of PLES in Xinjiang, and the correlation coefficient was used to determine the main factors affecting the change of PLES. Results show that (1) Xinjiang is dominated by ecological space, which accounts for more than 90% of the total area of Xinjiang and has significant continuity. They are mainly distributed in Tarim, Turpan, and the northern Junggar Basin. The production space area accounts for about 5% of the total area of Xinjiang and is distributed in the vicinity of the Tianshan and Kunlun Mountains. Living space accounts for about 1% of Xinjiang's total area and is scattered around cities. (2) From 2000 to 2020, the change degree of PLES in Xinjiang in the last decade is higher than that in the first decade, most of which is the transformation from ecological space to production space. The three types of spaces influence and restrict each other in the development process. (3) Population, crop sown area, natural conditions, policy and the development level of agricultural science and technology are the main factors affecting the spatial distribution of production. Environmental factors such as altitude, soil erosion and temperature have a great influence on ecological space. Population, the output value of various industries and total retail sales of consumer goods are the main factors affecting residential space. The evolution of Xinjiang PLES is the result of multiple factors. (4) The medium spatial conflict dominates, mainly distributed in Tarim Basin and Junggar Basin. The weak and strong space conflicts are concentrated in the oases in the north of the Tianshan and Kunlun Mountains, and the number is small. From 2000 to 2020, the increasing degree of spatial conflicts in Xinjiang is due to land desertification. [ABSTRACT FROM AUTHOR]