Positioned in the era of the transformation of China's primary social contradictions, this study delves into the new connotations of regional coordinated development(RCD) from the perspective of “factors” coordination within the region and constructs an RCD evaluation system from five subsystems of regional economic coordination(REC), urban-rural coordination(URC), economic and social coordination(EASC), resource and environmental coordination(RAEC), and material and spiritual civilization coordination(MASCC). Then, the Entropy weight-TOPSIS model is used to evaluate the RCD levels of the 19 provinces located in the Yangtze River Economic Belt(YREB) and Yellow River Basin(YRB) from 2010 to 2019, and the two-way fixed-effects model is employed to illustrate the driving mechanisms of various influencing factors on the RCD in YRB and YREB. The results show that:(1)the RCD levels of YRB and YREB show a fluctuating upward trend during 2010 and 2019, however, both regions have low RCD levels, as seen by the mean RCD indices for YREB and YRB, which are only 0.433 and 0.309, respectively. (2) The RCD level of YREB is higher than that of YEB. In 2019, the “coordinated” provinces in YRB and YREB account for 37.50% and 81.82% of the total number of provinces in the basins, respectively, the “uncoordinated” and “low coordinated” provinces all located in YRB. (3) The RCD of YRB and YREB is significantly improved by REC, URC and RAEC, but not significantly positively by MASCC or EASC, and insufficient development of MASCC is the main contradiction limiting the increase in the RCD level of YRB, while the low level of EASC has become the main obstacle limiting the RCD of YREB. (4)Finally, based on the varying impact degrees and directions of different influencing factors on the RCD in YRB and YREB, the recommendations to promote RCD are proposed.

Based on a new development philosophy, this paper constructs an index system for measuring and evaluating high-quality developments in the Yellow River Basin using the entropy weight TOPSIS model and the obstacle degree analysis model to carry out a diagnostic analysis of the spatio-temporal differences in the level of high-quality development and obstacle factors in nine Yellow River Basin provinces from 2010 to 2020. The results show that: (1) During the period 2010–2020, the Yellow River Basin’s high-quality development index showed a rising trend and the subindexes showed a trend of “coordinated development > shared development > green development > open development > innovative development”. However, the overall level of high-quality development in the basin is not high, and there is still much room for improvement. (2) The global Moran’s I of the high-quality development indexes in 2010, 2015 and 2020 are −0.216, −0.204 and −0.103, respectively, indicating that the level of high-quality development in each province and region within the Yellow River Basin is discrete and develops in a spatially unbalanced direction. (3) The obstacle degree analysis shows that green development, innovation development and open development are the main bottlenecks affecting the high-quality development of the basin. The restrictive role of green development is increasingly prominent, and the low level of scientific and technological innovation and achievement transformation, serious resource consumption and low resource utilization rate of industrial development, in addition to the low level of openness to the outside world are becoming key factors hindering the high-quality development of the provinces in the Yellow River Basin.

In order to promote the precise governance of air pollution in the Yellow River Basin(YRB), it is of great significance to reveal the spatio-temporal patterns of urban air pollution in the basin and its spatial mismatch characteristics with air pollutant emissions. Based on spatial autocorrelation model and spatial mismatch model, this paper selected air pollution-related monitoring data from 69 cities in YRB from 2015 to 2020 as samples, and used ArcGIS, Stata, GeoDa and other softwares to analyze the spatio-temporal patterns of urban air pollution and its spatial mismatch characteristics with air pollutant emissions in YRB. The results showed that: (1) Temporally, the average annual Air Quality Index (AQI) values of cities in YRB ranged from 78.22 to 97.08 in 2015–2020, among which, the average annual AQI values of cities in the upper, middle and lower reaches of the basin decreased from 79.86, 89.23 and 122.14 in 2015 to 66.87,82.98 and 98.43 in 2020. (2) Spatially, there were obvious spatial differences in urban air pollution in YRB, and the AQI was roughly distributed in a geographical gradient of upper reaches < middle reaches < lower reaches, and there were significant spatial correlations in urban air pollution, mainly showing ‘high-high’ and ‘low-low’ aggregating characteristics. Among them, the lower reaches of YRB had formed a concentrated ‘high pollution zone’. (3) There was an obvious spatial mismatch between urban air pollution and air pollutant emissions in YRB, among which the spatial mismatch was obvious in cities such as Wuhai, Zibo, Shizuishan, Yangquan, Taiyuan, Datong, Jiyuan, Kaifeng, Puyang and Xi’an. (4) To improve the overall situation of air pollution in the cities of YRB, this paper proposed that the geographical gradient difference of air pollution in the upper, middle and lower reaches of YRB needs to be fully considered, following the principle of ‘focused treatment, gradual progress, enhanced prevention’, and according to the spatial mismatch characteristics of urban air pollution and air pollutant emissions, it is necessary to build a ‘differentiated’ governance strategy system for urban air pollution in the basin, which is ‘tailored to local conditions and categorized measures’.