Manufacturing agglomeration is an important manifestation for cities to enhance their competitiveness, and the resource and environmental effects caused by agglomeration have become a hot topic. Based on the relevant data of prefecture-level cities in the Yellow River Basin from 2006 to 2019, this study used a Markov transition matrix to study the characteristics of carbon emission transfer and constructed an SDM model to analyze the effect of manufacturing agglomeration on carbon emissions and spatial spillover; the study drew the following conclusions: carbon emissions and the concentrations of manufacturing industries in the Yellow River Basin are on the rise, with carbon emissions showing a distribution pattern of “downstream > midstream > upstream”. Manufacturing agglomeration has a significant positive influence on carbon emissions, reflecting the necessity for the green transformation of manufacturing agglomeration. Manufacturing agglomeration has a spatial spillover effect on carbon emissions. The direct effect is positive, and the indirect effect is negative. The polarization effect caused by agglomeration weakens the development degree of neighboring areas, which may reflect the technological spillover effect of manufacturing agglomeration on neighboring areas. Manufacturing agglomeration has regional heterogeneity in carbon emissions. Compared with the middle and lower reaches of the Yellow River Basin, the effect is more obvious in the upper reaches. The study proposes countermeasures in terms of optimizing the spatial pattern of the manufacturing industry and other aspects to provide references for promoting the transformation development of the manufacturing industry in the Yellow River Basin.

Instead of being merely an important embodiment of regional productivity, the manufacturing industry also serves as a significant sector of economic operation and the supply chain system that is highly dependent on resources and the environment. Studying the spatial pattern of the manufacturing industry and its environmental effect is extremely significant for optimizing the spatial layout of urban industry, allocating production factors in a rational manner, and promoting the green transformation of industry. In this regard, this study aimed to further reveal the spatial pattern characteristics of the regional manufacturing industry and its impact on PM_2.5. Using data from micro-enterprises in the manufacturing industry in the Yangtze River Economic Belt, its spatial pattern characteristics are explored and an econometric model is constructed to analyze the impact of the manufacturing industry on PM_2.5 by comprehensively applying approaches including kernel density estimation, nearest proximity index, and Dagum Gini coefficient decomposition. Three research conclusions were drawn: (1) an obvious “core-edge” feature is present in the spatial distribution of the manufacturing industry in the studied area showing an apparent pattern of “high in the east and low in the west”. The core density of the manufacturing industry in the central cities is significantly higher than that in the surrounding cities. (2) In the manufacturing industry and its subdivisions, the characteristics of spatial agglomeration are unveiled, while the agglomeration and spatial differences are diminished during the study period for the spatial equilibrium of the manufacturing industry. (3) A significantly positive impact is exerted on PM_2.5 pollution that is not limited to local cities by the manufacturing industry, which, due to the development differences within the study region, is also heterogeneous. In view of this, policy proposals for aspects such as forging a green manufacturing cluster area, establishing an industrial integration development platform, giving play to regional advantages and technological potential, etc., are put forward in this study, so as to provide a useful reference for optimizing the industrial pattern and promoting the green transformation of industries.