Industrial agglomeration is a major source of regional economic development and the main pattern enterprises employ after having developed to a certain stage. Industrial agglomeration also affects the emissions of air pollutants in production. Based on provincial panel data for China from 2006 to 2019, this paper introduces the full generalized least squares (FGLS) panel econometrics model. By considering spatial correlation, the potential endogenous problem has been controlled using the instrumental variable and the effects of the co-agglomeration of manufacturing and producer services on three major air pollutants, i.e., SO₂, PM_2.5, and NO_x, have been empirically estimated. The empirical results show that: (1) The agglomeration of manufacturing increases the emission of PM_2.5 in the air, while the agglomeration of producer services and the co-agglomeration of manufacturing and producer services reduce it. Moran correlation index test showed that SO₂ and NO_x had no significant spatial correlation. (2) The agglomeration of manufacturing, the agglomeration of producer services, and co-agglomeration exert the most significant effects on PM_2.5 in the air in central and western China. This is probably because of the availability of basic natural resources in these areas. (3) The energy consumption structure mediates the effect of the agglomeration of manufacturing on PM_2.5, and human capital mediates the effect of the agglomeration of producer services on PM_2.5 emissions. Based on the results, policy suggestions to improve the atmospheric environment during the process of industrial agglomeration are proposed.

Under the influence of the dual policies of sustainable economic development and the national dual-carbon target, the establishment of an environmental protection department for the treatment of heavily polluting industries is imminent, and the country has launched pollution control policies and regulations to restrict the emission rights of heavily polluting industries. Therefore, this paper focuses on whether the restriction of emission rights in key industries has reduced carbon emissions. To achieve this, this paper uses panel data of prefecture-level cities in China from 2006 to 2019 and adopts a two-way fixed-effects DID model to systematically analyze the impact of the key pollution industry governance policies launched by the Ministry of Environmental Protection on CO₂ emissions in 2017. And further analyze the role of variables such as green technology innovation patents and energy efficiency using this model, while parallel trend tests and placebo tests, and related policies are used to ensure the robustness of the regression results. This paper reveals that: (1) The heavy pollution industry governance policy implemented in 2017 can effectively reduce CO₂ emissions in the cities of the treated group, and the effect is more significant in the year of policy implementation; (2) Green utility patents and energy-use efficiency are the effective mediating mechanisms to reduce CO₂ emissions; (3) Over time, the effect of heavy pollution industry governance policy on CO₂ emissions gradually decreases; (4) The reliability of the baseline regression results of this paper is proved by the use of parallel trend tests, placebo tests, and tests excluding the influence factors such as relevant policies in the same period. Therefore, the key polluting industries treatment policy launched by China’s Ministry of Environmental Protection in 2017 under the recent dual-carbon policy development goals formulated by China, can effectively reduce carbon emissions; however, in the future economic development process, the government should give more consideration to the continuity of the policy impact and its coherence on economic development when implementing the policy.

Land consolidation is a crucial strategy for optimizing land use structure and ensuring cultivated land security and food safety. Since 2019, Zhejiang Province has been piloting and exploring Whole-Region Comprehensive Land Consolidation (WRCLC). However, there remains an insufficient understanding of the feasibility of WRCLC in ensuring cultivated land security and its potential for synergy with other policies. This study utilizes panel data from 707 townships in Zhejiang Province spanning from 2013 to 2022. By categorizing cultivated land security into two dimensions—quantity and quality—this study employs a double machine learning approach to evaluate the impact of WRCLC policies on township cultivated land security. The results indicate that implementing WRCLC significantly enhances both the quantity and quality of cultivated land. A heterogeneity analysis reveals that WRCLC is particularly effective in improving the quality of cultivated land in non-major grain-producing areas and low economic development areas. Furthermore, examining policy synergies indicates that agricultural mechanization and agricultural industry integration policies work well in conjunction with WRCLC, thereby enhancing both the quantity and quality of cultivated land. However, the synergy with rural tourism policies improves cultivated land quality without effectively increasing cultivated land quantity.