Influence mechanism of industrial agglomeration on carbon emission intensity-a perspective on borrowing performance.

Under the background of urban connectivity, whether there are similarities and differences in the impacts of local industrial agglomeration and inter-city industrial agglomeration borrowing performance on carbon emission intensity(CI), and how cities can fully utilize the external force-borrowing performance to reduce local CI, these issues are of great significance for the cost saving and efficiency enhancement in the process of carbon emission (CE) reduction. Based on panel data of 280 prefecture-level cities in China from 2003 to 2020, the panel dual fixed-effect model, instrumental variable method, and adjustment effect model were used to analyze the impacts of the manufacturing agglomeration (MA), producer service agglomeration (PA), and the collaborative agglomeration (CA) on the CI from the perspective of individual cities and the urban system. The results showed that the influence of MA on CI presents a significant inverted U-shaped relationship, PA significantly reduces CI, and the CA of the two industries increases CI. Further analysis showed that the borrowing MA performance improves CI, especially in newer industrial-based cities, non-resource-based cities, and medium and big cities; the borrowing PA performance reduces CI, especially in old industrial-based cities, non-resource-based cities, and large cities; and the borrowing CA performance has no significant effect on CI. In addition, the development of the Internet strengthens the influence of borrowing performance in MA and PA on CI.

Can industrial collaborative agglomeration drive the regional ecological efficiency improvement to fulfill COP26 requirements?

COP26 provided a roadmap to world leaders for taking policy measure for the climate change effects mitigation. In this regard, policy makers of major countries devoted their overwhelming support. Similarly, to achieve the targets of COP26, the role of industrial and energy sector critically important. In this paper, we have developed a new energy saving path to meet COP26 requirements through the industrial collaborative agglomeration index (ICAI) model which is constructed by taking location entropy of single industrial agglomeration as the basis. The super undesirable SBM (SUSBM) model is constructed to measure regional ecological efficiency (EE). Results show great differences in ICAI among the 3 regions and 11 provinces. Industrial collaborative agglomeration level of the upstream region shows fluctuation upward trend, while that of midstream and downstream regions shows fluctuation downward trend. The EE in downstream region is highest. The impact of ICAI on EE is significant and shows as a U-shaped curve. The increasing of proportion of the secondary industry in the industrial structure and increasing of per capita energy consumption inhibit the improvement of EE. The high proportion of non-state-owned economy in the economic system, the strengthening of environmental regulation intensity, and the improvement of economic development level and push technological innovation are conducive to the improvement of regional EE.

The impacts of industrial collaborative agglomeration on industrial sulfur dioxide emissions in China: from the novel perspective of spatiotemporal matrix.

This paper explores the impacts of industrial collaborative agglomeration on industrial sulfur dioxide intensity from a spatiotemporal perspective based on panel data on the 284 prefecture-level cities from 2003 to 2019, with systematic consideration of the underlying mechanism of channels and actions. The empirical results show that industrial co-agglomeration significantly intensifies industrial SO2 intensity, especially with increasing agglomeration. In addition, its positive spatial spillover effects are established in geographical proximity to the city. Furthermore, the channel analysis shows that the industrial structure path, industrial efficiency path, and industrial scale path account for a sharp increase in industrial SO2 intensity. The market forces reverse and moderate this exacerbating process more significantly than the government does, which provides evidence for the importance of pursuing a dynamic equilibrium between them. Finally, there exist heterogeneous effects across cities with different administrative levels, innovation capacities, and macropolicies of special emission limits for air pollutant policy. While arguing for the environmental pollution effects of industrial co-agglomeration, this paper also provides solid support and a new perspective for promoting sustainable economic development and achieving win-win economic and environmental benefits.

Can industrial collaborative agglomeration improve carbon emission efficiency? Empirical evidence from China.

Against the backdrop of low-carbon development, it is imperative to cultivate a modernized industrial system and new development model. Industrial collaborative agglomeration (ICA) between manufacturing and producer services may offer an opportunity to aid carbon reduction in this scenario. Using balanced panel data of China's 30 provinces and municipalities from 2008 to 2019, this paper attempts to investigate the influences of ICA on carbon emission efficiency (CEE), its heterogeneous effects, impact mechanisms, and spillover effects. Our main findings can be concluded as follows: (1) There is a U-shaped relationship between ICA and CEE; namely, ICA will inhibit first and then promote CEE. (2) The heterogeneity results further indicate that this U-shaped relationship is significant in the eastern area while there exists an inverted U-shaped relationship between ICA and CEE in the western area; however, the influence of ICA on CEE is not significant in the central area. (3) More deeply, the mechanism identification uncovers that industrial structure upgrading and green technological innovation are important channels through which ICA affects CEE. (4) Importantly, we unfold that ICA in the local area has spatial spillover effects; namely, it will influence CEE in neighboring areas, which also presents a U-shaped relationship. These findings provide not only new insights into understanding the environmental effects of ICA but also helpful inspiration for regional policymakers to scientifically formulate industrial development policies and effectively implement carbon emission control actions.

Study on the Impact of Collaborative Agglomeration of Manufacturing and Producer Services on PM2.5 Pollution: Evidence from Urban Agglomerations in the Middle Reaches of the Yangtze River in China.

In this paper, using panel data of 28 cities in the middle reaches of the Yangtze River from 2003 to 2020 as the research sample, we built a dynamic spatial Durbin model based on the STIRPAT (stochastic impacts by regression on population, affluence, and technology) model and conducted an empirical study on the impact of the coordinated agglomeration of manufacturing and producer services on particulate matter (PM) 2.5 pollution. The results show a significant positive spatial spillover effect of PM2.5 pollution in the middle reaches of the Yangtze River. The coordinated agglomeration of manufacturing and producer services in the urban agglomerations there is conducive to reducing PM2.5 pollution. Similar to the inverted-U curve of the classic environmental Kuznets curve hypothesis, there is a significant inverted-U curve relationship between PM2.5 pollution and economic growth in urban agglomerations in the middle reaches of the Yangtze River. The proportion of coal consumption, the proportion of secondary industry, and the urbanization level are significantly and positively correlated with PM2.5 pollution in urban agglomerations in this area. Technological innovation, environmental regulation, and annual average humidity play an important role in addressing the PM2.5 pollution and spatial spillover effect. Industrial structure and technological innovation are the main ways for the coordinated agglomeration of manufacturing and producer services to affect PM2.5. The research conclusion can be of great practical significance to optimize the regional industrial layout, control PM2.5 pollution, and establish a sustainable development policy system in the middle reaches of the Yangtze River in China.

Does industrial collaborative agglomeration improve environmental efficiency? Insights from China's population structure.

Nowadays, the development of green economy and the improvement of environmental efficiency have been a hotspot in both academia and industry. Especially, the effect of the collaborative agglomeration of manufacturing and productive services industries on environmental efficiency has drawn attention from Chinese policymakers, during a critical period of industrial transformation and upgrading and ecological civilization construction in China. However, few studies have explored whether and how industrial collaborative agglomeration affects environmental efficiency based on population structure perspective. To bridge this gap, using the methods of the stochastic frontier approach (SFA), the moderating effect of population structure, and the spatial effect, and employing the panel data of 66 cities in eastern China during 2009-2018, this paper studies the effect of industrial collaborative agglomeration on environmental efficiency and measure the fluctuates of influence including population structure. The results show that industrial collaborative agglomeration has the effect of improving environmental efficiency, and both of them have strong spatial spillover effect. Direct effect of the industrial collaborative agglomeration is more significant positive than indirect effect. It indicates that the environmental efficiency is affected by the industrial collaborative agglomeration in both the local region and neighboring regions. In addition, population density, aging and quality play a positive moderate role by strengthening the spillover effect of industrial collaborative agglomeration, while the moderating effect of population urbanization is not significant. Then, the recommendations and policy implications to improve environmental efficiency are put forward based on the research results: optimizing the coordinated governance system of regional ecological environment, accelerating the innovation of industrial value chain, and promoting the sustainable development of industry and ecology with the advantage of population structure.

Can industrial collaborative agglomeration reduce carbon intensity? Empirical evidence based on Chinese provincial panel data.

The collaborative agglomeration of manufacturing and producer services is an essential tool for the green transformation of China's economic model. This paper explores the impact of industrial collaborative agglomeration on carbon intensity, using the spatial Durbin model (SDM) based on China's provincial panel data from 2012 to 2019. The empirical results indicate that there is an inverted N-shaped relationship between industrial collaborative agglomeration and carbon intensity, with the turning points of 2.5255 and 2.8575. Regional industrial collaborative agglomeration tends to initially reduce carbon intensity, then aggravates to carbon emission, then finally inhibits carbon intensity. There is an obvious heterogeneity in the impact of producer-service subsectors and manufacturing collaborative agglomeration on carbon intensity. When the industrial collaborative agglomeration level exceeds a certain threshold, the clustering of information transmission, software and information technology service, and financial intermediation service have the greatest emission reduction potential. Industrial collaborative agglomeration has obvious spatial spillover effect, and carbon intensity has obvious spatial convergence effect. This paper provides some novelties for research perspectives on carbon intensity reduction and theoretical references for the development and implementation of differentiated industrial collaborative agglomeration policies.

Can Industrial Collaborative Agglomeration Reduce Haze Pollution? City-Level Empirical Evidence from China.

We analyze the mechanism for industrial co-agglomeration in Chinese 283 cities to affect haze pollution from 2003 to 2016 and examine the possible mediating effects of urbanization and energy structure between haze pollution and industrial co-agglomeration, finally obtaining the following results. First, industrial co-agglomeration and haze pollution across China, including central and eastern regions keep a typical inverted U-shaped curve relationship. That is, industrial co-agglomeration first promotes haze pollution and then restrains it. However, the impact of industrial co-agglomeration on haze pollution in western China is still on the left side of the inverted U-shaped curve, reflecting a promotion effect. Second, industrial co-agglomeration has a significant spatial spillover effect on haze pollution. Additionally, industrial co-agglomeration can promote haze pollution in local regions but inhibit it in surrounding regions in both the short and long run. In contrast, when the industrial co-agglomeration index exceeds the inflection point (3.6531), it benefits the reduction of haze pollution in local regions, while not being conducive to it in the neighboring regions. Third, industrial co-agglomeration can affect haze pollution through urbanization and energy structure, that is, urbanization and energy structure play an intermediary role between them.