Pollution-intensive Industries Research Articles

Investigation of the causality between participation in global value chains and CO2 emissions between developed and developing countries

The production and consumption activities are cross-border and therefore, it is important to understand the role of Global Value Chains (GVCs) in fulfilling a country’s specific climate commitments. This study examines the causal relationship between selected GVC indices and CO2 emissions. We use the GVC position index, considered robust in comparison to the frequently used GVC participation index, for determining the impact on emissions. The forward and backward participation indices are considered in the analysis. The paper presents an analysis of 62 developing and developed economies from 1995 to –2018 using the Juodis A., Y. Karavias, and V. Sarafidis [2021. “A Homogeneous Approach to Testing for Granger non-Causality in Heterogeneous Panels.” Empirical Economics 60 (1): 93–112] approach, which is an improvement over the traditional approaches to analysing causality. The results show that the overall position in GVCs positively affects CO2 emissions for developing countries but a causal relationship does not exist for the developed countries. The developed countries attain a higher participation index but a lower position index. On the other hand, developing countries with fewer stringent environmental regulations may opt for an upstream position (more export-oriented) and by design specialize in more pollution-intensive industries. Noteworthy, production-based emissions in developed countries are reduced because of an increase in imports of emission-intensive products from developing countries.

Environmental Justice and Corporate Green Innovation: The Role of Legitimacy Pressures

This study examines the impact of environmental judicial reinforcement on green technology innovation, constructing a progressive difference-in-differences model using firm- and city-level panel data from 2006 to 2019 and taking the successive establishment of environmental courts by the Intermediate People’s Court in Chinese prefectural-level cities as a quasi-natural experiment. We find that establishing environmental courts in China promotes green technology innovation. This finding still holds after a series of robustness tests such as selected fixed-effects Poisson model regression. The mechanism analysis suggests that environmental courts primarily promote increased green innovation output by heavily polluting firms by exerting more substantial pressure regarding environmental legitimacy. The heterogeneity analysis reveals that the positive impact of the establishment of environmental courts on green technology innovation is more pronounced in water pollution-intensive industries and areas with high public participation and media attention. Our findings provide new insights into how environmental justice affects firms’ green innovation and validate the Porter hypothesis. Also, they serves as a reference for constructing environmental courts in China and other policy jurisdictions that may be interested.

What Attracts Green: Value Differentiation of Environmental Industry and Coagglomeration with Pollution-Intensive Industries in China

Scholars have spent decades studying how environmental (“green”) industry can promote sustainability. Few studies, however, have discussed corporate dynamics within green industry and their spatial interactions with other manufacturing and service industries. Drawing on the theoretical perspective of industrial value chain differentiation, this study unpacks the spatiotemporal dynamics of environmental enterprises by various types in China. We use the Wasserstein coagglomeration index and Poisson regression to identify the spatial coagglomeration of green and pollution-intensive (“brown”) industries. The results show that (1) China’s environmental industry is still in the early and middle stages of development with low and medium added value as the core; (2) green enterprises are mainly distributed in the eastern coastal areas and a few inland provinces with developed infrastructure; and (3) the entry and spatial distribution of equipment and engineering enterprises are highly correlated with local brown industries, whereas high-end service enterprises tend to concentrate in economically developed urban agglomerations. This research hopes to reveal the spatial characteristics of environmental industry in the regional green transition through the decomposition of its value chain and the analysis of the spatial coagglomeration effect.

Robots, firm relocation, and air pollution: unveiling the unintended spatial spillover effects of emerging technology

Amidst the global upsurge in industrial robot deployment, there remains a notable gap in our understanding of their environmental impact. This paper explores how the introduction of industrial robots has changed air quality at both the local and neighborhood levels in China. Using the Spatial Durbin Model, we investigate the regional spillovers of PM 2.5 concentration and the diffusion of this innovative technology. Our findings reveal that the rise of robots significantly reduces air pollution in the local area, while exacerbating it in neighboring regions. This contrast is mainly because pollution-intensive industries are more inclined to relocate to neighboring regions than their cleaner counterparts, after the local use of robots increases. Throughout the process, internal costs rather than external costs dominate firms’ relocation decisions. This study provides novel insights into the complex environmental externalities associated with the spread of industrial robots and highlights the critical issue of growing environmental inequality in the era of emerging technologies.

The role of related variety and exporting on a firm’s labour productivity in pollution-intensive industries in China

ABSTRACT This study investigates the influence of regional industrial variety and export activities on labour productivity in China’s pollution-intensive manufacturing sectors from 2003 to 2009. Analysing data from 345,654 firms, we discover that regional related variety significantly boosts labour productivity. Moreover, this study reveals that firms with a higher export ratio experience an amplified benefit from the related variety on labour productivity. Our findings suggest the need for comprehensive policies that balance economic growth with environmental sustainability, emphasizing the nuanced role of industrial variety and global market integration in shaping productive efficiency.

The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence

Artificial Intelligence (AI) can improve production efficiency and general quality of life through assisting human labor, potentially leading to the conversion of employment types, enhancing industrialization, and upgrading energy structure. This paper enriches the role of AI in improving sustainable growth by curbing hypocritical sustainable and greenwashing behaviors. By accessing the panel data from Chinese listed-firms for the period 2014–2021, we have shown that AI can significantly mitigate the existence of greenwashing behaviors by raising the disclosure quality of ESG rating scores. Moreover, the role of AI in mitigating greenwashing behaviors performs significantly in SOEs, less pollution-intensive industries, high environmental regulation and less developed green finance regions. Furthermore, the potential mechanisms of AI in mitigating greenwashing behaviors are displayed, including alleviating financial constraints, easing management cost, improving green innovations.

Has the digital transformation promoted energy-saving-biased technological progress in China’s manufacturing sector?

ABSTRACT In the context of ‘Digital China’ and the ‘Dual-Carbon’ targets, there is an escalating need for energy saving and pollution reduction in China’s manufacturing sector. By optimizing resource allocation, enhancing precision in energy consumption monitoring and fostering the integration of traditional production factors, digital elements are pivotal in steering the sector towards energy technology progress, thereby affecting overall energy usage and carbon emissions. This study leverages panel data from 2009 to 2020 to quantify the manufacturing sector’s digital transformation and its energy-saving technology progress bias. It also examines the catalytic role of digital transformation in fostering energy-saving technological progress. The findings reveal the following: (1) The trajectory of technological progress within China’s manufacturing sector has progressively improved and predominantly demonstrates an energy-saving bias. (2) Digital transformation has significantly catalysed energy-saving-biased technological progress across various manufacturing subsectors, this conclusion is still significantly credible after a series of robustness tests. (3) Heterogeneity analysis reveals that as the digital transformation progresses from collaborative innovation to comprehensive digitalization phases, it has dramatically optimized the energy-saving-biased technological progress in various industries, especially in pollution-intensive industries. These insights offer substantial implications for policy formulation and industrial evolution.

Energy price uncertainty, environmental policy, and firm investment: A dynamic modeling approach

Environmental quality is closely related to the production and investment behavior of enterprises, which depends on the discounted future cash flows that are affected by energy price uncertainty. Meanwhile, with the increasing awareness of environmental protection, environmental policies have been introduced to restrict firm investment choices. However, the role of environmental policy has received less attention in the previous research on energy prices and firm investment. Therefore, this paper develops a dynamic firm investment model that incorporates energy price uncertainty and environmental regulation and makes the following predictions. First, ceteris paribus, energy price uncertainty negatively impacts firm investment. Second, environmental regulations mitigate this negative impact of energy price uncertainty. Third, the mitigating effect of environmental policy is greater in pollution-intensive industries. This paper merges the micro-data on A-share listed firms in China between 2004 and 2018 with the macro-data on energy prices and environmental regulation. The empirical results align with the theoretical predictions. The robustness tests, including instrumental variables, alternative measurements, and estimation methods, validate the baseline findings. These theoretical and empirical findings yield important implications for policymakers.

Unleashing the power of artificial intelligence for climate action in industrial markets

Artificial Intelligence (AI) is a game-changing capability in industrial markets that can accelerate humanity's race against climate change. Positioned in a resource-hungry and pollution-intensive industry, this study explores AI-powered climate service innovation capabilities and their overall effects. The study develops and validates an AI model, identifying three primary dimensions and nine subdimensions. Based on a dataset in the fast fashion industry, the findings show that the AI-powered climate service innovation capabilities significantly influence both environmental and market performance, in which environmental performance acts as a partial mediator. Specifically, the results identify the key elements of an AI-informed framework for climate action and show how this can be used to develop a range of mitigation, adaptation and resilience initiatives in response to climate change.

A rapid and environment-friendly process for dolomite pellets calcination with Joule-heating

Dolomite is an important industrial raw material for the production of metal magnesium. However, the calcination of dolomite is a typical pollution-intensive industry and is one of the major contributors to CO2 emissions in China. The requirements of energy conservation and environmental protection are driving the development of new calcination technologies. Herein, we developed a rapid and environment-friendly strategy for the calcination of dolomite used in subsequent magnesium production through carbothermal reduction, in which the pellets containing dolomite and carbon additive are calcined with in-situ Joule-heating in a vacuum. The effect of input volumetric specific power, heating time, vacuum conditions, carbon additive, and the size of the pellets on the decomposition process has been systematically studied. The dolomite in the pellets can be completely decomposed within tens of seconds. And the kinetic analysis shows that the activation energy of the decomposition of dolomite with the Joule-heating method is 108.4 kJ mol−1, which is much lower than the previous reports. Note that, the novel strategy shows a reduction of calcination time by 70 times, a reduction of energy consumption by 6.22% and a reduction of direct carbon emissions by 56.77% compared to the traditional methods. Combining the results of finite element simulations and density functional theory calculations, we revealed the mechanism of Joule-heating to enhance the decomposition of dolomite. The results show that the Joule-heating method can offer a distinct heating mechanism and deteriorate the structure stability of CaMg(CO3)2.

Cross-border M&As and the export green-technological sophistication: evidence from China

ABSTRACT Based on the Chinese Annual Survey of Industrial Firms (CASIF) database, this paper constructs a PSM-DID model to analyse the impact of cross-border mergers and acquisitions (M&As) on the export green-technological sophistication of Chinese industrial firms. The results show that cross-border M&As can effectively promote the export green-technological sophistication of acquired firms. The promoting effect of M&As increases gradually over time. Further, the heterogeneity results demonstrate that the promoting effect is more significant in private firms, partially acquired firms, firms in pollution-intensive industries and eastern areas. Finally, cross-border M&As can improve the export green-technological sophistication through two channels: improving green innovation capabilities and introducing pollution control equipment. Our results are significant for developing countries’ foreign investment guidance policies and firms’ green transformation.

Temporary prosperity or sustainable development: the long-run impact of developing pollution-intensive industries

Abstract This paper proposes a dynamic model to capture the interaction among the environment, human capital accumulation, and economic growth. We emphasize the mechanism that pollution stock depresses human capital accumulation, which has received increasing support from empirical studies. The model predicts that the development of pollution-intensive industries can help an economy gear up a short-run prosperity, but it impairs the capability for long-run economic growth, trapping the economy at a low development level. The cost for a dirty economy to switch is expensive and even infeasible if the environmental degradation is irreversible. Policy interventions, such as tax on pollution and subsidy on human capital, can help alleviate but cannot eradicate the economic stagnation.

Research on the Impact of Green Credit Policy on Corporate Environmental Social Responsibility

Since the 1970s, my country's industrialization process has continued to advance. However, with the improvement of economic level, the contradiction between my country's economic growth and environmental protection has become increasingly prominent. Green development has become an important principle guiding the high-quality development of my country's economy in the new era. In response to increasingly severe environmental problems, my country promulgated the "Green Credit Guidelines" in 2012, requiring financial institutions to include enterprises' environmental performance into credit review standards, implement differentiated credit interest rates for different enterprises, and raise the threshold for corporate loans. Penal high-interest credit is issued to highly polluting enterprises to limit the blind expansion of pollution-intensive industries. Since debt financing from banks and other financial institutions is the main source of funds for Chinese enterprises, changes in credit principles will inevitably affect the business and development strategies of enterprises. Then, can the green credit policy promote high-polluting enterprises to undertake environmental and social responsibilities? This issue deserves our in-depth study. This article designs a quasi-experimental based on the "Green Credit Guidelines" promulgated in 2012, constructs a difference-in-difference model to study the impact of green credit policies on corporate environmental responsibility levels, and analyzes the transmission mechanism of this impact. At the same time, it analyzes the differentiated impact of the "Green Credit Guidelines" on corporate environmental social responsibility under different enterprise sizes, proportions of institutional investors, regional legal environments, and factor market development levels.

Pollution Haven Hypothesis and the Bilateral Trade Between India and China

The pollution haven hypothesis is studied from a bilateral trade perspective in this study, taking the reference of two Asian giants, namely, India and China. For this purpose, trade in pollution-intensive industries is analysed using data collected from the United Nations Comtrade dataset based on Standard Industrial Trade Classification codes for 1992–2019. The analysis helps us argue that between the two, China's demand is more pollution-intensive and India is the major supplier of pollution-intensive products. From an environmental perspective, this implies that China seems to be gaining from trade, and India is becoming a pollution haven in its trade with China.

Does the pilot emissions trading system in China promote innovation? Evidence based on green technology innovation in the energy sector

The Chinese government promulgated a carbon emissions trading system (ETS) pilot in 2011 and gradually expanded its scope. Based on energy-related green patent applications in 283 Chinese cities from 2003 to 2018, this study investigates the impact of the ETS pilot on green technology innovation in the energy sector (GTIES). By employing a spatial difference in difference (SDID) model and multi-dimensional empirical tests, our results show, first, that the pilot policy has reduced GTIES to a certain extent, due to the higher environmental regulation compliance costs. Second, the ETS pilot has weakened the green technology innovation ability of both pollution intensive industries and non-pollution intensive industries, and its total effect on non-pollution intensive industries is about 1.85 times that on pollution intensive industries. Third, the development of GTIES in pilot regions has been restrained weakly, and the promoting impact on GTIES in the neighboring region is not significant. This study provides empirical evidence for the evaluation of the pilot policy at the city-industry-regional level, revealing enlightenment on industrial policy and the need for regional collaboration in the presence of spatial spillover effects.

Green innovation and political embeddedness in China's heavily polluted industry: role of environmental disclosure, gender diversity, and enterprise growth.

Innovation in green technology is an efficient approach to reducing carbon emissions and achieving energy conservation, which is essential for fostering sustainable and green economic development. Even though the development of eco-friendly technologies is accelerating, the grasp of how political ties affect firms' adoption of green technologies remains hazy. This paper examines the effect of a firm's total political embeddedness (government ownership and political connections) along with the influencing mechanisms by employing a panel fixed effect regression approach on a dataset of Chinese A-share enterprises operating in pollution-intensive industries spanning 2012 to 2021. The findings offer conclusive evidence that political embeddedness encourages the enterprises' development of green technologies and boosts their output of innovation. In addition, mechanism analysis reveals that companies' political embedding influences their green innovation behavior through environmental disclosure. Moreover, board gender diversity and company growth rate are found to reinforce the impact of political embeddedness on green innovation. Besides expanding the current research on green innovation and corporate political involvement, the findings also provide important policy recommendations for the sustainable development of companies in emerging markets.

The side effects of local government debt: Evidence from urban investment bonds and corporate pollution in China

Local government debt plays a vital role in achieving financial financialization and regional economic growth. However, the environmental side effects of the debt-financed infrastructure development model have received little attention. Using a large panel data of Chinese enterprises from 2007 to 2016, we explored the relationship between local government debt in terms of urban investment bonds and corporate pollution emission. We observe that the increase in local government debt exaggerates the intensity of COD emission, equal to 26% of the average. This pollution-promoting effect remains after a series of robust checks. In heterogeneous analysis, local government debt is more likely to affect enterprises located in coastal areas, from pollution intensive industry, operating in regions with weak fiscal strength and operating in regions with low governance quality. The mechanistic exploration from government environmental governance and financial constraint reveals that the local government debt increases corporate pollution when the local fiscal finance emphasizes economy over environmental governance, which has been alleviated after the central government advocates the construction of an environmentally friendly and resource-saving society; An increase of corporate pollution is also possible when local government debt increases the financing constraints of enterprises. We also unveil the source of corporate pollution, and find that if enterprises do not actively adopt environmental strategies either in terms of “end-of-pipe” or “source prevention”, they choose to emit more to face with the onslaught of local debt. This study uncovers the environmental impacts of government debt, and explores the potential mechanisms, which can help reduce pollution from local government debt and achieve global climate governance.

The heterogeneous effects of Chinese industrial parks on environmental pollution

As a form of regional agglomeration, industrial parks create huge benefits for China's economic development, but they also generate considerable environmental externalities and are expected to become the breakthrough to achieve green transformation. This study builds a panel data set by combining a variety of data on the environmental and economic characteristics of firms, industrial parks, and regions, and empirically investigates the effects of establishing industrial parks on emissions of COD, NH3, SO2, and dust. We find such effects are heterogeneous across scales of investigation and types of industrial parks. After entering the industrial parks, firms can reduce their environmental pollution, and the emissions of COD, SO2 and dust have decreased by 9.3 %, 13.4 % and 4.6 %, respectively. However, the study at the regional level finds that, after the establishment of industrial parks, the overall emissions of COD, NH3, SO2, and dust have increased by 37.9 %, 365 %, 45.5 % and 34.9 %, respectively. The expansion of production scale and the increase of pollution-intensive industries are the main factors that cause more serious regional pollution. Meanwhile, the improvement of pollution treatment is very limited. After the establishment of a new park, the emission intensities of newly entered firms are higher than those of pre-existing firms, indicating industrial parks may lower environmental requirements in exchange for economic growth. Parks with clean dominant industries, high levels of water reuse and technical innovation tend to emit less pollutants. Based on the results, this study gives four suggestions for establishing environment-friendly industrial parks, that is, to plan the industrial layout rationally, to speed up the construction of pollution treatment facilities, to increase the environmental threshold for entrance, and to promote technical innovation.

A Study on the Spatial Distribution and Gradient Transfer of Atmospheric Pollution Intensive Industries Such as the Thermal Power Industry in Hebei Province

Owing to a long-term, extensive development model and inadequate industrial development planning, cases of atmospheric environment pollution frequently occur in Hebei province. By using such approaches as the Spatial Gini Coefficient, the Herfindahl–Hirschman Index and location entropy, this paper analyzes the spatial-distribution characteristics of atmospheric pollution-intensive industries such as the thermal power industry in Hebei province. As shown, atmospheric pollution-intensive industries, such as the thermal power industry in Hebei province, excessively cluster. As industrial agglomeration continuously intensifies, the spatial imbalance becomes increasingly prominent. Taking the number of days with excellent air quality as a benchmark, this paper divides prefecture-level cities of Hebei province into four types of industrial management and designs targeted strategies for the optimization of atmospheric pollution-intensive industries, such as the thermal power industry. In terms of policies, Type I and Type II cities are advised to strengthen the transfer of atmospheric pollution-intensive industries such as the thermal power industry, and Type III and Type IV cities are advised to improve capacities in atmospheric self-purification and green-technology innovation in a bid to help government departments to scientifically manage atmospheric pollution-intensive industries such as the thermal power industry.

Political uncertainty and Corporate Philanthropy: Evidence from China

Abstract This study investigated the relationship between political uncertainty and corporate philanthropy in emerging markets, using China as the research setting. The growth of companies in China depends largely on various national policies which are also the main drivers on Chinese economic development. Those polices are actually executed by local leaders with a certain degree of autonomy. Each leader has a personal style of policy implementation in his/her jurisdictions. Once the local leader shifts, enterprises in the region may face the risk of policy implementation changes. Leadership transitions in Chinese cities were chosen to represent political uncertainty. After a change in local government leadership, more philanthropic activities and higher charitable spending were identified for listed companies in the region. The trend was exceptionally prominent for companies with higher regulatory risks. In that regard, companies in the private sector or owned by the local government, from pollution-intensive industries, or with a considerable size were riskier. In addition, the study identified the potential of charitable giving in lessening administrative punishments for the donating companies. The research expanded the literature on political uncertainty and corporate philanthropy by illustrating the effectiveness of the former as a response to the latter.