Exploring Greenhouse Gas‐Mitigation Strategies in Chinese Eco‐Industrial Parks by Targeting Energy Infrastructure Stocks

China has more than 1,500 industrial parks, which, collectively, play a crucial role in facilitating industrialization and urbanization. A key characteristic of these parks is that most rely on shareable energy infrastructure, an efficient configuration that can also deliver substantial and sustainable reductions in greenhouse gas (GHG) emissions. This study offers strategies for mitigating GHG emissions from Chinese industrial parks. We focus on extensive data collection for the 106 industrial parks listed in the national demonstration eco‐industrial park (EIP) program. In doing so, we carefully examine the evolution of 608 serviceable energy infrastructure units by vintage year, fuel type, energy output, and technologies of combined heat and power units. We assess direct GHG emissions from both energy infrastructure and the parks, and then identify the features and driving forces of energy infrastructure development in the EIPs. We also offer recommendations for ways to mitigate the GHG emissions from these industrial parks. The energy infrastructure stocks in Chinese EIPs are characterized by heavy coal dependence (87% of capacity) and high ratios of direct GHG emissions versus the total direct emissions of the park (median value: 75.2%). These findings establish a baseline from which both technology and policy decisions can then be made in an informed way.     

Barriers to Promoting Eco‐Industrial Parks Development in China

For at least the past two decades, eco‐industrial parks (EIPs) have been promoted as policy and commercial instruments for achieving industrial sustainable development. Yet, few EIPs have seen successful operational implementation, especially if they begin as standard industrial parks. Rapid economic growth, commensurate with increasing environmental damage in China, has resulted in officials’ further pursuing EIP policy as a significant element of the broader circular economy and ecological modernization efforts. This article examines the barriers for EIP development from industrial park senior manager perspectives. Using resource dependence theory and the resource‐based view as theoretical lenses, we investigate the external and internal barriers for EIP development in 51 Chinese industrial parks. A number of barriers are identified and grouped through a factor analysis. Cluster analysis is utilized to help categorize and evaluate the perceived levels of barriers and hardships experienced by various senior officials that manage the EIPs. It is found that few respondents encounter no significant barriers. Barriers related to technological development and capacity building are the most prevalent. These results highlight the relative importance of various activities that may be necessary by policy makers and other stakeholders to overcome the barriers. For example, cooperation in developing technological solutions for EIPs seems to be a major thrust that should be pursued by EIP development stakeholders. Other policy and managerial insights based on the general findings of this study are also presented.     

Modeling and Optimization of a Coal‐Chemical Eco‐industrial System in China

China is coal dependent, and this situation will persist for a long time. Because more and more attention has been paid to energy security, the coal‐chemical industry has become a hot topic and has developed quickly. To improve efficiency and reduce emissions, industrial symbiosis (IS) can be introduced when establishing a coal‐chemical eco‐industrial system to achieve harmonious development between nature, industry, and society. In order to learn the influence of IS on the current industrial system, a model of coal‐chemical eco‐industrial systems was built. Using scenario optimization and linear programming, the behaviors and optimal industrial structures of the system under different scenario settings were compared, and industrial ecological analysis was performed. By comparative analysis, results showed that the greatest proportional decrease in the use of coal for coking was 15% compared with actual data for 2005. The resource‐productivity and eco‐productivity were 828 yuan/ton and 2.51, which are much higher than the values of 548 yuan/ton and 1.23 in 2005. The symbiosis index and the link density were found to be 0.675 and 1.67, compared with 0.588 and 0.94 in 2005. Research results showed that the coal‐chemical eco‐industrial system achieved a high value‐added utilization of coal and an updated product profile. Such systems will constitute the main direction and the inevitable trend of China's coal utilization in the future, which will reduce the harm to the environment from increased coal use and benefit the energy industry, the economy, and society.     

Longitudinal Analysis of the Eco‐Design Management Standardization Process in Furniture Companies

This article discusses how eco‐design management standards have been adopted and the environmental and economic results that have been obtained by the Spanish furniture manufacturers. This is precisely the industry sector in Spain where the dissemination of eco‐design standards has been most important. Using multiple case‐study methodology, the research has shown that, in three companies, more than 90% of the environmental impact of the companies’ products occurs within the manufacturing phase. Companies have implemented tools for life cycle assessment with eco‐indicators values that allow them to assess complex products and evaluate their significant environmental impacts at each stage. The environmental strategies of these companies are based on the continuous improvement of the internal processes and the review and monitoring of their activities. In this approach, the proper choice of materials and the environmental management of the supply chain are the main problems for companies. The outcomes achieved by the companies included some improvements, such as a greater control of product management and a reduction in operating costs, that have allowed them to obtain competitive advantages. Moreover, the adoption of standard management has enabled the companies to drive innovation of products, improve the image of companies and their products, significantly reduce the environmental impact of their products, and adapt to new, more demanding environmental laws and regulations.     

Eco‐evolutionary dynamics in response to selection on life‐history

Understanding the consequences of environmental change on ecological and evolutionary dynamics is inherently problematic because of the complex interplay between them. Using invertebrates in microcosms, we characterise phenotypic, population and evolutionary dynamics before, during and after exposure to a novel environment and harvesting over 20 generations. We demonstrate an evolved change in life‐history traits (the age‐ and size‐at‐maturity, and survival to maturity) in response to selection caused by environmental change (wild to laboratory) and to harvesting (juvenile or adult). Life‐history evolution, which drives changes in population growth rate and thus population dynamics, includes an increase in age‐to‐maturity of 76% (from 12.5 to 22 days) in the unharvested populations as they adapt to the new environment. Evolutionary responses to harvesting are outweighed by the response to environmental change (~ 1.4 vs. 4% change in age‐at‐maturity per generation). The adaptive response to environmental change converts a negative population growth trajectory into a positive one: an example of evolutionary rescue.     

Assessing the “Short Mental Distance” in Eco‐Industrial Networks

Like many economic exchanges, industrial symbiosis (IS) is thought to be influenced by social relationships and shared norms among actors in a network. While many implicit references to social characteristics exist throughout the literature, there have been few explicit attempts to operationalize and measure the concepts. The “short mental distance,”“trust,”“openness,” and “communication” recorded among managers in Kalundborg, Denmark, set a precedent for examining and encouraging social interactions among key personnel in the dozens of eco‐industrial networks around the world. In this article we explore the relationships among various aspects of social embeddedness, social capital, and IS. We develop a conceptual framework and an approach using quantitative and qualitative methods to identify and measure these social characteristics, including social network structure, communication, and similarities in norms and conceptions of waste, and apply them in an industrial network in Nanjangud, South India. The findings suggest that there is a fairly high level of shared norms about dealing with waste—the “short mental distance”—in this network, but by‐product transactions are only weakly correlated with the structure and content of communication among managers. Replication of this approach can increase the understanding and comparability of the role of social characteristics in eco‐industrial activities around the world.     

An Approach to Integrating Environmental Considerations Within Managerial Decision‐Making

Recent environmental trends, including (1) an expansion of existing command and control directives, (2) the introduction of market‐based policy instruments, and (3) the adoption of extended producer responsibility, have created a need for new tools to help managerial decision‐making. To address this need, we develop a nonlinear mathematical programming model from a profit‐maximizing firm's perspective, which can be tailored as a decision‐support tool for firms facing environmental goals and constraints. We typify our approach using the specific context of diesel engine manufacturing and remanufacturing. Our model constructs are based on detailed interviews with top managers from two leading competitors in the medium and heavy‐duty diesel engine industry. The approach allows the incorporation of traditional operations‐planning considerations—in particular, capacity, production, and inventory—together with environmental considerations that range from product design through production to product end of life. A current hurdle to implementing such a model is the availability of input data. We therefore highlight the need not only to involve all departments within businesses but also for industrial ecologists and business managers to work together to implement meaningful decision models that are based on accurate and timely data and can have positive economic and environmental impact.     

Environmental Performance Analysis of Eco‐Industrial Parks in China: A Data Envelopment Analysis Approach

In pursuit of more sustainable development of industry, China has been actively developing eco‐industrial parks (EIPs) for more than a decade. However, the environmental value of these EIPs remains largely unverified. This study aimed to evaluate the environmental performance of national EIPs in China using data envelopment analysis. Eco‐efficiency and environmental performance indices were used to represent the static and dynamic environmental performance of EIPs, respectively. An environmental performance index was formed by combining measures of eco‐efficiency in a dynamic setting with the sequential Malmquist index approach. We obtained three main empirical findings. First, 34 national EIPs exhibited a cumulative environmental performance improvement of 89.4% from 2007 to 2010, which is primarily the result of eco‐efficiency change rather than environmental technical change. Second, compared with the trial EIPs, the demonstration EIPs had a higher average eco‐efficiency (0.611 vs. 0.446 in 2010) and experienced greater average environmental performance improvement (129% vs. 60%). Third, the EIPs retrofitted from high‐tech industrial development zones exhibited much higher average eco‐efficiency (0.798 vs. 0.440 in 2010) than those retrofitted from economic and technical development zones. The key measures supporting the performance improvement and policy implications for the development of EIPs are also discussed.     

The Influence of State‐Ownership on Eco‐Innovations in Russian Manufacturing Firms

This paper studies drivers for eco‐innovation in Russian manufacturing firms on a sample of 2,212 innovative firms, of which over 600 introduced eco‐innovations. The companies in our sample specifically mention environmental regulation as a reason for engaging in eco‐innovations. Furthermore, we show that those firms who engage in eco‐innovations are motivated even stronger by the desire to increase resource efficiency. Companies under state ownership are especially prone to a higher likelihood to invest. We conclude that regulations are mostly relevant to the late comers who are obliged to follow minimum standards. On the other hand, the state uses its controlling influence to press companies under their control to exceed these minimum standards. Thus, we argue, state ownership does indeed have an influence on both the likelihood to eco‐innovate and on the levels of spending. Eco‐innovative state‐owned companies are only prone to invest in eco‐innovations, if they get additional money.     

Eco‐evolutionary partitioning metrics: assessing the importance of ecological and evolutionary contributions to population and community change

Interest in eco‐evolutionary dynamics is rapidly increasing thanks to ground‐breaking research indicating that evolution can occur rapidly and can alter the outcome of ecological processes. A key challenge in this sub‐discipline is establishing how important the contribution of evolutionary and ecological processes and their interactions are to observed shifts in population and community characteristics. Although a variety of metrics to separate and quantify the effects of evolutionary and ecological contributions to observed trait changes have been used, they often allocate fractions of observed changes to ecology and evolution in different ways. We used a mathematical and numerical comparison of two commonly used frameworks – the Price equation and reaction norms – to reveal that the Price equation cannot partition genetic from non‐genetic trait change within lineages, whereas the reaction norm approach cannot partition among‐ from within‐lineage trait change. We developed a new metric that combines the strengths of both Price‐based and reaction norm metrics, extended all metrics to analyse community change and also incorporated extinction and colonisation of species in these metrics. Depending on whether our new metric is applied to populations or communities, it can correctly separate intraspecific, interspecific, evolutionary, non‐evolutionary and interacting eco‐evolutionary contributions to trait change.     

Renewable Eco‐industrial Development

This article reviews the scope of the discipline of industrial ecology and, in the context of an urgent requirement for substantial and rapid change in the face of global sustainability challenges, argues that the discipline could embrace a more proactive, interventionist stance in the form of renewable eco‐industrial development. Existing eco‐industrialism is presented as flawed, with many cases premised on the use of nonrenewable resources. Renewable eco‐industrial development, while still nascent, has the potential both to resolve some sustainability challenges and to offer a new area of endeavor for industrial ecology, albeit one with its own unique difficulties, such as conflict with food production. Renewable eco‐industrial development is further argued to bring industrial ecology into a more socially critical stance as it concerns the future allocation of scarce resources.     

Industrial Ecosystems and Food Webs: An Expansion and Update of Existing Data for Eco‐Industrial Parks and Understanding the Ecological Food Webs They Wish to Mimic

Cyclical industrial networks are becoming highly desirable for their efficient use of resources and capital. Progress toward this ideal can be enhanced by mimicking the structure of naturally sustainable ecological food webs (FWs). The structures of cyclic industrial networks, sometimes known as eco‐industrial parks (EIPs), are compared to FWs using a variety of important structural ecological parameters. This comparison uses a comprehensive data set of 144 FWs that provides a more ecologically correct understanding of how FWs are organized than previous efforts. In conjunction, an expanded data set of 48 EIPs gives new insights into similarities and differences between the two network types. The new information shows that, at best, current EIPs are most similar to those FWs that lack the components that create a biologically desirable cyclical structure. We propose that FWs collected from 1993 onward should be used in comparisons with EIPs, given that these networks are much more likely to include important network functions that directly affect the structure. We also propose that the metrics used in an ecological analysis of EIPs be calculated from an FW matrix, as opposed to a community matrix, which, to this point, has been widely used. These new insights into the design of ecologically inspired industrial networks clarify the path toward superior material and energy cycling for environmental and financial success.     

Consequential Life Cycle Assessment of Policy Vulnerability to Price Effects

The application of life cycle assessment (LCA) in a policy context highlights the need for a “consequential” LCA (CLCA), which differs from an “attributional” LCA (ALCA). Although CLCA offers some advantages over ALCA, such as a capacity to account for emissions resulting from both substitution and price effects, it entails additional assumptions and cost and may yield estimates that are more uncertain (e.g., estimates of impact of biofuel policies on greenhouse gas [GHG] emissions). We illustrate how a CLCA that relies on simple partial equilibrium models could provide important insights on the direction and magnitude of price effects while limiting the complexity of CLCA. We describe how such a CLCA, when applied early in the policy life cycle, could help identify policy formulations that reduce the magnitude of adverse price effects relative to the beneficial substitution effect on emissions because—as the experience with biofuel regulations indicates—regulating price effects is costly and controversial. We conclude that the salient contribution of CLCA in the policy process might lie in warning policy makers about the vulnerabilities in a policy with regard to environmental impact and to help modify potentially counterproductive formulations rather than in deriving the precise estimates for uncertain variables, such as the life cycle GHG intensity of product or average indirect emissions.     

Measuring and Improving Eco‐efficiency Using Data Envelopment Analysis

The concept of eco‐efficiency can be defined with the “product value/environmental influence” ratio. Different models have been proposed to measure eco‐efficiency. The main difference among them is the weighting system used to aggregate the environmental results. Data envelopment analysis (DEA) permits this aggregation without requiring a subjective judgment about the weights. In this study, we applied a DEA model to Spanish Mahón‐Menorca cheese production to determine the most eco‐efficient production techniques. To this end, 16 scenarios of Mahón‐Menorca cheese production were built regarding technical (degree of automation) and cleaner production criteria. The environmental impacts were assessed by means of life cycle assessment. We carried out an economic assessment by determining the economic value added and the net income for each scenario. The results are referred to as 1 kilogram (kg) cheese ripened over 105 days. Through DEA, an eco‐efficiency ratio between 0 and 1 was obtained. Three scenarios were found to be eco‐efficient, with a high degree of automation (enclosed vat and molding and demolding machines) and accelerated cheese ripening. We used Monte Carlo simulation to carry out a sensitivity analysis to compare the influence of price changes on the eco‐efficiency ratio. The results emphasize the consistency and stability of the eco‐efficient scenarios.     

Ecological Footprint Policy? Land Use as an Environmental Indicator

This article argues that policies aimed at sustainability need to address the spatial dimensions of environmental problems and their solutions. In particular, spatial configurations of economic activities deserve attention, which means addressing land use, infrastructure, trade, and transport. Unfortunately, good theory and indicators to support the analysis and design of spatial‐environmental policies are not fully developed. One approach that has become very popular in the last decade is the ecological footprint (EF). It is both an environmental accounting tool and aggregate indicator, which is used by scientists, environmental organizations, and popular media. Despite criticisms of the EF method in the past, its popularity has only increased. In fact, an increasing number of publications with an application of the EF appear in scientific journals. We review the EF approach from indicator‐methodology and welfare angles and assess its policy relevance. Our conclusion is that it does not offer any meaningful information for public policy.     

Framework for Applying a Complex Adaptive System Approach to Model the Operation of Eco‐Industrial Parks

Models of eco‐industrial parks (EIPs) might help us transform our production systems by fostering the emergence of sustainable EIPs since such models have the potential to support the decision‐making processes of cooperative companies that participate and to decrease operational uncertainties. In this article, a conceptual framework for modeling the operation of EIPs is presented. The framework is underpinned by complex adaptive systems theory, industrial ecology, and an analysis of the experiences of existing EIPs. The proposed framework draws on the observed strengths of two types of industrial symbiosis models—planned eco‐industrial parks (PEIPs) and EIPs that developed through self‐organizing symbiosis (SOS)—as well as their observed weaknesses and the features of complex adaptive systems. From this analysis, five key properties to be modeled are deduced: functionality, reliability, life span, theoretical knowledge, and adaptability. It is proposed that the properties of functionality and theoretical knowledge are determined by the goals of the EIP and its member companies, while the property of adaptability is determined by the understanding that the companies in an EIP have of the environment surrounding the EIP, while the properties of reliability and life span are determined by the internal and external relationships of the companies that make up an EIP.     

Scaling‐Up of Industrial Symbiosis in the Korean National Eco‐Industrial Park Program: Examining Its Evolution over the 10 Years between 2005–2014

In 2005, South Korea initiated the 15‐year National Eco‐Industrial Park Development Program in three stages to gradually transform aged industrial complexes into eco‐industrial parks (EIPs) by promoting industrial symbiosis (IS). Building upon the pilot experiences from the first 5 years, the second phase of the program focused on the scaling‐up of IS at a broader regional level. Key scaling‐up strategies included the expansion of target areas by connecting multiple industrial complexes, the standardization of processes and dissemination of learning, and the development of large‐scale projects that could contribute to the regional development. In this study, we examined the evolution of IS over the last 10 years between 2005 and 2014, primarily to understand the characteristics and impact of these scaling‐up strategies. Our findings showed that the scale of IS in the second phase had increased in various aspects in comparison to that in the first phase. The number of operating projects had increased from 52 to 159, the number of participating firms increased from 90 to 596, and the average distance of IS increased from 40 to 48 kilometers. The size of economic and environmental benefits also increased along with an increase in the private investment and government research funding. We further analyzed the role of the regional EIP centers as facilitators, how their activities influenced the scaling‐up of IS, and discussed the characteristics of the Korea's approach to IS.     

Mars, Materials, and Three Morality Plays: Materials Flows and Environmental Policy

Although industrial ecology represents a captivating metaphor and rich repertoire of analytical tools, its impact on environmental policy has been marginal at best. This article examines the insights provided by the studies of three common materials in the US. economy-lead, arsenic, and silver-and the abilrty of such studies to illuminate some larger and looming challenges for future environmental policy. Three specific challenges are explored: the flow of materials across national borders, the increasing embodiment of emissions in products, and the dangers of unchallenged assumptions about the drivers of material flows. The article argues that industrial ecology can inform public policy but that it is time for the practitioners of industrial ecology, an applied science, to apply it in the often messy world of environmental policymaking.     

Using Attributional Life Cycle Assessment to Estimate Climate‐Change Mitigation Benefits Misleads Policy Makers

Life cycle assessment (LCA) is generally described as a tool for environmental decision making. Results from attributional LCA (ALCA), the most commonly used LCA method, often are presented in a way that suggests that policy decisions based on these results will yield the quantitative benefits estimated by ALCA. For example, ALCAs of biofuels are routinely used to suggest that the implementation of one alternative (say, a biofuel) will cause an X% change in greenhouse gas emissions, compared with a baseline (typically gasoline). However, because of several simplifications inherent in ALCA, the method, in fact, is not predictive of real‐world impacts on climate change, and hence the usual quantitative interpretation of ALCA results is not valid. A conceptually superior approach, consequential LCA (CLCA), avoids many of the limitations of ALCA, but because it is meant to model actual changes in the real world, CLCA results are scenario dependent and uncertain. These limitations mean that even the best practical CLCAs cannot produce definitive quantitative estimates of actual environmental outcomes. Both forms of LCA, however, can yield valuable insights about potential environmental effects, and CLCA can support robust decision making. By openly recognizing the limitations and understanding the appropriate uses of LCA as discussed here, practitioners and researchers can help policy makers implement policies that are less likely to have perverse effects and more likely to lead to effective environmental policies, including climate mitigation strategies.