Search results

In this paper, we discuss methods to integrate ecological resources, ecosystem services, risk, and the transition to long-term stewardship on Department of Energy lands. Three types of information are required about ecological resources before decisions can be made about remediation, site transitions, and long-term stewardship: (1) the ecological resources and ecosystem functions (such as productivity) present on site and their spatial pattern, (2) the ecosystem services these resources provide to people, and (3) the risks from the interactions between people and these ecosystems. Once the ecological resources and ecosystem services are evaluated, then decisions about future land use, preservation, conservation, or protection of ecological resources within a designated land use can be implemented. Long-term stewardship requires both ecosystem protection in terms of biological resources and ecosystem function as well as biomonitoring to ensure minimal radiological or chemical risk and to inform future management. In some cases, protection of ecological resources may be preferable to cleanup that is physically disruptive, provided land use designation is consistent with ecological protection. In such instances, less site cleanup can prove preferable to more.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

With the macroprudential approach, systemic risk is explained by a general equilibrium (GE) model. However, since on-balance-sheet and off-balance-sheet (OBS) risks are structurally segmented, for example annually or periodically on financial statements, the GE model might need further integration with OBS risks including ecological shocks.

This study develops a theoretical two-period model with consumption, investment and loans, which further includes carbon emissions to distinguish between loans for “green” or “brown” firms to enhance the perspective of ecological sustainability.

The paper shows how the environmental, social and governance (ESG) factors might be of relevance in the standard bank capital regulatory structure. In dealing with ecological sustainability, a new methodological framework with the green K-index introduces penalties to be paid in the capital structure related to ESG factors. The model is enhanced for screening green or brown firms related to impact investing. The integrated view of financial stability and ecological sustainability further illuminates how a wide cross-sectoral resilience of a green K-index measure for the economy might be achievable.

A stock-flow consistent model with balance-sheet methods raises the question whether all necessary variables and parameters can be computed in practice. Compared to the agent-based model (ABM), this model additionally lacks inputs from agents' behaviour, thus non-rational decisions, which may be relevant in practice. More generally, by adopting a balance-sheet structure, the model shows a coherent framework with relevant variables. The methodology of the GE model with OBS has not been scholarly explored and thus is presented for discussion rather than generalisation. The GE model with OBS provides a new interpretation of systemic risk and interbank relations with a consideration of ecological aspects. Its economic implication contributes to contemporary banking theory as well as to the sustainability discussions in the larger financial sector.

Banks and investors can more carefully measure the ecological risks in their loan portfolios and make better informed decisions leading to a better sustainability of the financial markets.

This study develops a theoretical GE model with off-balance-sheet risks. The model adds green regulation enhancing the capital regulation framework relevant to sustainability. This, in turn, enhances the role of banks in a coherent economic framework for loan decisions towards a much greener finance.

This study aims to acquire a better understanding on the characteristics and risks of heavy metals (HMs) in PM_2.5 from an industrial city – Handan, China.

PM_2.5 samples were collected on the basis of daytime and nighttime at the state controlling air sampling site in Handan city. Ten metal elements (V, Cr, Mn, Fe, Ni, Cu, Rb, Sr, Cd and Ba) in PM_2.5 were determined with an inductively coupled plasma mass spectrometry. The pollution levels of metals were characterized by enrichment factors, and the sources of metals were identified with principle component analysis and cluster analysis. The ecological and health risks of metals were assessed using ecological and health risk indexes.

Results showed that the highest and lowest PM_2.5 concentration appeared in winter and summer, respectively. The concentration of PM_2.5 at night was higher than in the daytime in winter, yet it is the opposite in other seasons. The total mass concentration of detected metals was the highest in winter, and the total mass concentration in the daytime was higher than at night in all four seasons. The elements V, Rb, Sr and Ba exhibited a deficient contamination level; Cr, Ni and Cu exhibited a moderate contamination level; while Fe and Cd were at an extreme contamination level. The metals in PM_2.5 originated from a mixture source of fossil fuel combustion and manufacture and use of metallic substances (34.04%), natural source (26.01%) and construction and traffic-related road dust (17.58%). Results from the ecological risk model showed that the ecological risk of metals was very high, especially risks related to Cd. Health risk model presented that both the non-carcinogenic and carcinogenic risk coefficients of metals were above the tolerance level of the human body.

The significance of the study is to further know the pollution characteristics of PM_2.5 and related HMs in Handan city, and to provide references for ensuring local resident health and ecological environment.

This chapter presents research and analysis on the Institute for Economics and Peace’s (IEP’s) index in the Ecological Threat Report (ETR). In the analysis, 178 countries are examined at the sub-national level, accounting for 99.9% of the global population. The estimate consists of five indicators that aggregate to yield an index of ecological threats. These five indicators are water risk, the prevalence of stunting, the impact of natural disasters, projected population growth and projected temperature rise. The ETR is a tool that can be used to identify the countries that are at the highest risk of ecological threats. The index identifies that 30 countries facing the highest level of ecological threats as well as low levels of resilience are home to 1.26 billion people. At the end of 2020, in these 30 countries, 68% of the total people were forcibly displaced beyond their borders. As these 30 countries suffer collectively from the highest ecological threats and without the reversal of ecological degradation, displacement is very likely to continue. Without urgent development, ecological threats will continue to create humanitarian emergencies and will likely increase without a sustained effort to reverse the current trend.

In psychological testing, the term ‘ecological validity’ (EV) refers to the degree to which a test assesses (or estimates) via a proxy task a person's ability to do a ‘real‐life’ task. While EV has been a critical evaluative component of some areas of psychological testing, it has not featured to date as important in the area of risk assessment. If the goal of risk assessment is to enhance risk management, then this is a critical oversight. It would appear that all forms of risk assessment measures are lacking EV. EV is important because risk management occurs in the community. The ARMIDILO is mentioned as an instrument that has attempted to include environmental variables to enhance EV and thus facilitate the risk manageability of ID sex offenders. It is proposed that the EV of other risk measures could be enhanced by the inclusion of similar environmental variables.

This paper seeks to discuss technology transfer – and its role in climate change mitigation – within the United Nations framework of sustainable development. Innovation is broadly considered as a tool to bring about breakthrough results in climate change alleviation. To ensure that innovative technology serves sustainable development, a massive international effort on the part of the regulators is required to create an integrated legislative framework to standardize eco‐innovation policies worldwide. To facilitate a global ecological regulatory framework, it is essential to use universal measurement tools which provide input to the decision‐making process at an international level, and address the mechanism of monitoring progress.

The concept of eco‐innovation potential is introduced as one of the inputs to the decision‐making process on the global level. A composite index with such constituents as ecological balance (deficit or reserve), innovation, and energy intensity of economy, is built. The concept of innovation credits is introduced.

The simulation shows that ecological balance can potentially be increased for countries with greater eco‐innovation potential. The innovation credits can be given to countries with the highest eco‐innovation potential to foster eco‐innovation and perform technology transfer.

Earlier research developed focus on innovation as a means to transition to sustainable development and to create climate positive technological regimes applied at a national or industry level. The paper illustrates that the eco‐innovation potential index can be applied globally and can provide key input to the decision‐making process at a global level.

This paper aims to concentrate on classifying and analyzing the risks associated with the Industry 4.0 (I4.0) concept in manufacturing industries and developing strategies for managing risks.

In this research paper, risks categories and their sub-components associated with the I4.0 concept are identified by performing a systematic literature survey of peer-reviewed journal articles and taking inputs from industry experts and academicians. Then, the importance of the identified risks and causal relations among risks are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Finally, the strategies are developed to mitigate the identified risks.

From the literature survey, 6 risk categories and their 19 sub-components associated with the I4.0 concept are identified. The DEMATEL method resulted in economic risks and technical risks as the top two risk categories in the I4.0 concept. Ecological risks and legal and political risks are relatively low-ranked risk categories.

Causal relations and ranking among risk categories and their sub-components are obtained by analyzing responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

This research paper will help the industrialists to effectively manage the risks involved in adopting I4.0 concept in manufacturing industries by adopting strategies.

This research paper gives an idea about risks associated with the implementation of the I4.0 concept in manufacturing industries. Also, this paper uses the DEMATEL method for ranking the identified risk categories and their sub-components.

Environmental behavior studies suggest that knowledge, in addition to other psychological and social factors, can play an important role in consumers’ environmental behavior change. The purpose of this paper is to understand the relationship between knowledge and various psychological factors which encourage consumers’ participation in pro-environmental behaviors. The relationships that link an individual’s attitudes toward science, environmental values, different types of knowledge (i.e. scientific facts, environmental facts, and subjective environmental knowledge), environmental risk perception, and willingness to pay (WTP) for the environment with pro-environmental behavior were examined.

Theoretically guided hypotheses and model were formulated and tested with multiple linear regression models. The study was based on measures and data obtained from the large-sample secondary database of the 2010 General Social Survey (n=2,044).

Results indicated that while attitudes toward science had direct effects on knowledge of scientific facts and knowledge of environmental facts, environmental values showed effects on knowledge of environmental facts and subjective knowledge on environmental issues. The results also indicated that from different types of knowledge, subjective knowledge on environmental issues had effects on both environmental risk perception and WTP for the environment. Knowledge on environmental facts, on the other hand, was able to predict only environmental risk perception. The scientific factual knowledge did not show an effect on mediator of pro-environmental behavior. Also, subjective knowledge indicated indirect effects on pro-environmental behavior through environmental risk perception and WTP for the environment.

Although research on understanding factors influencing pro-environmental behaviors and potential relations to individual knowledge has grown in recent years, there has been very little attempt at distinguishing between different types of knowledge and investigating their potential roles in the context of environmentally relevant behaviors. This study will help understand the functioning of different types of consumer environmental knowledge and their impacts on pro-environmental behaviors more in depth.