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The purpose of this paper is to identify knowledge gaps on insinuations of possible directions of European Union (EU) and international climate policies.

This study has used participatory approach of highly experienced stakeholders’ engagement, involved directly or indirectly in the process of policymaking. A range of priority issues has been initially identified through desk analysis and key stakeholders have been selected and invited to partake in the process. Preliminary results have been validated through interaction with stakeholders during a series of workshops.

The results show the identification of a series of sectors, where climate policy is expected to focus in the future and the definition of 11 specific topics upon which knowledge gaps are expected to appear. Results on the identified knowledge needs are analysed and categorized by each prioritized main topic and compared with literature findings. Emphasis is identified to be placed on the topics of renewable energy, EU climate policy and international climate negotiations, which are the most popular ones, followed by energy policy and energy efficiency.

A key element of the approach is the consideration of key experts’ feedback on their specific area of expertise, instead of general public engagement, therefore leading to accurate results. Despite the fact that our approach was applied to a specific problem, the overall analysis could provide a framework for supporting applications in various problems in the field of priorities’ identification and even expanding to decision-making problems.

The aggregate index and per capita index have different meanings for some countries or regions. CO₂ emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO₂ emissions per capita. In this study, mathematical formulas will be derived and verified.

First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.

The CO₂ emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO₂ decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO₂ emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO₂ emission intensity target and economic growth target, the growth rate of per capita CO₂ emissions must fall within the range of [−0.92%, 6.1%].

Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.

Most countries face important economic, social and environmental challenges and are strongly committed to invest in research and development (R&D) activities to help support the long-run economic sustainable growth. This paper aims to extend the previous research on macro-economic growth models and introduces endogenous variables to determine the amount of investments in R&D activities.

The model considers four different criteria and six economic sectors and aims at finding the optimal allocation of labor across different sectors. The model also endogenously determines the amount of investments in pollution abatement activities together with energy-related R&D efforts. The paper presents an application to the case of Kazakhstan, an emerging Asian country, that aims to become one of the top 30 most developed countries in the world by 2050.

The model shows the limits of the Kazakh agenda that identified too ambitious goals as the country has to go through a sociotechnical transition that involves a range of modifications in institutional structures, together with changes in user practices and the technological dimension. Kazakhstan should invest more in R&D activities able to develop sustainable energy sources to face the current electricity consumption demand and to reduce the greenhouse gas emission in the future.

The paper provides valuable knowledge for researchers and policy makers interested in the impact of R&D on the long-run economic sustainable growth.

The study examines the social and environmental responsibility indicators disclosed by three International Council on Mining and Metals (ICMM) corporate mining members in their social and environmental reporting (SER) from 2006 to 2014. To achieve this aim, the author limits the data two years before (i.e. from 2006 to 2007) and six years after (i.e. from 2009 to 2014) the implementation of the Sustainable Development Framework in the mining sector in 2008.

Using the techniques of content analysis and interpretive textual analysis, this study examines 27 social and environmental responsibility reports published between 2006 and 2014 by three ICMM corporate mining members. The study develops a disclosure index based on the earlier work of Hackston and Milne (1996), together with other disclosure items suggested in the extant literature and considered appropriate for this work. The disclosure index for this study comprised six disclosure categories (“employee”, “environment”, “community involvement”, “energy”, “governance” and “general”). In each of the six disclosure categories, only 10 disclosure items were chosen and that results in 60 disclosure items.

A total of 830 out of a maximum of 1,620 social and environmental responsibility indicators, representing 51% (168 employees, 151 environmental, 145 community involvement, 128 energy, 127 governance and 111 general) were identified and examined in company SER. The study showed that the sample companies relied on multiple strategies for managing pragmatic legitimacy and moral legitimacy via disclosures. Such practices raise questions regarding company-specific disclosure policies and their possible links to the quality/quantity of their disclosures. The findings suggest that managers of mining companies may opt for “cherry-picking” and/or capitalise on events for reporting purposes as well as refocus on company-specific issues of priority in their disclosures. While such practices may appear appropriate and/or timely to meet stakeholders’ needs and interests, they may work against the development of comprehensive reports due to the multiple strategies adopted to manage pragmatic and moral legitimacy.

A limitation of this research is that the author relied on self-reported corporate disclosures, as opposed to verifying the activities associated with the claims by the sample mining companies.

The findings from this research will help future social and environmental accounting researchers to operationalise Suchman’s typology of legitimacy in other contexts.

With growing large-scale mining activity, potential social and environmental footprints are obviously far from being socially acceptable. Powerful and legitimacy-conferring stakeholders are likely to disapprove such mining activity and reconsider their support, which may threaten the survival of the mining company and also create a legitimacy threat for the whole mining industry.

This study innovates by focusing on Suchman’s (1995) typology of legitimacy framework to interpret SER in an industry characterised by potential social and environmental footprints – the mining industry.

The study aims to fill a gap in the literature on the economic impact of industrial and international diversification on firm performance in the energy sector. Li et al. (2016) investigate firms listed in China, and this study analyzes firms listed in (Western) Europe.

A sample of 129 energy firms is extracted from Datastream and covers the period from January 2009 to December 2015. Univariate and multivariate regression analyses are used to determine a plausible relation of diversification on corporate performance. Also, the difference between renewable energy firms and conventional energy firms is explored.

A univariate analysis using both return on assets and Tobin's Q as a variable shows that renewable energy firms have a higher profitability than conventional energy firms. However, a multivariate analysis does not confirm this result. The authors also document a negative relation between diversification strategies and firm performance.

The study uses main industry codes. Yet, one might make a distinction between renewable energy and conventional energy amounts with corporations. Also, the authors cover financial crisis years. Researchers might take into account more recent years.

The findings of the study highlight the importance of short-term and long-term considerations for practitioners related to demand, the energy mix, oil prices and firm strategies.

The authors contribute to the debate and the literature when identifying similarities and differences between conventional energy firms and renewable energy firms in their application of diversification strategies and their (relation to) firm performance.

Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.

The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.

There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.

The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.

The decarbonization of power generation is key to achieving carbon neutrality in China by the end of 2060. This paper aims to examine how green finance influences China’s low-carbon transition of power generation. Using a provincial panel data set as an empirical study example, green finance is assessed first, then empirically analyses the influences of green finance on the low-carbon transition of power generation, as well as intermediary mechanisms at play. Finally, this paper makes relevant recommendations for peak carbon and carbon neutrality in China.

To begin with, an evaluation index system with five indicators is constructed with entropy weighting method. Second, this paper uses the share of coal-fired power generation that takes in total power generation as an inverse indicator to measure the low-carbon transition in power generation. Finally, the authors perform generalized method of moments (GMM) econometric model to examine how green finance influences China’s low-carbon transition of power generation by taking advantage of 30 provincial panel data sets, spanning the period of 2007–2019. Meanwhile, the implementation of the 2016 Guidance on Green Finance is used as a turning point to address endogeneity using difference-in-difference method (DID).

The prosperity of green finance can markedly reduce the share of thermal power generation in total electricity generation, which implies a trend toward China’s low-carbon transformation in the power generation industry. Urbanization and R&D investment are driving forces influencing low-carbon transition, while economic development hinders the low-carbon transition. The conclusions remain robust after a series of tests such as the DID method, instrumental variable method and replacement indicators. Notably, the results of the mechanism analysis suggest that green finance contributes to low-carbon transformation in power generation by reducing secondary sectoral share, reducing the production of export products, promoting the advancement of green technologies and expanding the proportion of new installed capacity of renewable energy.

This paper puts forward relevant suggestions for promoting the green finance development with countermeasures such as allowing low interest rate for renewable energy power generation, facilitating market function and using carbon trade market. Additional policy implication is to promote high quality urbanization and increase R&D investment while pursuing high quality economic development. The last implication is to develop mechanism to strengthen the transformation of industrial structure, to promote high quality trade from high carbon manufactured products to low-carbon products, to stimulate more investment in green technology innovation and to accelerate the greening of installed structure in power generation industry.

This paper first attempts to examine the low-carbon transition in power generation from a new perspective of green finance. Second, this paper analyses the mechanism through several aspects: the share of secondary industry, the output of exported products, advances in green technology and the share of renewable energy in new installed capacity, which has not yet been done. Finally, this study constructs a system of indicators to evaluate green finance, including five indicators with entropy weighting method. In conclusion, this paper provides scientific references for sustainable development in China, and meanwhile for other developing countries with similar characteristics.

The purpose of this paper is to investigate the functionality and effectiveness of the Carbon Risk Real Estate Monitor (CRREM tool). The aim of the project, supported by the European Union’s Horizon 2020 research and innovation program, was to develop a broadly accepted tool that provides investors and other stakeholders with a sound basis for the assessment of stranding risks.

The tool calculates the annual carbon emissions (baseline emissions) of a given asset or portfolio and assesses the stranding risks, by making use of science-based decarbonisation pathways. To account for ongoing climate change, the tool considers the effects of grid decarbonisation, as well as the development of heating and cooling-degree days.

The paper provides property-specific carbon emission pathways, as well as valuable insight into state-of-the-art carbon risk assessment and management measures and thereby paves the way towards a low-carbon building stock. Further selected risk indicators at the asset (e.g. costs of greenhouse gas emissions) and aggregated levels (e.g. Carbon Value at Risk) are considered.

The approach described in this paper can serve as a model for the realisation of an enhanced tool with respect to other countries, leading to a globally applicable instrument for assessing stranding risks in the commercial real estate sector.

The real estate industry is endangered by the downside risks of climate change, leading to potential monetary losses and write-downs. Accordingly, this approach enables stakeholders to assess the exposure of their assets to stranding risks, based on energy and emission data.

The CRREM tool reduces investor uncertainty and offers a viable basis for investment decision-making with regard to stranding risks and retrofit planning.

The approach pioneers a way to provide investors with a profound stranding risk assessment based on science-based decarbonisation pathways.

The purpose of this paper is to investigate the role of distinct types of heating technology and their price impact in German residential real estate markets, considering a wide range of other housing market determinants. The authors aim to test and to verify specifically, whether the obsolescence of heating technology leads to a significant price discount and whether higher technological standards (and environmental friendliness) come with a price premium on the market.

The authors create housing market models for rental and sales segments by constructing generalized additive models with explicit multi-layered spatial components. To elaborate a profound and contemporary answer using these models, the authors perform large-sample regression analyses based on more than 400,000 observations covering German residential properties in 2015.

First and foremost, the heating system indeed shows significant explanatory importance for measuring housing rents and purchasing price. Second, the authors find that it makes a difference whether clean “green” technologies are implemented or whether “brown” systems with obsolete technology or fossil energy sources is on hand. Ultimately, the authors conclude that while low energy consumption indeed comes with a price premium, this needs to be interpreted together with the property’s heating type, as housing markets seem to outweigh the “green premium” by “brown discounts” if low energy consumption figures are powered by a certain type of heating technology system.

Aside of a possible omitted variable bias, the main research limitation is constituted by the integration of asking prices in the analysis, as actual transaction prices are not systematically transparent on national level in Germany. Limitations are discussed at the end of the paper.

This work supports investors who face the challenge of making environmental- and energy-related decisions as well as appraisers who deliver financial fundamentals for such. Third, the paper supports both asset managers as well as investment strategists in argumentation pro-environmental investments beyond all ecological necessity.

This paper contributes to the current discussion on climate change and the eclectic role of real estate in this context. The authors deliver evidence on pricing effects as a measure of socioeconomic acceptance of progressive heating technology and environmental friendliness as an imperative of twenty-first century societies.

This is the first study on “green premiums” or “brown discounts” that includes heating technology as a potential and distinct driver of value and rents. It is a contemporary contribution and delivers original information on the quantitative impact of contemporary and anachronistic technology in heating to researchers as well as investors and appraisers.

This paper aims to forecast the availability of used but operational electric vehicle (EV) batteries to integrate them into a circular economy concept of EVs' end-of-life (EOL) phase. Since EVs currently on the roads will become obsolete after 2030, this study focuses on the 2030–2040 period and links future renewable electricity production with the potential for storing it into used EVs' batteries. Even though battery capacity decreases by 80% or less, these batteries will remain operational and can still be seen as a valuable solution for storing peaks of renewable energy production beyond EV EOL.

Storing renewable electricity is gaining as much attention as increasing its production and share. However, storing it in new batteries can be expensive as well as material and energy-intensive; therefore, existing capacities should be considered. The use of battery electric vehicles (BEVs) is among the most exciting concepts on how to achieve it. Since reduced battery capacity decreases car manufacturers' interest in battery reuse and recycling is environmentally hazardous, these batteries should be integrated into the future electricity storage system. Extending the life cycle of batteries from EVs beyond the EV's life cycle is identified as a potential solution for both BEVEOL and electricity storage.

Results revealed a rise of photovoltaic (PV) solar power plants and an increasing number of EVs EOL that will have to be considered. It was forecasted that 6.27–7.22% of electricity from PV systems in scenario A (if EV lifetime is predicted to be 20 years) and 18.82–21.68% of electricity from PV systems in scenario B (if EV lifetime is predicted to be 20 years) could be stored in batteries. Storing electricity in EV batteries beyond EV EOL would significantly decrease the need for raw materials, increase energy system and EV sustainability performance simultaneously and enable leaner and more efficient electricity production and distribution network.

Storing electricity in used batteries would significantly decrease the need for primary materials as well as optimizing lean and efficient electricity production network.

Energy storage is one of the priorities of energy companies but can be expensive as well as material and energy-intensive. The use of BEV is among the most interesting concepts on how to achieve it, but they are considered only when in the use phase as vehicle to grid (V2G) concept. Because reduced battery capacity decreases the interest of car manufacturers to reuse batteries and recycling is environmentally risky, these batteries should be used for storing, especially renewable electricity peaks. Extending the life cycle of batteries beyond the EV's life cycle is identified as a potential solution for both BEV EOL and energy system sustainability, enabling more efficient energy management performance. The idea itself along with forecasting its potential is the main novelty of this paper.