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The objective of the study is to analyse what and how researchers are covering sustainable low carbon recovery pathways in the post-COVID 19 scenario across various content categories. The unit or categories of content for thematic analysis taken under study includes a total of 121 content published within the year 2020-22. The study also assesses the focus and frames of research on sustainable low carbon recovery being conducted from 2020 to 2022 in order to gain a better understanding of the issues and best practises in global economies. For more valid results, the research design seeks novelty by concluding the qualitative and quantitative methodologies with statistical analysis of identified themes using thematic analysis. The data is analysed using Kruskal Wallis Test. The analysis shows that researchers are concerned about carbon emission and its impact on countries, sectors, industries, over the globe and are more inclined towards studying the impact of carbon emission, issues, and challenges posed in sustainable low carbon recovery pathways and measures. The studies also suggest the role of the public and policy in the recovery process with a focus on energy sector. The studies are primarily concerned with carbon emissions and green recovery measures for future sustainable development.
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Under the pressure of economic uncertainty and environmental protection in the post-COVID-19 era, achieving a new round of employment dividends has become one practical choice. Using the panel data of 30 Chinese provinces from 2007 to 2019, this study estimates the employment outcomes of carbon ETS pilots based on the difference-in-differences model. The findings of this study indicate the following: (1) Carbon ETS pilots can positively increase employment scales with an average effect of 7.12%. (2) This promoting effect will become more significant in provinces with high education levels, provinces with high average wages, and eastern region provinces. But there is no obvious difference between gender. (3) This positive effect can be transferred and enhanced by market competition and energy consumption. At the crossroads of green economic recovery, it will be greatly beneficial to formulate the national carbon market development roadmap under the carbon neutrality strategy.
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The COVID-19 outbreak has posed significant challenges to the worldwide supply chain. As result, there is an urgent need to develop a model for the manufacturer that includes multi-phase manufacturing with fluctuating demand during various levels of pandemic and a supply system that takes into account the environmental benefits of the product and production. This study recommends inventory model to the company for estimating optimal production amount and replenishment cycle in order to reduce overall cost and maximize profit along with green product pricing and carbon tax. The current study considers models with and without shortages for instantaneously deteriorating commodities. Because of the social awareness concern, firms can avoid the suffering from labor shortage during the pandemic crisis. Numerical examples are given to demonstrate the model's use. A sensitivity analysis of crucial factors was performed in order to uncover more sensitive parameters that offer a clear portrayal of current concerns. [ FROM AUTHOR] Copyright of Journal of Industrial & Production Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Resources management in the modern era is a crucial perspective of a sustainable environment linked with sustainable development. Therefore, it is crucial to re-estimate the resources-environment management nexus in a new setting. Concerning environmental management from the COP27 perspective, economies are taking various economic, financial, and environmental steps to reduce hazardous emissions in the region. Recently, BRICS economies have invested in renewables and enhanced capital formation to accelerate environmental recovery. In this respect, this study tends to examine the influence of electricity from renewable resources (ELREC), resources management (resources rents), research and development (RDEV) and gross fixed capital formation (GFCF) on carbon emissions of the BRICS economies throughout 1989-2021. Using various diagnostic tests, this study confirms the long-run equilibrium association between the variables. This study uses non-parametric estimation approaches and concludes that ELREC and RDEV significantly enhance environmental sustainability. Except for forest and oil resources, the rest of the forms of the resources increase emissions. On the other hand, economic growth and GFCF significantly lead to higher emissions, which degrades the environment. Resources rents also contribute to increasing carbon emissions.
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The COVID-19 pandemic has exposed socioeconomic vulnerabilities around the world. After fighting the coronavirus for more than 1 and a half years now, the countries are recovering from the epidemic with the help of cutting-edge medical research. The policymakers are implementing stimulus packages for post-pandemic economic recovery. However, sustainable "green recovery" plans are yet to get adequate attention. Sustainable investment in green industries can create green jobs, promote a low-carbon economy, and foster long-lasting economic growth in the post-pandemic world. COVID-19 affected countries with emerging economies call for even more focus on such investments. In Bangladesh, the bicycle industry - a growing low-carbon industry - has been showing promising potential for growth since the beginning of the pandemic. Both the local and global markets of Bangladeshi bicycles have seen substantial growth during the epidemic. In this paper, we analyze the potential of the Bangladeshi bicycle industry as an effective green recovery driver. We conduct semi-structured interviews with relevant experts and professionals, analyze their opinions, and perform a "strengths, weaknesses, opportunities, and threats (SWOT)" analysis. The analysis reveals valuable insights regarding post-pandemic sustainable economic and environmental recovery which will be beneficial to the policymakers of Bangladesh and similar developing countries.
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In China, there has been a significant increase in carbon emissions in the new era. Therefore, evaluating the influence of industrial structure upgrades and energy structure optimization on reducing carbon emissions is the objective of this research. Based on the provincial panel data of 30 provinces and cities across China from 1997 to 2019, this paper builds up a fixed-effect panel quantile STIRPAT model to investigate the differences in the impact of industrial structure on carbon emission intensity at different quantile levels from the provincial perspective, and as a way of causality test, the mediation effect model is adopted to empirically test the transmission path of "industrial structure upgrading-energy structure optimization-carbon emission reduction". The research results show that: (1) Both industrial structure upgrades and energy structure optimization have significant inhibitory effects on carbon emissions, and there are regional heterogeneities. (2) The upgrading of industrial structure has a significant positive effect on optimizing energy structure. (3) The upgrading of industrial structure can not only directly restrain carbon emissions but also indirectly have a significant inhibitory effect on carbon emissions by promoting the optimization of energy structure. Based on the above conclusions, corresponding policy recommendations are proposed to provide suggestions for China to achieve the goal of carbon neutrality.
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This paper proposes a formal model to assess the introduction of hydrogen technology in the air transport sector when the initial market is uncovered, a situation relevant to the current COVID-19 crisis. The "flight shame” movement causes some passengers to leave the market while allowing for some willingness-to-pay for cleaner technologies. Starting from a horizontally differentiated duopoly between airlines with old technology and an uncovered market, the introduction of hydrogen technology provides the opportunity for vertical differentiation in line with the increased environmental consciousness of passengers. The principal methodological novelties start from an uncovered market and combine horizontal and vertical differentiation. The main results are the airlines' optimal strategy sets and the adoption strategy dynamics with an increased valuation of quality by passengers. We justify a regulator's intervention and draw several potential policy implications from this dynamic, such as a minimum subsidy level and educational advertising. © 2022
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To achieve carbon emission reduction target (CERT) by 2030 and carbon-neutrality in 2050, it is important to actively reduce the emission gap in the private building sector. However, the ongoing COVID-19 pandemic and the Russian-Ukraine war are threatening the green remodeling policy (GRP) worldwide. Therefore, this study analyzed energy consumption savings, GHG emission reduction, and net present value when applying green remodeling to a private building to predict whether or not the current GRP could achieve 2030 CERT and 2050 carbon-neutrality. The main findings are as follows. First, yearly electricity and gas consumption of 84.97 m2 type households can be reduced by 6.19% and 15.58% through green remodeling. Second, based on the energy saving, yearly GHG emission can be reduced about 0.34tCO2eq. Third, the economic feasibility of green remodeling cannot be achieved via the current policy, and NPV17 decreases up to USD-51,485 depending on the credit loan interest rate and the green remodeling interest subsidy program. In other words, it is difficult to reach 2030 CERT and 2050 carbon-neutrality via the current policy. Therefore, the South Korean government is required to reorganize financial policies, establish active systems, increase public awareness of the policy, and improve energy efficiency technology. © 2023 Elsevier B.V.
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Carbon emissions from human activities are the main cause of climate warming. Under the background of economic and social digital transformation, accurately assessing the carbon emission reduction effect of the development of the digital economy is of great significance for countries to deal with climate warming in the post-COVID-19 era. This paper constructs a dynamic evaluation model of orthogonal projection to measure the level of digital economy development at the provincial level in China from 2007 to 2019. On this basis, the panel fixed effects model and mediation model are used to empirically test the impact of digital economy development on carbon emission intensity and its mechanism. The results indicate that: (1) The development of China's digital economy is unbalanced among regions, showing a geospatial pattern of decreasing from east to west. (2) China's carbon emission intensity has a trend of decreasing year by year, and there are geospatial differences of "high in the west and low in the east” and "high in the north and low in the south.” (3) The digital economy development can effectively reduce regional carbon emission intensity through industrial structure optimization effect and resource allocation effect, and the industrial structure optimization effect can suppress carbon emission intensity more obviously. (4) The development of digital economy in different regions has different degrees of reducing carbon emission intensity. The development of digital economy in the eastern region has a stronger inhibitory effect on carbon emission intensity than that in the middle and western regions, and the development of digital economy in economically developed regions can suppress carbon emission intensity more. This paper provides enlightenment for policy makers to deal with climate warming. Copyright © 2023 Lyu, Zhang and Wang.
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Understanding and examining energy markets correctly is crucial for stakeholders to attain maximum benefit and avoid risks. As a matter of fact, the volatility that occurred in energy markets and recent crises had major impacts on national economies. Dynamic connectedness relationships (DCRs) can make quite powerful predictions for both low-frequency data and limited time-series data. The objective of this study is to explicate the dynamic connectedness relationships among the BIST sustainability index, BIST 100 index, S&P Global Clean Energy index (S&P GCEI), and S&P GSCI carbon emission allowances (EUA). The daily data obtained over the period 11 April 2014–11 November 2022 were used for the research study. The DCRs among the variables used in the study were investigated by employing the time-varying parameter vector autoregressive (TVP-VAR) model. As a result of the study, the volatility from carbon emission allowances was determined to spill over to S&P GCEI, BIST 100, and BIST sustainability indexes. During the COVID-19 pandemic, significant reductions were detected in the volatility spillover (VS) from carbon emission allowances to S&P GCEI, BIST 100, and BIST sustainability indexes. Moreover, it was revealed that a weak VS existed from S&P GCEI to BIST sustainability and BIST 100 indexes. The findings reveal the importance of policymakers taking some incentive measures in EUA prices and also its role in portfolio diversification. © 2023 by the authors.
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The prevalence of global unilateralism and the shock of COVID-19 brought considerable uncertainty to China's economic development. Consequently, policy selection related to the economy, industry, and technology is expected to significantly impact China's national economic potential and carbon emission mitigation. This study used a bottom-up energy model to assess the future energy consumption and CO2 emission trend before 2035 under three scenarios: a high-investment scenario (HIS), a medium-growth scenario (MGS), and an innovation-driven scenario (IDS). These were also used to predict the energy consumption and CO2 emission trend for the final sectors and calculate each sector's mitigation contribution. The main findings were as follows. Firstly, under HIS, China would achieve its carbon peak in 2030, with 12.0 Gt CO2. Moderately lowering the economic growth rate to support the low-carbon transition of the economy by boosting the development of the low-carbon industry and speeding up the employment of key low-carbon technologies to improve energy efficiency and optimize energy structure in the final sectors, the MGS and the IDS would achieve carbon peak approximately in 2025, with a peak of 10.7 Gt CO2 for the MGS and 10.0 Gt CO2 for the IDS. Several policy recommendations were proposed to meet China's nationally determined contribution targets: instigating more active development goals for each sector to implement the "1+N" policy system, taking measures to accelerate the R&D, boosting the innovation and application of key low-carbon technologies, strengthening economic incentives, forming an endogenous driving force for market-oriented emission reduction, and assessing the climate impacts of new infrastructure projects.
Subject(s)
COVID-19 , Carbon Dioxide , Humans , Carbon Dioxide/analysis , Economic Development , China , Carbon/analysisABSTRACT
Accurate carbon price forecasting can better allocate carbon emissions and thus ensure a balance between economic development and potential climate impacts. In this paper, we propose a new two-stage framework based on processes of decomposition and re-estimation to forecast prices across international carbon markets. We focus on the Emissions Trading System (ETS) in the EU, as well as the five main pilot schemes in China, spanning the period from May 2014 to January 2022. In this way, the raw carbon prices are first separated into multiple sub-factors and then reconstructed into factors of 'trend' and 'period' with the use of Singular Spectrum Analysis (SSA). Once the subsequences have been thus decomposed, we further apply six machine learning and deep learning methods, allowing the data to be assembled and thus facilitating the prediction of the final carbon price values. We find that from amongst these machine learning models, the Support vector regression (SSA-SVR) and Least squares support vector regression (SSA-LSSVR) stand out in terms of performance for the prediction of carbon prices in both the European ETS and equivalent models in China. Another interesting finding to come out of our experiments is that the sophisticated algorithms are far from being the best performing models in the prediction of carbon prices. Even after accounting for the impacts of the COVID-19 pandemic and other macro-economic variables, as well as the prices of other energy sources, our framework still works effectively.
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This paper aims to investigate the dynamic connectedness and the cross-quantile dependence structure between carbon emission trading and commodity markets in China. We employ both the Baruník and Křehlík (2018) connectedness method and the Baruník and Kley (2019) cross-quantile dependence method to provide time-frequency-quantile evidence. In addition, we use a daily dataset from September 2, 2013, to September 30, 2022, to gauge the macroeconomic effects of the COVID-19 pandemic. We find that Petrochemical is the biggest contributor and recipient in the carbon-commodities system, and the results show that carbon markets are more influenced by other commodity markets than the reverse. Furthermore, the total connectedness is stronger in the short term but can increase over the long term, especially during the onset of COVID-19. The dynamic pair-wise results show that the carbon market can impact other commodity markets, but the effects are diverse and varied. The quantile-varying dependence between the carbon market and commodities is detected, and the cross-quantile dependence gradually strengthens as the trading days increase. This paper concludes with fruitful policy implications for resource decision-makers. © 2023 Elsevier Ltd
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This paper addresses the impact of the Covid-19 lockdown on the warehousing of perishable items facing demand-side shocks, mainly those with selling price and product quality dependent demand, for example, fresh fruits, meats, vegetables, packed foods, etc. Along with demand-side issues, such an inventory system consumes a significant amount of energy in terms of freshness, increasing carbon tax and dwindling the firm's total profit. We formulate two-warehouse inventory models of perishables items using the first-in-first-out (FIFO) dispatching policy under two different Covid-19 lockdown scenarios. The two-warehouse system primarily consists of an owned warehouse (OW) and a rented warehouse (RW). Two different lockdown scenarios are considered as;(i) the lockdown during the consumption of goods in OW and (ii) the lockdown during the consumption of goods in RW. The demand rate is assumed to decline and surge by a finite volume as lockdown is forced and relaxed. The proposed models help in assessing the impact of lockdown on (i) product quality, (ii) product cost, (iii) inventory level, (iv) freshness keeping efforts, (v) investment in green technologies, and (vi) carbon cap and trade policy. We determine the above six parameters to maximize the firm's total profit. The key findings of this model suggest that yield is primarily affected due to carbon cap and trade policy, lockdown period, item price, backlogging, and variation in the holding costs in OW and RW. These models may assist the small, medium, and large firms involved in perishable or cold supply chains to assess the effect of Covid-19 like disruption and take corrective measures to maximize their profit.
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Climate change has become mankind's main challenge. Greenhouse gas (GHG) emissions from shipping are not totally irresponsible for this representing, roughly, 3% of the global total;an amount equal to that of Germany's total GHG emissions. The Fourth Greenhouse Gas Study 2020 of the International Maritime Organization (IMO) predicts that the share of GHG emissions from shipping will increase further, as international trade recovers and continues to grow, alongside with the economic development of India, China, and Africa. China and the European Union have proposed to include shipping in their carbon emissions trading systems (ETS). As a result, the study of the relationship between the carbon finance market and the shipping industry, attempted here for the first time, is both important and timely, both for policymakers and shipowners. We use wavelet analysis and the spillover index methods to explore the dynamic dependence and information spillovers between the carbon finance market and shipping. We discover a long-term dependence and information linkages between the two markets, with the carbon finance market being the dominant one. Major events, such as the 2009 global financial crisis;Brexit in 2016;the 2018 China-US trade frictions;and COVID-19 are shown to strengthen the dependence of carbon finance and shipping. We find that the dependence is strongest between the EU carbon finance market and dry bulk shipping, while the link is weaker in the case of tanker shipping. Nonetheless, carbon finance and tanker shipping showed a relatively stronger dependence when OPEC refused to cut production in 2014, and when the China-US trade disputes led to the collapse of oil prices after 2018. We show that information spillovers between carbon finance and shipping are bidirectional and asymmetric, with the carbon finance market being the principal transmitter of information. Our results and their interpretation provide guidance to governments on whether (and how) to include shipping in emissions trading schemes, supporting at the same time the environmental sustainability decisions of shipping companies. © 2023 The Authors
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The COVID-19 pandemic precipitated a unique set of circumstances where the provision of care via telemedicine was rapidly adopted. Delivering high-quality care is a primary focus and the consideration of sustainability should be central to this process. Value in healthcare is often defined by outcomes for patients and populations in relation to economic costs;however, a more holistic approach using the 'triple bottom line' factors in environmental and societal impacts. The primary drivers in developing dermatology video consultations were the promotion of equitable and co-produced care, constructing sustainable healthcare and mitigating against environmental impacts, and demonstrating leadership in establishing new methods of outpatient care delivery. Patient video consultation demographics and outcomes were captured from 24 June 2020 to April 11 2020. Data were collected via the hospital software and dictation system with ethical approval. Patient experience was assessed via an online questionnaire. One hundred video consultation episodes were examined. The rate of nonattendance at scheduled video consultation was 10%. Successful video consultations were completed in 90% of patient episodes. Conversion to a telephone consultation was required in 12% and face-to-face presentation in 4%. Further information (e.g. photographs) was required to complete the consultation in 18%. In relation to outcomes, 25% of patients were discharged back to their general practitioner. Day case procedures were arranged in 12% of patients. Follow- up was conducted via telephone in 21% of patients (n = 12/56) and face to face in 79% (n = 44/56). The rate of change in diagnosis following face-to-face follow-up/investigation was 8%. Seventy patients completed an online questionnaire;the response rate was 70%. Mean age was 39 years (range 16-74). Eighty-five per cent were satisfied or very satisfied with their consultation, 83% felt their skin complaint was adequately addressed and 73% rated their overall user experience as very good or excellent. In relation to environmental impacts 12 760 km and 228.6 h of travel time were saved, and carbon emissions were reduced by 2.19 metric tonnes of CO2. In terms of accessibility, 84% of households in the area have fixed broadband and 42% have mobile broadband. When endeavouring to determine the quality of a new service many aspects require attention. Our service demonstrates equity in accessibility with a wide age range and good broadband coverage. The rate of change in diagnosis was low at 8% and patient satisfaction was high. Questionnaire responses provide an opportunity for co-production and positive environmental and societal impacts are also created.
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Resource-based cities (RBCs) are not only important for ensuring national resource and energy security, but they also face serious ecological and environmental problems. To achieve China's carbon peaking and neutrality goals in the coming years, RBCs' achievement of a low-carbon transformation has become increasingly significant. The core of this study is an investigation as to whether governance, including environmental regulations, can facilitate the low-carbon transformation of RBCs. Based on RBC data from 2003 to 2019, we establish a dynamic panel model to research the influence and mechanism of environmental regulations on low-carbon transformation. We found that China's environmental regulations facilitate a low-carbon transformation in RBCs. Mechanism analysis identified that the environmental regulations facilitate the low-carbon transformation in RBCs by strengthening foreign direct investment, enhancing green technology innovation and promoting industrial structure upgrading. Heterogeneity analysis found that the environmental regulations play a greater role in facilitating the low-carbon transformation of RBCs in regions with more developed economies and less dependence on resources. Our research provides theoretical and policy implications for environmental regulations for the low-carbon transformation of RBCs in China, applicable to other resource-based areas.
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Carbon , Industry , Cities , China , Internationality , Economic Development , Carbon DioxideABSTRACT
Understanding the interactions among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets, especially the role of climate change in this system is of great significance for policy makers, energy producers/consumers and relevant investors. The present paper aims to quantify the time-varying connectedness effects among the four factors by using the TVP-VAR based extensions of both time- and frequency-domain connectedness index measurements proposed by Antonakakis et al. (2020) and Ellington and Barunik (2021) [8,48]. The empirical results suggest that, firstly, the average total connectedness among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets is not so strong for the heterogenous fundamentals underlying them. Nevertheless, the time-varying total connectedness fluctuates fiercely through May 2005 to September 2021, varying from about 8% to 30% and rocket to very high levels during the global subprime mortgage crisis and the COVID-19 pandemic. Furthermore, the total connectedness mainly centers on the short-term frequency, i.e., 1–3 months. Secondly, climate change is generally the leading information contributor among the four factors, although not particularly strong, and its leading role also performs mainly on the short-term frequency (1–3 months). Thirdly, renewable energy stock market and crude oil market show tight interactions between them and they are the two major bridges of information exchanges across various time frequencies (horizons) in this system. Finally, we confirm the evidence that the primary net connectedness contributor and receiver switch frequently across different time frequencies, implying that it is extremely essential for policy makers, energy producers/consumers and investors to make time-horizon-specific regulatory, production/purchasing or investment decisions when facing the uncertain effects of climate change on the interactions among carbon emission allowance, crude oil and renewable energy stock markets. © 2022 Elsevier Ltd
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Since the fossil fuels are the principal energy sources across the globe, it is considered as the major reason for environmental degradation. Although, the fossil fuel consumption contributes to maintain industrial production, which is a key factor of economic growth, yet tourism is also among the key sources of revenue for China in the pre-Covid-19 pandemic. However, after the emergence of this novel pandemic, both fossil fuel consumption and tourism are severely affected that slowdowns China's economic progress and could have influence on environmental quality. This study investigates the impact of traditional fossil fuel, economic growth, and tourism on carbon emissions level in China over the period 1995–2020. Using time series estimating approaches, all the variables are found stationary at first difference. Due to irregular distribution of data, this study employed the novel Quantile-on-Quantile regression. The estimated results reveal that consumption of fossil fuel significantly enhances the level of carbon emissions in China. Whereas the impact of economic growth and tourism on carbon emission is mixed. The influence of both the variables is found positive in the lower and medium quantiles, while negative in the upper quantiles. This study also employed the pairwise Granger causality test, that validates two-way causal nexus between fossil fuel consumption—carbon emission and economic growth—carbon emissions. While one way causality from tourism to carbon emissions is evident in the empirical results. This study suggests lowering of fossil fuel consumption by using the alternative energy sources and increase tourism stringent environmental regulations for environmentally destructive tourism activities. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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The paper investigates the volatility spillover across China's carbon emission trading (CET) markets using the connectedness method based on the quantile VAR framework. The non-linear result shows strong volatility spillover effects in upper quantiles, resulting from major economic and political events. This is in accordance with the risk contagion hypothesis that volatility of carbon price returns is affected by the shocks of economic fundamentals and spills over to other pilots. Guangdong and Shanghai are the most significant contributors to volatility transmission because of their high liquidity and active markets. Hubei CET pilot has shifted from transmitter to receiver since the COVID-19 pandemic. Regarding the pairwise directional connectedness, geographical location and similar market attribute also matter in volatility transmission. This provides implications for policymakers and investors to attach importance to risk management given the quantile-based method rather than the average shocks. © 2023 Elsevier B.V.