Investigating asymmetric impacts of total factor energy efficiency on carbon emissions in India.

As many complex energy relations are not linear and have diminishing returns, assuming a symmetric (linear) effect of energy efficiency (ENEF) on carbon emissions (CAE) has limited our understanding of the emission-ENEF nexus. This research, therefore, initially estimates total factor energy efficiency by applying a stochastic frontier technique using sample panels for India encompassing the period from 2000 to 2014. Further, a nonlinear panel autoregressive distributed lag modelling framework is utilised in order to investigate the asymmetric (nonlinear) long- and short-run impacts of ENEF on CAE. The findings demonstrated that ENEF has asymmetric long- and short-run impacts on CAE in India. Based on the outcomes, numerous crucial implications are discussed with a particular reference to developing economies like India.

Research on cold chain logistics optimization model considering low-carbon emissions

Cold chain logistics distribution orders have increased due to the impact of COVID-19. In view of the increasing difficulty of route optimization and the increase of carbon emissions in the process of cold chain logistics distribution, a mathematical model for route optimization of cold chain logistics distribution vehicles with minimum comprehensive cost is established by considering the cost of carbon emission intensity comprehensively in this paper. The main contributions of this paper are as follows: 1) An improved hybrid ant colony algorithm is proposed, which combined simulated annealing algorithm to get rid of the local optimal solution. 2) Chaotic mapping is introduced in pheromone update to accelerate convergence and improve search efficiency. The effectiveness of the proposed method in optimizing cold chain logistics distribution path and reducing costs is verified by simulation experiments and comparison with the existing classical algorithms. © 2023 The Author(s). Published by Oxford University Press.

The evaluation of government subsidy policies on carbon emissions in the port collection and distribution network: a case study of Guangzhou Port

The collection and distribution network of ports is the main cause of carbon emissions. The carbon peak is a basic policy in China, and the subsidy policy is one of the common measures used by the government to incentivize carbon reduction. We analyzed the transportation methods and the flow direction of a port and proposed a carbon emission calculation method based on emission factors. Based on the transportation time and the cost, a generalized transportation utility function was constructed, and the logit model was used to analyze the impacts of subsidy policies on transportation, thus calculating the effects of the subsidies on carbon reduction. We used Guangzhou Port as a case study, and calculated the carbon reduction effects in six different subsidy policy scenarios and concluded that the absolute carbon reduction value was proportional to the subsidy intensity. In addition, we constructed a subsidy carbon reduction efficiency index and found that the Guangzhou Port collection and distribution network had higher subsidy carbon reduction efficiency in low-subsidy scenarios. Finally, a sensitivity analysis was conducted on the subsidy parameters, and scenario 8 was found to have the highest subsidy carbon reduction efficiency. This achievement can provide decision support for the carbon emission strategy of the port collection and distribution network.

Spatiotemporal patterns and drivers of carbon emissions from municipal solid waste treatment in China.

Reducing carbon emissions from municipal solid waste (MSW) treatment is non-negligible for China to meet its "carbon peaking and carbon neutrality" targets. It is critical to objectively evaluate the spatiotemporal patterns and drivers of carbon emissions from MSW treatment. This study estimates the carbon emissions from MSW treatment across 30 Chinese provinces from 2011 to 2020. The joint approach LMDI-PDA model is further used to refine the impact of policy on carbon emission changes from technical and efficiency perspectives, while considering the socio-economic factors. The results showed that carbon emissions from MSW treatment grew significantly until peaking at 202.05Mt CO2e in 2017 and then stabilized, finally dropping to 165.10 Mt CO2e in 2020 due to the impact of COVID-19. Compared with the "12th Five-Year Plan" period, the MSW emissions intensity declined significantly during the "13th Five-Year Plan" period, indicating the effective implementation of waste emission control measures. Furthermore, the slowdown in the growth of national emissions was primarily driven by technological advances in waste treatment. Technical efficiency change effect, MSW generation intensity effect, economic scale effect, and population scale effect impeded national emissions decline. Since the performance of various drivers varied greatly in different provinces, a cluster analysis was conducted to provide policy recommendations in provinces with similar characteristics. Both the methods and results of this study can provide better decision-making support for national and provincial carbon emissions control policies targeting MSW treatment.

Hourly based methods to assess carbon footprint flexibility and primary energy use in decarbonized buildings

Constant emission factors to assess the carbon footprint of buildings energy use, as usually included in national Building Technical Codes, show their limitations since the electrical grid mix changes constantly. For this reason, hourly-based methods using time-varying penalty signals to calculate carbon emissions and primary energy use in buildings constitute more effective assessment methods, especially with the aim to activate energy flexibility in buildings based on those inputs. Such signals have been developed and tested in the present work. The robustness and effectiveness of the methods is tested throughout two study cases. The first case compares the impact of using hourly signals over constant factors from the standards. For that purpose, a measured aggregated consumption profile corresponding to 226 real households is analyzed. In the second study case, demand response is implemented through control strategies reacting to the hourly penalty signals, aiming to decrease the emissions, primary energy use and cost. Results for the first case reveal that hourly rates better capture the variability of the electric grid compared to constant yearly factors from national standards, with a 50% difference in carbon emissions and a 20% overestimation with primary energy. Results from the second study case show how the implemented modulation strategies offer benefits in the flexible scenarios compared to the base scenarios, in terms of accumulated emissions or primary energy. Improvements are especially perceived when splitting data seasonally and considering periods with higher demand. Furthermore, this study provides insights for developing energy flexibility inputs when assessing the building performance during critical events such as the COVID19 pandemic or extreme weather conditions, where hourly and seasonal variation might have greater impact. Demand response mechanisms as energy flexibility strategies studied through this work might help in the reduction of total emissions and primary energy. Depending if the goal is to shift the demand due to environmental or economical reasons, different modulation strategies can be implemented to reach greater benefits.

Towards a green hospital approach in Oman: A case study of quantifying an environmental impact.

INTRODUCTION: The environmental impact of hospitals and healthcare providers practices is substantial, although often unnoticed and infrequently tracked. A green and healthy hospital is one that promotes public health by continuously monitoring and reducing its environmental impact. METHODS: We adopted a descriptive case study design with a multi-dimensional evaluation and monitoring of carbon emission equivalence (CO2e) using two examples from a tertiary care hospital practice in Oman. One example (1) was related to inhalation anaesthetic gases (IAG) consumption and the second example (2) was related to estimation of telemedicine clinics (TMCs) CO2e travel-related savings. RESULTS: The cumulative consumption of three different (1) IAG over three years (2019, 2020, 2021) was generated with estimated CO2e for each year for sevoflurane, isoflurane and desflurane. Desflurane had the lowest consumption with a yearly cumulative consumption of 6000 mL, 1500 mL, and 3000 mL for the years 2019, 2020 and 2021. The (2) TMCs during the first two years of the COVID-19 pandemic travel related CO2e savings were in the range of 12.65-3483.1 tonnes. In the second year of launching this service it doubled to a range of 24-6610.5 tonnes of CO2e savings. CONCLUSION: A green and healthy hospital approach of tracking and monitoring environmental impact of healthcare providers practices is critical for health planning and management of the environmental policy. This case study illustrated the importance of closely tracking hospital-based practices from an environmental perspective towards a green hospital approach.

Application of Data Mining to Support Facilities Management in Smart Buildings

Concerns about the effects of global warming and predicted rising sea levels are radically changing government policies to lower carbon emissions using sustainable green technologies. The United Kingdom aims to reduce its carbon emissions by 78% by 2035 and achieve net zero by 2050. This is a major driver for energy management and is influencing development of buildings which use autonomous smart technologies to assist in lowering carbon footprints. These Smart Buildings use digital technologies by connecting sensor data with intelligent systems which can be monitored remotely to provide more efficient facilities management. The data harvested and transmitted from the IoT sensors provides a key component for Big Data Analytics using techniques such as Association rule mining for intelligent interpretation which can assist facilities management becoming more agile regarding office space utilization. The shift toward hybrid working particularly instigated by the COVID-19 pandemic and recent energy supply concerns caused by the Ukraine crisis presents facilities management with opportunities to optimize their space, reduce energy consumption, and allow them to identify commercial opportunities for the unused space throughout the building. This chapter discusses the use of association rules for data mining derived from a simulated dataset for an investigative analysis of office workflow patterns for facilities management operations, resource conservation, and sustainability. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Environment and natural resources degradation under COVID-19 crises: Recovery post pandemic.

Environmental stability improved during the covid 19 pandemic when production and industrial activities, and natural resources depletion processes stopped during the lockdown environment worldwide; however, based on the judgment of COP26 and the recent COP27, environmental degradation increased in the world in post-pandemic; therefore, policymakers and researchers re-focused their attention on the determinants of CO2 in economies. Hence, this study investigates the nexus of natural resource rents, including oil rents, mineral rents, and coal rents, on the carbon emissions of upper-middle-income economies from 1984 to 2021. The study included economic growth and renewable energy as additional determinants. We have presented detailed time series methods that aid in examining the modeled variables characteristics in the current research, i.e., ADF and ADF-GLS for a unit root in the data variables and considering their stationarity, Johansen cointegration for long-term cointegration among variables, FMOLS, DOLS and CCR for the long run elasticities between dependent and independent variables and Granger causality test in our range of methods. Robustness checks analysis is done through a non-parametric approach by quantile regression and robust regression analysis. Our results exhibit that two natural resource rents that are oil rents and coal rents, have adverse impacts on carbon emissions, and both are positive and significant. In contrast, mineral rents have no statistical significance and role in the carbon emissions of upper-middle-income economies. Moreover, economic growth and renewable energy also positively and significantly impact carbon emissions. Granger causality analysis exerts that natural resources rents, except for mineral rents, economic growth, and renewable energy, all granger causes CO2 emissions, and the feedback is also true. The relevant findings are suitable for policymakers in upper-middle-income economies to ensure environmental sustainability in upper-middle-income economies.

Near-real-time methodology for assessing global carbon emissions

Climate change is a major challenge for the sustainable development of mankind. Carbon emissions from human activities are the main driving force of global climate change, and the quantification of carbon emissions is the basis for coping with global changes and achieving carbon neutrality. Developing more spatially and temporally fine-grained carbon emission data to achieve more precise, accurate, and timely carbon emission monitoring is at the current forefront of the field and a major national demand. Here, a carbon emission quantitative method for near-real-time global carbon emissions is proposed, based on multi-source activity data such as statistics, satellite remote sensing, and observation. By parameterizing the extent of daily human activity, it can achieve a near-real-time quantitative estimation of global and regional carbon emissions according to the methodology of the IPCC 2006 guidelines, resolving preexisting challenges, including time lag of yearly emission inventories and how to spatialize the national inventories in high temporal resolution. This paves the way for more accurate, reliable, and verifiable carbon monitoring. Specifically, near-real-time estimates can reveal daily, weekly, monthly, and seasonal changes in global carbon emissions. Results show that emissions are highly related to human activity (e.g., the emissions from Monday to Friday are at a high level but return to a relatively low level during weekends). In addition, winter emissions are higher than those of summer, reflecting the greater demand for heating in the winter for populations in the northern hemisphere and cooling demands in summer. This phenomenon can indicate the variations of seasonal changes in each country, where temperatures at different latitudes reflect heating and cooling demands. Sectoral emissions demonstrate the seasonality of power, including that used by residential sectors. During the COVID-19 pandemic, emissions dropped unprecedentedly, with the emissions of the power sector decreasing rapidly. During the pandemic, domestic aviation emissions were similar to ground transport emissions, while international aviation emissions remained low due to the restrictions imposed on entering and leaving countries. Spatialized daily emissions reveal discrepancies of fine-grained sectoral emissions with a spatial resolution of 0.1 degrees x0.1 degrees. Global daily average emissions show that emissions are concentrated within eastern America, western Europe, southeastern China, etc., with the emerging hotspots being the megacities in each region. Sectoral emissions vary because the sources of emissions of each sector are diverse. Uncertainties are crucial for evaluating the performance of spatialization and fine-grained temporal discretization of activity data. This methodology considers per-sector uncertainties according to the IPCC 2006 guidelines. The uncertainties for power, industry, ground transport, residential, aviation, and international shipping sectors are 14%, 36%, 9.3%, 40%, 10.2%, and 13.0%, respectively. For spatialization, the uncertainties come from national emission data and the EDGAR and GID datasets. The baseline emissions, point-source emissions and scale, non-point-source distribution, and proxy data contribute to the uncertainties. In the future, additional high spatiotemporal resolution data will be used in extra cross-validation and corrections to achieve more precise carbon monitoring.

Environmental reverberations of geopolitical risk and economic policy uncertainty resulting from the Russia-Ukraine conflict: A wavelet based approach for sectoral CO2 emissions.

After the COVID-19 pandemic, Russia invaded Ukraine in February 2022, and a natural gas crisis between the European Union (EU) and Russia has begun. These events have negatively affected humanity and resulted in economic and environmental consequences. Against this background, this study examines the impact of geopolitical risk (GPR) and economic policy uncertainty (EPU) caused by the Russia-Ukraine conflict, on sectoral carbon dioxide (CO2) emissions. To this end, the study analyzes data from January 1997 to October 2022 by using wavelet transform coherence (WTC) and time-varying wavelet causality test (TVWCT) approaches. The WTC results show that GPR and EPU reduce CO2 emissions in the residential, commercial, industrial, and electricity sectors, while GPR increases CO2 emissions in the transportation sector during the period from January 2019 to October 2022, which includes Russia-Ukraine conflict. The WTC analysis also indicates that the reduction in CO2 emissions provided by the EPU is higher than that of the GPR for several periods. According to the TVWCT, there are causal impacts of the GPR and the EPU on sectoral CO2 emissions, but the timing of the causal impacts differs between the raw and decomposed data. The results suggest that the EPU has a larger impact on reducing sectoral CO2 emissions during the Ukraine-Russia crisis and that production disruptions due to uncertainty have the greatest impact on reducing CO2 emissions in the electric power and transportation sectors.

The Impact of ESG Practices in Industry with a Focus on Carbon Emissions: Insights and Future Perspectives

In recent years, interest in economic, environmental and social sustainability has increased significantly. Companies are gradually adopting behaviors aimed at achieving the Sustainable Development Goals, which represent a crucial aspect of the 2030 Agenda. In practice, they are currently incorporating organizational strategies that jointly consider environmental, social and corporate governance (ESG), with the aim of generating value for all stakeholders. This paper aims to review, through a recognized seven-step procedure, the current literature on the impact that ESG practices have in industry, with a focus on the reduction of carbon emissions. The results are extremely useful for both researchers and entrepreneurs. The bibliometric analysis shows that interest in the ESG paradigm has grown considerably in the last three years. Furthermore, through the analysis of 13 key documents, it emerges that (i) the European community is pushing significantly towards the adoption of ESG practices through new regulations, (ii) the link between industrial operations and carbon emissions can no longer be neglected within the factory of the future, and (iii) significant efforts are still needed to standardize, in terms of variables and KPIs, the adoption of ESG-centric strategies.

The impact of the COVID-19 pandemic on global trade-embodied carbon emissions.

We evaluate the response of global supply chains to carbon emissions through compiling multi-regional input-output (MRIO) models for import and export shocks in 14 countries/territories dominated by the COVID-19 crisis. Instead of traditional production-based inventories, we achieve CO2 emissions inventories based on intermediate inputs and final consumption to analyze the connected environmental impacts. In addition, we adopt the available data up to date to construct inventories of carbon emissions involved in imports and exports from different sectors. The results show that global carbon emissions could be decreased by 6.01% during the COVID-19, while export carbon emissions remained basically unchanged. As a result, imported carbon emissions fell by 5.2%, with the energy products sector most affected by the pandemic. Transport sector witnessed 18.42% carbon emission reduction. The impact of developing countries with a large proportion of resource-based industries is comparatively higher than that of developed countries with the technological advantage. International trade plays a crucial role in the choice of supply chain partners to control carbon emissions. Building a sustainable supply chain and reducing the "trade carbon deficit" between countries/regions requires the coordination of all departments of each country/region to promote the trade of energy-saving products, environmental protection services and environmental services.

Energy-environmental-economic assessment of green retrofit policy to achieve 2050 carbon-neutrality in South Korea: Focused on residential buildings

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.

Energy policy simulation in times of crisis: Revisiting the impact of renewable and non-renewable energy production on environmental quality in Germany

In this paper, we examine for the first time in the literature the implications of energy policy alternatives for Germany considering the aftermath of coronavirus as well as Electricity and Gas energy supply shortages. Whilst several policy options are open to the government, the choice of investment in renewable energy generation versus disinvestment in non-renewable energy such as coal energy generation provides divergent impacts in the long term. We utilize data from British Petroleum and the World Bank Development Indicator database for Germany covering 1981 to 2020 to explore a Carbon function by applying a battery of Autoregressive distributed lag model (ARDL), dynamic ARDL and Kernel-Based Regularized Least squares approaches. The particular policy tested is the pledge by Germany to decrease emissions by ∼100% in 2050, and this was integrated through the estimation of dynamic ARDL estimation. The simulation result shows that a ＋61% shock in renewable energy production decreases carbon emissions unlike coal energy production which increases carbon emissions in the beginning but the carbon emissions decrease thereafter. The findings highlight the inevitability of cutting down on coal production, and recommends energy investment alternatives. Hence, Germany's energy policy should contemplate more thoroughly on these factors. © 2023 The Author(s)

ENLIGHTENMENT OF INTERNATIONAL CARBON EMISSION TRADING PRACTICE TO CHINA

In the era of "Post-epidemic" and "Dual-carbon targets", the focus of research on China's carbon trading market has changed from basic framework design to problem solving and development paths in the process of practice. Foreign carbon trading markets have developed for many years, and have experienced the financial crisis and the impact of the coronavirus epidemic. By analyzing the important problems and countermeasures encountered in the process of carbon trading market by representative organizations such as EU, USA, New Zealand, Korea and Japan, the valuable experience and reference significance of foreign carbon trading practice were summarized. At the same time, comparing the similarities and differences between Chinese and foreign carbon trading national conditions, and taking into account the current development of China's carbon trading market, this paper put forward some carbon trading strategies with Chinese characteristics and absorbing foreign advanced experience, such as choosing appropriate emission caps, balancing regulation, formulating price stabilization mechanism, and leaving interfaces for international cooperation. © 2023 Research Institute of Petroleum Processing, SINOPEC. All rights reserved.

Impact of COVID-19 and green finance on transportation energy carbon emissions in China: From the perspective of an automobile energy consumption structure

Background: In China, the transportation sector is the main energy consumer and the main source of carbon emissions. Reducing carbon emissions in the transportation sector is an important goal for China, especially during the current period of economic development. Due to the impact of pandemic shocks, the rapid development of green finance is conducive to supporting the transportation sector in achieving a carbon peak. Thus, we examined whether the development of green finance is still effective under the impact of a pandemic and the actual effect of green finance on the reduction of carbon emissions. Methods: In this study, we searched the internet for consumption structure data of vehicles and green finance indices of 30 Chinese provinces and cities from 2016 to 2021. A regression discontinuity model was constructed to test the effect of pandemic shock and green finance development on the reduction of transportation energy carbon emissions. Results: The results show that the impact of the COVID-19 pandemic has helped people change their preference toward more energy-efficient vehicles and reduce carbon emissions in the transportation sector. Green finance can effectively contribute to the reduction of transportation energy carbon emissions;however, the overall mitigation effect is limited. Conclusion: The empirical evidence is not only helpful in assessing the long-term impact of the COVID-19 pandemic but also conducive to the appropriate establishment of policy tools for supporting green finance development, which is further conducive to reducing carbon emissions in the transportation sector. Copyright © 2023 Liu, Cheng, Guan, Liu, Zhang, Li and Yang.

Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction

This study measures the total factor carbnon dioxide (CO2) emissions performance of the metal industry, iron and steel, nonferrous metal, and metal processing industries in 39 Japanese prefectures from 2008 to 2019. The true fixed-effects panel stochastic frontier model identifies regional carbon efficiency as well as the inefficiency determinants. The main results are as follows. First, a decrease in the coal ratio and an increase in the electricity ratio in total energy consumption improves efficiency. This result suggests that electrification in the metal industry, especially conversion from blast furnaces to electric furnaces in the iron and steel industry, contributes to reducing carbon emissions. Second, industrial agglomeration improves carbon emissions performance in the metal industry. This implies that agglomeration and decarbonization policies focusing on there are more effective, rather than a uniform national policy. Third, compared to the cumulative CO2 emissions over the sample period, 49,017 × 103 tons, the cumulative CO2 mitigation potential is 29,703 × 103 tons, indicating that CO2 emissions can be reduced by 60.6% without affecting the output. Forth, to examine the green economic recovery with efficiency in Japan's metal industry after COVID-19, we present a simple scenario analysis where a k% replacement coal ratio with an electricity ratio in total energy consumption, assuming that each prefecture will achieve the maximum CO2 emission amount during the sample period. By replacing 10% of the coal ratio with the electricity ratio, CO2 emissions can be reduced by 23.0%. In the case of a 20% replacement, CO2 emissions can be reduced by 33.0%. Our results show that Japan's targets in the post-COVID-19 green recovery process should be a decrease in coal consumption, an increase in electricity, and industrial agglomeration. © 2023 Elsevier Ltd

Prioritising Climate Change Mitigation Behaviours and Exploring Public Health Co-Benefits: A Delphi Study.

Climate change requires urgent action; however, it can be challenging to identify individual-level behaviours that should be prioritised for maximum impact. The study aimed to prioritise climate change mitigation behaviours according to their impacts on climate change and public health, and to identify associated barriers and facilitators-exploring the impact of observed behaviour shifts associated with COVID-19 in the UK. A three-round Delphi study and expert workshop were conducted: An expert panel rated mitigation behaviours impacted by COVID-19 in relation to their importance regarding health impacts and climate change mitigation using a five-point Likert scale. Consensus on the importance of target behaviours was determined by interquartile ranges. In total, seven target behaviours were prioritised: installing double/triple glazing; installing cavity wall insulation; installing solid wall insulation; moving away from meat/emission heavy diets; reducing the number of cars per household; walking shorter journeys; and reducing day/weekend leisure car journeys. Barriers related to the costs associated with performing behaviours and a lack of complementary policy-regulated subsidies. The target behaviours are consistent with recommendations from previous research. To ensure public uptake, interventions should address behavioural facilitators and barriers, dovetail climate change mitigation with health co-benefits and account for the long-term impacts of COVID-19 on these behaviours.

Do Environmental Regulations Facilitate a Low-Carbon Transformation in China's Resource-Based Cities?

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.