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Subnational climate actors are expected to play an increasingly important role in climate actions. However, a trade-off between equity and efficiency emerges when nationally determined contributions (NDCs) are distributed into subnational actions. In this study, we propose a two-staged carbon quota allocation method, with an equity-based 1st-stage allocation mechanism wherein provincial carbon reduction efforts are shared equally and an efficiency-based 2nd-stage allocation mechanism to maximize input–output efficiency. Using China as a case study, we convert China's NDC carbon intensity reduction target into a total emissions cap and apply the allocation method to show that the 2nd-stage allocation significantly increases the total provincial carbon emission efficiency without seriously compromising equity. As the allocation method changes from equity-based to efficiency-based, the carbon quotas mainly flow out from provinces with small emissions and high energy intensity to provinces with large emissions and low energy intensity. The two-staged carbon quota allocation method effectively considers the equity and efficiency principles, which can reduce resistance to the implementation of national NDCs. Generally, the approach has promising application potential for countries to break down the NDC into subnational shares. [ABSTRACT FROM AUTHOR]

Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions. [ABSTRACT FROM AUTHOR]

The freight transport industry in Mexico has grown significantly since the establishment of trade agreements in North America, which has brought significant environmental consequences to the main transport corridors. This paper proposes a methodology for the estimation of emissions for freight vehicles on road transportation corridors. The variables included in this analysis allow adequate characterization of the conditions of the vehicle fleet, the geometry and the quality of the road, the environment, and the average annual daily traffic (AADT) of heavy vehicles. The results were structured to show two indicators, the amount of CO2 emissions per kilometer and the amount of emissions per tonne transported. These results will allow establishing a baseline of CO2 emissions through which we can implement actions in the road transport sector to reduce greenhouse gases (GHG) to mitigate climate change and develop parameter values for use in Cost Benefit Analysis. The indicators can also be applied to geospatial modeling of emissions in road transport corridors and forecast its growth. [ABSTRACT FROM AUTHOR]

Emerging countries are at the frontier of climate change actions, and carbon emissions accounting provides a quantifiable measure of the environmental impact of economic activities, which allows for comparisons of emissions across different entities. However, currently there is no study covering detailed emissions inventories for emerging countries in Central Asian. This paper compiles detailed and accurate carbon emissions inventories in several Central Asian countries (i.e., Kazakhstan, Kyrgyzstan, Pakistan, Palestine, Tajikistan, and Uzbekistan) during the period 2010–2020. Using the IPCC administrative territorial approach, we for the first time compile their emissions inventories in 47 economic sectors and five energy categories. Moreover, we also investigate decoupling status based on Tapio decoupling model and examine emissions driving factors based on the index decomposition analysis method. The primary results illustrate that carbon emissions in Central Asian countries are increasing with huge differences. Decoupling results highlight that most of the sample countries still need more effort to decouple the economy and emissions except that Pakistan achieves an ideal strong decoupling state. The results of the decomposition indicate that the economy and population both raise emissions, while energy intensity and carbon intensity are negative drivers in some countries. We propose practical policy implications for decarbonization and energy transition roadmap in Central Asian countries. [ABSTRACT FROM AUTHOR]

Cities are the main emission sources of the CO2 produced by energy use around the globe and have a great impact on the variation of climate. Although the implications of urbanization and socioeconomic elements for carbon emission have been extensively explored, previous studies have mostly focused on developed cities, and there is a lack of research into naturally related elements due to the limited data. At present, remote sensing data provide favorable conditions for the study of large-scale and long-time series. Also, the spillover mechanism of urbanization effects on the discharge of carbon has not been fully studied. Therefore, it is necessary to distinguish the types of influence that various urbanization factors have on emissions of CO2. Firstly, this study quantifies the urban CO2 emissions in China by utilizing nighttime lighting images. Then, the spatio-temporal variations and spatial dependence modes of CO2 emissions are explored for 284 cities in China from 2000–2018. Finally, the study further ascertains that multi-dimensional urbanization, socio-economic and climate variables affect the discharge of carbon using spatial regression models. The results indicate that CO2 emissions have a remarkable positive spatial autocorrelation. Urbanization significantly increases CO2 emissions, of which the land urbanization contribution towards CO2 emissions is the most important in terms of spillover effects. Specifically, the data on urbanization's direct effects reveal that CO2 emissions will increase 0.066%when the urbanization level of a city rises 1%, while the spillover effect indicates that an 0.492% emissions increase is associated with a 1% rise of bordering cities' average urbanization level. As for the socio-economic factors, population density suppresses CO2 emissions, while technological levels boost CO2 emissions. The natural control factors effect a remarkable impact on CO2 emissions by adjusting energy consumption. This study can provide evidence for regional joint prevention in urban energy conservation, emission reduction, and climate change mitigation. [ABSTRACT FROM AUTHOR]

This paper investigates the role of export quality in climate action goal of the sustainable development goals in emerging Asian countries. For this purpose, the empirical model that observes the impact of real GDP, energy use and export quality index on carbon emissions is constructed and is analyzed by ARDL bounds testing approach for the period from 1970 to 2014. We also include the square of real GDP as independent variable to observe the existence of environmental Kuznets curve (EKC) hypothesis which implies the parabolic relationship between economic growth and environmental degradation. The findings show that increase in export quality leads to a fall in CO2 emissions for China and India. In contrast, the effect of increasing export quality increases CO2 emissions in Thailand and the Philippines. Lastly, our asymmetric causality results show that the positive shocks of export quality causes positive shocks of CO2 emissions in Thailand and Indonesia. Furthermore, we found that positive export quality shocks cause negative CO2 emissions shocks in India while negative export quality shocks cause positive CO2 emissions shocks in China. We also confirm the inverted U-shaped EKC hypothesis in China and Thailand. [ABSTRACT FROM AUTHOR]

The motivation of this study stems from the United Nations Sustainable Development Goals on clean and responsible energy consumption, climate change mitigation and sustainable economic growth (UN-SDGs-7, 11, 12 and 13). The present study examines the impact of institutional quality on CO 2 emissions in the presence of the Environmental Kuznets Curve (EKC) framework using data on CO 2 emissions and the six dimensions of institutional quality from the World Governance Indicators (WGI). The current study focuses on selected 30 Sub-Saharan African (SSA) countries over the annual period from 2000 to 2021. The EKC hypothesis revealed CO 2 emissions are substantially reduced by corruption control, regulatory quality, and the rule of law. Findings from the Dumitrescu and Hurlin causality test showed a one-way causality running from CO 2 emissions to industrialization. Similar uni-directional causality is observed between economic growth, and energy consumption. On the other hand, we observed a two-way causality flow from CO 2 emissions to population growth and all indices of institutional quality over the investigated period. These findings indicate that government agencies should efficiently implement acceptable strategies for pollution control and enact public benefit environmental regulations in the form of a healthier climate for the entire population. • We examined the impact of institutional quality on CO 2 emissions in the presence of the Environmental Kuznets Curve (EKC) framework. • 30 Sub-Saharan Africa (SSA) countries are selected for empirical investigation. • We reveal that CO 2 emissions are substantially reduced by corruption control, regulatory quality, and the rule of law. • Meanwhile, one-way causality runs from CO 2 emissions to industrialization. • A two-way causality flow from CO 2 emissions to population growth and all indices of institutional quality are reported. [ABSTRACT FROM AUTHOR]

[Display omitted] China is playing an increasing role in global climate change mitigation, and local authorities need more city-specific information on the emissions trends and patterns when designing low-carbon policies. This study provides the most comprehensive CO 2 emission inventories of 287 Chinese cities from 2001 to 2019. The emission inventories are compiled for 47 economic sectors and include energy-related emissions for 17 types of fossil fuels and process-related emissions from cement production. We further investigate the state of the emission peak in each city and reveal hidden driving forces. The results show that 38 cities have proactively peaked their emissions for at least five years and another 21 cities also have emission decline, but passively. The 38 proactively peaked cities achieved emission decline mainly by efficiency improvements and structural changes in energy use, while the 21 passively emission declined cities reduced emissions at the cost of economic recession or population loss. We propose that those passively emission declined cities need to face up to the reasons that caused the emission to decline, and fully exploit the opportunities provided by industrial innovation and green investment brought by low-carbon targets to achieve economic recovery and carbon mitigation goals. Proactively peaked cities need to seek strategies to maintain the downward trend in emissions and avoid an emission rebound and thus provide successful models for cities with still growing emissions to achieve an emission peak. [ABSTRACT FROM AUTHOR]

• CO 2 flows by forest dynamics and forest operations in one simulation tool. • Generic meta -model for plugging in any silvicultural concept of interest. • Freely available as an open source R-package on CRAN. Carbon stocks and flows in forest ecosystems play an important role in the context of climate change mitigation. Different aspects of the forest carbon balance, however, are often treated independently, leading to a fragmented, disciplinary knowledge. With the R-package care4cmodel we want to support a consolidated view of forest growth and forest operations with respect to carbon flows. The software is, in essence, a pragmatic simulation tool that allows juxtaposing the CO 2 uptake due to wood increment and the CO 2 emissions due to forest operations for given silvicultural concepts in an arbitrary area, over time. At the core, the approach is a dynamic forest area model where forest development stages are represented in a cyclical sequence, which can be broken by disturbances. The model scales up growth and yield information given per forest development stage and unit area to the dynamically simulated development stage areas. This allows to quantify the total forest area's CO 2 uptake, and to estimate the CO 2 emissions caused by forest operations. The forest operations in our implementation include the maintenance of the forest road network, felling trees, debranching and bucking the stems, and extracting the timber to a landing at a forest road. The transport from there to the industry is beyond the system boundary. For the CO 2 uptake of the forest system, the current model version focuses on the wood increment only. We use a practical example to demonstrate the basic features of the model and its plausible behaviour. Beyond the current focus of the model, we see a broad field of applications as a generic meta model, especially in the context of ecosystem service provision. [ABSTRACT FROM AUTHOR]

Efforts to enhance greenhouse gas (GHG) emission reduction in East Asia play a pivotal role on both global and regional scales in advancing climate mitigation strategies. This study aimed to better constrain anthropogenic CO 2 emission estimates by expanding the network of near-surface in-situ stations for CO 2 observations across South Korea. To achieve an optimal CO 2 network design, we conducted an Observing System Simulation Experiment (OSSE) coupled with the Stochastic Lagrangian Transport model (STILT), utilizing meteorological data from the Korean Integrated Model (KIM). Our inversion setup incorporated two CO 2 emission datasets with a 0.1o resolution: EDGAR v6 for prior emissions and GRACED for truth emissions. A uniform model-mismatch error of 3 ppm was introduced across sites. The effectiveness of the existing five in-situ stations, termed the base network, in South Korea was evaluated to gauge their ability to constrain CO 2 surface flux estimates. However, the findings revealed a reduction in flux uncertainty of only 29.2%, which fell short of the desired uncertainty reduction goal. In this base network, the Lotte World Tower (LWT: 37.5126°E, 127.1025°E) in Seoul and the Anmyeondo (AMY: 36.538576° N, 126.330071° E) site in Taean county stood as major contributors, with estimated reductions of 17.48% and 6.35%, respectively. Consequently, we proposed and developed an extended network, identifying seven candidate sites based on consideration of logistical factors, existing infrastructures, and proximity to the emission source regions. An incremental optimization scheme ranked their contributions, resulting in an additional 25% reduction, bringing the total to 54.13%. However, it is noteworthy that diminishing returns (ranging from 13% to less than 0.1%) were observed with an increase in station count mainly due to the possibility that adding a station earlier in the sequence might render subsequent stations redundant. Despite this, the proposed CO 2 network successfully reduced uncertainty in emissions, narrowing the gap with the objectives of the Global Greenhouse Gas Watch (G3W). • Designing CO 2 near-surface observation network over South Korea. • New stations selected considering logistic factors, existing infrastructures, and proximity to emission sources. • The base network was able to reduce 29.18% of the uncertainty in CO 2 emissions. • Extending network, by adding new seven candidate sites, led to a total uncertainty reduction of 54.13%. [ABSTRACT FROM AUTHOR]

Nature-based climate solutions are playing an increasingly significant role under the long-term goal of carbon-neutrality. Carbon storage and sequestration are important service functions of the ecosystem, but these potential in neutralizing carbon emissions at provincial level is rarely evaluated. Here we take Qinghai province in northwest China to conduct a case study, as it possesses the country's best solar and wind energy resource, one of the largest ecosystem therefore great carbon sequestration potential, and has been strived to set off a carbon neutral pilot in China. We combine the carbon density observation database and the land use/cover change (LUCC) data with the InVEST model to study the spatiotemporal dynamics of the carbon stock for Qinghai's terrestrial ecosystem, which are then compared to the energy related carbon emissions. The results reveal a tale of two stages, as Qinghai transformed from being a fast growing carbon emitter during 2000e2015 to be a carbon neutral player during the 13th Five-Year Plan (2015e2020). Land management interventions can contribute to climate change mitigation through avoided emissions from ecosystem degradation, and through negative emissions via biomass growth and, soil carbon sequestration. The duel-effort of greening the power grid and enhancing the ecosystem carbon sequestration is critical in achieving Qinghai's transition. Practices like agrophotovoltaic power plant in the barren or degraded lands have demonstrated great synergies of harvesting solar energy and enhancing ecosystem carbon sequestration, and offer good example for regions alike. [ABSTRACT FROM AUTHOR]

Renewable energy appears to be the most optimal alternative to fossil fuel and the widely accepted pathway towards the mitigation of climate change. However, the costs of adopting renewable energy are high, and it appears the wealth of nations, the stages of economic development and growth and institutional willingness and quality are important in winning this global challenge. However, there is limited information on the interplay of all the factors that are perceived as critical in moving the world towards the use of renewable energy sources to meet most of the domestic and industrial energy needs. This study investigates the inter-temporal causal relationship between institutions, renewable energy, carbon emissions and economic growth for 45 sub-Saharan Africa countries using annual data for the period 1960–2017. We used the generalised method of moment panel vector autoregression (GMM-PVAR) technique to explore the linkages. From a general perspective, the results reveal that no causal relationship exists between institutions and economic growth, but a bidirectional causality exists between economic growth and renewable energy. Our results indicate that economic growth causes carbon emissions, and institutions are more likely to respond to carbon emissions and renewable energy but prompts no causality exists between carbon emissions and renewable energy. Interestingly, these results differ between countries with different institutional origin. The policy implications are discussed. [ABSTRACT FROM AUTHOR]

Growing concern over climate change mitigation has heightened the search for low-carbon, affordable, and non-intermittent energy alternatives. In this perspective, hydropower, thermal, solar, photovoltaic, and nuclear energy sources fit all these qualities as they are well-known as cleaner and ecosystem-friendly energy sources. However, despite the attractiveness of the clean energy transition, the extant literature has less documentation on the pertinent role of nuclear energy in the "climate change mitigation (SDG-13)" agenda, hence making it difficult to predict nuclear energy-CO 2 emissions (CO 2 e) nexus. Hence, the present study, using IPAT and the "environmental Kuznets curve (EKC)" framework, explores the consequences of nuclear energy generation, population dynamics, and economic progress on CO 2 e in the "United States of America (USA)" by applying a "dynamic autoregressive distributed lag (DARDL)" model from 1973 to 2021. The study provides evidence the existence of the EKC phenomena, suggesting that economic expansion hurts the environment up to a specific threshold level of per capita income, which is identified as US$ 29,581.16. Further empirical findings also show the detrimental effect of population-induced-emission. Remarkably, a 1% rise in nuclear energy generation dwindles CO 2 e by around 0.819%. The outcomes of this research demonstrate that economic growth level, population, and CO 2 emission are entangled. However, there is a need for a collective role from both stakeholders and policymakers in achieving "SDG-13" as well as "clean and affordable energy (SDG-7)" with a paradigm shift of the USA energy portfolio away from fossil fuels to renewables. • The nexus between nuclear energy-population-CO 2 emissions is investigated for USA. • We applied dynamic ARDL simulations model. • Environmental Kuznets Curve (EKC) hypothesis prevails in USA. • Nuclear energy generation dampens the effect of CO 2 emission. • The population induced-emission in both the short- and long-run is observed. [ABSTRACT FROM AUTHOR]

Efforts to avoid the acceleration of global warming have tended to focus on countries with high CO 2 emissions levels and large populations, with a high level of economic development or industrialization. African countries, which often do not conform to such criteria, are more vulnerable to climate change due to their dependence on climate-sensitive industries and their limited infrastructure and technological capacity to cope with its impacts. The long-term economic growth rates projected for Africa's rapid development period will, further, make Africa a potential emission hotspot in the near future. Here, for the first time, we built an energy-related emissions inventory for 19 African countries for 2010–2019, which addresses emissions from 47 economic sectors and 5 energy types, making it the most comprehensive of its kind. The degree of decoupling of economy and emissions, and drivers of CO 2 emission changes are also examined. Most African countries experienced rapid growth in CO 2 emissions, with an average annual growth rate of 5.5% for fossil fuel-related CO 2 emissions and 6.0% for unsustainable biomass-related CO 2 emissions. Only two countries, South Africa and Tanzania, have achieved a strong decoupling of economic growth from CO 2 emissions. Economic and population are the most important drivers of emissions, while energy intensity has been identified as a key factor in mitigating CO 2 emissions, especially for those countries that have reached strong or weak decoupling. The findings from this study provide essential insights that could guide the development of low-carbon policies and strategies in Africa. • We provide energy-related emission inventories for 19 African countries from 2010 to 2019. • African countries experienced rapid growth in CO2 emissions. • Two countries achieved strong decoupling of GDP from CO2 emissions. • Economic and population growth are the most important drivers of emissions. [ABSTRACT FROM AUTHOR]

Renewable energy and institutions have emerged among other variables touted to address climate change problems. However, empirical results have been conflicting. With a relatively poorer state of institutional quality and a lower level of renewable energy development amidst rising carbon dioxide (CO 2) emissions in Africa, the study assesses: a) the direct effect of renewable energy and institutional quality on CO 2 emissions in Africa; and b) the moderation role of institutional quality on the effect of renewable energy on CO 2 emissions in Africa. The study relies on panel data covering 2002–2021 for 32 African countries. The Fully-Modified OLS regression method is employed to analyze the data based on the environmental Kuznets curve (EKC) hypothesis and Stochastic Impacts by Regression on Population, Affluence, & Technology (STIRPAT) model. The results show that urbanization and trade openness increase CO 2 emissions. Although income has a positive effect on carbon emissions, the square term has a negative confirming the EKC hypothesis. Renewable energy also reduces CO 2 emissions. Institutional quality variables of control of corruption, rule of law, regulatory quality, political stability and absence of violence, voice and accountability, government effectiveness and institutional index created from the above indicators reduce CO 2 emissions. In addition, except government effectiveness, the remaining indicators of institutional quality negatively moderate the effect of renewable energy on CO 2 emissions. The results among other things imply that intensifying the development and usage of renewable energy would help address the rising carbon dioxide emissions trend in Africa. Also, strengthening institutions promises to reduce CO 2 emissions. • Determinants of environmental degradation is estimated. • Renewable energy consumption reduces pollution. • Institutions reduce carbon emissions. • Institutions reinforce the effect of renewable energy. [ABSTRACT FROM AUTHOR]

As for the interconnections among 17 UN Sustainable Development Goals (SDGs), reconciling decarbonization (SDG 13) with the needs of economic growth and productive employment (SDG 8) is vital. However, balancing trade-offs between SDG 13 and SDG 8 is complicated by the difficulty of assessing how the interconnections between these two SDGs vary across cities. Here we identified the patterns among CO 2 emissions, economic growth and employment structure across 297 Chinese cities through machine learning. We show that, industrial transitions towards the tertiary sector are not always the optimal option for decoupling economic growth from CO 2 emissions. In contrast, manufacture and construction industries with sustainable technical enhancement can not only promote decoupling but also stabilize social employment. Our study thus has provided novel insights into the city-level interactions between SDG 13 and SDG 8, enhancing the realism of guiding regions to act as a whole for nationwide sustainability improvement. [Display omitted] [ABSTRACT FROM AUTHOR]

The residential sector has been targeted as the one with a huge potential for reducing carbon emissions. In order to determine the present carbon footprint and the potential for achieving carbon neutrality, the study examines electricity consumption in average households, whose electricity is supplied by their national power grids. 31 European countries (27 EU and 4 non-EU countries) were included in this analysis. Our results indicate that the annual carbon emissions of these average households range from 0.09 to 6.44 tCO 2 e (1.36 tCO 2 e on average), depending on a country. In addition, the calculated electricity costs per tCO 2 e emission for an average household vary significantly (from 94 to 10,135 EUR/tCO 2 e).Carbon offsetting is a mechanism which enables households to achieve carbon neutrality, i.e. households can compensate for the emissions caused by their electricity consumption by purchasing voluntary carbon offsets. This study also analyses the financial implications of purchasing voluntary carbon offsets. The results indicate that voluntary carbon offsets do not burden household budgets significantly because their share in total electricity costs is small. European households, particularly those in countries where electricity is more expensive, can comfortably achieve carbon neutrality with voluntary carbon offsets. In this way, they can contribute to global sustainable development. [Display omitted] • Average carbon footprint of grid-connected household in Europe is less than 2 tCO2e. • The cost of electricity per CO2 emissions varies from 94 to 10,135 EUR/tCO2. • Voluntary carbon offset costs in electricity costs vary widely across Europe. • Carbon offsetting is a practical solution for achieving a carbon-neutral household. [ABSTRACT FROM AUTHOR]

Limiting global warming well below 2 °C requires substantial increase in the installation of low-carbon electricity generation technologies (EGTs). EGTs however require several critical materials and materials associated with considerable energy, water and CO 2 emissions. This paper assesses the implications of materials and energy efficiencies for climate change mitigation potential of global energy transition scenarios (GETS). The analysis is carried out using a dynamic material flow-stock model for 21 materials and 15 scenarios combining GETS developed by international organizations including International Energy Agency (IEA) and Greenpeace (GP), materials scenarios, and energy, water, and emissions intensities scenarios. Materials related CO 2 emissions are expected to constitute between 4% and 14% the emissions reported in the IEA Sustainable Development scenario, while expected to be between 10% and 28% in GP Advanced Revolution scenario. Increasing material efficiency and reducing emissions intensities (driven by increasing energy efficiency, renewable technologies in energy supply mix, and recycling) reduce cumulative emissions by 73.2% and 26.3% respectively, while both reduce emissions by 79.5%. Increasing materials efficiency in EGT, energy and water efficiency in mining activities mainly for iron, aluminium, and nickel, and recycling, combined with careful selection of EGTs are significant to realize the full potential of GETS in climate change mitigation. • Materials and energy efficiencies implications for climate change mitigation potential of energy scenarios are assessed. • Dynamic material flow-stock model for 21 materials and 15 combined materials and energy scenarios are used. • Materials related CO 2 emissions constitute between 4% and 14% of emissions reported in IEA Sustainable Development scenario. • Increasing material efficiency and reducing emission intensities reduce cumulative emissions by 79.5%. • Increasing materials efficiency and recycling, and careful selection of EGT are significant for climate change mitigation. [ABSTRACT FROM AUTHOR]

CO 2 emissions from global steel production may jeopardize climate goals of 1.5 °C unless current steel production practices will be rapidly decarbonized. At present, primary iron and steel production is still heavily dependent on fossil fuels, primarily coke. This study aims to determine which decarbonization pathways can achieve the strongest emission reductions of the iron and steel industry in Germany by 2050. Moreover, we estimate whether the German iron and steel industry will be able to stay within its sectoral carbon budgets for a 1.5 °C or 1.75 °C target. We developed three decarbonization scenarios for German steel production: an electrification, coal-exit, and a carbon capture and storage (CCS) scenario. They describe a phase-out of coal-fired production plants and an introduction of electricity-based, low-carbon iron production technologies, i.e. hydrogen-based direct reduction and electrowinning of iron ore. The scenarios consider the age and lifetimes of existing coal-based furnaces, the maturity of emerging technologies, and increasing recycling shares. Based on specific energy requirements and reaction-related emissions per technology, we calculated future CO 2 emissions of future steel production in Germany. We found that under the decarbonization scenarios, annual CO 2 emissions decrease by up to 83% in 2050 relative to 2020. The reductions of cumulative emissions by 2050 range from 24% (360 Mt CO 2) under the electrification scenario up to the maximum of 46% (677 Mt CO 2) under the CCS scenario compared to a reference scenario. This clearly demonstrates that the technology pathway matters. Nevertheless, the German steel sector will exceed its sectoral CO 2 budget for a 1.5 °C warming scenario between 2023 and 2037. Thus, drastic measures are required very soon to sufficiently limit future CO 2 emissions from German steel production, such as, a rapid decarbonization of the electricity mix, the construction of a hydrogen and CCS infrastructure, or early shutdowns of current coal-based furnaces. [Display omitted] • Scenarios for iron and steel production in Germany until 2050 • Adopting new technologies: hydrogen-based direct reduction and electrowinning • Comparison of CO 2 emissions with sectoral carbon budgets for the steel industry • Carbon budget for climate goal of 1.5 °C likely to be exceeded between 2023 and 2037 • Carbon capture scenario achieves lowest CO 2 emissions but has higher energy demand [ABSTRACT FROM AUTHOR]

This study contributed to the environmental research by analyzing the nexus between innovation in climate change mitigation technologies and carbon dioxide emissions in the United States, with the gross domestic product per capita, international collaboration in green technology development, renewable energy consumption, the labor force, and trade openness as control variables from 1990Q1 to 2018Q4. First, the results suggested that renewable energy consumption, innovation in climate change mitigation technologies, and international collaboration in green technology development are significant mitigating and determining factors for carbon dioxide emissions. Second, the findings also indicated that trade openness and gross domestic product per capita were positively associated with carbon dioxide emissions. Third, the Granger causality test results validated the presence of a bidirectional nexus between innovation in climate change mitigation technologies and carbon dioxide emissions, renewable energy consumption and carbon dioxide emissions, and international collaboration in green technology development and carbon dioxide emissions. Fourth, the results validated a one-way causality between gross domestic product per capita and carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Climate change and CO 2 emissions intertwine corporations and society in current political, social, environmental, and economic debates, specifically in Europe. The climate action plan formulated by the European Commission aims to achieve net zero emissions through eco-innovation by 2050. The objective of this study is to investigate the impact of the European eco-innovation index on CO 2 emissions produced by European firms. Using a dataset of 735 firms from 17 European countries listed during 2010–2018, we found a significant negative association between the country-level eco-innovation index and CO 2 emissions directly produced by the European firms. We also found a significant negative association between the eco-innovation index and indirect CO 2 emissions produced by the value chain of these firms. The results provide evidence that via eco-innovation, supportive steps taken by European countries provide a conducive environment for the European firms to adopt eco-innovative strategies that significantly reduce their direct and indirect CO 2 emissions per dollar of their corporate assets and make their value chains eco-friendly. The results also reveal that financial development brings in some environmental monitoring that cultivates a supportive culture for the corporations to promote corporate efforts to reduce CO 2 emissions. • The first study that uses an eco-innovation index, based on 5 dimensions, developed by the European Commission. • We find a negative impact of country-level eco-innovation on the reduction in direct and indirect corporate CO 2 emissions. • Eco-innovation initiatives taken by the European countries are helping European firms in reducing their CO 2 emissions. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel approach to study sector-level potential industrial heat pump applications. • The potential energy savings by electrifying process heat are 325 PJ p.a. in 2050. • The potential CO 2 savings by electrifying process heat are 31 Mt p.a. in 2050. • Electrified process heat supply can already abate 10 Mt of CO 2 p.a. in 2021. • The costs are high due to the large disparity between electricity and fuel prices. Decarbonization of the industrial process heat supply through electrification could contribute significantly to climate change mitigation efforts. In the U.S. industry, thermal processes accounted for more than two-thirds of the total final energy demand in 2021. Cross-cutting electrification technologies like industrial heat pumps are suitable for the process heat supply to several industrial unit operations in a sustainable way while also improving overall energy efficiency. This study employs a bottom-up approach to investigate the techno-enviro-economic potentials of deploying high-temperature and steam-generating heat pumps in the major U.S. food manufacturing sectors in different timeframes. The results show that the annual technical potential energy and CO 2 savings by electrifying process heat supply are 325 PJ (or approximately 20% of the total final energy demand in U.S. food manufacturing) and 31 MtCO 2 (equivalent to the annual CO 2 emissions from over 6 million cars in the U.S.) in 2050, respectively; however, these incur additional costs in each sector. Although there may be individual cost-effective opportunities for electrifying heat supply in specific industrial sites, the overall costs are estimated to be high in the food sectors due to the large disparity between electricity and natural gas prices and low heat source temperatures. To overcome the identified techno-economic barriers, comprehensive action plans for different stakeholders are needed. This study provides novel insights that should inform policymakers' and executives' decisions about the electrification of the current and future U.S. industrial heat supply in relevant industrial sectors. [ABSTRACT FROM AUTHOR]

The manufacturing industry is often caught in the sustainability dilemma between economic growth targets and climate action plans. In this study, a Log-Mean Divisia Index (LMDI) decomposition analysis is applied to investigate how the amount of industrial energy-related CO2 emissions in Latvia has changed in the period from 1995 to 2019. The change in aggregate energy-related CO2 emissions in manufacturing industries is measured by five different factors: the industrial activity effect, structural change effect, energy intensity effect, fuel mix effect, and emission intensity effect. The decomposition analysis results showed that while there has been significant improvement in energy efficiency and decarbonization measures in industry, in recent years, the impact of the improvements has been largely offset by increased industrial activity in energy-intensive sectors such as wood processing and non-metallic mineral production. The results show that energy efficiency measures in industry contribute most to reducing carbon emissions. In the future, additional policies are needed to accelerate the deployment of clean energy and energy efficiency technologies. [ABSTRACT FROM AUTHOR]

In this paper we evaluate whether the US states have been able to achieve convergence in their carbon emission cycles which may be a key factor in taking a leap as regards the development of a US climate change policy. The use of a dynamic unobserved component approach and a time-varying parameter model enable estimation of the short run dynamics of energy convergence over the extended period 1960–2017. To date, this type of analysis has not received enough attention in the literature. The results reveal the existence of cross-state links in the fluctuations of CO 2 emissions, although the degree to which a good part of the states are co-moving is weak. We also find that cyclical convergence patterns differ considerably in both the level and trajectories across the US states. The difficulties in increasing synchronization of the US CO 2 emissions highlight the importance of the states to lead climate change mitigation actions. The present study presents valuable information of interest regarding the short-run characteristics in carbon dioxide emissions, for better understanding of factors affecting CO 2 mitigation policies. Image 1 • Short run characteristics of CO2 emissions convergence at state-level are studied. • We rank US states by the level of cross-state links in CO2 fluctuations. • Cyclical convergence patterns are distinctively different across states. • National environmental initiatives only have transitory effects on CO2 emissions. • Dataset of CO2 emissions covering 1960–2017 at state level is provided. [ABSTRACT FROM AUTHOR]