Impact of electric vehicle charging demand on power distribution grid congestion.

California, a pioneer in EV adoption, has enacted ambitious electric vehicle (EV) policies that will generate a large burden on the state's electric distribution system. We investigate the statewide impact of uncontrolled EV charging on the electric distribution networks at a large scale and high granularity, by employing an EV charging profile projection that combines travel demand model, EV adoption model, and real-world EV charging data. We find a substantial need for infrastructure upgrades in 50% of feeders by 2035, and 67% of feeders by 2045. The distribution system across California must upgrade its capacity by 25 GW by 2045, corresponding to a cost between $6 and $20 billion. While the additional infrastructure cost drives the electricity price up, it is offset by the downward pressure from the growth of total electricity consumption and leads to a reduction in electricity rate between $0.01 and $0.06/kWh by 2045. We also find that overloading conditions are highly diverse spatially, with feeders in residential areas requiring twice as much upgrade compared to commercial areas. Our study provides a framework for evaluating EVs' impact on the distribution grid and indicates the potential to reduce infrastructure upgrade costs by shifting home-charging demand. The imminent challenges confronting California serve as a microcosm of the forthcoming obstacles anticipated worldwide due to the prevailing global trend of EV adoption.

Conflict and uneven development in the multidecade distributed solar energy transition in the United States.

A longitudinal analysis of small-scale solar energy generation in the United States is used to demonstrate how transition studies can explain nonlinearity in multidecade changes of consumption-production systems. Nonlinearity involves uneven development of sustainability innovations with episodes of rapid growth but also periods of slow growth, stalling, or even collapse. Factors that affect the increasing feasibility and attractiveness of small-scale solar include technological improvements, declining costs, and changes in global energy markets. However, a more complete explanation of nonlinearity highlights the importance of a type of systems analysis that also includes strategic action and broader societal and policy changes. Specifically, efforts by the utilities constrained the growth of small-scale solar by weakening policy support because of the perceived threat, but the solar industry and advocates responded with countervailing action in a changing context. As the transition developed, strategic action (including goals, targets, tactics, and coalition partners) changed and became more conflictual. However, by the beginning of the 2020 decade, the development of microgrids, digital technologies, storage, and virtual power plants in combination with net-zero energy policies provided indications of potential for a reconfiguration of the relationship that could be less polarized and conflicted.

Exploring the climate change mitigation potential and regional distribution of agrivoltaics with geodata-based farm economic modelling and life cycle assessment.

Tackling climate change remains a critical challenge for society. Achieving climate neutrality requires a massive expansion of renewable energies such as wind and photovoltaics (PV). Agriculture plays a key role in this context, especially as the expansion of ground-mounted PV systems often leads to land-use conflicts. Agrivoltaics (AV), which combines agricultural and electricity production, can be a solution, but the synergies are particularly dependent on local agronomic conditions. There is also a knowledge gap in how AV expansion impacts greenhouse gas (GHG) emissions at the landscape level and how it contributes to regional emission reduction targets. In this study, we analysed the economic and climate change mitigation impacts of AV expansion pathways in the German state Baden-Württemberg using an integrated land use model and life cycle assessment under the assumption of general rentability of electricity production by AV. We found that implementing AV on 1%-5% of the regions's arable and grassland area reduced the total agricultural gross margin by a maximum of approximately 0.5%. Concurrently, AV implementation reduced GHG emissions by about 1.2 million to 5.9 million metric tons of CO2 equivalent (Mt CO2-eq). Even if this reduction is almost exclusively accounted for in the energy sector, in absolute terms it amounts to more than the current GHG emissions from Baden-Württemberg's agricultural sector (about 4.4 Mt CO2-eq in 2021). In the 5% expansion scenario, almost 90% of the installations were installed on grassland, but this share dropped to 72% when considering landscape quality constraints. Although we found considerable regional disparity, our findings still suggest that AV is an essential component for regional emission reduction targets. These results are particularly relevant for policymakers in spatial planning, agricultural and energy policy.

Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies.

Across the globe, governments are developing policies and strategies to reduce carbon emissions to address climate change. Monitoring the impact of governments' carbon reduction policies can significantly enhance our ability to combat climate change and meet emissions reduction targets. One promising area in this regard is the role of artificial intelligence (AI) in carbon reduction policy and strategy monitoring. While researchers have explored applications of AI on data from various sources, including sensors, satellites, and social media, to identify areas for carbon emissions reduction, AI applications in tracking the effect of governments' carbon reduction plans have been limited. This study presents an AI framework based on long short-term memory (LSTM) and statistical process control (SPC) for the monitoring of variations in carbon emissions, using UK annual CO2 emission (per capita) data, covering a period between 1750 and 2021. This paper used LSTM to develop a surrogate model for the UK's carbon emissions characteristics and behaviours. As observed in our experiments, LSTM has better predictive abilities than ARIMA, Exponential Smoothing and feedforward artificial neural networks (ANN) in predicting CO2 emissions on a yearly prediction horizon. Using the deviation of the recorded emission data from the surrogate process, the variations and trends in these behaviours are then analysed using SPC, specifically Shewhart individual/moving range control charts. The result shows several assignable variations between the mid-1990s and 2021, which correlate with some notable UK government commitments to lower carbon emissions within this period. The framework presented in this paper can help identify periods of significant deviations from a country's normal CO2 emissions, which can potentially result from the government's carbon reduction policies or activities that can alter the amount of CO2 emissions.

Energy poverty in the Energy Community region: Interrogating policy formulation and coverage.

The capacity of the state to develop and implement policy at the complex nexus of energy infrastructure, social inequality and housing is indicative of the political priorities of governing structures and, by extension, the nature of statecraft more generally. We compare and contrast the energy poverty amelioration policies of two former Yugoslav and two post-Soviet states located outside the European Union, but seeking to join its regulatory sphere - Serbia, Montenegro, Ukraine and Georgia - against the background of deep and persistent patterns of domestic energy hardship. We are particularly interested in uncovering the time horizons, socio-technical systems and target constituencies of different policy measures, as well as energy sector-specific responses to the COVID-19 pandemic. We find that most states in the region have done little to address some of the more substantive challenges around improving housing quality, energy efficiency and gender inequality. However, energy poverty is present in the policy lexicon of all case study countries, and Ukraine, in particular, has advanced a number of more sophisticated approaches and programmes.

Impacts of the Inflation Reduction Act on the Economics of Clean Hydrogen and Synthetic Liquid Fuels.

The Inflation Reduction Act (IRA) in the United States provides unprecedented incentives for deploying low-carbon hydrogen and liquid fuels, among other low-greenhouse gas (GHG) emissions technologies. To better understand the prospective competitiveness of low-carbon or negative-carbon hydrogen and liquid fuels under the IRA in the early 2030s, we examined the impacts of the IRA provisions on the costs of producing hydrogen and synthetic liquid fuel made from natural gas, electricity, short-cycle biomass (agricultural residues), and corn-derived ethanol. We determined that, with IRA credits (45V or 45Q) but excluding the incentives provided by other national or state policies, hydrogen produced by electrolysis using carbon-free electricity (green H2) and by natural gas reforming with carbon capture and storage (CCS) (blue H2) is cost-competitive with the carbon-intensive benchmark gray H2, which is produced by steam methane reforming. Biomass-derived H2 with or without CCS is not cost-competitive under the current IRA provisions. However, if the IRA allowed biomass gasification with CCS to claim a 45V credit for carbon-neutral H2 and a 45Q credit for negative biogenic CO2 emissions, this pathway would be less costly than gray H2. The IRA credit for clean fuels (45Z), currently stipulated to end in 2027, would need to be extended or similar policy support would need to be provided by other national or state policies in order for clean synthetic liquid fuel to be cost-competitive with petroleum-derived liquid fuels. The levelized IRA subsidies per unit of CO2 mitigated for all of the hydrogen and synthetic liquid fuel production pathways, except for electricity-derived synthetic liquid fuel, range from $65-$384/t of CO2. These values are within or below the range of the U.S. federal government's estimates of the social cost of carbon (SCC) in the 2030-2040 time frame.

The quest for improved air quality may push China to continue its CO2 reduction beyond the Paris Commitment.

China is challenged with the simultaneous goals of improving air quality and mitigating climate change. The "Beautiful China" strategy, launched by the Chinese government in 2020, requires that all cities in China attain 35 µg/m3 or below for annual mean concentration of PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm) by 2035. Meanwhile, China adopts a portfolio of low-carbon policies to meet its Nationally Determined Contribution (NDC) pledged in the Paris Agreement. Previous studies demonstrated the cobenefits to air pollution reduction from implementing low-carbon energy policies. Pathways for China to achieve dual targets of both air quality and CO2 mitigation, however, have not been comprehensively explored. Here, we couple an integrated assessment model and an air quality model to evaluate air quality in China through 2035 under the NDC scenario and an alternative scenario (Co-Benefit Energy [CBE]) with enhanced low-carbon policies. Results indicate that some Chinese cities cannot meet the PM2.5 target under the NDC scenario by 2035, even with the strictest end-of-pipe controls. Achieving the air quality target would require further reduction in emissions of multiple air pollutants by 6 to 32%, driving additional 22% reduction in CO2 emissions relative to the NDC scenario. Results show that the incremental health benefit from improved air quality of CBE exceeds 8 times the additional costs of CO2 mitigation, attributed particularly to the cost-effective reduction in household PM2.5 exposure. The additional low-carbon energy polices required for China's air quality targets would lay an important foundation for its deep decarbonization aligned with the 2 °C global temperature target.

A novel integrated optimization model for carbon emission prediction: A case study on the group of 20.

Carbon emission is a central factor in the study of the greenhouse effect and a crucial consideration in environmental policy making. Therefore, it is essential to establish carbon emission prediction models to provide scientific guidance for leaders in implementing effective carbon reduction policies. However, existing research lacks comprehensive roadmaps that integrate both time series prediction and analysis of influencing factors. This study combines the environmental Kuznets curve (EKC) theory to classify and qualitatively analyzes research subjects based on national development patterns and levels. Considering the autocorrelated characteristics of carbon emissions and their correlation with other influencing factors, we propose an integrated carbon emission prediction model named SSA-FAGM-SVR. This model optimizes the fractional accumulation grey model (FAGM) and support vector regression (SVR) using the sparrow search algorithm (SSA), considering both time series and influencing factors. The model is subsequently applied to predict the carbon emissions of the G20 for the next 10 years. The results demonstrate that this model significantly improves prediction accuracy compared to other mainstream prediction algorithms, exhibiting strong adaptability and high accuracy.

Key drivers of the textile and clothing industry decarbonisation within the EU-27.

The European Union has identified the Textile and Clothing industry as one of the essential objectives towards carbon neutrality in 2050 in line with the "European Green Deal". There are no previous research papers focused on analysing the drivers and inhibitors of the past greenhouse gas emission changes of the textile and clothing industry in Europe. This paper aims to analyse the determinants of the changes in these emissions, and the disassociation level between emissions and economic growth, throughout the 27 Member States of the European Union, from 2008 to 2018. A Logarithmic Mean Divisia Index that explains the key drivers of the changes in greenhouse gas emissions of European Union Textile and Cloth industry and a Decoupling Index have been applied. The results generally conclude that the intensity and carbonisation effects are key factors that contribute to reducing greenhouse gas emissions. The lower relative weight of the textile and clothing industry throughout the EU-27 was noteworthy, and favours lower emissions, partially counteracted by the activity effect. Also, most Member States have been decoupling the industry's emissions from economic growth. Our policy recommendation shows that if further reductions in greenhouse gas emissions are to be achieved, energy efficiency improvements and cleaner use of energy sources would offset the potential increase in emissions of this industry as a result of a relative increase in its gross value added.

Attitudes toward Wind Power in Norway-Solution or Problem in Renewable Energy Development?

Wind power has become an increasingly important source of renewable energy in Norway. Current demand and production capacity have exceeded expectations stipulated in energy policies a few years back. Wind power affects landscape characteristics, and the rapid development has created considerable public conflict. However, knowledge to date about public attitudes toward wind power development in Norway is limited. We surveyed a representative sample of the Norwegian public to examine relationships between wind power development and place attachment, localization, and policies. We also examined if attitudes toward wind power are linked to broader environmental attitudes and meaning of place. Public attitudes range from strong support to strong opposition. We found limited support for NIMBY effects. Support versus opposition correlates with attitudes toward place attachment, localization of wind power plants and energy policies. We found evidence of a dichotomy between the more fundamental world views of eco-modernism versus de-growth influencing the more specific wind power attitudes. We argue that policy institutions have underestimated the power of attitude diversity in the wind power debate, and that social acceptability of future wind power development will depend on improved understanding of how social values of landscapes are impacted.

GCC Countries Strategic Options in a Global Transition to Zero-Net Emissions.

Using a multi-level perspective approach combined with top-down macroeconomic models, we analyze the situation of the GCC countries in the perspective of a global transition to zero-net emissions before the end of the century. Based on these analyses, we propose strategic and political options for these oil and gas exporting countries. We show that it would be unwise for GCC member states to adopt an obstructionist strategy in international climate negotiations. On the contrary, these countries could be proactive in developing international emissions trading market and exploiting negative emissions obtained from CO2 direct reduction technologies, in particular direct air capture with CO2 sequestration, and thus contribute to a global net-zero-emissions regime in which clean fossil fuels are still used.

How will hydro-energy generation of the Nepalese Himalaya vary in the future? A climate change perspective.

Despite being one of the proven clean-energy technologies, hydroelectricity is losing attention in global research. Hydroelectricity is extremely important for countries possessing the required water resources, already heavily reliant on it and those lacking the financial capacity to invest in other expensive energy technologies. This study assessed the possible impact of climate change (CC) on hydro-energy generation in the Nepalese Himalaya (possessing eight peaks out of 14 over 8000 m) with a tremendous hydropower potential (∼50,000 MW). A planned 1200 MW storage type Budhigandaki Hydroelectricity Project is taken as a case. We estimated the energy generation for the baseline as well as 10 CC scenarios considering RCPs 4.5 and 8.5 at monthly, seasonal, and annual temporal scales for the mid-century. Results show that energy generation is highly dependent on the reservoir operating rule. The average annual energy generation is expected to vary within -5 to +12% of the base case in the mid-century, with significant variations across the months. We also infer that designing hydro-projects based on ensembled climate values could lead to a "rosy" but less probable and risky picture of energy generation in the future. Therefore, assessment of a wide spectrum of plausible CC scenarios are recommended. Storage type projects with provision of flexible operating rules considering finer temporal resolution and allocation to competing users (in case of multipurpose projects) supported by appropriate policies are desirable for climate resiliency. Complementing the existing energy generation mix with other technologies in areas where hydroelectricity is expected to undergo adverse impacts of CC is warranted for attaining future energy security and environmental safeguarding. Possibility of additional energy due to CC is a strong motivation for this region to focus on hydroelectricity development in the future.

Tracking emissions in the US electricity system.

Understanding electricity consumption and production patterns is a necessary first step toward reducing the health and climate impacts of associated emissions. In this work, the economic input-output model is adapted to track emissions flows through electric grids and quantify the pollution embodied in electricity production, exchanges, and, ultimately, consumption for the 66 continental US Balancing Authorities (BAs). The hourly and BA-level dataset we generate and release leverages multiple publicly available datasets for the year 2016. Our analysis demonstrates the importance of considering location and temporal effects as well as electricity exchanges in estimating emissions footprints. While increasing electricity exchanges makes the integration of renewable electricity easier, importing electricity may also run counter to climate-change goals, and citizens in regions exporting electricity from high-emission-generating sources bear a disproportionate air-pollution burden. For example, 40% of the carbon emissions related to electricity consumption in California's main BA were produced in a different region. From 30 to 50% of the sulfur dioxide and nitrogen oxides released in some of the coal-heavy Rocky Mountain regions were related to electricity produced that was then exported. Whether for policymakers designing energy efficiency and renewable programs, regulators enforcing emissions standards, or large electricity consumers greening their supply, greater resolution is needed for electric-sector emissions indices to evaluate progress against current and future goals.

Slouching or speeding toward net zero? Evidence from COVID-19 energy-related stimulus policies in the G20.

This paper analyzes the size and nature of green fiscal stimulus in the G20 countries in response to the COVID-19 crisis, with a focus on the energy-related policies. We exploit a new dataset, the Energy Policy Tracker (EPT), with detailed information on countries' policies since the start of the pandemic. Between January 2020 and December 2021, G20 countries enacted 913 stimulus measures that have direct impacts on energy supply and demand. The average country spent $395 USD per person on energy-related policies. Only 30% of this amount, on average, is devoted to low-carbon measures, mostly in the transit and buildings sectors, with considerable variation across countries. To properly compare countries' efforts in aligning their COVID-19 stimulus with climate goals, we construct a new index, the Green Energy Policy Index (GEPI), using principal components analysis, taking into account both "green" and "brown" stimulus measures. The GEPI varies considerably across countries. We find that on average, countries with a "greener" energy-related stimulus are wealthier and have a lower emission intensity. On average, countries that have experienced the crisis more acutely, both in terms of deaths and gross domestic product (GDP) loss, have "greener" stimulus packages. We discuss the implications of these findings for future research and climate energy policy-making.

Energy Sovereignty: A Values-Based Conceptual Analysis.

Achieving energy sovereignty is increasingly gaining prominence as a goal in energy politics. The aim of this paper is to provide a conceptual analysis of this principle from an ethics and social justice perspective. We rely on the literature on food sovereignty to identify through a comparative analysis the elements energy sovereignty will most likely demand and thereafter distinguish the unique constituencies of the energy sector. The idea of energy sovereignty embraces a series of values, among which we identified: (i) accessibility, to allow access to everyone, (ii) empowerment and recognition, to develop and sustain capabilities to collaboratively produce solution-oriented energy system knowledge and effectively participate in governance, (iii) stewardship and sustainability, to be able to design and manage decentralised renewable systems in view of protecting the environment, (iv) self-sufficiency, to reduce the negative shocks of exploitative business practises, (v) resilience, to maintain production capacities while withstanding socioeconomic, political, environmental and climatic shocks, (vi) peace, to establish production systems that do not involve hostile relations, (vii) transparency and self-determination, to establish democratic decision-making mechanisms that give a voice to previously underrepresented groups and limit corporate takeover (viii) gender-justice, by acknowledging the contributions of women and eliminate barriers to their empowerment. With a conceptual framework of energy sovereignty, we present a rationale that draws on the key values to be considered when formulating policy solutions for the energy sector.

Who owns the German subsurface? Ownership and sustainable governance of the subsurface in Germany.

In 1980, the Federal Mining Act was introduced to govern the use of the German subsurface. By paying royalties, companies can get permission to exploit resources. Yet, there is no official report breaking down the payments for hydrocarbons and lignite, in particular regarding the effectively levied fees. Hence, the objective of this study is to provide an overview of the ownership and paid royalties, and to discuss the sustainable use and management of the German subsurface in the face of ecological, social, and economic impacts of resource exploitation. Our analysis shows that the subsurface is partly state- and partly company-owned. Lignite is almost exclusively privately owned by two companies. In contrast, hydrocarbons are predominantly state-owned. In 2017, on average 13% was paid in royalties for gas and 11% for petroleum. These royalties have minor impact on state budgets. For instance, in the concerned state of Lower Saxony, the levies amount to 189 million € or 0.6% of the state budget. Thus, the state income from royalties is low. However, local communities and property owners have no financial benefits. Finally, to obtain a more sustainable use of subsurface, the current Federal Mining Act must be adapted to account for environmental and social impacts.

Clean energy and (E)SG investing from energy and environmental linkages.

The objectives of this study are to analyze the presence of environmental values in ESG indexes based on the positive value relationship between energy and the environment found in existing studies and to identify the characteristics of environmental, social, and governance (ESG) investments by examining the performance of ESG investments compared to market portfolios, as well as to consider the implications of ESG investment in clean energy policy based on the results of the empirical analysis of this study. This paper contributes threefold. First, using a supply and demand-based pricing model, we propose a new model of the expected return, risk, and performance ratio of the ESG premiums defined by the log price differences between ESG indexes and a market portfolio to analyze how ESG investments perform. Second, based on the empirical findings of this study that the correlation between ESG indexes and energy prices is a decreasing function of the latter in contrast to other environmental assets, this paper suggests that ESG indexes cannot adequately demonstrate environmental values but reflect social and governance values, i.e., (E)SG, in the complementary perspective. Third, using the empirical findings of this study that the information ratio of the ESG premium tends to be positive but declines and approaches zero over time, this paper indicates that although ESG investments can be significant compared to market index investments, the significance is limited because ESG investment performance converges with market portfolio performance. In conclusion, two points should be noted about ESG investing in clean energy policy: given the dilution of environmental values in ESG investing, a clear distinction should be made between ESG investing and renewable energy investing; even if investments in renewable energy projects are treated as ESG investments, reflecting current market trends, we should be prepared for the fact that the superior investment performance due to social and governance values, rather than environmental values, will not last long.

Estimation of end-of-life electric vehicle generation and analysis of the status and prospects of power battery recycling in China.

With the development of the electric vehicle (EV), vehicle end-of-life (EOL) management has become a significant challenge. This study sets two EV sales scenarios (low and high), compares the impact of two battery replacement methods (buying a new vehicle or replacing the battery) on future EOL EV production, and predicts the difference in the amount of EOL EV battery production under two probability functions (normal and Weibull's distributions). The results show that when the EV power battery is retired and the vehicle owner chooses to buy a new vehicle, the predicted scrap quantity under low sales and high sales (HS) scenarios in 2030 is 4.3 and 5.3 million, respectively. Replacing the battery and continuing to use the vehicle will mean fewer EOL vehicles are generated. Considering the construction of an EOL EV battery recycling management system in China is still in the exploratory period, it is necessary to encourage vehicle owners to replace the battery and continue to use the vehicle. Under a HS scenario, the predicted number of EOL EV batteries in 2030 is 3.8-7.4 million. In the next 10 years, the issue of EV recycling should be raised to the same level as the issue of EV popularisation.

Energy policy paradox on environmental performance: The moderating role of renewable energy patents.

The environmental and socioeconomic considerations of energy production have become crucial because of the increasingly complex relationship between energy and the environment. This study aims to develop possible mechanisms for perspectives on energy policy and the environment by exploring the mediating role of renewable energy patents. Non-radial data envelopment analysis and panel data models are applied using the panel data from 2010 to 2017 from 30 Chinese provinces. The results show an overall improvement in the environmental performance index (EPI) of China's provinces, but the average EPI is still relatively weak, with an average value between 0.44 and 0.52, which is far below the optimal value 1.. Furthermore, the econometric model offers evidence that provincial renewable energy and emission reduction policies positively impact the enhancement of EPI. The findings have several implications for energy and environmental policies.

The structure of environmental governance: How public policies connect and partition California's oil and gas policy landscape.

In this paper, we ask how the written composition of public policies structure an environmental governance system. We answer this question using semi-automated text analyses of 22 state-level policies governing oil and gas development in California between 2007 and 2017. The findings portray an environmental governance system that is both partitioned and connected into different focal areas (called "targeted action situations") through certain actors, issues, and rules. We conclude with substantive insights about California's oil and gas governance system, as well as theoretical and methodological contributions for analyzing the composition of public policy to advance knowledge about hybrid governance.