Carbon mineralization with concurrent critical metal recovery from olivine.

Carbon dioxide utilization for enhanced metal recovery (EMR) during mineralization has been recently developed as part of CCUS (carbon capture, utilization, and storage). This paper describes fundamental studies on integrating CO2 mineralization and concurrent selective metal extraction from natural olivine. Nearly 90% of nickel and cobalt extraction and mineral carbonation efficiency are achieved in a highly selective, single-step process. Direct aqueous mineral carbonation releases Ni2+ and Co2+ into aqueous solution for subsequent recovery, while Mg2+ and Fe2+ simultaneously convert to stable mineral carbonates for permanent CO2 storage. This integrated process can be completed in neutral aqueous solution. Introduction of a metal-complexing ligand during mineral carbonation aids the highly selective extraction of Ni and Co over Fe and Mg. The ligand must have higher stability for Ni-/Co- complex ions compared with the Fe(II)-/Mg- complex ions and divalent metal carbonates. This single-step process with a suitable metal-complexing ligand is robust and utilizes carbonation processes under various kinetic regimes. This fundamental study provides a framework for further development and successful application of direct aqueous mineral carbonation with concurrent EMR. The enhanced metal extraction and CO2 mineralization process may have implications for the clean energy transition, CO2 storage and utilization, and development of new critical metal resources.

Metal-Organic Framework (MOF)-Based Clean Energy Conversion: Recent Advances in Unlocking its Underlying Mechanisms.

Carbon neutrality is an important goal for humanity . As an eco-friendly technology, electrocatalytic clean energy conversion technology has emerged in the 21st century. Currently, metal-organic framework (MOF)-based electrocatalysis, including oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), hydrogen oxidation reaction (HOR), carbon dioxide reduction reaction (CO2RR), nitrogen reduction reaction (NRR), are the mainstream energy catalytic reactions, which are driven by electrocatalysis. In this paper, the current advanced characterizations for the analyses of MOF-based electrocatalytic energy reactions have been described in details, such as density function theory (DFT), machine learning, operando/in situ characterization, which provide in-depth analyses of the reaction mechanisms related to the above reactions reported in the past years. The practical applications that have been developed for some of the responses that are of application values, such as fuel cells, metal-air batteries, and water splitting have also been demonstrated. This paper aims to maximize the potential of MOF-based electrocatalysts in the field of energy catalysis, and to shed light on the development of current intense energy situations.

Climate Impacts of Hydrogen and Methane Emissions Can Considerably Reduce the Climate Benefits across Key Hydrogen Use Cases and Time Scales.

Recent investments in "clean" hydrogen as an alternative to fossil fuels are driven by anticipated climate benefits. However, most climate benefit calculations do not adequately account for all climate warming emissions and impacts over time. This study reanalyzes a previously published life cycle assessment as an illustrative example to show how the climate impacts of hydrogen deployment can be far greater than expected when including the warming effects of hydrogen emissions, observed methane emission intensities, and near-term time scales; this reduces the perceived climate benefits upon replacement of fossil fuel technologies. For example, for blue (natural gas with carbon capture) hydrogen pathways, the inclusion of upper-end hydrogen and methane emissions can yield an increase in warming in the near term by up to 50%, whereas lower-end emissions decrease warming impacts by at least 70%. For green (renewable-based electrolysis) hydrogen pathways, upper-end hydrogen emissions can reduce climate benefits in the near term by up to 25%. We also consider renewable electricity availability for green hydrogen and show that if it is not additional to what is needed to decarbonize the electric grid, there may be more warming than that seen with fossil fuel alternatives over all time scales. Assessments of hydrogen's climate impacts should include the aforementioned factors if hydrogen is to be an effective decarbonization tool.

Dynamic role of clean energy and sustainable economic growth in coastal region: Novel observations from China.

China's coastal region is the major geographical unit for the future development of China's industrial sector. The transformation of basic structure to high-class development in China's coastal places is a significant tool for promoting the changes related to quality, power and efficiency in regional economic development. In the 21st century, environmental and energy issues have increased worldwide, and challenges related to environmental pollution, energy crises, and ecological imbalances have emerged. To climate change and energy utilization, the sustainable progress of clean energy is the new route of future energy development. Based on China's non-polluting energy growth process in the last ten years, this article explores China's clean/green energy policies and economic growth development plans. Clean energy utilization is crucial for sustainable development in the context of high-quality economic growth and climate change. However, the monetary evolution and carbon emission are not investigated whole from the clean energy aspects. Using Wind energy sources as the acceptable variable, this paper employs threshold regression and impulse functions to assess the energy consumption and economic growth on carbon emission in 30 Chinese provinces over the 2000 to 2020 period. The Deep Belief Network (DBN) model predicts wind energy utilization and efficiency. The results show that economic development and carbon emissions are connected. Further, growth influences promote the offset of carbon emissions. Green innovation alters the nexus of carbon emissions, and China's economy reduces carbon usage. It provides the decision-making policies for clean energy development.

Impact of public-private partnerships investment and FDI on CO2 emissions: A study of six global investment countries.

This study investigates the impact of public-private partnerships investment in energy and FDI on environmental quality in global investment countries during 1995-2018. Economic growth, technological innovations and consumption of clean energy are also considered as additional determinants of environmental quality. The study applied advanced panel econometric models. Our empirical results affirm the evidence of a long-run association between environmental quality and its determinants. Specifically, economic growth as well as clean energy use improves quality of environment by lowering carbon emissions. Public-private partnerships investment in energy, FDI and technological innovations decrease carbon emissions. Energy consumption (generated from fossil fuel) increases carbon emissions. Heterogeneous causality evidence indicates the presence of a unidirectional causality relation from carbon emissions to public-private partnerships investment in energy and a feedback causality occurs between consumption of clean energy and CO2 emissions. This empirical evidence provides new insights for both policymakers and governments to support public-private partnership investments in energy for the improvement of quality of environment in global investment countries.

Environmentally clean and dirty energy equities during extraordinary global conditions.

I examine which extraordinary international events coincide with pronounced changes in the equity markets for some of the world's largest publicly traded suppliers on opposite sides of the global energy mix - oil and environmentally clean energy companies. First, I adapt an intuitively appealing non-parametric filter to empirically timestamp unexpected and prominent increases and decreases in a wide range of global indicators relevant to the international energy market. Then, I use such extraordinary conditions to characterise the performance of oil and environmentally clean energy equities, and their relationships. My findings suggest that jumps in the global stock market, international crude oil market shocks, and the US dollar real effective exchange rate, are the indicators that define the financial landscape during which considerable gains, losses, and instability across both types of energy markets materialise. In contrast, major elevated uncertainties related to geo-political risk and climate policy reflect relative stability in the equities of both oil and environmentally clean energy companies. Although these results imply that both energy assets are potentially lucrative hedging strategies for investors to exploit during heightened geo-political and climate policy uncertainties, clean energy equities offer market participants the option to combine profit maximising and sustainability objectives while minimising global energy security risks.

ESG practices mitigating geopolitical risks: Implications for sustainable environmental management.

As climate change and geopolitical conflicts intensify, understanding how geopolitical risks affect companies prioritizing Environmental, Social, and Governance (ESG) practices is crucial. This study investigates the dynamic relationship between global geopolitical risks and the performance of Environmental, Social, and Governance (ESG) and non-ESG companies, particularly their influence on green markets. Utilizing a robust methodological framework, including the dynamic time-varying parameters vector autoregression (TVP-VAR) model, and causal impact modeling, we analyze daily financial data from 2021 to 2024. The results reveal a substantial negative impact of geopolitical risks on non-ESG companies, contrasting with the resilience of ESG-committed counterparts. This suggests that ESG-committed companies demonstrate better resilience against geopolitical risks, emphasizing the protective role of ESG practices amid uncertainties. Additionally, the inclusion of ESG companies in green markets diminishes the severity of the negative impact of geopolitical risks, underlining the transformative role of ESG commitment in shaping investor behavior towards sustainable investments. Our findings offer insights for policymakers and investors navigating geopolitical risks and ESG performance, with a focus on environmental management, and provide guidance for effective risk mitigation and investment policies to enhance environmental sustainability.

When do climate change legislation and clean energy policies matter for net-zero emissions?

Achieving the global decarbonization goal under global conflicts is becoming more uncertain. Within this context, this article seeks to examine the effects of global environmental management and efforts to achieve this goal. Specifically, it investigates the role of democracy, control of corruption, and civil society participation as mechanisms that moderate the impact of environmental policy and legislation, particularly clean energy policy and climate change legislation (laws and regulations), on carbon emissions in highly polluted countries. The empirical results show that (i) the effects of democracy-clean energy policies and climate change legislation are relatively small in reducing carbon emissions; (ii) the effect of controlling corruption-climate change regulations is strong in reducing emissions, meaning that governments with higher control of corruption are more effective at enacting and executing laws and regulations dealing with environmental challenges which help achieve desirable environmental outcomes; (iii) strong civil society participation helps the execution of clean energy policies and climate change legislation to curb emissions, and (iv) the robustness check also provides strong evidence that higher control of corruption can contribute to the effectiveness of these policies and legislation in reducing carbon emissions. Overall, these findings suggest that the efficiency of well-designed environmental policy and legislation should be supported by a combination of higher civil society participation and greater control of corruption that can efficiently enforce such policies and legislation.

Assessing the environmental impacts of clean energy investment in Pakistan using a dynamic autoregressive distributed lag model.

In this study, the authors projected the impacts of clean energy investment on environmental degradation by applying a novel and dynamic Autoregressive Distributed Lag (DARDL) model for Pakistan from 1990 to 2022. Most researchers have used ecological footprint or CO2 emissions indicators to look at how clean energy investment affects environmental degradation, which primarily represents contamination induced by humans' consumption patterns and does not consider the impact of the supply side. Against this background, the study scrutinized the dynamic interaction between clean energy investment and environmental sustainability using the load capacity factor (LCF) as an ecological indicator in Pakistan, including economic growth, population density, trade openness, urbanization, and industrialization in the analysis. The long-run estimates from DARDL indicate that a 1 percent upsurge in clean energy investment mitigates environmental degradation by approximately 0.42 percent on average, controlling for other factors. Further, the study also revealed that a 1 percent increase in clean energy investment diminishes dirty energy consumption by approximately 0.45 percent. The validity of the findings is confirmed using alternate methods, i.e., KRLS. The study recommends that Pakistan prioritize investment in clean energy projects to promote environmental sustainability and enforce environmental regulations to reduce the adverse externalities associated with dirty energy activities.

Achieving zero emission targets: The influence of green bonds on clean energy investment and environmental quality.

The effectiveness of green finance in driving clean energy and environmental sustainability in the current era is receiving attention. Therefore, this study proposes an empirical framework highlighting the effects of green bonds (GB) on clean energy investment (CEI), clean energy investment efficiency (CEE) and environmental sustainability of 29 green bond issuing countries between 2014 and 2022. Using system and difference GMM approaches, this study finds that (i) green bond issuance drives clean energy investment. (ii) Green bonds sufficiently enhance the selected countries' environmental quality. These results supplement the promotion of green bonds in increasing the transfer of funds towards renewable energy projects by reducing reliance on fossil fuels. (iii) Using Driscoll & Kraay, Fully Modified-OLS, and changing the dependent variable, this study further supported the idea that green bonds effectively promote the CEE and environmental sustainability of the chosen countries. (iv) Similarly, this study conducted income heterogeneity, showing that green bonds improve high- and middle-income countries' CEI and environmental quality. (v) Finally, the results indicate that resource consumption escalates CO2 emissions by declining the CEI. Technological innovations increase CEI, whereas they do not mitigate CO2 emissions directly, hinting at the requirement for a comprehensive approach. Therefore, inclusive policies on green bond frameworks, robust incentives, and rigorous environmental criteria should be implemented to attract investment in clean energy development and ensure the environmental sustainability of the selected countries.

Guiding clean energy transitions in rural households: Insights from China's pilot low-carbon policies.

The impact of Low Carbon Pilot Policies (LCPPs) on carbon reduction and energy efficiency has been extensively studied. However, the potential of these policies to promote clean energy transition (CET) in rural households remains underexplored. This article constructed a staggered-DID model using data from the China Family Panel Studies (CFPS) to investigate the impact and mechanisms of LCPPs on rural households' CET. The findings indicate that LCPPs significantly enhance the CET among rural households. Moreover, the effects of LCPPs vary across cities, while differences within communities and households are less pronounced. Mechanism analysis reveals that LCPPs facilitate rural households' CET through income effects, infrastructure improvements, and enhanced low-carbon awareness. Notably, the income and low-carbon awareness effects are heterogeneous. Additionally, LCPPs have increased rural households' expenditures on home-cooked meals. We estimate the average fixed cost of the CET for rural households to be approximately $404.495. These insights provide valuable empirical evidence that can guide other countries and regions in promoting CET in rural areas.

Elevating clean energy through sludge: A comprehensive study of hydrothermal carbonization and co-gasification technologies.

This study explores the recycling challenges of industrial sludge, owing to its non-recyclable properties and associated environmental problems. To promote sustainable energy utilization, a novel approach combining hydrothermal carbonization and co-gasification was employed to facilitate the conversion from waste to energy. The industrial sludge was pretreated in the batch-type hydrothermal treatment unit at 180-220 °C, followed by co-gasification. The experimental results indicate that pretreating the sludge at the hydrothermal temperature of 200 °C maximized its thermal decomposition, leading to a rougher structure with obvious cracks, eventually transforming into numerous fragmented small particles. At 1100 °C with a blending mass ratio of 1:1, the sludge hydrochar at 200 °C significantly enhanced the reactivity of coal char, exhibiting the gasification reactivity index R0.9 of 1.57 times higher than that of untreated char. Using the in-situ technique with the heating stage microscope, it was first observed that the addition of pretreated sludge coal chars underwent gasification in the shrinking core mode, displaying a significant ash melt flow phenomenon. Based on the in-situ X-ray diffraction, it was discovered that more amorphous structures were formed by the reaction of Fe with other minerals in the sludge-coal blended char after hydrothermal carbonization at 200 °C. With pretreatment at the hydrothermal temperature of 200 °C, the sludge can increase the specific surface area of the blended char and facilitate the cracking of carbon crystals during co-gasification. Its specific surface area and the Raman spectroscopic ratio ID1/IG were 1.76 and 1.17 times that of coal char, respectively. Collectively, this study highlights the potential for energy recovery from industrial sludge, contributing to sustainable waste management in the chemical industry.

Utilizing support vector machines to foster sustainable development and innovation in the clean energy sector via green finance.

As the global demand for clean energy continues to grow, the sustainable development of clean energy projects has become an important topic of research. in order to optimize the performance and sustainability of clean energy projects, this work explores the environmental and economic benefits of the clean energy industry. through the use of Support Vector Machine (SVM) Multi-factor models and a bi-level multi-objective approach, this work conducts comprehensive assessment and optimization. with wind power base a as a case study, the work describes the material consumption of wind turbines, transportation energy consumption and carbon dioxide (CO2) emissions, and infrastructure material consumption through descriptive statistics. Moreover, this work analyzes the characteristics of different wind turbine models in depth. On one hand, the SVM multi-factor model is used to predict and assess the profitability of Wind Power Base A. On the other hand, a bi-level multi-objective approach is applied to optimize the number of units, internal rate of return within the project, and annual average equivalent utilization hours of the Wind Power Base A. The research results indicate that in March, the WilderHill New Energy Global Innovation Index (NEX) was 0.91053, while the predicted value of the SVM multi-factor model was 0.98596. The predicted value is slightly higher than the actual value, demonstrating the model's good grasp of future returns. The cumulative rate of return of Wind Power Base A is 18.83%, with an annualized return of 9.47%, exceeding the market performance by 1.68%. Under the optimization of the bi-level multi-objective approach, the number of units at Wind Power Base A decreases from the original 7004 to 5860, with total purchase and transportation costs remaining basically unchanged. The internal rate of return of the project increases from 8% to 9.3%, and the annual equivalent utilization hours increase to 2044 h, comprehensively improving the investment return and utilization efficiency of the wind power base. Through optimization, significant improvements are achieved in terAs the global demand for clean energy continues to grow, the sustainable development of clean energy projects has become an important topic of research. In order to optimize the performance and sustainability of clean energy projects, this work explores the environmental and economic benefits of the clean energy industry. Through the use of Support Vector Machine (SVM) multi-factor models and a bi-level multi-objective approach, this work conducts comprehensive assessment and optimization. With Wind Power Base A as a case study, the work describes the material consumption of wind turbines, transportation energy consumption and carbon dioxide (CO2) emissions, and infrastructure material consumption through descriptive statistics. Moreover, this work analyzes the characteristics of different wind turbine models in depth. On one hand, the SVM multi-factor model is used to predict and assess the profitability of Wind Power Base A. On the other hand, a bi-level multi-objective approach is applied to optimize the number of units, internal rate of return within the project, and annual average equivalent utilization hours of the Wind Power Base A. The research results indicate that in March, the WilderHill New Energy Global Innovation Index (NEX) was 0.91053, while the predicted value of the SVM multi-factor model was 0.98596. The predicted value is slightly higher than the actual value, demonstrating the model's good grasp of future returns. The cumulative rate of return of Wind Power Base A is 18.83%, with an annualized return of 9.47%, exceeding the market performance by 1.68%. Under the optimization of the bi-level multi-objective approach, the number of units at Wind Power Base A decreases from the original 7004 to 5860, with total purchase and transportation costs remaining basically unchanged. The internal rate of return of the project increases from 8% to 9.3%, and the annual equivalent utilization hours increase to 2044 h, comprehensively improving the investment return and utilization efficiency of the wind power base. Through optimization, significant improvements are achieved in terms of the number of units, internal rate of return within the project, and annual average equivalent utilization hours at Wind Power Base A. The number of units decreases to 5860, with total purchase and transportation costs remaining basically unchanged, the internal rate of return increases to 9.3%, and annual equivalent utilization hours increase to 2044 h. Energy consumption and CO2 emissions are significantly reduced, with energy consumption decreasing by 0.68 × 109 kgce and CO2 emissions decreasing by 1.29 × 109 kg. The optimization effects are mainly concentrated in the production and installation stages, with emission reductions achieved through the recycling and disposal of materials consumed in the early stages. In terms of investment benefits, environmental benefits are enhanced, with a 13.93% reduction in CO2 emissions. Moreover, there is improved energy efficiency, with the energy input-output ratio increasing from 7.73 to 9.31. This indicates that the Wind Power Base A project has significant environmental and energy efficiency advantages in the clean energy industry. This work innovatively provides a comprehensive assessment and optimization scheme for clean energy projects and predicts the profitability of Wind Power Base A using SVM multi-factor models. Besides, this work optimizes key parameters of the project using a bi-level multi-objective approach, thus comprehensively improving the investment return and utilization efficiency of the wind power base. This work provides innovative methods and strong data support for the development of the clean energy industry, which is of great significance for promoting sustainable development under the backdrop of green finance.

Which productivity can promote clean energy transition -total factor productivity or green total factor productivity?

Developing clean energy is a key pathway and an inevitable choice for achieving the goals of carbon peak and carbon neutrality. From a global perspective, technology is increasingly affecting the trajectory of energy transition, driving clean energy into a stage of rapid development. Therefore, this paper focuses on exploring the dynamic evolutionary characteristics of clean energy transitions driven by different productivity. Using panel data from 171 economies from 1990 to 2019, this paper systematically examines the impact of Total Factor Productivity (TFP) and Green Total Factor Productivity (GTFP) on clean energy transitions. The empirical results indicate that both TFP and GTFP positively impact clean energy transition. Specifically, clean energy consumption increases by 3.35% and 6.03%with a one standard deviation change in TFP and GTFP respectively. Upon decomposing TFP and GTFP, it was found that Green Efficiency Change (GECH) and Green Technical Change (GHCH), especially GECH, are the main factors driving the clean energy transition. Heterogeneity analysis shows that, in developed economies, GTFP has a larger positive impact on clean energy transition than TFP. Furthermore, GTFP demonstrates a significant positive impact on the clean energy transition both before and after the 2008 financial crisis, whereas TFP's positive impact is only evident before the crisis. Our findings emphasize the social benefits of further investments in GTFP.

Price bubbles and Co-bubbles in the green economy market.

In light of growing concerns about climate change and environmental issues, investor interest has surged in the new green economy market. However, the existing literature is limited regarding potential price bubbles and co-bubbles within this new domain. This study examines price bubbles and co-bubbles in the new green economy market, covering 31 indexes classified into three groups: the green economy market and its components, geographical regions, and sectors. Using daily data from August 31, 2005, to May 31, 2024, a test procedure is first applied to detect periods of price bubble in the various indexes, then logistic regressions are employed to examine price co-bubble behaviours. The results show evidence of price bubbles in the green economy market, particularly in solar and wind indexes, with peaks during the COVID-19 pandemic and Russia-Ukraine conflict, whereas the water index is the least prone to price bubbles. Regarding geographical region, the USA market exhibits a higher tendency for price bubbles than the Asian or European markets. Several sectors are resistant to price bubbles. The co-bubble analysis reveals a strong reliance of wind index on price bubbles in the solar and water indexes. Price bubbles in Asia significantly influence price bubbles in Europe and the USA. These findings have implications for investment portfolio management and risk management strategies in the new green economy market.

Magnesium-Based Hydrogen Storage Alloys: Advances, Strategies, and Future Outlook for Clean Energy Applications.

Magnesium-based hydrogen storage alloys have attracted significant attention as promising materials for solid-state hydrogen storage due to their high hydrogen storage capacity, abundant reserves, low cost, and reversibility. However, the widespread application of these alloys is hindered by several challenges, including slow hydrogen absorption/desorption kinetics, high thermodynamic stability of magnesium hydride, and limited cycle life. This comprehensive review provides an in-depth overview of the recent advances in magnesium-based hydrogen storage alloys, covering their fundamental properties, synthesis methods, modification strategies, hydrogen storage performance, and potential applications. The review discusses the thermodynamic and kinetic properties of magnesium-based alloys, as well as the effects of alloying, nanostructuring, and surface modification on their hydrogen storage performance. The hydrogen absorption/desorption properties of different magnesium-based alloy systems are compared, and the influence of various modification strategies on these properties is examined. The review also explores the potential applications of magnesium-based hydrogen storage alloys, including mobile and stationary hydrogen storage, rechargeable batteries, and thermal energy storage. Finally, the current challenges and future research directions in this field are discussed, highlighting the need for fundamental understanding of hydrogen storage mechanisms, development of novel alloy compositions, optimization of modification strategies, integration of magnesium-based alloys into hydrogen storage systems, and collaboration between academia and industry.

Construction of Highly Porous and Robust Hydrogen-Bonded Organic Framework for High-Capacity Clean Energy Gas Storage.

Development of highly porous and robust HOFs for high-pressure methane and hydrogen storage remains a grand challenge due to the fragile nature of hydrogen bonds. Herein, we report a strategy of constructing double-walled framework to target highly porous and robust HOF (ZJU-HOF-5a) for extraordinary CH4 and H2 storage. ZJU-HOF-5a features a minimized twofold interpenetration with double-walled structure, in which multiple supramolecular interactions are existed between the interpenetrated walls. This structural configuration can notably enhance the framework robustness while maintaining its high porosity, affording one of the highest gravimetric and volumetric surface areas of 3102 m2 g-1 and 1976 m2 cm-3 among the reported HOFs so far. ZJU-HOF-5a exhibits an extremely high volumetric H2 uptake of 43.6 g L-1 at 77 K/100 bar and working capacity of 41.3 g L-1 under combined swing conditions, and also impressive methane storage performance with a 5-100 bar working capacity of 187 (or 159) cm3 cm-3 at 270 K (or 296 K). SCXRD studies on CH4-loaded ZJU-HOF-5a reveal that abundant supramolecular binding sites combined with ultrahigh porosities account for its high CH4 storage capacities. Combined with high stability, super-hydrophobicity, and easy-recovery, ZJU-HOF-5a is placed among the most promising materials for H2 and CH4 storage applications.

Metal Phosphorous Chalcogenide: A Promising Material for Advanced Energy Storage Systems.

The development of efficient and affordable electrode materials is crucial for clean energy storage systems, which are considered a promising strategy for addressing energy crises and environmental issues. Metal phosphorous chalcogenides (MPX3 ) are a fascinating class of two-dimensional materials with a tunable layered structure and high ion conductivity, making them particularly attractive for energy storage applications. This review article aims to comprehensively summarize the latest research progress on MPX3 materials, with a focus on their preparation methods and modulation strategies. Additionally, the diverse applications of these novel materials in alkali metal ion batteries, metal-air batteries, and all-solid-state batteries are highlighted. Finally, the challenges and opportunities of MPX3 materials are presented to inspire their better potential in energy storage applications. This review provides valuable insights into the promising future of MPX3 materials in clean energy storage systems.

Recent Advances in Floating Photovoltaic Systems.

In recent years, floating photovoltaic (FPV) technologies have gained more importance as a key source of clean energy, particularly in the context of providing sustainable energy to buildings. The rise of land scarcity and the need to reduce carbon emissions have made FPV systems a cost-effective solution for generating electricity. This review article aims to explore the rapidly growing trend of floating PV systems, which can be a practical solution for regions with limited land areas. The article discusses the structure of the PV modules used in FPV plants and key factors that affect site suitability choice. Moreover, the article presents various techniques for cooling and cleaning FPV to keep optimal performance and discusses feasible trends and prospects for the technology. Finally, this paper proposes the potential integration of FPV systems with other technologies to enhance energy generation efficiency and discusses other research aimed at the advancement of the technology. By examining the various features of FPV systems, this review article contributes to understanding the advantages and challenges associated with using this sustainable energy technology in different regional contexts.

Carbon Mitigation and Environmental Co-Benefits of a Clean Energy Transition in China's Industrial Parks.

Industrial parks are emerging priorities for carbon mitigation. Here we analyze air quality, human health, and freshwater conservation co-benefits of decarbonizing the energy supply of 850 China's industrial parks. We examine a clean energy transition including early retirement of coal-fired facilities and subsequent replacement with grid electricity and onsite energy alternatives (municipal solid waste-to-energy, rooftop photovoltaic, and distributed wind power). We find that such a transition would reduce greenhouse gas emissions by 41% (equal to 7% of 2014 national CO2 equivalent emissions); emissions of SO2 by 41%, NOx by 32%, and PM2.5 by 43% and freshwater consumption by 20%, relative to a 2030 baseline scenario. Based on modeled air pollutant concentrations, we estimate such a clean energy transition will result in ∼42,000 avoided premature deaths annually due to reduced ambient PM2.5 and ozone exposure. Costs and benefits are monetized including technical costs of changes in equipment and energy use and societal benefits resulting from improvements in human health and reductions of climate impacts. We find that decarbonizing industrial parks brings annual economic benefits of US$30-156 billion in 2030. A clean energy transition in China's industrial parks thus provides both environmental and economic benefits.