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Climate change is directly linked to a broad array of changes because of disorganized activities within the economic system and human intervention. Climate change affects the well-being status of both non-living and living things. Relevant policies to mitigate and adapt to climate change conditions concentrate on solutions that intend to use renewable energy instead of fossil fuels or other conventional energy sources. This study aims to process a review focused on how renewables advance environmental quality and create relevant benefits within severe economic activities. This study elaborates on the case of China for two main reasons. First, China has a pivotal role in the economic system worldwide. Second, China is making serious attempts to transition into a low-carbon economy. An integrative review was processed to receive selected publications. The advantage of this process is that it considers empirical and non-empirical studies, policy papers, and conceptual frameworks. Inclusion and exclusion criteria were applied to retrieve the final number of publications. Review results from 39 well-acknowledged Journals provided 180 selected publications categorized into seven study groups: data analyses, model optimization studies, market issues, renewable energy technology publications, nuclear energy publications, ocean energy publications, and policy-related studies. Policy implications concern China's efforts to accelerate the integration of renewables in the energy mix. Hence, the country should increase energy efficiency in consumption and process investment plans based on robust research and development efforts. [ABSTRACT FROM AUTHOR]

As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model. [ABSTRACT FROM AUTHOR]

Among the technologies for the recovery of energy from waste, in particular residual municipal solid waste (rMSW), combustion is the most widely used thermo-chemical treatment process associated with thermal and electric power production by a steam cycle, named, shortly, Waste to Energy (WtE). Today, more than 500 WtE plants in the EU, about 400 in China and 76 in the USA are in operation, based on efficient technologies and advanced air pollution control systems. Energy recovery can be accomplished also by means of gasification; however, the presence of impurities together with the atmospheric pressure, at which syngas is normally produced, impose the feeding of syngas to a conventional steam cycle, leading to generally lower performances than WtE. The energy recovered by WtE offsets traditional energy sources such as fossil fuels and related emissions, providing savings in term of climate change. However, the savings obtainable by replacing electricity and/or heat will diminish as the energy systems will hopefully become increasingly renewable. Over this medium–long-term horizon, one possibility is to capture the CO2 from WtE flue gases and to store/use it. From the life cycle assessment perspective, it has been calculated that the introduction of CO2 capture and storage in WtE, despite energy penalties, is able to reduce the impact on climate change. The alternative approach, proposed to contain the emissions of greenhouse gases in the thermal treatment of waste, is using the carbon contained in it to produce commonly used chemical compounds (waste to chemicals). The benefits, in terms of reductions of greenhouse gases, are expected from the possibility of obtaining chemicals that can replace their analogue normally produced from fossil sources. To date, only one WtC demonstration plant is operating by being fed by rMSW-derived waste, and some similar initiatives are planned, but still adequate assurances in terms of robust knowledge of the involved complex processes, above all, if applied to highly inhomogeneous feed streams such as those obtained from rMSW, are not available. Once the several initiatives come to completion, it will enable waste management professionals to assess performance and to begin to consider such a facility in their planning. [ABSTRACT FROM AUTHOR]

Currently, the world is moving rapidly toward carbon neutrality, and renewable energy technology is very important in carbon neutrality. Among various renewable energy technologies, wind power is attracting much attention due to its sustainability, resource abundance, and high applicability. This study analyzed wind power patents from 2010 to 2021 to derive current global originality and convergence information. For IP5 countries, the growth stages of technology and the patent convergence networks were inferred by time series analysis and an association rule mining algorithm, respectively. The results showed that, during the analysis period, about 5000 patents were applied on annual average, and it was analyzed that China held the most patents at 48%, followed by the US, Europe, Korea, and Japan. According to the technology convergence network of patent codes from all the IP5 countries, patents related to 'wind turbines with rotation axes in the wind direction' occupied a very central position, and 'power conversion electric or electronic aspects' and 'integration of patents related to renewable energy sources in buildings with wind power' were found to show high connection strength. By country, it was analyzed that the US and China showed high patent competitiveness onshore and possessed many 'independent power conversion cluster' technologies. The research hypothesis was that technology development trends can be analyzed and the characteristics of each country can be understood through patent analysis in the wind power field. This hypothesis was analyzed through various patent analysis techniques, and this paper has novelty in that it presents the global megatrend in the wind power field through patent analysis and quantitatively presents the current status of technology development in five major countries. [ABSTRACT FROM AUTHOR]

High-impact weather affects the safety and economic operation of power systems. In this study, to provide regional microclimate of high-impact weather for the local power grid system in the northern Heibei province (known as the Jibei region in China), ERA5-Land global reanalysis data during 1981–2020 with a 0.1° grid size (about 9 km) are adopted to analyze the climate statistics and changes of the disastrous weather that affects the power grids. The results show that there have been significant climate changes in the region, including a temperature increase of about 1 °C, evident humidity and precipitation reductions, for the Jibei region and the six sub-regions that concentrated with wind and solar energy development in the 40 years. Due to the differences in terrain, the climate changes differ significantly among the six renewable energy development regions. The main types of high-impact weather that affect the power grid in the region are heavy fog and icing events, followed by cold waves, snowstorms, and rainstorms. In general, with climate changes in the last several decades, the weather disasters in Jibei region have become more frequent. Since most high-impact weather events have a small scale, it is necessary to simulate the weather processes with high-resolution models to accurately quantify the characteristics of the weather processes that affect the power grid. Therefore, a refined regional meteorological model (with grid size of 2 km) based on four-dimensional data assimilation (JB-FDDA) is established for the Jibei region. With one year of model reanalysis data, we found that JB-FDDA can significantly improve the accuracy of the local meteorological fields, and properly depicted the details of severe weather that affect the power grid operation. This study provide an analytical approach for regional electricity meteorological disasters by using reanalysis data. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are rapidly becoming a sustainable and viable mode of future transportation due to their multitude of advantages, such as reduced CO2 emissions, local air pollutants, and vehicular noise. This study aims to identify and analyze the scientific literature using bibliometric analysis to determine the main topics of authors, their sources, and the most-cited articles, countries, journals, and institutes in the literature on EVs. This bibliometric analysis included scientific work that was published from 2011 to 2022 to provide a thorough analysis of EVs, which will assist researchers and policymakers in understanding the most current global EV advancements. This analysis extracted all bibliometric information about EVs from the Scopus database, collecting 17,150 articles published between 2011 and 2022. The data were sorted for analysis by publication year, document type, author, institute, country, cited author, keyword, and keyword co-occurrence of the EVs. The VOSviewer software was employed to examine the sorted data due to its excellent analysis and visualization capabilities. We used VOSviewer to graphically represent the density, co-occurrence, trends, and linkage of the aforementioned data comprehensibly. The publishing patterns of EVs indicate that the research field is evolving, with a yearly increase in the number of publications. The analysis showed that China, the United States, and the United Kingdom are leading in EV research and large-scale applications. Furthermore, China is the leading country in terms of research institutions and authors involved in EVs. The journal Energies is the most prominent publication periodical. Keyword analysis revealed that during the past decade, EV research has concentrated on battery-management systems, energy storage, charging infrastructure, environmental concerns, etc. The bibliometric study offered pertinent details on the main themes explored concerning EVs and current technological developments. [ABSTRACT FROM AUTHOR]

The site selection plays an important role in the entire life cycle of a tidal power plant (TPP) project. However, some problems decrease the evaluation quality of TPP site selection: (a) suitable and effective methods are scarce since the TPP site selection involves multiple forms of data; (b) there is no comprehensive evaluation index system due to the unilateralism of existing criteria. In this paper, we firstly propose a novel method based on interval number with probability distribution weighted operation and stochastic dominance degree. It takes all stakeholders' preferences into consideration and can simultaneously deal with different forms of data in the TPP site selection; then, a comprehensive evaluation index system for TPP site selection is constructed on the basis of academic literature, feasibility research reports and expert opinions in different fields. It takes the factors of construction conditions, existing policies, social impacts as well as ecological and environmental impacts which reflects the inherent characteristics of TPP site selection fully into account. Finally, a Chinese case study is given to illustrate the applicability and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system for urban low-carbon development from the points of view of economic development and social progress, energy structure and usage efficiency, living consumption, and development surroundings. A weighted sum model was also established. Selecting 12 typical Chinese cities as cases studies, an integrated evaluation was conducted based on the index system and the assessment model. The development speed and limiting factors of different cities were also analyzed. The 12 cities were ultimately classified into three groups in terms of their low-carbon development patterns by integrating all of the analysis results. Furthermore, suitable regulation and management for different patterns were suggested. This study both aids in assessing the executive effect of low-carbon city construction and helps to determine existing problems and suggest effective solutions. [ABSTRACT FROM AUTHOR]

As an important part of the global ecosystem, wetlands and their dynamics greatly influence regional eco-environment systems. To understand the distributions, change processes and temporal-spatial characteristics of the wetlands of the inland river basin in an arid region (Heihe River Basin, HRB), this paper employed multi-source remote sensing data to facilitate multi-temporal monitoring of the HRB wetland using a wetland information extraction method. First, we performed monitoring of these wetlands for the years 2000, 2007, 2011 and 2014; then, we analyzed the variation characteristics of the spatial-temporal dynamics of the wetlands in the HRB over the last 15 years via the landscape dynamic change model and the transformation matrix. In addition, we studied the possible driving mechanisms of these changes. The research results showed that the total area of the HRB wetlands had decreased by 2959.13 hectares in the last 15 years (Since 2000), and the annual average loss was 1.09%. The dynamics characterizing the HRB wetlands generally presented a trend of slow increase after an initial decrease, which can be classified into three stages. From 2000 to 2007, the total wetland area rapidly decreased; from 2007 to 2011, the area slowly decreased; and from 2011 to 2014, the area gradually increased. The dynamic changing processes characterizing the wetland resources were ascribed to a combination of natural processes and human activities. The main driving mechanisms of wetland dynamic changes include climatic conditions, upper reach water inflows, population, water resources, cultivated area, and policy. The findings of this study can served as reference and support for the conservation and management of wetland resources in the HRB. [ABSTRACT FROM AUTHOR]

Green bonds have increasingly been utilized around the world as a source of financing for renewable energy development, designed with compliance requirements and measurable economic returns to investors, while mitigating climate change. However, the efficacy of green bond arranged in the emerging economies for financing renewable energy assets and how the underlying risks are managed have remained to be explored. The paper aims to examine the evolving green financial system sponsored by both public and private institutions in managing such risks within China's emerging economy. A case study of green financing for a bundle of wind power assets led by a state-owned enterprise (SOE) reveals an alternative approach by structuring public–private collaboration while stipulating market-based financial incentives to institutional stakeholders under a political economy. This institutional consortium is composed of a state development bank, a commercial bank, credit rating agencies, institutional and private investors, regional power purchasers, and carbon trading entities. Financial stakeholders' risk in such emerging sustainable investment is moderated by these participating institutions and structured "upsides" from carbon trading aligned with the framework of green finance and standards for green bond development. The results reveal the potentials of scaling up the development of renewable energy by adequately managing and sharing key risks, while allocating substantial funding into renewable energy projects under such a green financial system that is to be complementary with a scalable post COVID-19 economic recovery. [ABSTRACT FROM AUTHOR]

With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020. [ABSTRACT FROM AUTHOR]

Climate change has gained widespread attention, and the rapid growth of the economy in China has generated a considerable amount of carbon emissions. Zhejiang Province was selected as a study area. First, the energy-related carbon emissions from 2000 to 2014 were accounted for, and then the Logarithmic Mean Divisia Index (LMDI) decomposition model was applied to analyse the driving factors underlying the carbon emissions. Finally, three scenarios (inertia, comparative decoupling and absolute decoupling) for 2020 and 2030 were simulated based on the low-carbon city and Human Impact Population Affluence Technology (IPAT) models. The results showed (1) carbon emissions increased by 1.66 times from 2000 to 2014, and trends of carbon emissions were used to divide the study period into three phases (rapid, medium growth and slow decrease phases, with annual growth rates of 12.60%, 4.77% and -1.24%, respectively); (2) the energy intensity effect from 2000-2011 inhibited carbon emissions but was exceeded by the economic output effect, which increased emissions, whereas the energy intensity effect from 2011-2014 outweighed the economic output effect; (3) the scenario analyses revealed that both the comparative and absolute decoupling scenarios would remain consistent with the carbon emissions boundaries in 2020 and 2030, but the comparative decoupling scenario was more reasonable for sustainable development. In addition, appropriate design of emission trading scheme could help to achieve the comparative decoupling by financial incentives. [ABSTRACT FROM AUTHOR]

The conventional typical meteorological year (TMY) based on continuous-year original meteorological records without considering abrupt climate changes (ACC) may not be able to represent a real "typical" climate properly. Consequently, building performance analyses and simulations based on TMY may be not accurate. Current research rarely tackles this issue in TMY development. This paper presents an innovative TMY development with the consideration of ACC in the original meteorological records. It is based on the Chinese standard weather database method (CSWD) with the meteorological records of six Chinese cities in different climate zones. It applies the Moving t-test method to identify and exclude ACC points and to refine the timescales for TMY development. It also depicts the development of individual typical meteorological months again with the ACC impact to improve the accuracy of TMY. The method has been verified in several building energy consumption and thermal comfort analyses. The results demonstrate that the analysis based on the new TMY climate datasets when considering ACC will end up with less energy consumption and better thermal performance compared to the analyses based on the conversion dataset without considering ACC. This experimental research will refine TMY development, and further improve building energy performance analysis and design. [ABSTRACT FROM AUTHOR]

China has committed to ambitious targets to reduce its carbon emissions in the next decades, in order to combat climate change and improve the environment. The realization of the targets depends on the fair and effective mitigation plans of all provinces. However, with varying ecological and environmental conditions and social-economic development, it is a critical issue to quantify the provinces' efforts equally. This paper proposed a comprehensive fE index in coordinating ecology, equity and economy, by accounting for carbon emissions and sinks to characterize provincial carbon emission status in China, from 2000 to 2017, which shows a spatial pattern of "boundary high, central low". The provinces with higher fE value (>1.5) in boundary areas can be seen as "relative equality" provinces with good ecology circulation, equity and economic efficiency. The provinces with lower fE value (<0.7) in central areas around Bohai Bay are regarded as "severe inequality" provinces, and are identified as the hot-spot provinces, which have emitted more CO2 than their equity share by occupying the carbon emission space of other provinces in recent decades. These results could provide a reference for a provincial guide for carbon reduction and sustainable development of the low-carbon economy. [ABSTRACT FROM AUTHOR]

This paper looks at the current state of multilateral development banks (MDBs) for climate change measures and the funding status of those invested in mitigation technology in order to briefly review the current outcome of the technology transfer and financial support. In other words, the aim of this study is to collect and analyze information about the current status of total investment in the field of technology for mitigating GHGs (Greenhouse Gases) from MDBs and identify implications of the status. In this study, a screening technique has been used three times to make a database for project information in the field of mitigation of climate change. So far, based on the finalized DB (Database), mitigation technology projects supported by MDBs have been investigated; based on the result, a connected analysis has been conducted between MDBs, mitigation technology, and countries. According to the derived current status, project support in renewable energy and energy demand areas turned out to be the highest at 75% of the entire mitigation technology. Rather than the renewable energy and energy demand areas where climate technology projects have frequently been performed throughout the world, it was confirmed that long-term climate technology projects for GHG fixation were being performed. According to the results of comparison and analysis of countries with high GHG emissions and their centrality, centrality turned out to be high in the field of GHG fixation in China, the country with the highest GHG emissions. This seems to indicate that countries emitting a substantial amount of GHGs will invest more on projects in the field of GHG fixation as well as on projects on renewable energy. Thus, this study is expected to contribute to understanding the trends of climate technology projects for coping with climate change and using them in establishing future policies on climate technology. In addition, it is expected to be used as a reference for countries with insufficient investment in climate technology despite the high Climate Risk Index (CRI). [ABSTRACT FROM AUTHOR]

The wetland ecosystem in the "Three-River Headwaters" (TRH) region plays an irreplaceable role in water source conservation, run-off adjustment and biodiversity maintenance. In recent years, assessment of wetland resources affected by climate changes has aroused enormous attention, since it can further protect wetland resources and provide a scientific basis for decision makers. In this study, wetland changes and its response to climate changes in the TRH region from the early 1990s to 2012 were analyzed by remote sensing (RS) image interpretation and climate change trend analysis. The results showed that wetlands occupied 6.3% of the total land area in 2012, and swamps, streams & rivers and lakes were the dominant wetland types in the TRH region. Since the early 1990s, wetlands have undergone great changes, and total wetland area increased by 260.57 km2 (1.17%). Lakes, reservoir & ponds took on continuous increasing trend, but swamps, streams & rivers had a continuous decreasing trend. On the other hand, the wetland area in the Yangtze River basin showed an overall increasing trend, while in the Yellow River and Langcang River basins, it decreased in general. The climate turned from Warm-Dry to Warm-Wet. The average temperature and precipitation increased by 0.91 °C and 101.99 mm, respectively, from 1990 to 2012, and the average humidity index (HI) increased by 0.06 and showing an upward trend and a shifting of the dividing line towards the northwest in both the areas of semi-humid and semi-arid zone. The correlation analysis of wetland changes with meteorological factors from 1990 to 2012 indicated that the regional humidity differences and the interannual variation trend, caused by the change of precipitation and evaporation, was the main driving factor for the dynamic variation of wetland change in the TRH region. In the general, the increase of HI in the THR region since the 1990s, especially in the western TRH region, contributed to wetland increase continuously. The conclusions of this study will provide some scientific references for the management and protection of wetlands in the TRH region, especially for restoration, reconstruction and conservation of degradation wetland. [ABSTRACT FROM AUTHOR]

In the Carboniferous–Permian period, several organic-rich black shales were deposited in a marine–continental transitional environment in the Linfen area on the eastern margin of the Ordos Basin. Integrated sedimentological and organic geochemical analyses are performed on an outcrop in order to clarify the relationship between paleoenvironment and organic matter accumulation. The results of this study show that the marine–continental transitional strata of the Upper Carboniferous Benxi Formation to Lower Permian Taiyuan and Shanxi Formation exposed in the Linfen area are composed of sandstone, shale, coal, and limestone. Total organic carbon (TOC) contents of the studied samples were mainly distributed in the range of 0.59–35.4%, with an average of 7.32%. From Benxi Formation to Shanxi formation, the humidity gradually increased, and the climate gradually changed from hot and humid to warm and humid during Carboniferous to Permian. The deposition of the Shanxi Formation ended with the climate returning to hot and humid, having an oxic−suboxic conditions and a high paleoproductivity. Paleoredox conditions and paleoproductivity are the two vital factors controlling the formation of organic matter in black shales. The transitional environment characterized by oxic−suboxic, relatively high deposition rate, and various source of organic matter, although different from the marine environment, provides a good material basis for the deposition of organic-rich shales. [ABSTRACT FROM AUTHOR]

The development and utilization of wind energy has alleviated the problems of energy shortage and environmental pollution; however, it caused many negative impacts due to suboptimal site selections. This study proposes an innovative method integrating Geographic Information System (GIS), fuzzy Analytic Hierarchy Process (FAHP), and fuzzy VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) for site selection of wind farms in the Wafangdian region, China. The uncertainties caused by subjective judgments of the stakeholders were tackled by the FAHP method firstly, where weight values of six criteria were identified. Next, the fuzzy VIKOR method and GIS tool were used to generate the Qi value of each location for ranking their appropriate degrees for wind energy development. The results demonstrated that the middle and upper parts of the studied area are suitable for the exploitation of wind energy, while the central and eastern areas are unfavorable. The influences exerted by various weight combinations and climate change on a site suitability assessment were examined. The resulting comparison with existing wind farms reflected the practicability and reliability of the proposed method; the estimation of climate change impacts on site selection provided the suggestion and support of a long-term plan for wind power development, and even the energy structure adjustment scheme adapted to climate change. [ABSTRACT FROM AUTHOR]