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To address the issue of marine pollution caused by microplastics, the Japanese government started charging for plastic shopping bags in July 2020 and the Plastic Resource Recycling Promotion Law (PRRPL) was passed in April 2022, thereby discouraging plastic use in Japan. However, even before these laws and regulations were established, companies and offices had begun starting to make voluntary efforts to reduce plastic use. Among these efforts, this study focused on the shift from plastic to paper materials and company efforts to lower plastic use. This study aimed to investigate the impact of the social perception of marine plastic pollution since 2018 on companies' adoption of paper materials for containers and packaging. The companies reviewed may have used up to 236,699 tons of paper materials instead of plastic since 2018. This reduction in plastic consumption is expected to decrease emissions by up to 625,424 tons of carbon dioxide (tCO2) annually, as well as external costs by up to 180.7 million yen. Hence, the shift from plastic to paper materials through firms' voluntary efforts since 2018 has helped to reduce plastic use and ameliorate the effects of global warming. [ABSTRACT FROM AUTHOR]

Large-scale use of plastic grocery bags presents a significant burden on the environment, where paper bags are considered a popular alternative to plastic bags. However, it is important to assess the environmental impacts of both types to avoid adverse consequences of use of alternatives on false sense of benefits. Using life cycle assessment tool, this research investigates environmental impacts of two types of single use grocery bags (plastic and paper) commonly used in supermarkets in Sri Lanka. The results reveal that, under the framework considered in the study, the overall environmental impact of plastic bags is lower than that of paper bags. However, when considering the individual impact categories, plastic bags are relatively more detrimental for global warming, ionizing radiation, terrestrial ecotoxicity, freshwater ecotoxicity, marine ecotoxicity, human non-carcinogenic toxicity, mineral resource scarcity and fossil resource scarcity. On the other hand, paper bags yield adverse impacts on stratospheric ozone depletion, ozone formation: human health, ozone formation: terrestrial ecosystems, fine particulate matter formation, terrestrial acidification, freshwater eutrophication, marine eutrophication, human carcinogenic toxicity, and water consumption. Raw material extraction, bag production and end-of-life stages are the most influential life cycle stages of both bag types. [ABSTRACT FROM AUTHOR]

Climate change and the resulting higher frequency of extreme weather events have a direct negative impact on mental health. Natural disasters are particularly associated with an increase in the prevalence of depression, anxiety and posttraumatic stress disorder. Indirect consequences of climate change, such as food shortages, economic crises, violent conflicts and forced migration, additionally represent severe psychological risk and stress factors. Climate anxiety and solastalgia, the distress induced by environmental change, are new psychological syndromes in the face of the existential threat posed by the climate crisis. Accordingly, a sustainable psychiatry must prepare for increasing and changing demands. The principles of psychiatric treatment need to focus more on prevention to reduce the overall burden on the healthcare system. Waste of resources and CO2 emissions in psychiatric treatment processes as well as infrastructure must be perceived and prevented. Psychiatric education, training and continuing education concepts should be expanded to include the topic of climate change in order to comprehensively inform and sensitize professionals, those affected and the public and to encourage climate-friendly and health-promoting behavior. More in-depth research is needed on the impact of climate change on mental health. The DGPPN becomes a sponsor and aims for climate neutrality by 2030 by committing to climate-friendly and energy-saving measures in the area of finance, in relation to the DGPPN congress as well as the DGPPN office. [ABSTRACT FROM AUTHOR]

The diagnosis of dengue infection is still a critical factor determining success in the clinical management and treatment of patients. Here, the development of microfluidic paper-based analytical devices (μPADs) utilizing a sandwich immunoassay on wax patterned paper functionalized with anti-dengue NS1 monoclonal antibodies for point-of-care detection of dengue NS1 (DEN-NS1-PAD) is reported. Various assay conditions, including the length of the channel and diluent, were optimized, and the response detected by the naked eye and digitized images within 20–30 min. The DEN-NS1-PAD was successfully tested in the field for detecting dengue NS1 in buffer, cell culture media, and human serum. The limit of detection (LoD) of the DEN-NS1-PAD obtained with the naked eye, scanner, and a smartphone camera was 200, 46.7, and 74.8 ng mL−1, respectively. The repeatability, reproducibility, and stability of the DEN-NS1-PAD were also evaluated. High true specificity and sensitivity in the serum of pediatric patients were observed. These evaluation results confirm that the DEN-NS1-PAD can potentially be used in point-of-care dengue diagnostics, which can significantly impact on the spreading of mosquito-borne diseases, which are likely to become more prevalent with the effects of global warming. [ABSTRACT FROM AUTHOR]

Purpose: Pulp and paper manufacturing constitutes one of the largest industry segments in term of water and energy usage and total discharges to the environment. More than many other industries, however, this industry plays a key role in sustainable development because its most important raw material, wood fiber, is renewable Dias and Houtman (Environ Prog 23(4):347-357, ). Actually, even if the communication is dominated by electronic media, paper-based communication has a role to play due to its unique practical and aesthetic qualities. This research aims to assess the environmental impact of advertising folders produced with different papers and distributed by a system of Italian consumers' cooperatives in order to indicate the possible options of improvement and to assess the CO emitted during the entire life cycle. Methods: Life cycle assessment (LCA) was performed from cradle-to-grave considering paper production, transport from paper mill to printing site, printing, distribution, and disposal. Data for the study were directly collected from specific companies and completed on the basis of literature information. The analysis was conducted using the SimaPro 7.1.5 software and IMPACT 2002+ method to assess all its environmental impact and damage categories. Results and discussion: LCA analysis indicates that the higher environmental impact is mainly due to paper production and printing processes. The main operations which generate the major impact in the paper production stage are related to the direct or indirect fossil energy use, the production of additives for bleaching operations, and the collection and selection of waste paper. Printing causes relevant impacts for the electricity and ink production and for the aluminum plates used in the offset printing. Moreover, the use of paper with low quantity of additives and small amount of primary fibers causes a reduction of the environmental load of 13.94 %. The major global warming potential value was found for advertising folders made with little amount of mechanical pulp which slightly contributes to the absorption of CO. Conclusions: The analysis pointed out the relevance of the paper production phase and of the printing step within the advertising folders life cycle and allowed to detect the other critical stages of the life cycle. Paper composition greatly affects the environmental impact of the advertising folders' life cycle. [ABSTRACT FROM AUTHOR]

The impact of climate change on the Earth's environments has been widely discussed, although there is still little consensus on the degree of influence, and to what extent the effects are positive, negative or neutral. Predicting the impacts of climate change on organisms and their response to this process has been a growing challenge for ecologists in recent years. In this review, we surveyed the published research on the relationship between lizards and global climate change. We surveyed the keywords "climate change" and "warming", combined with "lizard*" (there is, all words with this prefix), in three reference databases. We identified 401 relevant papers, and analyzed in further detail the group of studies (59 papers, 14.7% of the total) that developed thermoregulatory models to predict the persistence of lizards in a scenario of global warming. These 59 papers focused on species of 13 lizard families found on five continents. Overall, 62.5% of the papers that predicted the impacts of climate change on lizards indicated negative effects, while 21.9% reported positive effects, and 15.6%, a neutral scenario. The lizards identified as the most vulnerable to warming were tropical, viviparous, and thermoconformers, whereas species adapted to cooler climates would be the most likely to benefit from warming. On a broader scale, however, this scenario would lead to competition between lowland and highland lizards, for example, for thermally favorable areas. We conclude that it will be important to develop more detailed models that contemplate the specific features of each group for the development of more reliable predictions, in addition to the need for social conservation projects and the systematic identification of priority areas for conservation. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this research is to identify at what extent e-book reading reduces global warming potential (GWP) of book reading activities relative to that of reading only paper books. Past studies assume e-books and paper books are interchangeable during consumption, but adopting e-book reading can alter reading patterns in reality. This research comparatively assessed the GWP of reading only paper books and that of reading pattern of after e-reader adoption of consumer segments.Methods: We computed GWP of book reading activities of consumer segments that include a life cycle of paper book, e-book, and e-book reading device. Two e-book devices were considered: a designated e-book device (e-reader) and a tablet. The functional units are book reading activities per person and per person-book, which account the number of books purchased or acquired and the reading hours per person. We collected data through a web survey in the USA. Consumer segmentation was performed by analyzing the level of importance in the aspects of book reading activities as a measurement variable. To observe the changes in reading patterns upon e-reader adoption within the same population, we conducted a 3-month social experiment involving e-readers in the USA.Results and discussion: Adopting e-readers was discovered to reduce both the GWP per person and the GWP per person-book of book reading activities. The GWP of e-books read with an e-reader and the GWP of paper books were found to break even at 4.7 books per year, provided consumers read less than 11 h a day. According to the web survey, e-reader users purchase more than seven e-books annually on average, which resulted in a smaller GWP per person-book relative to that of one paper book. Furthermore, the GWP per person in the social experiment was smaller for e-reader adopters than those who only read paper books because they substituted e-books for paper books. The overall book reading volume remains unchanged upon e-reader adoption.Conclusions: Adoption of e-readers reduces the GWP from book reading activities with only paper books, provided more than 4.7 paper books are substituted by e-books annually, and provided consumers’ total consumption volume remain unchanged. E-reader adopters read sufficient number of e-books to break even with paper books. However, most e-reader adopters are yet to fully abandon paper books for e-books. Analyzing the differences in the reading experience between e-books and paper books is a future task. [ABSTRACT FROM AUTHOR]

The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale. [ABSTRACT FROM AUTHOR]

Over the past decades, three major challenges to marine life have emerged as a consequence of anthropogenic emissions: ocean warming, acidification and oxygen loss. While most experimental research has targeted the first two stressors, the last remains comparatively neglected. Here, we implemented sequential hierarchical mixed-model meta-analyses (721 control-treatment comparisons) to compare the impacts of oxygen conditions associated with the current and continuously intensifying hypoxic events (1-3.5 O 2  mg l -1 ) with those experimentally yielded by ocean warming (+4 °C) and acidification (-0.4 units) conditions on the basis of IPCC projections (RCP 8.5) for 2100. In contrast to warming and acidification, hypoxic events elicited consistent negative effects relative to control biological performance-survival (-33%), abundance (-65%), development (-51%), metabolism (-33%), growth (-24%) and reproduction (-39%)-across the taxonomic groups (mollusks, crustaceans and fish), ontogenetic stages and climate regions studied. Our findings call for a refocus of global change experimental studies, integrating oxygen concentration drivers as a key factor of ocean change. Given potential combined effects, multistressor designs including gradual and extreme changes are further warranted to fully disclose the future impacts of ocean oxygen loss, warming and acidification.

In this paper, an electric servo actuator implementation scheme with an energy recovery link is proposed to address the potential energy being wasted when a load falls. The new electric servo actuator recovers the potential energy dissipated during the load-falling progress by using an accumulator. The accumulator can also provide extra thrust when the load is lifted. Moreover, a dynamic model is established based on the theory of power bond graphs to analyze the dynamic and energy consumption characteristics of the new electric servo actuator. The simulation results show that the new electric servo actuator can significantly reduce the required motor power and effectively recover the potential energy of the load. This achievement is very significant for improving the energy efficiency of electric servo actuators and mitigating global warming. In addition, the modeling method used in this paper has important reference significance for the energy consumption analysis of other mechanical systems with complex energy domains. [ABSTRACT FROM AUTHOR]

Among papers stating a position on anthropogenic global warming (AGW), 97 % endorse AGW. What is happening with the 2 % of papers that reject AGW? We examine a selection of papers rejecting AGW. An analytical tool has been developed to replicate and test the results and methods used in these studies; our replication reveals a number of methodological flaws, and a pattern of common mistakes emerges that is not visible when looking at single isolated cases. Thus, real-life scientific disputes in some cases can be resolved, and we can learn from mistakes. A common denominator seems to be missing contextual information or ignoring information that does not fit the conclusions, be it other relevant work or related geophysical data. In many cases, shortcomings are due to insufficient model evaluation, leading to results that are not universally valid but rather are an artifact of a particular experimental setup. Other typical weaknesses include false dichotomies, inappropriate statistical methods, or basing conclusions on misconceived or incomplete physics. We also argue that science is never settled and that both mainstream and contrarian papers must be subject to sustained scrutiny. The merit of replication is highlighted and we discuss how the quality of the scientific literature may benefit from replication. [ABSTRACT FROM AUTHOR]

The global warming caused by greenhouse gas emissions has received widespread attention from all around the world. In this regard, how to calculate the carbon footprint (CF) scientifically and accurately produced by human activities to achieve emission reduction goals has been widely discussed by scholars. In recent years, related research on this issue has increased, leading to a significant expand in the number of publications. It is necessary to excavate and summarize the current development status and possible future trends of this field based on quantitative methods. To achieve this goal, this paper develops a main path analysis (MPA) of the entire field and three research sub-topics (agriculture, energy fuels, and business economic) based on the 4973 papers extracted from Web of Science (WoS) database. The results show that the CF domain mainly focuses on optimizing the CF calculation methods from a theoretical perspective to improve the accuracy of estimation. Furthermore, scholars engaged in the agricultural research mainly focus on adjusting the life cycle assessment (LCA) model, which has advantage on microlevel CF accounting, according to actual needs to achieve more accurate predictions, while researchers who pay attention to the topic of business economic are committed to improving the input–output model, which is suitable for meso and macro analysis, to enhance accounting accuracy. In general, this article is beneficial for presenting the intellectual structure and knowledge diffusion trajectories of the CF domain from horizontal and vertical perspectives. [ABSTRACT FROM AUTHOR]

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

The unflinching upsurge in global warming has put the world into a state of disarray, and policymakers are not sure of what the future holds for the ecosystem. To get the global environment back on track of sustainability, efforts are relentlessly emanating from both developed and developing economies to identify the hindering and enhancing factors. Given the preceding narratives, this paper investigates the tripartite impacts of renewable and nonrenewable energy, trade openness, and institutions on sustainable environment in 54 African countries from 1996 to 2019. The study employs the two-step system generalized methods of moment (SYS-GMM) in estimating the effects of the regressors on four indicators of sustainable environment. Six findings are prominent from the study. First, nonrenewable energy (NRE) and trade openness (TO) hinder sustainable environment, while renewable energy enhances it. Second, the unconditional impacts of institutions drive the path to a sustainable environment. Third, the interaction of institutions with NRE and TO hinders sustainable environment. However, after conducting institutional enhancement estimations, the interactive terms became supportive of sustainable environment. Fourth, the thresholds are policy-relevant across the specifications. Specifically, a 31.11% utilization of nonrenewable energy and 43.75% openness to trade contribute to a sustainable environment. Sixth, the impacts of economic growth and its square empirically support the inverted U-shaped EKC. This study suggests the adoption of carbon-taxing on nonrenewable energy products, price-subsidization for renewable energy goods and services, and institutional quality reforms as pathways towards achieving a sustainable environment in Africa. [ABSTRACT FROM AUTHOR]

In recent decades, the atmospheric moisture capacity has increased globally in concert with global warming, with a particularly notable warming trend in Arctic regions. However, due to limited observational data, the variation and causes of polar precipitation, especially large-scale precipitation events associated with Arctic cyclones, remain unclear. In this paper, GPM satellite data are compared with ERA5 reanalysis data to explore the characteristics of summer precipitation at the northern margin of the Eurasian region (NMER) and the influence of cyclone activity on precipitation. It is revealed that high precipitation values in the Arctic region, as indicated by the GPM and ERA5 data, are mainly concentrated at the NMER. However, the GPM data show an overall larger precipitation amount, while the station observations more closely agree with the ERA5 precipitation changes at the NMER. The cyclone identification results indicate that summer cyclones at the NMER are mainly distributed in the Barents, Kara and Laptev Seas, and the precipitation contribution rate of ERA5-derived cyclones is 37.35%, which is significantly higher than that of GPM-derived cyclones (29.47%). Furthermore, high cyclone activity results in more intense precipitation, with the top 5% of the strongest cyclones contributing 60% (GPM) and 40% (ERA5) to the total cyclonic precipitation. [ABSTRACT FROM AUTHOR]

The 2015 Paris Agreement has set out the climate change target of limiting global warming to 1.5 °C, which poses a serious challenge to countries to reduce emissions. As the world's largest carbon emitter, promoting the realization of the "dual-carbon" goal is the key to realizing China's green transformation and high-quality development. Chinese asset managers play active roles in the capital market as an important channel of asset allocation. Currently, the vast majority of Chinese asset managers hold high percentages of high-carbon industries in their portfolios, and lack quantitative data of their carbon footprints embodied in equity investments, which faces huge carbon-related risks. Therefore, it's an urgent need to comprehensively and scientifically measure financed emissions of Chinese asset managers, which is of great significance for asset managers' carbon risk management and sustainable investment. This paper develops a detailed inventory of carbon emissions for equity portfolios managed by Chinese asset managers from 2010 to 2020, which stands as a pivotal reference for in-depth analysis of emission characteristics. [ABSTRACT FROM AUTHOR]

Biodiversity reserves are a crucial in-situ method to conserve biodiversity hotspots as they are sensitive to climate change. The Nanda Devi Biosphere Reserve (NDBR) in the western Himalayas is enriched with diverse endemic flora and fauna and endorses the second-highest mountain peak in the world. However, in the recent decade, this region has potentially warmed at an alarming rate. With 36 temperature and precipitation indices from high-resolution 40-year data from ERA5 reanalysis and CHIRPS, this paper assesses the state of warming and extreme climatic events. Apart from the indices, Landsat (NASA/USGS, USA) and QuickSCAT (ISRO, India) were utilized to assess the region's response to climate change. An increase of 0.73ºC in the last decade for minimum, 0.26°C for maximum temperatures was observed, with the highest anomaly of 1.7°C in 2016. The reserve's vegetation pattern has changed with the vegetative region's dispersal towards the north and higher elevations. In the year 2000, the area without any vegetation covered 79% of the total area, which declined to a mere 23.8% in the year 2020, equivalent to a 70% decline in the area. Similarly, the area with very dense region covered only 0.02% of the total area in the year 2000, and in the year 2020, it increased to 109%. Snow cover seems to be worst affected in the region with dense snow cover declining maximum by 2020. From coverage of 12.3% of the total area of the reserves, it was reduced to a mere 0.02%, showing a decline of nearly 100% in the region. Our findings show that although protected areas are meant to be resilient to external anthropogenic intrusions, they are highly susceptible to the intrinsic forces of induced climate change. We suggest that reserve managers enable robust measures to identify the distribution of vulnerable species and introduce new methods to preserve the pristine hotspot region. [ABSTRACT FROM AUTHOR]

As many business activities—especially those associated with the energy-intensive industries—continue to be major sources of greenhouse gas emissions, and hence significantly contributing to global warming, there is a perceived need to identify ways to make business activities eventually carbon neutral. This paper explores the implications of a changing climate for the global tourism business and its intertwining global aviation industry that operates in a self-regulatory environment. Adopting a bibliometric analysis of the literature in the domain of global tourism and climate change (772 articles), the paper reveals the underlying sustainability issues that entail unsustainable energy consumption. The aviation industry as a significant source of carbon emission within the sector is then examined by analyzing the top 20 largest commercial airlines in the world with respect to its ongoing mitigating measures in meeting the Paris Agreement targets. While self-regulatory initiatives are taken to adopt Sustainable Aviation Fuels (SAF) as alternative fuel production and consumption for drastically reducing carbon emission, voluntary alignment and commitment to long-term targets remain inconsistent. A concerted strategic approach to building up complementary sustainable infrastructures among the global network of airports based in various international tourist destination cities to enable a measurable reduction in carbon emission is necessary to achieve a transformational adaptation of a business sector that is of essence to the recovery of the global economy while attempting to tackle climate change in a post-COVID-19 era. [ABSTRACT FROM AUTHOR]

Global warming has endangered the natural ecosystem's balance, as well as human existence and development, and it is mostly caused by carbon dioxide. Identifying carbon emission characteristics and predicting carbon emission reasonably is helpful to provide indication for the effective design of emission reduction path. The most literature use a single prediction model; this paper predicts carbon emission using a number of strategies based on previous research. Considering the prediction accuracy, advantages, and disadvantages of each method, a new method combining autoregressive integrated moving average (ARIMA) model and NAR neural network (NAR-NN) is proposed; in addition, this paper attempts to explain the carbon emission characteristics and emission reduction paths of each region from the new perspective of clustering. First, the results show that China's carbon emission features can be divided into four categories: low-carbon demonstrative type, low-carbon potential type, high-carbon developed type, and high-carbon traditional type. Moreover, low-carbon demonstrative type includes merely Beijing and Shanghai, low-carbon potential type is distributed in the southeast coastal areas of China, the high-carbon developed type is mainly distributed in Northeast China, and the western region basically belongs to high-carbon traditional type. Second, ARIMA model and NAR-NN are the two best methods in terms of prediction effect, and the combined model has better prediction effect than the single model. Third, carbon emissions in most regions of China will increase in the next few years; the time of carbon peak in the east is earlier than that in the west regions of China. Beijing will probably be the first region in China to complete the carbon peak. Besides, there is a certain correlation between the carbon peak time and the type of carbon emission in each region. [ABSTRACT FROM AUTHOR]

Kirschbaum (Mitig Adapt Strat Glob Change 11:1151-1164, 2006) explores the climatic impact over time of temporarily sequestering carbon from the atmosphere. He concludes that temporary storage of carbon in the terrestrial biosphere ''achieves effectively no climate-change mitigation''. His strongly worded statement begs for a response. This paper argues that Kirschbaum's conclusion is an artifact of the specific perspective of his analysis and his choice of a definition for climate-change impact. Even temporary sinks put us on a lower path for climate change, a path that will not otherwise be accessible. For carbon sinks in the terrestrial biosphere, we argue that sooner is better and longer is better, but even known temporary sinks have value. [ABSTRACT FROM AUTHOR]

It is essential to predict carbon prices precisely in order to reduce CO2 emissions and mitigate global warming. As a solution to the limitations of a single machine learning model that has insufficient forecasting capability in the carbon price prediction problem, a carbon price prediction model (GWO–XGBOOST–CEEMDAN) based on the combination of grey wolf optimizer (GWO), extreme gradient boosting (XGBOOST), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is put forward in this paper. First, a random forest (RF) method is employed to screen the primary carbon price indicators and determine the main influencing factors. Second, the GWO–XGBOOST model is established, and the GWO algorithm is utilized to optimize the XGBOOST model parameters. Finally, the residual series of the GWO–XGBOOST model are decomposed and corrected using the CEEMDAN method to produce the GWO–XGBOOST–CEEMDAN model. Three carbon emission trading markets, Guangdong, Hubei, and Fujian, were experimentally predicted to verify the model's validity. Based on the experimental results, it has been demonstrated that the proposed hybrid model has enhanced prediction precision compared to the comparison model, providing an effective experimental method for the prediction of future carbon prices. [ABSTRACT FROM AUTHOR]

In early studies, northern vegetation response to global warming recognised both increases in biomass/cover and shrinking of species' distributional ranges. Subsequent field measurements focussed on vegetation cover and biomass increases ("greening"), and more recently decreases ("browning"). However, satellite observations show that more than 50% of arctic vegetation has not changed significantly despite rapid warming. While absence of change in remote sensing data does not necessarily mean no ecological change on the ground, the significant proportion of the Arctic that appears to be stable in the face of considerable climate change points to a greater need to understand Arctic ecosystem stability. In this paper, we performed an extensive review of the available literature to seek balances or imbalances between research focussing on "greening", "browning" and "stability/no change". We find that greening studies dominate the literature though two relatively small areas of the Arctic are disproportionately represented for this main change process. Critically, there are too few studies anywhere investigating stability. We highlight the need to understand the mechanisms driving Arctic ecosystem stability, and the potential longer-term consequences of remaining stable in a rapidly changing climate. [ABSTRACT FROM AUTHOR]

Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2 ˚C or 1.5 ˚C. However, with substantial variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University's Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research. [ABSTRACT FROM AUTHOR]

The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China's goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

Restoring tree cover changes albedo, which is the fraction of sunlight reflected from the Earth's surface. In most locations, these changes in albedo offset or even negate the carbon removal benefits with the latter leading to global warming. Previous efforts to quantify the global climate mitigation benefit of restoring tree cover have not accounted robustly for albedo given a lack of spatially explicit data. Here we produce maps that show that carbon-only estimates may be up to 81% too high. While dryland and boreal settings have especially severe albedo offsets, it is possible to find places that provide net-positive climate mitigation benefits in all biomes. We further find that on-the-ground projects are concentrated in these more climate-positive locations, but that the majority still face at least a 20% albedo offset. Thus, strategically deploying restoration of tree cover for maximum climate benefit requires accounting for albedo change and we provide the tools to do so. Restoring tree cover is a prominent climate solution but can cause global warming due to changes in albedo. This paper maps albedo and carbon changes from restoring tree cover to highlight where the greatest net climate benefits can be achieved. [ABSTRACT FROM AUTHOR]

Climate change is a complex issue with significant scientific and socio-economic uncertainties, making it difficult to assess the effectiveness of climate policies. Dynamic Integrated Climate-Economy Models (DICE models) have been widely used to evaluate the impact of different climate policies. However, since climate change, long-term economic development, and their interactions are highly uncertain, an accurate assessment of investments in climate change mitigation requires appropriate consideration of climatic and economic uncertainties. Moreover, the results of these models are highly dependent on input parameters and assumptions, which can have significant uncertainties. To accurately assess the impact of climate policies, it is crucial to incorporate uncertainties into these models. In this paper, we explore the impact of parameter uncertainties on the evaluation of climate policies using DICE models. Our goal is to understand whether uncertainty significantly affects decision-making, particularly in global warming policy decisions. By integrating climatic and economic uncertainties into the DICE model, we seek to identify the cumulative impact of uncertainty on climate change. Overall, this paper aims to contribute to a better understanding of the challenges associated with evaluating climate policies using DICE models, and to inform the development of more effective policy measures to address the urgent challenge of climate change. [ABSTRACT FROM AUTHOR]

Extreme weather is an unexpected shock to the socioeconomic, which is likely to create climate risks in the process of global warming mitigation. The aim of this study is to investigate the impact of extreme weather on prices of China's regional emission allowances, by using the panel data of four representative pilots in China (Beijing, Guangdong, Hubei, and Shanghai) from April 2014 to December 2020. The overall findings reveal that extreme weather, especially extreme heat, has a short-term lagged positive impact on carbon prices. In particular, the specific performance of extreme weather under different conditions is as follows: (i) carbon prices in tertiary-dominated markets are more sensitive to extreme weather, (ii) extreme heat has a positive effect on carbon prices while extreme cold does not, and (iii) the positive impact of extreme weather on carbon market is significantly stronger during compliance periods. This study provides the decision-making basis for emission traders to avoid losses caused by market fluctuations. [ABSTRACT FROM AUTHOR]

As global warming becomes more prominent, the need to reduce carbon emissions to achieve China's carbon peak target is increasing. It is imperative to seek effective methods to predict carbon emissions and propose targeted emission reduction measures. In this paper, a comprehensive model integrating grey relational analysis (GRA), generalized regression neural network (GRNN) and fruit fly optimization algorithm (FOA) is constructed with carbon emission prediction as the research objective. Firstly, GRA is used for feature selection to find out the factors that have a strong influence on carbon emissions. Secondly, the parameter of GRNN is optimized using FOA algorithm to improve the prediction accuracy. The results show that (1) fossil energy consumption, population, urbanization rate and GDP are important factors affecting carbon emissions; (2) FOA-GRNN outperforms GRNN and back propagation neural network (BPNN), verifying the effectiveness of FOA-GRNN model for CO2 emission prediction. Finally, by analyzing the key influencing factors and combining scenario analysis with forecasting algorithms, the carbon emission trends in China for 2020-2035 are forecasted. The results can provide guidance for policy makers to set reasonable carbon emission reduction targets and adopt corresponding energy saving and emission reduction measures. [ABSTRACT FROM AUTHOR]

With the continuous development of the global economy, global environmental pollution, climate degradation and global warming are becoming increasingly serious. In order to deal with the increasingly serious environmental problems, the government is vigorously supporting and promoting the development of new energy vehicles (NEVs). As the core unit of NEVs, one of the main challenges faced by hydrogen fuel cell (HFC) supplier is to select the best supplier for their business among all possible suppliers. Selecting the optimal supplier is a key decision in green supplier management. Therefore, it is extremely important and meaningful to select an optimal HFC supplier to provide power for NEVs. This paper proposes a new decision-making framework based on Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and Complex proportional assessment (COPRAS) method under interval-valued probabilistic linguistic environment to select the appropriate HFC supplier of NEVs. Firstly, this paper establishes the evaluation criteria system of HFC supplier assessment which is the synthesis of economical, environmental, social, technical, organisation and service aspects. Then, in order to express the uncertainty of expert decision-making, this paper uses interval-valued probabilistic linguistic term set (IVPLTS) to describe the evaluation information. Next, the interval-valued probabilistic linguistic term set decision-making trial and evaluation laboratory (IVPLTS-DEMATEL) method is applied to calculate the criteria weights. Moreover, this paper constructs the interval-valued probabilistic linguistic term set Complex Proportional Assessment (IVPLTS-COPRAS) model for the selection of HFC supplier of NEVs. Finally, a case in China with sensitivity analysis and comparison analysis are executed to illustrate the feasibility and validity of the proposed approach. This paper provides valuable references for investors and companies to select the most appropriate HFC supplier of NEVs under uncertain environment. [ABSTRACT FROM AUTHOR]

Since global warming worsens with economic development and emitted CO2 is one of the main greenhouse gases, it is important to understand the relationship between CO2 emissions and economic growth. The paper applies a new panel cointegration test with cross-sectional dependence and structural breaks to examine this relationship in developed and developing countries, respectively. The results indicate that the "Environmental Kuznets Curve" does not hold in either group. For developing countries, there is neither linear nor quadratic long-term equilibrium relationship between CO2 emissions and economic growth. For developed countries, the quadratic relationship does exist between CO2 emissions and economic growth, whereas the linear one does not. A half of these countries have inverted U-shaped curves, while the other half have U-shaped curves. Besides, most of these countries are still on the rising stage of the curve. This paper gives new insights for policymakers to keep a balance between sustainable economic growth and suitable environmental quality. [ABSTRACT FROM AUTHOR]

In recent years, under the influence of changes in natural conditions and human social activities, the issue of global warming has become increasingly prominent. So it is crucial to effectively predict the future trend of temperature changes. In this regard, from the perspective of statistical models, this paper studies a new combination model, namely the new GM-ARIMA model, based on linear combination of weight calculation. Furthermore, it also analyzes the prediction effect through comparative experiments and uses multiple performance evaluation indicators, so as to prove the scientificity and effectiveness of the proposed combination model in this paper. Finally, according to the experimental results, it can be clearly found that among the four methods for calculating the weights of linear combination, namely the equal weight method, the variance reciprocal method, the residual reciprocal method and the standard deviation method, the combination model using the standard deviation method for calculation has the highest prediction accuracy, so it is finally decided to use this method to build the combination model (namely S-GM-ARIMA). In addition, the experimental results show that the S-GM-ARIMA model achieves the best prediction results compared to other existing prediction models. Among them, the MAE of S-GM-ARIMA decreases by 10.38% and 16.22% compared to the GM(1,1) model and ARIMA model, respectively. The RMSE of S-GM-ARIMA decreases by 4.52% and 10.03% compared to the GM(1,1) model and ARIMA model, respectively. And the MAPE of S-GM-ARIMA decreases by 10.34% and 16.17% compared to the GM(1,1) model and ARIMA model, respectively. Therefore, the new GM-ARIMA combination model studied in this paper has relatively higher prediction accuracy when making predictions, and can be used to make more effective and accurate predictions of global average temperature. This study can also provide reference for countries in making decisions to address global warming issues. [ABSTRACT FROM AUTHOR]

Climatic and geographic factors characterizing local conditions, as well as the ecological state of the external environment, have a direct effect on human health, morbidity, and life expectancy. The paper considers the basic concepts of medical ecology, a pathogenetic role of environmental atmospheric pollution in the development of environmentally induced and environmentally dependent diseases associated with exposure to meteorological factors. In addition to the major hygienic risk factors affecting the public health (a level of air, water, and soil pollution), the levels of acoustic and electromagnetic background, the type of human nutrition, architectural and planning conditions of human life are of significant importance. Global climate warming causes numerous environmental changes, primarily an increase in surface air temperature, which in turn entails global changes in weather conditions that lead to various weather anomalies. Human health is directly dependent on environmental conditions and a degree of adaptation to them. The paper highlights the issues of diagnosing environmentally induced diseases and measures to counteract their spread. Based on the system diagnosis using physiological indicators of human health and the integration of the adaptation and nosological approaches, a hardware-software complex has been developed and introduced into medical practice. Corrective technologies of regenerative medicine that are used for ecologically dependent pathologies are described. Their application in the process of the complex sanatorium and resort treatment is most effective. [ABSTRACT FROM AUTHOR]

How global warming affects human development is a central question for economists as well as social scientists. While most of the literature has focused on the impact of weather on income, less is known on the relationship between climate and local human development. This paper considers shocks in precipitation, temperature, and an original measure of soil aridity to first exploit the association between climate warming and human development, and second, on its dimensions. We show that while precipitations do not have a significant long-term impact on human development growth, variations in temperature and potential evapotranspiration negatively affect two of the three determinants of the Human Development Index, namely life expectancy at birth and education. These results suggest that other climate indicators, such as the potential evapo-transpiration of the soil, should be considered in addition to the standard indicators, when evaluating the localized economic effects of climate change. [ABSTRACT FROM AUTHOR]

Food is the material basis for human survival. Therefore, food security is a top priority for the people's livelihood and the sustainable development and future destiny of human beings. In the context of global warming in recent decades, the Arctic region has experienced more significant temperature anomalies than the midlatitudes due to the "Arctic amplification," and the rate of sea ice reduction has accelerated, which has an important impact on climate change in the middle and high latitudes, especially the frequent occurrence of extreme climate disasters that seriously affect food security and China's agricultural production. However, little research has been conducted on the role of changes in this important system of Arctic sea ice in China's agricultural production. Therefore, this paper analyzes the interannual variability and multi-year trends of Arctic sea ice concentration, CO2, air temperature, precipitation and China's major crop yield data to explore the possible effects and mechanisms of the rapid decrease in Arctic sea ice on China's grain production. From the analysis, it was found that the yield of major grains (rice, maize, wheat and soybean) in China was closely related to the Arctic sea ice anomaly in the previous summer and autumn, and the influence process was primarily through the dynamic process of the Arctic sea ice anomaly affecting the meridional temperature gradient and the positive and negative Arctic Oscillation phases, which in turn affected the air temperature anomalies in Eurasia and China, and finally led to the anomalous changes in Chinese grain yield. Based on this, a prediction model of China's major grain yield was established by stepwise nonlinear multiple regression analysis, which is a good fit and is expected to increase China's major crop yield by 11.4% in 2022 compared with last year. This presents new ideas and methods for future grain yield assessment in China and has far-reaching guidance for the stability and development of national and regional economies worldwide. [ABSTRACT FROM AUTHOR]

This article is an introduction to Part II of a special section on "Behavior and Cultural Systems Analysis for Climate Change" published in Behavior & Social Issues. The introduction highlights the growing severity of the climate crisis and the need for behavior analysis to play a role in shaping solutions. Part I of the special section provided examples of how behavior analysis can contribute to climate change mitigation, including interventions for reducing greenhouse gas emissions and conserving resources. Part II includes four papers that further explore these topics, such as incorporating climate resilience into educational practices, analyzing participants' willingness to enroll in green home energy programs, examining framing effects on public transportation use, and discussing the challenging role of behavior science in achieving global climate justice. The introduction also identifies common themes that emerged from the papers, including the importance of verbal behavior and climate change communication, the need for education and scaling of interventions, the use of behavioral economic analyses, leveraging technological innovations, and engaging policymaker support. The article concludes by emphasizing the urgency of avoiding a catastrophic rise in global temperature and the potential for behavior analysis to contribute to climate solutions. [Extracted from the article]

This research paper presents an eco-epidemiological model that investigates the intricate dynamics of a predator–prey system, considering the impact of fear-induced stress, hunting cooperation, global warming, and memory effects on species interactions. The model employs fractional-order derivatives to account for temporal dependencies and memory in ecological processes. By incorporating these factors, we aim to provide a more comprehensive understanding of the underlying mechanisms that govern the stability and behavior of ecological systems. Mathematically we investigate system's existence, equilibria and their stability. Moreover, global stability and hopf bifurcation also analyzed in this study. Numerical simulations have been performed to validate the analytical results. We find that the coexistence equilibrium is stable under specific conditions, along with the predator equilibrium and the disease-free equilibrium. Bifurcation analyses demonstrate the intricate behavior of species densities in response to changes in model parameters. Fear and global warming are found to stabilize the system, while cooperation and additional food for predators lead to destabilization. Additionally, the influence of species memory has been explored. We observe that memory tends to stabilize the system as species memory levels increase. [ABSTRACT FROM AUTHOR]

Although the UN concluded, already in 1997, that water would be the most contentious issue of the 21st century, water governance is still confused, nearly everywhere. Even the severe impacts of escalating water bankruptcy and global warming have so far failed to incur a marked improvement in governance systems. The global community has adopted sustainable development as a common vision and guide for the future. Yet, the adoption of the underlying principles of sustainable development has been slow in the water sector and elsewhere. Despite the realization that water governance is a political issue, the near-universal neoliberal agenda tends to only employ technologic and economic solutions to address water problems. This paper presents a historical overview, from the end of the Second World War (WWII) and onwards, of events that could, or should, have had an impact on water management frameworks. It evidences some important consequences of the institutional rigidity exposed during that period. The paper also turns to the fields of science, policy, and management, to pinpoint failures in the translation of political rhetoric as well as new scientific findings into change at the operational level. It explores how an updated knowledge base could serve a quest for sustainable water governance strategies. It is argued that a persistent failure to learn is an important reason behind the dire state that we are now in. As a result, water management is still based on century-old, technocratic, and instrumental methodologies that fail to take advantage of important scientific advancements since WWII and remain unable to properly deal with real-world complexities and uncertainties. The paper concludes that when it is linked to a transformation of the institutional superstructure, adaptive water management (AWM), a framework rooted in systems thinking, emerges as a prominent way to embark on a needed, radical transformation of the water governance systems. [ABSTRACT FROM AUTHOR]

This paper studies how interaction between economic decision-making and environmental awareness affects US business cycle and GHG emissions in a two-sector DSGE model. We emphasize the mechanisms that relate carbon emissions dynamics, consumer behavior, and environmental awareness in a framework incorporating two classes of goods (i.e., "clean" and "dirty"). This paper offers three main results. First, green consumption preferences play a key role in emissions reduction when they internalize emissions concentrations. Second, a green preference shock is the second source of fluctuation in many sectoral variables and stabilizes the business cycle. Third, a pollutant supply shock leads to sustainable consumption procyclicality documented in US data, only if households are environmentally aware. [ABSTRACT FROM AUTHOR]

The massive use of energy has caused a rapid increase in global carbon dioxide emissions, resulting in a series of environmental problems such as climate warming. Investment in the energy industry can guide funds into green and clean production, reduce carbon emissions in the energy industry, and promote the green development of the energy industry. This paper considers the energy, the environment, the economy, and other factors and focuses on energy consumption and investment structure. Taking 30 provinces in China as research samples, a dynamic spatial Durbin model is established. The results show that the first-order term of carbon emissions has a driving force of 0.5068% for current carbon emissions at a significance level of 1% and that the increase in current carbon emissions will lead to a continued increase in carbon emissions in the next period. The increase in the carbon emissions of neighbouring provinces will increase their carbon emissions through the spatial spillover effect. Whether in the short term or long term, the increase in energy investment and the optimization of the energy investment structure can reduce carbon emissions. The above conclusions can provide a reference for the formulation of government environmental policies. [ABSTRACT FROM AUTHOR]

Since 1984, the AHV journal has provided a key forum for a community of interdisciplinary, international researchers, educators, and policy makers to analyze and debate core issues, values and hopes facing the nation and the world, and to recommend strategies and actions for addressing them. This agenda includes the more specific challenges and opportunities confronting agriculture, food systems, science, and communities, as well as broader contextual issues and grand challenges. This paper draws extensively on 40 years of AHV journal articles and reviews and begins with a focus on a limited number of key grand challenges (climate change and global warming; threats to democracy and the growing neo-nationalism, populism, and authoritarianism; and increasing national and international inequality). With these challenges as the underlining context, the remainder of the paper addresses core journal themes of sustainable agriculture and local food systems, citizen and public science, and empowered communities. Highlighted are numerous important journal contributions to the analyses and recommendations to address these hopes and themes. I conclude that these themes and hopes not only deserve to live but are essential for changing and redirecting an unsustainable and destructive environmental, economic, political and social agenda to a viable, livable and just democratic society. [ABSTRACT FROM AUTHOR]

Vineyard landscapes significantly contribute to the economy, identity, culture, and biodiversity of many regions worldwide. Climate change, however, is increasingly threatening the resilience of vineyard landscapes and of their ecological conditions, undermining the provision of multiple ecosystem services. Previous research has often focused on climate change impacts, ecosystem conditions and ecosystem services without systematically reviewing how they have been studied in the literature on viticulture. Here, we systematically review the literature on vineyard landscapes to identify how ecosystem conditions and services have been investigated, and whether an integrative approach to investigate the effects of climate change was adopted. Our results indicate that there are still very few studies that explicitly address multiple ecosystem conditions and services together. Only 28 and 18% of the reviewed studies considered more than two ecosystem conditions or services, respectively. Moreover, while more than 97% of the relationships between ecosystem conditions and services studied were addressing provisioning and regulating services, only 3% examined cultural services. Finally, this review found that there is a lack of integrative studies that address simultaneously the relationships between ecosystem condition, ecosystem services and climate change (only 15 out of 112 studies). To overcome these gaps and to better understand the functioning of vineyard socio-ecological systems under climate change, multidisciplinary, integrative, and comprehensive approaches should be adopted by future studies. A holistic understanding of vineyard landscapes will indeed be crucial to support researchers and decision makers in developing sustainable adaptation strategies that enhance the ecological condition of vineyards and ensure the provision of multiple ecosystem services under future climate scenarios. [ABSTRACT FROM AUTHOR]

The paper analyzed the spatial-temporal variability of rainfall and detection of potential trend change point over Kosi River basin, Kumaon Lesser Himalaya, India, using long-term gridded data and historical metrological records in hilly river basin of Uttarakhand. The Mann-Kendall (MK) test was used to determine the spatio-temporal trend using IMD (0.25° × 0.25°) gridded rainfall data during 1901–2015. The Theil-Sen slope was used to determine the magnitude of change in rainfall during the study period. Additionally, the sequential Mann-Kendal (SQ-MK) test and Pettitt's test has been used to find the abrupt change point in historical time series (1980–2019). Results of the study show that northeastern and southwestern parts of the Kosi River basin exhibit a statistically significant decreasing trend in both June and July months at 5% significance level. Northeastern and southwestern parts of the basin exhibit a statistically significant decreasing trend for monthly and annual rainfall. The range of Sen's slope values varies from −0.6 to −6.6 mm/year. Based on the analysis of SQ-MK and Pettitt's test, the change points for Almora, Mukteshwar, and Hawalbagh were 1991, 2004, and 1998 respectively. Therefore, this paper attempts to provide actionable knowledge for irrigation water planning, water management, and soil and water conservation for Uttarakhand. [ABSTRACT FROM AUTHOR]

With the growth of global food demand, agricultural carbon emissions caused by agricultural production have become a major challenge in controlling global warming. However, a systematic and visual literature review of food security and carbon emissions (FSCE) is still lacking, and there is a lack of exploration on the balanced path between ensuring food security and realizing carbon emission reduction. Based on 872 articles related to FSCE in the Web of Science (WOS) core database, this paper used CiteSpace and VOSviewer bibliometric software to analyze the relevant research focus and trends. This study found that developed countries dominated the research in this field, and the quantity, quality, and intensity of their authors, institutions, and cooperation among countries are higher than those of developing countries. Although the intensity of interdisciplinary cooperation has increased, it remains at a low level. Since 2007, the number of papers published in this field has increased significantly, and the research perspectives have diversified. Moreover, the research theme continues to expand with the core of "food security," involving the impact of climate change, crop production and food security, soil carbon sequestration, and farmers' livelihood sustainability. In addition, food production, food transportation, and food loss reduction are key paths that need to be balanced to ensure global food security and realize carbon emission reduction, and how to promote "economic growth" under the constraints of FSCE will be a future research hotspot. [ABSTRACT FROM AUTHOR]

The paper discusses the distribution and origin of organic matter in natural waters with regard to the latitudinal geographic zoning in the European territory of Russia (ETR) and Western Siberia (WS) and demonstrates how conditions on the catchments and climate affect the content of autochthonous and allochthonous organic matter. Conditional coefficients of the ratios of these forms are calculated. The influence of the temperature factor on the content of autochthonous organic matter in the waters of the southern territories of the ETR and WS was proved by multivariate statistical methods of analysis. General trends and relations are identified in the distribution of lipids, proteins, and carbohydrates of the autochthonous and allochthonous organic compounds. The mechanism of biochemical transformation of bound carbohydrates of allochthonous organic compounds into free autochthonous ones via the microbial decomposition is demonstrated, which is more typical of waters in the southern regions of WS. The paper discusses how natural and climatic conditions can influence changes in concentrations of organic compounds in the lake waters and structural characteristics of these compounds (contents of aromatic and aliphatic fragments). [ABSTRACT FROM AUTHOR]

We present a methodology to develop the integrated toxicity and climate change risk assessment of Europe based facilities, industries and regions. There is an increasingly important need for large scale sustainability measurement solutions for company reporting with high granularity. In this paper we measure key aspects of Sustainable Development Goals in terms of human, cancer and non-cancer toxicity, ecotoxicity together with global warming impact potentials from point source pollutant releases of more than 10,000 companies and their 33,000 facilities in Europe from 2001 to 2017, by using the European Pollutant Release and Transfer Register. For our assessment, we deploy a scientific consensus model, USEtox for characterizing human and ecotoxicological impacts of chemicals and the global warming potential values from the Intergovernmental Panel on Climate Change. We discuss water and air emissions of dozens of pollutants in urban, rural, coastal and inland areas. Companies in the electricity production sector are estimated to have the largest human toxicity impact potential (46% of total) and the largest global warming impact potential (50%), while companies in the sewerage sector have the largest ecotoxicity impact potential (50%). In the overall economy, the correlation between facilities' global warming and toxicity impact potentials is positive, however, not very strong. Therefore, we argue that carbon footprint of industrial organizations can be only used as a climate change risk indicator, but not as an overall environmental performance indicator. We confirm impact potentials of major pollutants in previous research papers (Hg accounting for 76% of the total human toxicity and Zn accounting for 68% of total ecotoxicity), although we draw the attention to the limitations of USEtox in case of metals. From 2001 to 2017 total human toxicity dropped by 28%, although the downward trend reversed in 2016. Ecotoxicity and global warming impact potentials remained unchanged in the same period. Finally, we show that the European pollutant release monitoring data quality could be further improved, as only three quarters of the toxic releases are measured in the Member States of the European Union, and a high share of toxic pollutant releases are only estimated in some countries. Of the measured or calculated toxic releases, only one third is reported according to the most robust CEN/ISO standards and about one fifth according to the least preferred other methods, like engineering judgements. [ABSTRACT FROM AUTHOR]

Climate change with global warming as the main feature associated with fossil energy use has been recognized as a threat to public health and welfare. Energy-related carbon emission reduction is a more serious challenge for BRI (Belt and Road Initiative) countries with rapid economic development. Examining key impact factors is necessary and helpful. This paper is the first study providing detailed country-by-country analyses aiming to identify the key drivers and inhibitors of energy-related carbon emission in 66 BRI countries with more systematic impact factors. The results show that: (1) Economic development (A), population (Ps), urbanization (Pu), and industrialization (Ss) are the key drivers for 52%, 26%, 11%, and 6% countries of BRI countries. Technological progress (T), energy consumption structure (E), and tertiary industry proportion (St) serve as key inhibitors for 65%, 17%, and 8% countries of BRI countries. (2) Different carbon emission reduction strategies should be formed on different geographical scales. At the international level, carbon emission reduction consensus should be reached and carbon emission reduction targets should be formulated. At the regional level of the Belt and Road Initiative, a carbon emission reduction cooperation fund should be established, and carbon emission reduction technologies and measures should be exchanged and data should be shared to promote the green development of the Belt and Road. At the national level, there should be carbon emission reduction policies reflecting national characteristics. At the local level, there should be specific carbon reduction measures in line with local conditions. [ABSTRACT FROM AUTHOR]

Global warming has constituted a major global problem. Carbon dioxide emissions from the burning of fossil fuels are the main cause of global warming. Therefore, carbon dioxide emission forecasting has attracted widespread attention. Aiming at the problem of carbon dioxide emissions forecasting, this paper proposes a new hybrid forecasting model of carbon dioxide emissions, which combines the marine predator algorithm (MPA) and multi-kernel support vector regression. For further strengthening the prediction accuracy, a novel variant of MPA is proposed, called EGMPA, which introduces the elite opposition-based learning strategy and the golden sine algorithm into MPA. Algorithm test results show that EGMPA can effectively improve the convergence speed and optimization accuracy. The carbon dioxide emission data of China from 1965 to 2020 are taken as the research objects. Root-mean-square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are used to evaluate the performance of the proposed model. The proposed multi-kernel support vector regression model is used to forecast China's carbon dioxide emissions during the "14th Five-Year Plan" period. The results show that the proposed model has RMSE of 37.43 Mt, MAE of 30.63 Mt, and MAPE of 0.32%, which significantly improves the prediction accuracy and can accurately and effectively predict China's carbon dioxide emissions. During the "14th Five-Year Plan" period, China's carbon dioxide emissions will continue to show an increasing trend, but the growth rate will slow down significantly. [ABSTRACT FROM AUTHOR]

Global warming caused by increased carbon emissions is a common challenge for all mankind. Facing the unprecedented pressure of carbon emission reduction, it is particularly important to grasp the dynamics of carbon emission in time and accurately. This paper proposes a novel daily carbon emission forecasting model. Firstly, the daily carbon emission data is decomposed into a series of completely noise-free mode functions by improved complete ensemble empirical mode decomposition method with adaptive noise (ICEEMDAN). Then, a two-stage feature selection method composed of partial autocorrelation function (PACF) and ReliefF is applied to select appropriate input variables for the next prediction process. Finally, the extreme learning machine optimized by improved sparrow search algorithm (ISSA-ELM) is used to predict. The empirical results show that the proposed two-stage feature selection method can further improve the prediction accuracy. After two-stage feature selection, the values of R2, MAPE, and RMSE were improved by 0.55%, 30.23%, and 28.46%, respectively. It can also be found that ISSA has good optimization performance. By combining with ISSA, R2, MAPE, and RMSE improved by 7.60%, 31.97%, and 44.79%, respectively. Therefore, the proposed model can provide a valuable reference for the formulation of carbon emission reduction policies and future carbon emission prediction research. [ABSTRACT FROM AUTHOR]

This paper presents an approach for assessing lifestyle carbon footprints and lifestyle change options aimed at achieving the 1.5 °C climate goal and facilitating the transition to decarbonized lifestyles through stakeholder participatory research. Using data on Finland and Japan it shows potential impacts of reducing carbon footprints through changes in lifestyles for around 30 options covering food, housing, and mobility domains, in comparison with the 2030 and 2050 per-capita targets (2.5–3.2 tCO2e by 2030; 0.7–1.4 tCO2e by 2050). It discusses research opportunities for expanding the footprint-based quantitative analysis to incorporate subnational analysis, living lab, and scenario development aiming at advancing sustainability science on the transition to decarbonized lifestyles. [ABSTRACT FROM AUTHOR]

This is an extended editors’ commentary on the topical collection “Historical and recent change in extreme climate over East Asia”, which collects a total of 15 papers related to the change and variability of extreme climate events in East Asia over the last few hundreds years. The extreme climate events are broadly classified into three categories: temperature and extreme warmth/coldness, precipitation and floods/droughts and western North Pacific typhoons. This commentary briefly summarizes the main findings presented in each paper in this topical collection, and outlines the implications of these findings for monitoring, detecting and modeling of regional climate change and for studying climate change impacts and adaptability. It also assesses the uncertainties of these studies, as well as the remaining knowledge gaps that should be filled in the future. One solid conclusion we can draw from these studies is that there was a marked decadal to multi-decadal variability of extreme climate events in East Asia in recent history, and the extreme events as observed during the last decades of the instrumental era were still within the range of natural variability except for some of those related to temperature. More severe and enduring droughts occurred in the early 20 th century or the earlier periods of history, frequently leading to great famines in northern China. Uncertainties remain in reconstructing historical extreme climate events and analyzing the early instrumental records. Further research could focus on the improvement of methodology in proxy based reconstruction of multi-decadal variations of surface air temperature and precipitation/drought, the recovery, digitization, calibration and verification of the early instrumental records, and the mechanisms of the observed multi-decadal variability of extreme climate in the region. [ABSTRACT FROM AUTHOR]