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Using an aerosol–climate coupled model, this paper has investigated the changes in distributions of anthropogenic and natural particles due to 4 × CO2-induced global warming, under the low emission scenario of Representative Concentration Pathway 4.5 (RCP4.5). Special attention is paid to the seasonal variations of aerosol size modes. With rising CO2 levels, surface warming, and changes in atmospheric circulations and hydrologic cycles are found during both summer (JJA) and winter (DJF). For anthropogenic particles, changes in fine anthropogenic particulate matter (PM2.5, particles with diameters smaller than 2.5 μm) decrease over high-latitude regions and increase over the tropics in both DJF and JJA. Global mean column concentrations of PM2.5 decrease by approximately 0.19 mg m−2, and concentrations of coarse anthropogenic particles (CPM, particles with diameters larger than 2.5 μm) increase by 0.005 mg m−2 in JJA. Changes in anthropogenic particles in DJF are similar to those in JJA, but the magnitudes of maximum regional changes are much smaller than those in JJA. The coarse anthropogenic particles (CPM, particles with diameters larger than 2.5 μm) increase over northern Africa and the Arabian Peninsula during JJA, whereas changes in anthropogenic CPM during DJF are minimal. During both JJA and DJF, changes in anthropogenic CPM are about two orders of magnitude smaller than those of anthropogenic PM2.5. Enhanced wet deposition by large-scale precipitation under rising CO2-induced surface warming is the critical factor affecting changes in anthropogenic particles. For natural particles, the distribution of change in the natural PM2.5 burden is similar to that of natural CPM, but much larger than natural CPM during each season. Both natural PM2.5 and CPM burdens increase over northern Africa and the Arabian Peninsula during JJA, but decrease over most of the continental regions during DJF. Changes in surface wind speed, divergence/convergence of surface wind, and precipitation are primary reasons for the variation of natural particles. [ABSTRACT FROM AUTHOR]

In the marine ecosystem, phytoplankton plays a vital role as the primary supplier of oxygen, contributing to 50% of the total oxygen production. Not only does it serve as a significant source of food for other species, but it also sustains life in the ocean. However, the rising ocean temperatures caused by global warming have severely hindered the ability of phytoplankton to generate oxygen. Furthermore, fishes are crucial consumers of oxygen within the marine ecosystem. This research paper presents a model that intricately connects the dynamics of oxygen, phytoplankton, zooplankton, and fish using the Caputo fractional derivative. The model aims to examine the impact of global warming on the collective dynamics by considering the relationship between the rate of oxygen generation, temperature, and time. The paper establishes the existence and uniqueness of solutions and also analyzes the stability of equilibrium points. Numerical simulations are conducted to demonstrate the impact of fractional derivatives and global warming on oxygen depletion and species extinction. [ABSTRACT FROM AUTHOR]

Although designing a structure is an iterative process by nature, a very limited number of iterations can be done with the traditional methods to reach the near-optimal solution. However, with the development of information technologies, the usage of parametric design in the construction industry has expanded. This paper aims to show the potential benefits of implementing parametric design and optimization techniques in the early structural design process. For this purpose, a simple parametric model of a steel frame with a truss roof system was created and then optimized for minimum mass and a given floor area. The case study demonstrated that the application of parametric design can reduce the Global Warming Potential of the structure by 7.6 % by optimizing the geometry and the cross-sections, leading to a more sustainable solution. [ABSTRACT FROM AUTHOR]

As the Arctic and its rivers continue to warm, a better understanding of the possible future impacts on people would benefit from close partnership with Indigenous communities and scientists from diverse fields of study. We present efforts by the Arctic Rivers Project to conduct community‐engaged research to increase collective understanding of the historical and potential future impacts of climate change on rivers, fish, and Indigenous communities. Working in central to northern Alaska and the Yukon Territory in Canada, the project seeks to engage with Indigenous communities in ethical and equitable ways to produces science that is useful, useable, and used that may serve as an example for future research efforts. Toward this goal, we formed an Indigenous Advisory Council and together developed project‐specific knowledge co‐production protocols. This paper provides a novel model of design and implementation to co‐produce knowledge with communities across a large study domain. Plain Language Summary: The Arctic and rivers located in the Arctic and subarctic are warming due to climate change. To understand the impacts this warming will have on people, partnering with impacted Indigenous communities in the region is important. It is also important that these partnerships are ethical and equitable and produce science that is actionable. This paper discusses efforts undertaken by a specific project, the Arctic Rivers Project, to conduct ethical and equitable research with Indigenous communities and generate science that is useful to those communities. Through this research our goal is to better understand potential future impacts of climate change on rivers, fish, and Indigenous communities in central northern Alaska and the Yukon Territory in Canada. To achieve this goal, the project formed an Indigenous Advisory Council (IAC) and together developed guidelines for how we can work collaboratively with Indigenous communities. Our specific process of forming an IAC and guidelines is, to our knowledge, a new way to approach collaborative research when working across a large geographic area. We present our process here so that it may provide an example for other research efforts. Key Points: Arctic climate information can be made useful, useable, and used by equitably accounting for diverse community adaptation needs through knowledge co‐productionInstitutional and community capacity, including means and ability, is necessary for equitable knowledge co‐production to occurWe present an approach for co‐producing knowledge with Indigenous communities that can serve as an example for other scientific efforts [ABSTRACT FROM AUTHOR]

The performance of the pilot is closely related to their comfort during flight. An important factor that needs to be addressed is the temperature in the pilot's cockpit and how it is distributed and managed. This paper aims to address the issue of air dispersion because the current location of the ventilation ports do not take into account current human proportions and adaptability demonstrated by humans with regard to global warming. Once this problem is solved, the next step is to optimize the distribution of temperature in the cockpit. As solutions, this work proposes the creation of new ventilation grids that will optimize the way air is managed in the cockpit. [ABSTRACT FROM AUTHOR]

The glacial lakes in the Southeastern Qinghai–Tibet Plateau (SEQTP) have undergone dramatic expansion in the context of global warming, leading to several glacial lake outburst floods (GLOFs) disasters. However, there is a gap and incompleteness in glacial lake inventories across this area due to the heavy cloud cover. In this study, an updated and comprehensive glacial lake inventory was produced by object-based image analysis (OBIA) and manual vectorization based on the Sentinel-1 SAR and Sentinel-2 MSI images acquired in 2022. Detailed steps regarding the OBIA were provided, and the feature set of Sentinel-1 SAR images suitable for extracting glacial lakes was also determined in this paper. We found that the mean combination of ascending-orbit and descending-orbit images is appropriate for mapping glacial lakes. VV-polarized backscattering coefficients from ascending-orbit achieved a better performance for delineating glacial lakes within the study area. Moreover, the distribution of glacial lakes was characterized in terms of four aspects: size, type, elevation, and space. There were 3731 glacial lakes with a total area of 1664.22 ± 0.06 km2 in the study area; most of them were less than 0.07 km2. Ice-contacted lakes were primarily located in the Palongzangbo basin (13.24 ± 0.08 km2). Nyang Qu basin had the most abundant glacial lake resources (2456 and 93.32 ± 0.18 km2). A comparison with previously published glacial lake datasets demonstrated that our dataset is more complete. This inventory is useful for evaluating water resources, studying glacier–glacial lake interactions, and assessing GLOFs' susceptibility in the SEQTP. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the research output on climate change, environmental risks and insurance from 1986 to 2020, thereby revealing the development of the literature through collaborative networks. The relationship between insurance, climate change and environmental threats has gained research attention. This study describes the interaction between insurance, climate change and environmental risk. Design/methodology/approach: This study is a bibliometric analysis of the literature and assessed the current state of science. A total of 97 academic papers from top-level journals listed in the Scopus database are shortlisted. Findings: The understanding of climate change, environmental risks and insurance is shaped and enhanced through the collaborative network maps of researchers. Their reach expands across different networks, core themes and streams, as these topics develop. Research limitations/implications: Data for this study were generated from English-written journal articles listed in the Scopus database only; subsequently, this study was representative of high-quality papers published in the areas of climate change, environmental risks and insurance. Practical implications: The results of this study can be useful to academic researchers to aid their understanding of climate change, environmental risks and insurance research development, to identify the current context and to develop a future research agenda. Social implications: The findings of this study can improve the understanding of industry practitioners about climate change and global warming challenges, and how insurance can be used as a tool to address such challenges. Originality/value: This study is a novel attempt. To the best of the authors' knowledge, this is one of the first studies to better understand climate change, environmental risks and insurance as a research topic by examining its evolution in an academic context through visualization, coupling and bibliometric analysis. This bibliometric study is unique in reviewing climate change literature and providing a future research agenda. Using bibliometric data, this study addressed the technical aspects and the value it adds to actual practice. Bibliometric indicators quantitatively and qualitatively evaluate emerging disciplinary progress in this topic. [ABSTRACT FROM AUTHOR]

Soil carbon stored in high-latitude permafrost landscapes is threatened by warming, and could contribute significant amounts of carbon to the atmosphere and hydrosphere as permafrost thaws. Permafrost disturbances, especially active layer detachments and retrogressive thaw slumps, have increased in frequency and magnitude across the Fosheim Peninsula, Ellesmere Island, Canada. To determine the effects of retrogressive thaw slumps on net ecosystem exchange (NEE) of CO2 in high Arctic tundra, we used two eddy covariance (EC) tower systems to simultaneously and continuously measure CO2 fluxes from a disturbed site and the surrounding undisturbed tundra. During the 32-day measurement period in the 2014 growing season the undisturbed tundra was a small net sink (NEE = −0.12 g C m-2 d-1); however, the disturbed terrain of the retrogressive thaw slump was a net source (NEE = +0.39 g C m-2 d-1). Over the measurement period, the undisturbed tundra sequestered 3.84 g C m-2, while the disturbed tundra released 12.48 g C m-2. Before full leaf out in early July, the undisturbed tundra was a small source of CO2, but shifted to a sink for the remainder of the sampling season (July), whereas the disturbed tundra remained a source of CO2 throughout the season. A static chamber system was also used to measure fluxes in the footprints of the two towers, in both disturbed and undisturbed tundra, and fluxes were partitioned into ecosystem respiration (Re) and gross primary production (GPP). Average GPP and Re found in disturbed tundra were smaller (+0.41 μmol m-2 s-1 and +0.50 μmol m-2 s-1, respectively) than those found in undisturbed tundra (+1.21 μmol m-2 s-1 and +1.00 μmol m-2 s-1, respectively). Our measurements indicated clearly that the permafrost disturbance changed the high Arctic tundra system from a sink to a source for CO2 during the growing season. [ABSTRACT FROM AUTHOR]

Sediment denitrification in lakes alleviates the effects of eutrophication through removal of nitrogen to the atmosphere as N2O and N2. However, N2O contributes notably to the greenhouse effect and global warming. Human lands uses (e.g., agricultural and urban areas) strongly affect lake water quality and sediment characteristics, which, in turn, may regulate lake sediment denitrification and N2O production. In this study, we investigated sediment denitrification and N2O production and their relationships to within-lake variables and watershed land uses in 20 lakes from the Yangtze River basin in China. The results indicated that both lake water quality and sediment characteristics were significantly influenced by watershed land uses. Increased background denitrification rate would result in increased N2O production rate. Background denitrification and N2O production rates were positively related to water nitrogen concentrations but were not significantly correlated with sediment characteristics and plant community structure. A significant positive relationship was observed between background denitrification rate and percentage of human-dominated land uses (HDL) in watersheds. Structural equation modelling revealed that the indirect effects of HDL on sediment denitrification and N2O production in Yangtze lakes were mediated primarily through lake water quality. Our findings also suggest that although sediments in Yangtze lakes can remove large quantities of nitrogen through denitrification, they may also be an important source of N2O, especially in lakes with high nitrogen content. [ABSTRACT FROM AUTHOR]

In the face of ongoing global warming and glacier retreat, the composition and flux of organic matter in glacier-fjord systems are key variables for updating the carbon cycle and budget, whereas the role of Arctic valley glaciers seems unimportant when compared with the huge Greenland Ice Sheet. Our field observations of the glacier-fed Bayelva River, Svalbard, and the adjacent Kongsfjorden allowed us to determine the compositions of particulate organic matter from glacier to fjord and also to estimate the flux of organic carbon, both for the river and for Svalbard in general. Particulate organic carbon (POC) and dissolved organic carbon (DOC) in the Bayelva River averaged 56 and 73 µM, respectively, in August 2012. Amino acids (AAs) and phytoplankton pigments accounted for ~ 10% of the particulate organic matter (POM) in the Bayelva River, while AAs represented > 90% of particulate nitrogen in fjord surface water, suggesting the strong in situ assimilation of organic matter. Bacteria accounts for 13 and 19% of the POC in the Bayelva River and the Kongsfjorden, respectively, while values for particulate nitrogen (PN) are much higher (i.e., 36% in Kongsfjorden). The total discharge from the Bayelva River in 2012 was 29 × 106 m³. Furthermore, we calculated the annual POC, DOC, and PN fluxes for the river as 20 ± 1.6, 25 ± 5.6, and 4.7 ± 0.75 t, respectively. Using the POC content and DOC concentration data, we then estimated the annual POC and DOC fluxes for Svalbard glaciers. Although the estimated POC (0.056 ± 0.02 × 106 t yr-1) and DOC (0.02 ± 0.01 × 106 t yr-1) fluxes of Svalbard glaciers are small compared with those of the Greenland Ice Sheet, the area-weighted POC flux of Svalbard glaciers is twice that of the Greenland Ice Sheet, while the flux of DOC can be 4 to 7 times higher. Therefore, we propose that valley glaciers are efficient high-latitude sources of organic carbon. [ABSTRACT FROM AUTHOR]

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction of alpine grasses to low altitude regions has long been a crucial strategy for enriching germplasm diversity, cultivating and acclimating high-quality species, enhancing ecosystem resilience and adaptability, as well as facilitating ecosystem restoration. However, there is an urgent need to investigate the impacts of planting Gramineae seeds on greenhouse gas (GHG) emissions, particularly during the critical stage of early plant growth. In this study, four species of grass seeds (Stipa breviflora, Poa pratensis, Achnatherum splendens, Elymus nutans) were collected from 19 high-altitude regions surrounding the Qinghai-Tibet Plateau and sown at low-altitude. Measurements of GHG emissions at early seedling growth in the mesocosm experiment using static chamber method showed a strong increase in the cumulative emissions of CO 2 (5.71%-9.19%) and N 2 O (11.36%-13.64%) (p < 0.05), as well as an elevated CH 4 uptake (2.75%-5.50%) in sites where the four grass species were introduced, compared to bare soil. Consequently, there was a substantial rise in global warming potential (13.87%-16.33%) (p < 0.05) at grass-introduced sites. Redundancy analysis showed that seed traits, plant biomass, and seedling emergence percentage were the main driving biotic factors of three GHGs fluxes. Our study unveils the potential risk of escalating GHG emissions induced by introducing high altitude grasses to low altitude bare soil, elucidating the mechanism through linking seed traits with seedling establishment and environmental feedback. Furthermore, this offers a new perspective for assessing the impact of grass introduction on ecological environment of introduced site., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

One of the main disturbances caused by coastal nuclear power plants is the discharge of thermal effluents capable of affecting a number of marine systems, including macroalgal forests that support key ecosystem services such as carbon uptake, fisheries increment and coastal protection. This study aimed at describing the long-term trend (1992-2022) in the abundance of Sargassum forests from sites located inside and outside areas affected by the thermal effluent discharged by the Brazilian Nuclear Power Station (BNPS) and at evaluating the relationship between Sargassum cover and seawater temperature. This information is interesting to provide insights on whether and how Sargassum populations would likely be affected by increasing temperature due to climate change. We detected a long-term decline in Sargassum cover inside, but not outside the area affected by the BNPS thermal plume. Mean summer surface seawater temperature above 30 °C was identified as an important factor driving the decline of Sargassum abundance. This study highlights the impact caused by decades of discharge of the BNPS thermal effluent on Sargassum forests, which leads to predict the likely disappearance of marine forests under a climate change scenario in other sites situated in warm temperate regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The Paris Agreement, a landmark international treaty signed in 2016 to limit global warming to 2°C, has urged researchers to explore various strategies for achieving its ambitious goals. While Renewable Energy (RE) innovation holds promise, it alone may not be sufficient as critical deadlines approach. This field of research presents numerous challenges, foremost among them being the costliness of materials involved. However, emerging advancements in Machine Learning (ML) technologies provide a glimmer of hope; these sophisticated algorithms can accurately predict the output of energy systems without relying on physical resources and instead leverage available data from diverse energy platforms that have emerged over recent decades. The primary objective of this paper is to comprehensively explore various ML techniques and algorithms in the context of Renewable Energy Systems (RES). The investigation will address several vital inquiries, including identifying and evaluating existing RE technologies, assessing their potential for further advancement, and thoroughly analyzing the challenges and limitations associated with their deployment and testing. Furthermore, this research examines how ML can effectively overcome these obstacles by enhancing RES performance. By identifying future research opportunities and outlining potential directions for improvement, this work seeks to contribute to developing environmentally sustainable energy systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Greenhouse gas emissions from the use of fossil energy are the main drivers of global warming. China's dominant consumption of fossil energy necessitates adjustments in its energy consumption structure to break free from the carbon lock-in (CLI) phenomenon. Market-based environmental regulations, represented by the carbon trading market (CTM), play an important role in achieving the dual carbon goals of China. Using panel data of 270 prefecture-level cities in China from 2005 to 2020, this study applies a difference-in-difference model to identify the effect of CTM on urban CLI, analyze its transmission mechanism, and further examine the impact of urban characteristic heterogeneity on policy effects from multiple perspectives. Results show that the construction of CTM significantly reduces the degree of CLI of pilot cities; (2) CTM mainly affects urban CLI by promoting urban green technology innovation, industrial structure upgrading, and public green behavior; and (3) the inhibitory effect of CTM on CLI is more significant in cities with high carbon price, industrialization, and digital finance levels. The primary paths toward realizing carbon unlocking include optimizing the institutional design for CTM, enhancing the effective promotion and application of low-carbon technologies, cultivating the green awareness of the public, and increasing government investments in energy-saving and emission reduction techniques., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The emission of large amounts of carbon dioxide has caused serious environmental problems and hindered the construction of a green and low-carbon society. Efficient carbon dioxide capture has become an important means to slow down global climate warming and achieve effective utilization of carbon dioxide. Membranes synthesized by electrospinning technology are becoming promising carbon capture materials due to their unique characteristics. This review describes the features of membranes prepared from available raw materials and presents their application performances in carbon capture. The preparation methods of various types of membrane materials with excellent capture performance are summarized, and the effects of electrospinning parameters on electrospun fibers are systematically analyzed. Furthermore, recommendations and expectations for further development of electrospun membranes for carbon capture applications are given. These works provide important references for an in-depth understanding of the development status of electrospun membranes in the field of carbon capture and for expanding future research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In the effort to limit global warming to 1.5°C above the pre-industrial level, decarbonization of supply chains is crucial. Companies will need to reduce not only their direct and indirect emissions (scope 1 and 2) but also their indirect emissions (scope 3). In some sectors, the upstream scope 3 emissions can actually be larger than the companies' direct emissions. Therefore, a systematic literature review was carried out to understand how previous research in the field of supply chain management (SCM) approached energy efficiency and energy management in the upstream supply chain. The results indicate that only a few studies have addressed energy efficiency within SCM, and the majority assess energy solely as total energy use, without exploring opportunities to reduce final energy use among upstream suppliers. Moreover, results show that there is a lack of standards and methods to assess suppliers' energy use, making it difficult for suppliers, particularly small and medium-sized enterprises, to overcome barriers to implementing energy management. In conclusion, even though energy efficiency is a cost-effective means to reduce CO2 emissions, only a limited number of studies in the field of SCM have integrated energy efficiency, revealing a vast knowledge gap in this field. [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]

The seminal outcome of COP28 was the Global Stocktake (GST), which referenced transitioning for the first time among all the United Nations' climate agreements. While the GST's attempt at energy transition is welcomed, it is deficient. In this paper, the historical challenges of international climate policymaking and implementation has been explored. The challenges that undermined previous UN agreements will likely hinder the global stocktake. Moreover, the GST's failure to use more forceful language could be a fatal flaw. Furthermore, the GST did not sufficiently define key terms like net zero and energy transition. Likewise, it did not give due consideration to energy justice. The GST missed the opportunity to take strategic advantage of state actors while creating an ecosystem for non-state actors to contribute to the fight against climate change. The GST should have taken advantage of the avalanche of scientific knowledge available on energy transition to mandate timely climate mitigation plans. Subsequent GSTs must proactively address the shortcomings of the first GST if the current generation, which is touted as the generation with the last chance to combat climate change, hopes to achieve the primary goal of the Paris Agreement. [ABSTRACT FROM AUTHOR]

As global warming intensifies, reducing carbon emissions has become a global common mission. Tourism transportation is one of the important sources of carbon emissions, and reducing its carbon emissions is a key part of achieving China's carbon reduction goals. Based on the panel data of various provinces and cities in North China from 2000 to 2022, this paper calculates the carbon emissions of tourism transportation by using the carbon emission coefficients of different transportation modes in different segments. Moreover, the temporal and spatial evolution of the tourism economy is systematically analyzed. The Tapio decoupling model and LMDI addition decomposition model are used to analyze the relationship between carbon emissions and tourism economic growth and the effects of 11 influencing factors on carbon emissions. The results show that: (1) The carbon emission of tourism transportation in North China has experienced four stages: a steady growth period, a transitional adaptation period, a stable equilibrium period, and a drastic decline period. The overall carbon emission level of tourism transportation is as follows: Hebei Province > Shanxi Province > Inner Mongolia Autonomous Region > Beijing City > Tianjin City. (2) The decoupling coefficient between tourism traffic carbon emissions and economic development fluctuates but mainly shows a weak decoupling state. (3) In terms of influencing factors, passenger size and passenger density have the greatest impact on the carbon emissions of tourism transportation. [ABSTRACT FROM AUTHOR]

A typical Madden–Julian Oscillation (MJO) generates a large region of enhanced rainfall over the equatorial Indian Ocean that moves slowly eastward into the western Pacific. Tropical cyclones often form on the poleward edges of the MJO moist-convective envelope, frequently impacting both southeast Asia and northern Australia, and on occasion Eastern Africa. This paper addresses the question of whether these MJO-induced tropical cyclones will become more numerous in the future as the oceans warm. The Lagrangian Atmosphere Model (LAM), which has been carefully tuned to simulate realistic MJO circulations, is used to study the sensitivity of MJO modulation of tropical cyclogenesis (TCG) to global warming. A control simulation for the current climate is compared with a simulation with enhanced radiative forcing consistent with that for the latter part of the 21st century under Shared Socioeconomic Pathway (SSP) 585. The LAM control run reproduces the observed MJO modulation of TCG, with about 70 percent more storms forming than monthly climatology predicts within the MJO's convective envelope. The LAM SSP585 run suggests that TCG enhancement within the convective envelope could reach 170 percent of the background value under a high greenhouse gas emissions scenario, owing to a strengthening of Kelvin and Rossby wave components of the MJO's circulation. [ABSTRACT FROM AUTHOR]

With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact. Optuna–LightGBM–XGBoost, a novel power and carbon emission relationship model that aims to improve the efficiency of carbon emission monitoring and estimation for power generation companies, is proposed in this paper. Deeply exploring the intrinsic link between power production data and carbon emissions, this model paves a new path for "measuring carbon through electricity", in contrast to the emission factor method commonly used in China. Unit data from power generation companies are processed into structured tabular data, and a parallel processing framework is constructed with LightGBM and XGBoost, and optimized with the Optuna algorithm. The multilayer perceptron (MLP) is used to fuse features to enhance prediction accuracy by capturing characters that the individual models cannot detect. Simulation results show that Optuna–LightGBM–XGBoost can achieve better performance compared to existing methods. The mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) of the model are 0.652, 0.939, 0.136, and 0.994, respectively. This not only helps governments and enterprises to develop more scientific and reasonable emission reduction strategies and policies, but also lays a solid foundation for achieving global carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Urban greenery is a strategy to improve the thermal environment in urban areas affected by heat islands and global warming. These phenomena can harm the citizens' quality of life. Researchers have investigated the thermal benefits of urban vegetation, but only a few have explored its complexities across diverse urban scales. Understanding these variations is critical for precise analysis, customized solutions, efficient resource allocation, and enhancing urban living quality while promoting sustainability and climate resilience. This paper reviews 250 scientific articles about the relationship between greenspace and the urban thermal environment published between 2010 and 2023 through urban scales. It summarizes the parameters and findings of greenery's contribution to cooling the urban environment. The data reveal that most studies concentrated on the block scale, public open spaces, neighborhoods, parks, grouped vegetation, mixed arrangements, high vegetation, spatial parameters, and the use of air temperature data to report their findings. The cooling-effect evidence shows that the block scale has an average mitigation range of 0.7–2.7 °C, the neighborhood scale of 1.1–2.9 °C, and the city scale of 0.5–2.2 °C. Furthermore, it is critical to define reliable research methods and perform thorough software validation to assess model performance and establish guidelines for urban-landscape design accurately. [ABSTRACT FROM AUTHOR]

The use of wine dealcoholisation has multiplied in recent years as a result of various factors, including the increase in alcohol content due to global warming and changes in consumer drinking habits. There are several post-fermentation dealcoholisation methods in the literature which allow for the partial or total elimination of the alcohol content of wine. However, there are no studies on the patented very low temperature vacuum wine distillation technology called GoLo. Therefore, for the first time, this paper evaluates the quality of dealcoholised white, rose and red wines using GoLo technology. For this purpose, alcohol content, pH, total SO2, free SO2, total acidity and volatile acidity were measured. There were no significant differences in the variations in pH, total acidity and volatile acidity after the dealcoholisation process using GoLo technology and dealcoholised wines showed a reduction of 22.1% in total SO2 and a complete absence of ethanol and free SO2. A model for predicting the total SO2 content of dealcoholised wines and a model for predicting the amount of sulphites to be added after dealcoholisation were found after the statistical treatment of the data. GoLo dealcoholisation delivers 100% removal of alcohol and free SO2 in less time, with less loss and energy than other dealcoholisation technologies. The verification and extension of these results will be the focus of future studies. [ABSTRACT FROM AUTHOR]

With the reduction in fossil fuels and growing concerns about global warming, energy has become one of the most important issues facing humanity. It is crucial to improve energy utilization efficiency and promote a low-carbon transition. In comparison with traditional heat exchangers, heat pipe heat exchangers indicate high compactness, a flexible arrangement, complete separation of hot and cold fluids, good isothermal operations, etc. As a result, heat pipe heat exchangers have attracted wide attention and application in various fields in recent years. This paper provides an overview of the application of heat pipe heat exchangers, with a focus on the application in waste heat recovery, and analyzes the opportunities and challenges of heat pipe heat exchanger applications based on existing publications. [ABSTRACT FROM AUTHOR]

The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

Simple Summary: Since the 1990s, the golden cuttlefish (Sepia esculenta) has become the dominant cuttlefish fisheries target in the seas around China. In this paper, we aim to determine the current resource status and spatio-seasonal variation in the population in the East China Sea region. We found more juveniles at latitudes of 27.50–28.00° N and 29.00° N and more subadult individuals at 28.50° N in autumn, exhibiting different growth rates and resource densities. In addition, we found the majority of the catches were composed of parent groups in spring, while in autumn, the majority of the catches were composed of juvenile groups. We concluded that the subadult groups might have dispersed widely for feeding and growth along the latitude of 30.00° N and to the south in summer, and the southern area of the Yangtze River extending north was the spawning ground in spring. The groups of S. esculenta preferred to stay in areas with a stable water temperature of ~20.00 °C, and many S. esculenta juveniles might have adapted to endure the negative influence of the low oxygen content in summer. The depth range of the S. esculenta population was 10.00–133.00 m from spring to autumn, but this shrank to 66.00–107.00 m in winter. The golden cuttlefish (Sepia esculenta) is an important cephalopod species with a lifespan of approximately one year. The species plays a crucial role in marine ecological support services and is commercially valuable in fisheries. In the seas around China, this species has emerged as the main target for cuttlefish fisheries, replacing Sepiella maindroni since the 1990s. Variations in oceanographic conditions associated with global warming could significantly impact the temporal-spatial distribution of the species. In this study, we performed bottom trawling surveys with four cruises during 2018–2019 in the East China Sea region to determine the current resource status and seasonal-spatial variations in S. esculenta. We found that the average individual weight (AIW) values were 4.87 and 519.00 g/ind at stations located at 30.50° N, 124.00° E and 30.50° N, 124.50° E, respectively, with the aggregation of larvae and parent groups in spring. The species was not distributed north of 32.00° N in summer. The catch per unit effort by weight (CPUEw) value decreased in the order of 2772.50→2575.20→503.29→124.36 g/h, corresponding to latitudes of 34.50° N→34.00° N→33.50° N→32.50° N 121.50° E in autumn. The most suitable fishing areas were the south of the East China Sea region in spring; the south of the East China Sea region extending to the center and outer parts of the East China Sea region in summer; the south of the Yellow Sea close to the Haizhou Bay fishing ground and the forbidden fishing line region of the Lusi and Dasha fishing grounds in autumn; and the south and center of the East China Sea region in winter. The most suitable sea bottom temperature (SBT) values from spring to winter were 14.76–20.53 °C, 19.54–22.98 °C, 11.79–17.64 °C, and 16.94–20.36 °C, respectively. The most suitable sea bottom salinity (SBS) values were 31.53–34.80‰ in spring, 32.95–34.68‰ in summer, 31.51–34.77‰ in autumn, and 33.82–34.51‰ in winter. We concluded the following: (1) the southern and northern areas of the East China Sea region are spawning and nursery grounds, respectively, in spring; (2) the central distribution is located at a latitude of 28.00° N in autumn and winter; and (3) the southern area of the Yangtze River to the north is a spawning ground in spring, and the areas located at 29.00–34.50° N, 124.00–124.50° E, and 28.00–30.50° N, 125.50–126.50° E are nursery grounds. The results of this study provide useful guidance for appropriate fisheries management, thereby avoiding a collapse in the S. esculenta population, which has been experienced in other species in this area. [ABSTRACT FROM AUTHOR]

In this paper, the global distribution of precipitation for 2023, in terms of global totals and regional anomaly patterns, is analyzed using information from the new Global Precipitation Climatology Project (GPCP) V3.2 Monthly product, including how the precipitation amounts and patterns from 2023 fit into the longer record from 1983–2023. The tropical pattern of anomalies for 2023 is dominated by the effect of the El Nino which began during the Northern Hemisphere spring, after three plus years of La Nina conditions. The transition from La Nina conditions through 2022 shows the rapid change in many regional features from positive to negative anomalies or the reverse. Comparison of the observed regional trend maps with climate model results indicates similarity between the observations and the model results forced by observed SSTs, while the "free-running" model ensemble shows only a broad general agreement over large regions. Global total precipitation shows about a 3% range over the span of data, with El Nino and La Nina years prominent as positive and negative features, with 2023 showing a small positive global anomaly. The ITCZ (Inter-Tropical Convergence Zone) latitude band, 0–10° N, sets a record high mean rain rate in 2023 after a steady upward trend over the decades, probably a response related to global warming. [ABSTRACT FROM AUTHOR]

Uneven rainfall, in the context of global warming, can cause soil moisture fluctuations (SMFs) that harm crop growth, and it is not yet known whether nitrogen (N) can mitigate the harm caused by a strong SMF. This paper uses okra as a test subject and sets three SMFs of 45–55% FC (W1), 35–65% FC (W2), and 25–75% FC (W3) and three N applications of 0 kg hm−2 (N0), 110 kg hm−2 (N1), and 330 kg hm−2 (N2) to investigate the effects of SMF and N application on the physiological and biochemical aspects of okra. The results demonstrated that okra exhibited the highest values in stem diameter, number of leaves, photosynthesis characteristics, antioxidant enzyme activity, and yield under the N1 treatment. The average yield in the N1 treatment was 149.8 g, significantly surpassing the average yields of the N0 (129.8 g) and N3 (84.0 g) treatments. Stomatal density, antioxidant enzyme activity, malondialdehyde content, and proline content in okra leaves were highest in the W3 treatment, indicating that plants experienced stress in the W3 treatment. However, the agronomic traits and yields of okra in the N1 treatment were higher than those in the N0 and N1 treatments, indicating that the crop damage caused by W3 could be mitigated by an appropriate amount of N application. The N1W1 treatment emerged as the most suitable combination for okra growth in this study, exhibiting the highest stem diameter, leaf count, photosynthetic characteristics, and yield (201.3 g). Notably, this yield was 67.8% higher than the lowest treatment (N2W3), signifying a significant improvement. [ABSTRACT FROM AUTHOR]

Freeze–thaw (FT) erosion intensity may exhibit a future increasing trend with climate warming, humidification, and permafrost degradation in the Qinghai–Tibet Plateau (QTP). The present study provides a reference for the prevention and control of FT erosion in the QTP, as well as for the protection and restoration of the regional ecological environment. FT erosion is the third major type of soil erosion after water and wind erosion. Although FT erosion is one of the major soil erosion types in cold regions, it has been studied relatively little in the past because of the complexity of several influencing factors and the involvement of shallow surface layers at certain depths. The QTP is an important ecological barrier area in China. However, this area is characterized by harsh climatic and fragile environmental conditions, as well as by frequent FT erosion events, making it necessary to conduct research on FT erosion. In this paper, a total of 11 meteorological, vegetation, topographic, geomorphological, and geological factors were selected and assigned analytic hierarchy process (AHP)-based weights to evaluate the FT erosion intensity in the QTP using a comprehensive evaluation index method. In addition, the single effects of the selected influencing factors on the FT erosion intensity were further evaluated in this study. According to the obtained results, the total FT erosion area covered 1.61 × 106 km2, accounting for 61.33% of the total area of the QTP. The moderate and strong FT erosion intensity classes covered 6.19 × 105 km2, accounting for 38.37% of the total FT erosion area in the QTP. The results revealed substantial variations in the spatial distribution of the FT erosion intensity in the QTP. Indeed, the moderate and strong erosion areas were mainly located in the high mountain areas and the hilly part of the Hoh Xil frozen soil region. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, China has become the world's largest carbon emitter. China not only has an obvious growth rate of industrial carbon emissions but also the intensity of agricultural carbon emissions is hovering at a high level. The development of China's agricultural economy has largely come at the expense of high emissions. Currently, under the background of global warming and difficulty in controlling greenhouse gas emissions, the development of low-carbon agriculture is an important way to realize the harmonious development of the ecological environment and economic growth and to promote the sustainable development of agriculture. The agricultural production efficiency is the main factor affecting the intensity of agricultural carbon emissions. Based on provincial panel data of China from 2010 to 2019, this paper establishes an indicator system and uses the super-efficiency SBM model to measure agricultural production efficiency. The regional agricultural carbon emissions were estimated using carbon-emission-related agricultural production activities. In order to study the nonlinear relationship between agricultural production efficiency and agricultural carbon emission intensity in the narrow sense, this paper uses a threshold regression model with agricultural carbon emissions as the threshold variable. Based on the analysis of China's agricultural production efficiency and agricultural carbon emissions from 2010 to 2019, an empirical test is conducted through a threshold regression model. The results show an "inverted U-shaped" relationship between agricultural production efficiency and agricultural carbon emission intensity. In areas with high agricultural production efficiency, the improvement of production efficiency can suppress the intensity of agricultural carbon emissions; in areas with low agricultural production efficiency, the improvement of production efficiency increases the intensity of agricultural carbon emissions. Finally, based on the research conclusions, this paper provides feasible suggestions and countermeasures for China's agricultural carbon emission reduction and improvement of agricultural production efficiency. [ABSTRACT FROM AUTHOR]

Recent developments in modelling soil organic carbon decomposition include the explicit incorporation of enzyme and microbial dynamics. A characteristic of these models is a positive feedback between substrate and consumers which is absent in traditional first order decay models. Under sufficient large substrate, this new feedback allows an unconstrained growth of microbial biomass. A second phenomenon incorporated in the microbial decomposition models is decreased carbon use efficiency (CUE) with increasing temperature. Here, first we analyse microbial decomposition models by parameterising changes in CUE based on the differentiation between growth and maintenance respiration. We then explore mechanisms that curb unrestricted microbial growth by including finite potential sites where enzymes can bind and by allowing microbial scavenging for enzymes. Finally, we propose a model where enzyme synthesis is associated with a respiratory cost and microbial population adjusts enzyme production in order to optimise their growth. When applying a step increase in temperature, we find fast responses that reflect adjustments to enzyme dynamics and maintenance respiration, a short-term adjustment in microbial growth, and the long-term change in carbon storage. We find that mechanisms that prevent unrestricted microbial growth lead to a similar response to warming as traditional first order decomposition models. [ABSTRACT FROM AUTHOR]

Robust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. Currently, two such levels are discussed in the context of the international climate negotiations as long-term global temperature goals: a below 2 °C and a 1.5 °C limit in global-mean temperature rise above pre-industrial levels. Despite the prominence of these two temperature limits, a comprehensive assessment of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5 °C and 2 °C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between 1.5 °C and 2 °C. For heat-related extremes, the additional 0.5 °C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2 °C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature induced bleaching from 2050 onwards. This fraction is reduced to about 90 % in 2050 and projected to decline to 70 % by 2100 for a 1.5 °C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and several hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9 to 17 % between 1.5 °C and 2 °C, and the projected lengthening of regional dry spells increases from 7 % longer to 11 %. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and Northern South America are projected to face local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50 cm rise by 2100 relative to year 2000-levels under a 2 °C warming, which is about 10 cm lower for a 1.5 °C scenario. Our findings highlight the importance of regional differentiation to assess future climate risks as well as different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a solid foundation for future work on refining our understanding of warming-level dependent climate impacts. [ABSTRACT FROM AUTHOR]

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) dynamics through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of northern Eurasia. The retrospective simulations were conducted over the 1960-2009 record and at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from sitebased eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote sensing data. The site-based comparisons show the timing of peak GPP to be well simulated. Modest overestimates in model GPP and ER are also found, which are relatively higher for two boreal forest validation sites than the two tundra sites. Across the suite of model simulations, NEP increases by as little as 0.01 to as much as 0.79 gCm in future model development and intercomparison studies. Resulting improvements in parameterizations and processes driving productivity and soil respiration rates will increase confidence in model estimates of net CO2 exchange, component carbon fluxes, and underlying drivers of change across the northern high latitudes. [ABSTRACT FROM AUTHOR]

Temperature sensitivity of SOC mineralization (Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration, thus understanding the factors influencing the interannual variation in Q10 is important to accurately estimate the local soil carbon cycle. In situ SOC mineralization was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow soil in the Loess Plateau (35° 12' N, 107° 40' E) in Changwu, Shaanxi, China form 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 gCm-2 y-1 (mean= 253 gCm-2 y-1; CV= 13 %), annual Q10 ranged from 1.48 to 1.94 (mean= 1.70; CV= 10 %), and annual soil moisture content ranged from 38.6 to 50.7% WFPS (mean= 43.8% WFPS; CV= 11 %), which were mainly affected by the frequency and distribution of precipitation. Annual Q10 showed a negative quadratic correlation with soil moisture. In conclusion, understanding of the relationships between interannual variation in Q10 of SOC mineralization, soil moisture and precipitation is important to accurately estimate the local carbon cycle, especially under the changing climate. [ABSTRACT FROM AUTHOR]

Large amount of organic carbon is stored in high latitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an arctic-enabled version of the process-based dynamic ecosystem model, LPJ-GUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment comprising both mineral and peatland soils. The model is applied at 50m resolution and is shown to be able to capture the seasonality and magnitudes of observed fluxes at this fine scale. The modelled magnitudes of CO2 uptake generally follow the descending sequence: birch forest, non-permafrost Eriophorum, Sphagnum and then tundra heath during the observation periods. The catchment-level carbon fluxes from aquatic systems are dominated by CO2 emissions from streams. Integrated across the whole catchment, we estimate that the area is a carbon sink at present, and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modelled sinks are very dependent on future atmospheric CO2 concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO2 increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO2 fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, integrating comprehensive and diverse fluxes including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modelling subarctic ecosystem responses to climate change including aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances and peatland expansion, our application provides a mechanism to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes. [ABSTRACT FROM AUTHOR]

In the debate over global warming, treeline position is considered an important ecological indicator of climate change. Currently, analysis of upward treeline shift is often based on various spatial data processed by geomatic techniques. In this work, considering a selection of 31 reference papers, we assessed how the scientific community is using different methods to map treeline position and/or shifts using spatial datasets. We found that a significant number of published studies suffer from a low degree of awareness of processed data, which outcomes in potentially unreliable results that may compromise the validity of inference from the studies. Moreover, we propose an operational approach for easily incorporating consideration of spatial data quality, so as to improve reliability of results and better support ecological conclusions. Finally, we present a simulation of potential treeline vertical error for the Alpine region of Northern Italy, as driven by primary data quality. [ABSTRACT FROM AUTHOR]

The China–Pakistan Economic Corridor is the pilot area of the Belt and Road, where glaciers and lakes are widely distributed. Recent years, global warming has accelerated the expansion of glacier lakes, which increased the risk of natural disasters such as glacier lake outburst. It is important to monitor the glacier lakes in this region. In this paper, we propose a method combining the object-oriented image analysis with boundary recognition (OOBR) to extract lakes in several study areas of China–Pakistan Economic Corridor (CPEC). This method recognized the lake boundary with the symmetrical characteristic according to the principle of seed growth of watershed algorithm, which can correct the boundary extracted by the object-oriented method. The overall accuracy of the proposed method is up to 98.5% with Landsat series images. The experiments also show that the overall accuracy of our method is always higher than that of the object-oriented method with different segmentation scales mentioned in this paper. The proposed method improved the overall accuracy on the basis of the results obtained by the object-oriented method, and the results with the proposed method are more robust to the seeds than that with the boundary correction method of the watershed algorithm. Therefore, the proposed method can obtain a high extraction accuracy while reducing the complexity of the object-oriented extraction. [ABSTRACT FROM AUTHOR]

In recent years, global warming has become increasingly severe, and the ecological and environmental problems facing mankind have become increasingly serious. As the main areas of transportation activities, cities are also the main places of carbon emissions. As a necessary condition for human's daily-life travel, it is particularly important to calculate the carbon emissions from urban transportation. Due to the different characteristics of economy and population in different regions of a city, the carbon emissions of urban buses show different characteristics in terms of temporal and spatial distribution. The developments of science and technology promote the application of big data analysis to specific practical life, enabling people to research and solve problems from a new perspective. This paper uses the GPS data of urban buses in Sanya City, China, to identify operation conditions from urban buses, and calculates the distance and time under different conditions. Based on the measured data of carbon emissions, this paper visualizes the distribution characteristics of carbon emissions by density analysis; explains the time distribution characteristics by the visual analysis of carbon emissions in different time periods, working days and rest days, and different energy types; and illustrates the spatial distribution characteristics by the spatial distributions of carbon emissions from Sanya's buses on working days and rest days, as well as in different routes, providing reference for a low-carbon development of urban green transport. [ABSTRACT FROM AUTHOR]

Specimen‐based data have played a central role in documenting body‐size shifts as a possible response to global warming over the last century. Identification of the drivers and patterns of these trends requires comparisons across taxa, often through meta‐analyses; however, a lack of repeatability within and interoperability (i.e. the potential for a dataset to be augmented for future research) among published studies is a major obstacle.We reviewed published studies on mammal body‐size changes in the Anthropocene, focusing on those that used museum specimens to analyse body‐size trends over time in at least one species. We assessed these papers for repeatability and interoperability with the following criteria: raw data and specimen identifiers were published and accessible, measurements were unambiguously defined, and potential sex‐ and age‐based size differences among individuals were accounted for.Most published body‐size studies have low potential for replication or augmentation; only one of 27 met all of our criteria. Although these 27 papers collectively generated an estimated 51,790 new body‐size measurements, only 1.25% (649) could be repeated or readily used in further investigations, as the remainder did not include raw data and/or specimen identifiers.Based on these findings, we recommend the following best practices in the study of body‐size trends. First, authors should explicitly define and justify all measures of size and quantify measurement error and publish all data, including measurements and specimen catalogue numbers. In addition to complying with the fundamental scientific tenet of repeatability, this minimizes redundant handling and the concomitant risk of damage to irreplaceable and often fragile museum specimens. Second, authors should test and account for the effects of demography, as some dimensions can change throughout an individual's life. Adopting these practices will improve the quality of body‐size studies, enhance the utility of extended specimen data from natural history collections, and enable researchers to conduct more expansive investigations of size trends over time. [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]

The Canadian Prairies are associated with high natural hydroclimatic variability including the frequent periodic occurrence of droughts and pluvials. These extremes carry various risks including significant damage to the economy, environment and society. The well-documented level of damage necessitates further risk assessment and planned reductions to vulnerability, particularly in light of a warming climate. A logical starting point involves awareness and information about the changing characteristics of such climate extremes. We focus on the compound occurrence of droughts and pluvials as the risks from this type of event are magnified compared to the hydroclimatic extremes in isolation. Compound droughts and pluvials (CDP) are drought and pluvial events that occur in close succession in time or in close proximity in area. Also, research on CDP is limited even for the worldwide literature. Therefore, the purposes of this paper are to synthesize recent literature concerning the risks of CDP, and to provide examples of past occurrences, with a focus on the Canadian Prairies. Since literature from the Prairies is limited, global work is also reviewed. That literature indicates increasing concern and interest in CDP. Relationships between drought and pluvials are also characterized using the SPEI Global Monitor for the Prairies, emphasizing the recent past. Research mostly considers drought and pluvials as separate events in the Prairies, but is integrated here to characterize the relationships of these extremes. The spatiotemporal patterns showed that several of the extreme to record pluvials were found to be closely associated with extreme droughts in the Prairies. The intensities of the extremes and their dry to wet boundaries were described. This is the first research to explore the concept of and to provide examples of CDP for the Prairies and for Canada. Examples of CDP provide insights into the regional hydroclimatic variability. Furthermore, most literature on future projections strongly suggests that this variability is likely to increase, mainly driven by anthropogenic climate change. Therefore, improved methods to characterize and to quantify CDP are required. These findings suggest means of decreasing vulnerability and associated damages. Although the study area is the Canadian Prairies, the work is relevant to other regions that are becoming more vulnerable to increasing risks of and vulnerabilities to such compound extremes. [ABSTRACT FROM AUTHOR]

The interaction between climate warming and alien fish invasions could have severe consequences in inland waters, which represent isolated environments with high biodiversity richness. Due to the current climatic trend, increasing water temperatures and salinization, shorter ice cover period, and altered flow regimes are predicted for these environments. The aim of this review is to offer a comprehensive analysis at a global scale of the recent studies available in the literature, focused on the responses of invasive freshwater fish to the effects of climate change in both lotic and lentic environments. To achieve this purpose, we selected 34 relevant papers, using the Scopus and Google Scholar database. New alien species establishment, distribution range expansion of species already introduced, and exacerbating impacts on freshwater ecosystems and the native fish communities they host were included in the topics covered by the analyzed papers. Despite the uncertainties related to the unpredictability with which the effects of global warming will occur, the findings of the selected studies served as a support to evaluate conservation and management implications, with particular reference to possible mitigation strategies. [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]

This Special Issue intended to collect articles focusing on the assessment of the possible effects of climate changes on aquatic species inhabiting inland waters all over the world, including the possible synergistic effects in combination with other anthropogenic stressors. A total of six original articles were published that report on investigations of different freshwater ecosystems across the world, including the mountain streams of the Western United States and Northwest Italy, river basins of Northwest China and Central Italy, a larger lowland river in north Italy, and a high-elevation temporary pond in Central Italy. In most of these papers, special attention was devoted to the repercussions of the climate change and its effects on three important components of the biotic community: the fish, benthic macroinvertebrates, and zooplankton. According to the aims of this Special Issue, three of the articles offer new insight into the synergistic effects of global warming together with other anthropogenic stressors, including water exploitation and alien species invasions. In light of the studies' aim to highlight the effects of climate change, three papers provided analyses of environmental data collected through long-term monitoring. The scientific findings provided by these studies could help to create sound management strategies for freshwater biodiversity conservation. [ABSTRACT FROM AUTHOR]