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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]

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]

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 paper discusses the radiation budget and its temporal variability over Poland. The data analysis is based on the MERRA-2 reanalysis for the years 1980–2020. During the last four decades, the enhancement of climate warming has been observed, which coincides with the changes in the radiation budget. Positive and statistically significant trends at the top of the atmosphere (TOA; 0.7 ± 0.2 W/m2/10 year) and on the Earth's surface (1.5 ± 0.2 W/m2/10 year) radiation budget (net downward flux) are mainly a consequence of changes in the amount of aerosol and greenhouse gases (GHG). According to MERRA-2, the AOD during this period decreased by − 0.19 (at 550 nm), which is 87% of the long-term (1980–2021) mean value (0.22). The reduction of AOD is due mainly to the decline of non-absorbing sulfate particles, which leads to a reduction of single-scattering albedo (SSA) by − 0.008 per decade and Angstrom exponent (AE) by − 0.06 per decade (both trends statistically significant). On the other hand, the GHG concentration increased by 4.9%/10 year and 3%/10 year, respectively, for CO2 and CH4. The total column of water vapor increased (1.3%/10 year), while ozone decreased (− 1%/10 year). Despite the fact that cloud cover and cloud optical depth (COD) decreased (− 1.8%/10 year and − 1.0%/10 year), the impact of cloud on temporal variability radiation budget is small. It can be explained by nearly compensated shortwave (SW) cooling and longwave (LW) heating effects. During the analysis period, near-surface air temperature increased by 2.0 °C. The estimated increase in SW net surface radiation (7.9 W/m2) leads to climate warming by 0.8 °C, which is a consequence mainly of the reduction of aerosol (0.4 °C) and cloud cover (0.2 °C). The impact of the change of SW radiation on air temperature is more pronounced during the warm season, while during the cold, air temperature change is controlled mainly by the variability of air mass advection. [ABSTRACT FROM AUTHOR]

Global warming poses a prominent challenge to every country. As one of the largest developing countries, China has experienced rapid economic transformation in its pursuit of sustainable development. This paper delves into a quasi-natural environmental experiment conducted in China, specifically focusing on the low-carbon city program initiated in 2010. Our study uncovers the phenomenon of regional competition among Chinese local governments with regard to carbon emissions, which in turn generates spillover effects stemming from the policy. To identify the effects of the low-carbon city policy on both economic and environmental development, we employ the spatial difference-in-differences approach. Our analysis suggests that reductions in carbon emissions in the pilot cities will lead to a decrease in carbon emissions and economic performance in the surrounding areas. Finally, by exploring firm-level data, we find that the policy significantly impacts large private firms operating in non-secondary industries. [ABSTRACT FROM AUTHOR]

The spatial clustering of life satisfaction scores noted in recent empirical research suggests that 'happier' people may live in specific neighbourhoods or regions. This prompts the questions: Do 'happier' people choose to move to specific places? Does living in specific places make people 'happier'? To answer these questions, this paper explores possible occurrences of selective mobility, and social and ecological influence. Using panel data collected in Australia from 2013 to 2021, we examine the association between life satisfaction scores and selective geographic mobility, and the possible influence that living at specific locations may have on individual life satisfaction trajectory, while controlling for individual personality traits and socio-demographic factors. Our results indicate that urban residents reporting lower life satisfaction scores before the move have a higher probability of moving to a rural area. Similarly, lower life satisfaction scores are associated with a higher probability of moving to a region with a different climate. We also find evidence that moving from the city to the country is associated with an uplift of the life satisfaction trajectory for the individual. A similar conclusion is reached for people who moved to a warmer climate, but not for a move to a cooler climate. To our knowledge, this is the first time the concepts of selective mobility and social and ecological influence have been applied in life satisfaction research. Our work provides an indicator that can be important to demographers predicting population movements. It can also inform policy development around assisting regional and rural areas attract/ retain residents to support regional sustainability. [ABSTRACT FROM AUTHOR]

AI chatbots such as ChatGPT help people produce texts. According to media reporting, these texts are also used for educational purposes. Thus, AI influences people's knowledge and perception of current issues. This paper examines the narrative of ChatGPT's stories on climate change. Our explorative analysis reveals that ChatGPT's stories on climate change show a relatively uniform structure and similar content. Generally, the narrative is in line with scientific knowledge on climate change; the stories convey no significant misinformation. However, specific topics in current debates on global warming are conspicuously missing. According to the ChatGPT narrative, humans as a species are responsible for climate change and specific economic activities or actors associated with carbon emissions play no role. Analogously, the social structuration of vulnerability to climate impacts and issues of climate justice are hardly addressed. ChatGPT's narrative consists of de-politicized stories that are highly optimistic about technological progress. [ABSTRACT FROM AUTHOR]

Carbon emissions are important factors causing global warming, which requires global efforts to deal with. In this paper, we investigate the mechanism of financial innovation on reducing carbon emissions in China by constructing a financial innovation development index with factors of green finance as well as fintech development. Empirical results show that financial innovation contributes to reduce carbon intensity by promoting energy structure transition as well as public fiscal expenditure on energy conservation and environmental protection. Moreover, heterogeneity exists in the effect of financial innovation on carbon emission reduction. Financial innovation has a significant role in reducing carbon intensity in eastern regions, but has a relatively small influence on central and western regions. Furthermore, financial innovation has a lag effect on reducing carbon intensity. [ABSTRACT FROM AUTHOR]

During extreme heat events (EHEs) the public often learns about health protective actions through the media. Visual news coverage can act as a powerful tool to help convey complex health protective actions to the public. Despite the importance of images in helping the public understand the risk, there has been no systematic analysis to assess what images have been used by media outlets in Canada during EHEs. This paper helps to fill that gap by analyzing how the Canadian media visually communicated the risks of extreme heat to the public during the unprecedented 2021 Heat Dome. A review of thousands of online news media articles published about the 2021 Heat Dome in Canada was conducted on five subscription news databases. Overall, 845 images were coded to identify denotative, connotative, and ideological content. Only 16% of these published images implied that heat was dangerous, of which only 40% depicted people, and 46% implied human suffering. Our findings demonstrate that the majority of images used in Canadian news coverage on the 2021 Heat Dome are incompatible with, and frequently contradict, evidence-based heat protective actions. Governments, public health agencies, and other stakeholders engaged in distributing heat preparedness messaging (e.g., journalists) should prioritize improving the images of extreme heat in news coverage to align with evidence-based public health messages. With rising global temperatures due to climate change and the associated increases in the frequency and intensity of extreme heat events, prioritizing these actions is critically important to offset the threat posed to public health. [ABSTRACT FROM AUTHOR]

In northern regions, the long-term serviceability of infrastructure founded on frozen ground is adversely affected by climate warming. Rates of change in temperature, which are not identical spatially and temporally, can remarkably dictate the magnitude and evolution of permafrost degradation. Investigating such impacts requires a non-isothermal rate-dependent geomechanical constitutive model for ice-contained geomaterials. In this paper, a critical-state thermo-elasto-viscoplastic (TEVP) constitutive model is developed for modeling time- and temperature-dependent behavior of frozen soils using the concepts of thermo-elasticity and thermo-viscoplasticity. Solid phase stress (defined as the excess of total stress over fluid pressure), in addition to the cryogenic suction, are considered as the two independent stress state variables to establish the model. The proposed model is able to satisfactorily capture the rate-dependent behavior of frozen soils observed in the experimental tests reported in the literature. [ABSTRACT FROM AUTHOR]

The total amount of global municipal solid waste (MSW) will reach 3.5 billion tons by 2050, thereby bringing tremendous environmental pressure, especially global warming. Large amounts of greenhouse gases (GHGs) have been released during MSW management (MSWM). Accounting for GHG emissions is a prerequisite for providing recommendations on appropriate treatment options to mitigate emissions from MSWM systems. There are many methods involved in estimating emissions. This paper summarizes the computing models commonly used in each process of the integrated MSWM system and emphasizes the influence of parameters and other factors. Compared with other disposal methods, landfilling has the highest emissions, commonly estimated using first-order decay (FOD) methods. Emission reduction can be realized through waste to energy (WtE) and resource recovery measures. IPCC is commonly used for calculating direct emissions, while LCA-based models can calculate emissions including upstream and downstream processes, whose results depend on assumptions and system boundaries. The estimation results of models vary greatly and are difficult to compare with each other. Besides, large gaps exist between the default emission factors (EFs) provided by models and those F measured in specific facilities. These findings provide a systematic view for a bettering understanding of MSW emissions as well as the estimating methods and also reveal the key points that need be developed in the future. [ABSTRACT FROM AUTHOR]

In the context of global warming and intensified human activities, glacier instability in plateau regions has increased, and glacier debris flows have become active, which poses a significant threat to the lives and property of people and socioeconomic development. The mass movement process of glacier debris flows is extremely complex, so this paper uses the 2018 Sedongpu glacier debris flow event on the Qinghai-Tibet Plateau as an example and applies a numerical simulation method to invert the whole process of mass movement. In view of the interaction between phases in the process of motion, we use the fluid-solid coupling method to describe the mass movement. The granular-flow model and drift-flux model are employed in FLOW3D software to study the mass movement process of glacier debris flows and explore their dynamic characteristics. The results indicate that the glacier debris flow lasted for 700 s, and the movement process was roughly divided into four stages, including initiation, scraping, surging and deposition; the depositional characteristics calculated by the fluid-solid coupling model are consistent with the actual survey results and have good reliability; strong erosion occurs during the mass movement, the clear volume amplification effect, and the first wave climbs 17.8 m across the slope. The fluid-solid coupling method can better simulate glacier debris flows in plateau regions, which is helpful for the study of the mechanism and dynamic characteristics of such disasters. [ABSTRACT FROM AUTHOR]

Drought concepts, definition, and classification processes have been in the field of research for decades, and especially the effects of global warming and the resulting climate change have accelerated these researches. The most used procedure for drought categorization has been in the literature under the name of Standardized Precipitation Index (SPI) with the recommendation of the World Meteorological Organization, and many modified versions of it have appeared in the open literature. Although conceptually the SPI is based on the probabilistic standardization index (PSI), some publications use the statistical standardization procedure (SSP) incorrectly. This paper lays out and explains the difference between the two types of standardization. In proper SPI applications, it is necessary to convert a given hydro-meteorological time series probability distribution function (PDF) to a standard (Gaussian) PDF with zero mean and unit standard deviation. SSP cannot accomplish this task, because the original PDF type remains the same after shifting and scaling applications. The comparison of PSI vs. SSP is provided along with their pros and cons. Accurate application of PSI is presented for annual Danube discharge, New Jersey temperature, and Istanbul/Florya precipitation records. [ABSTRACT FROM AUTHOR]

Globally, more than 2 billion tonnes of municipal solid waste (MSW) are generated each year, with that amount anticipated to reach around 3.5 billion tonnes by 2050. On a worldwide scale, food and green waste contribute the major proportion of MSW, which accounts for 44% of global waste, followed by recycling waste (38%), which includes plastic, glass, cardboard, and paper, and 18% of other materials. Population growth, urbanization, and industrial expansion are the principal drivers of the ever-increasing production of MSW across the world. Among the different practices employed for the management of waste, landfill disposal has been the most popular and easiest method across the world. Waste management practices differ significantly depending on the income level. In high-income nations, only 2% of waste is dumped, whereas in low-income nations, approximately 93% of waste is burned or dumped. However, the unscientific disposal of waste in landfills causes the generation of gases, heat, and leachate and results in a variety of ecotoxicological problems, including global warming, water pollution, fire hazards, and health effects that are hazardous to both the environment and public health. Therefore, sustainable management of MSW and landfill leachate is critical, necessitating the use of more advanced techniques to lessen waste production and maximize recycling to assure environmental sustainability. The present review provides an updated overview of the global perspective of municipal waste generation, composition, landfill heat and leachate formation, and ecotoxicological effects, and also discusses integrated-waste management approaches for the sustainable management of municipal waste and landfill leachate. [ABSTRACT FROM AUTHOR]

Once marginal in climate governance, supply-side policies which seek to restrict the production of climate warming fossil fuels are now gaining greater prominence. From national level bans and phase out policies to divestment campaigns and the creation of 'climate clubs' such as the Beyond Oil and Gas Alliance, an increasing number of such policies are being adopted by governments, cities and financial actors around the world. But why would states voluntarily relinquish potentially profitable reserves of fossil fuels? How can we account for the rise of supply-side policies, the form they take and the sites in which they are being adopted? What conditions and contexts are most conducive to the adoption and sustainability of 'first mover' bans and phase out policies? This paper seeks to build an interdisciplinary account fusing insights from diverse theoretical traditions from international political economy, political science, sociology and the literature on socio-technical transitions in order to capture the interaction of political, economic and socio-cultural drivers in national and international settings which can provide the basis of a more integrated and multi-dimensional understanding of supply-side policies. Such an account, we suggest, helps to understand the origins and evolution of supply-side policies and, more critically, the conditions which might enable the expansion of supply-side climate policies to new sites. [ABSTRACT FROM AUTHOR]

Agriculture is the leading sector that is responsible for global climate change through its significant contribution to greenhouse gas (GHG) emissions. Intriguingly, sub-Saharan Africa (SSA) is experiencing higher temperatures and lesser rainfall due to climate change enhanced by anthropogenic GHG emissions. Agriculture and energy use in the SSA predominantly influence the anthropogenic GHG leading to global warming. Therefore, reducing agricultural GHG emissions (such as carbon dioxide, nitrous oxide, and methane) plays a significant role in climate change adaptation. This paper reviews the potential implication of agriculture and energy use on climate change and its implications on environmental sustainability in SSA. Herewith, we explored various GHGs emitted through agriculture-energy use, their effects on climate change, as well as several climate change adaptation mechanisms, and gaps in existing knowledge that necessitate more research, were also explored. We found that agriculture had negative implications on climate change impacts in the SSA countries and that a more focused strategy that is both economically and technically feasible in terms of preferences for land use, effective energy use, and food supply would aid in GHG emission reduction and environmental sustainability. Adapting to the projected changes in the short term while investing in long-term mitigation strategies might be the only way toward a sustainable environment in this region. [ABSTRACT FROM AUTHOR]

An Erratum to this paper has been published: https://doi.org/10.1134/S1028334X23070188 [ABSTRACT FROM AUTHOR]

Calcareous algae are an important marine ecosystem that is under threat due to global warming and local stressors like oil and gas offshore. Under this condition, an important Brazilian oil and gas company started to monitor that environment. To carry out this monitoring, a deep learning classifier was proposed. However, the elaborated dataset presented noisy labels. Noisy labels mean that some dataset samples are mislabeled, and it degenerates the robustness of the model. State-of-the-art models to deal with it use small loss technique. This technique excludes from the training set noisy labels and keeps the cleans. The state-of-the-art models apply different techniques on the set of clean samples to improve their performance. We introduce in this work a novel framework to deal with noise, that can improve "small loss" models' performance, named retrieving discard samples (RDS), that under ideal conditions is equivalent to training without any noise. The main idea of this method is to retrieve the discarded samples, add a pseudo-label to the excluded samples and return them to the training stage. This paper demonstrates the adaptability of the framework RDS to other models utilizing the small loss approach. Furthermore, two novel models are proposed to effectively handle noisy labels. Results show that RDS significantly improves the accuracy of both models, achieving superior results than the state-of-the-art approaches. We also developed a deep learning model for calcareous algae environmental monitoring based in RDS approach that improved the performance of F'-Score in 4.2% when compared to standard deep learning classifiers. [ABSTRACT FROM AUTHOR]

Ecological footprint (EFP) measures the amount of area, that is land or sea, which is required to absorb the waste generated through human activities or to support the production of resources consumed by populations. EFP index therefore includes six dimensions that are cropland, forestland, carbon, fishing grounds, grazing land, and built-up area. Human activities have impacted the environment, leading to global warming, widespread droughts, and diseases. The present study aims to investigate the role of renewable energy (RE) and energy efficiency on the EFP index. Past researchers have widely used carbon emission (CE) to represent environmental impact, and recent studies have shown that EFP index is a better proxy of environmental degradation. Therefore, the present research differs from past studies in that it compares on how the determinants of environmental degradation affects EFP index and CE. Panel dataset of the OECD countries from 1990 to 2020 is employed. The CS-ARDL, DCCEMG, and AMG techniques, which overcome dynamics, heterogeneity, and cross-sectional dependence, are employed. The main findings depict that RE significantly reduces EFP and CE, while economic growth significantly exacerbates them. Energy efficiency reduces CE, but does not significantly affect EFP. Non-renewable energy and research & development significantly increase CE, while an insignificant positive effect is observed with EFP. This paper shows that factors that significantly influence CE may not always significantly affect the EFP index. Thus, to reduce environmental degradation it is fundamental to understand on how each dimension of EFP is influenced. [ABSTRACT FROM AUTHOR]

Low-carbon design that reduces the life cycle carbon emissions of products at source is increasingly becoming an important direction in product design to mitigate global warming further. An important design principle should be minimizing the product's weight and movement efficiency while minimizing its life cycle carbon emissions. This paper proposed a product kinematic analysis based on carbon footprint. After that, it developed a flexible picking actuator for tomato fruit based on the Bricard mechanism. Through kinematic analysis of the picking actuator, the optimized design of the mechanism is followed by simulation tests to reduce the carbon footprint over its life cycle. A systematic carbon footprint calculation model for the Bricard mechanism-based picking actuator is also developed and applied in the product design process to verify the design mechanism's feasibility, method and technology. [ABSTRACT FROM AUTHOR]

The paper is devoted to anthropogenic and biogeochemical processes that effect the formation of the water and bottom sediment (BS) of subarctic Imandra Lake. The data of long-term observations are presented that show changes in the chemical composition of the water during the period of maximum pollution and after the reduction in the anthropogenic load over the past 30 years. The concentrations of toxic metals in the water has decreased, but climate warming has increased the inflow of organic matter and nutrients, and this intensified the production processes. The enrichment of the water in heavy metals during the period of intense pollution resulted in the accumulation of these metals in the bottom sediments, with the highest concentrations of the metals found in the uppermost layers accumulated during the modern sedimentation period. The development of anoxic conditions in the bottom water horizons due to sedimentation and oxidation of organic matter leads to the circulation of metals and hampers their burial. Physicochemical and biogeochemical processes are considered as explaining the diffusion of metals to the surface of the bottom sediments and the accumulation of anomalously high concentrations of metals in the surface layers of BS despite the significant decrease in the concentrations of metals in water. A hypothesis is suggested for the beginning of initial diagenesis stage in bottom sediments. [ABSTRACT FROM AUTHOR]

Two algorithms have been proposed in this paper. One is another scanning t test of trend change points in regression slope coefficients in two phases, along with a coherency analysis of trend changes between two time series. It is different from the previously published scanning Fmax test of trend changes. The second is a fuzzy weighted moving average (FWMA). Then, the algorithms were applied to two series of monthly temperatures over global land and ocean surfaces for 1850–2021. The applied results show that significant changes in segment trends appeared in two gradations on the interdecadal and intradecadal scales. All subsample regression models were found to fit well with those data. Global warming started in April 1976 with a good coherency of warming trends between land and sea. The global warming "hiatus" mainly occurred in SST cooling from November 2001 to April 2008, but was not evinced over land on interdecadal scales. The "land/sea warming contrast" was detected only in their anomaly series, but disappeared in their standardized differences. We might refer to the anomalies in distribution N(0,s) as "perceptual" indicators and refer to the standardized differences in N(0,1) as "net" indexes. [ABSTRACT FROM AUTHOR]

This special issue aims to display the breadth and depth of qualitative studies of the environment. In terms of breadth, the work here demonstrates that sociology should have a capacious definition of the environment and treat it with the same scrutiny as other folk concepts. Doing so—with the caveat that individual studies need to carefully operationalize ‘the environment’—reveals how a sociology of the environment has great deal to contribute to our understandings of community, culture, and inequality. In terms of depth, these articles develop new theoretical and empirical areas for environmental sociology, expanding the subfield internationally and bringing it up to date in terms of its relevance for understanding our current moment of pandemic, global warming, and nature fetishization. The outstanding papers collected in this special issue provide manifold lessons, connect to other sociological subfields, and, together, generate a sense of urgency for more qualitative studies of the environment. [ABSTRACT FROM AUTHOR]

As an important food crop in the world, potato has been attracting scholarly attention to improve its yield in the future, particularly under climate change. Therefore, analyzing the potential yield of potato as affected by global warming is of great significance to direct the production of crops worldwide. However, up to now, most research reports estimated the potential yield of potatoes by models which are based on the theory of production functions while there are few theoretical studies on the time-series approach based on stationary stochastic processes. Thus, in this paper, both average and top (national) yields of potato between 2021 and 2030 are projected creatively using an auto-regressive integrated moving average and trend regression (ARIMA-TR) model basing the projection on historic yields from 1961 to 2020 to explore the potential yield of the crop in the future; the effects of global warming on both average and top (national) yields of potato from 1961 to 2020 are analyzed using binary regression models in which global mean temperature is treated as the independent variable and the yield as the dependent variable, to reveal how climatic events drive the variation trend of these two types of yield. Our results show that between 2021 and 2030, the average yield of potato is projected to be from 21,234 to 23,773 kg/ha while the top yield ranges from 50,240 to 51,452 kg/ha; the average will approach from 42.26 to 46.20% of the top, or the gap between these two yields will be gradually narrowed in the ensuing decade; from 1961 to 2020, global warming exerts a positive effect on the average yield of potato with a quadratic function (R-squared = 0.772 and F = 96.417) more than on the top yield with an inverse function (R-squared = 0.568 and F = 76.201), which partly makes the gap between these two types of yields shrink. Our study concludes that for potato by 2030, the opportunities for improving global production should be dependent on both high- and low-yield countries as the average yield is in the main body of an S-shaped curve in the evolutionary trend in the long run. These insights provide the academic circle with innovative comprehension of the potential yield of potato for global food security under climate change. [ABSTRACT FROM AUTHOR]

Cryospheric hazards - in this case, thaw slumps (TS) and thermo-erosion gullies (TEG) - are phenomena typical of permafrost-dominated landscapes. Open datasets informing about their spatial, temporal and size distributions in the Arctic are still uncommon, as opposed to the systematic availability of this information for geomorphic processes in mid- to low- latitudes. To date, only the most populated region of Svalbard was covered with TS and TEG inventories. Here, we extend the respective information to most of the Archipelago, totalling 8491 polygons, out of which 3679 are TSs and 4812 are TEGs. These have been manually mapped from aerial photographs throughout Svalbard across the 14 largest ice-free regions. The SvalCryo inventory is highly relevant as the Arctic environment undergoes alarming changes in response to global warming. The idea behind the two inventories is to support the geoscientific community in the quest to evaluate the environmental response to climate change, by creating a baseline for change monitoring, and ultimately to serve as basis for susceptibility, hazard and risk assessment models. [ABSTRACT FROM AUTHOR]

Arctic sea ice mediates atmosphere-ocean momentum transfer, which drives upper ocean circulation. How Arctic Ocean surface stress and velocity respond to sea ice decline and changing winds under global warming is unclear. Here we show that state-of-the-art climate models consistently predict an increase in future (2015–2100) ocean surface stress in response to increased surface wind speed, declining sea ice area, and a weaker ice pack. While wind speeds increase most during fall (+2.2% per decade), surface stress rises most in winter (+5.1% per decade) being amplified by reduced internal ice stress. This is because, as sea ice concentration decreases in a warming climate, less energy is dissipated by the weaker ice pack, resulting in more momentum transfer to the ocean. The increased momentum transfer accelerates Arctic Ocean surface velocity (+31–47% by 2100), leading to elevated ocean kinetic energy and enhanced vertical mixing. The enhanced surface stress also increases the Beaufort Gyre Ekman convergence and freshwater content, impacting Arctic marine ecosystems and the downstream ocean circulation. The impacts of projected changes are profound, but different and simplified model formulations of atmosphere-ice-ocean momentum transfer introduce considerable uncertainty, highlighting the need for improved coupling in climate models. The authors use climate models and show that projected declining and weakening Arctic sea ice, combined with stronger winds, will enhance ocean surface stress. This increased momentum transfer will spin up surface currents, leading to a more energetic Arctic Ocean in the future. [ABSTRACT FROM AUTHOR]

Understanding the alterations in soil microbial communities in response to climate warming and their controls over soil carbon (C) processes is crucial for projecting permafrost C-climate feedback. However, previous studies have mainly focused on microorganism-mediated soil C release, and little is known about whether and how climate warming affects microbial anabolism and the subsequent C input in permafrost regions. Here, based on a more than half-decade of in situ warming experiment, we show that compared with ambient control, warming significantly reduces microbial C use efficiency and enhances microbial network complexity, which promotes soil heterotrophic respiration. Meanwhile, microbial necromass markedly accumulates under warming likely due to preferential microbial decomposition of plant-derived C, further leading to the increase in mineral-associated organic C. Altogether, these results demonstrate dual roles of microbes in affecting soil C release and stabilization, implying that permafrost C-climate feedback would weaken over time with dampened response of microbial respiration and increased proportion of stable C pool. Understanding microbial responses to climate warming is crucial for projecting permafrost carbon-climate feedback. Here, the authors reveal dual microbial roles in promoting both soil carbon release and stable soil carbon accrual under warming scenario. [ABSTRACT FROM AUTHOR]

This interdisciplinary study critically analyzes current research, establishing a profound connection between sea water, sea ice, sea temperature, and surface temperature through a 4D hyperchaotic Caputo fractional differential equation. Emphasizing the collective impact on climate, focusing on challenges from anthropogenic global warming, the study scrutinizes theoretical aspects, including existence and uniqueness. Two sliding mode controllers manage chaos in this 4D fractional system, assessed amid uncertainties and disruptions. The global stability of these controlled systems is also confirmed, considering both commensurate and non-commensurate 4D fractional order. To demonstrate the intricate chaotic motion within the system, we employ the Lyapunov exponent and Poincare sections. Numerical simulations are conducted by using the predictor-corrector method. The effects of surface temperature on chaotic dynamics are discussed. The crucial role of sea ice reflection in climate stability is highlighted in two scenarios. Correlation graphs, comparing model and observational data using the predictor-corrector method, enhance the proposed 4D hyperchaotic model's credibility. Subsequently, numerical simulations validate theoretical assertions about the controllers' influence. These controllers indicate which variable significantly contributes to controlling the chaos. [ABSTRACT FROM AUTHOR]

In today's era, environmental concerns are given equal importance to economic growth to attain sustainability. By implementing economic strategies, we can achieve economic enrichment, while adopting pollution prevention practices can lead to environmental and economic improvements. Therefore, this study examines the impact of pollution prevention practices on the economic and environmental sustainability of nine Asian countries. This study utilizes data from selected economically thriving Asian countries and employs the ARDL approach using EViews v10 for estimation. This study holds great significance for these states, as they are the most vulnerable to global warming and adverse effects of climate change. Furthermore, the findings of this study have policy implications for Asian economies and other developing nations, providing guidelines for governments and policymakers to effectively sustain their environmental resources for both current and future use, while simultaneously boosting their economic and environmental sustainability. [ABSTRACT FROM AUTHOR]

Understanding the large-scale pattern of soil microbial carbon use efficiency (CUE) and its temperature sensitivity (CUET) is critical for understanding soil carbon–climate feedback. We used the 18O-H2O tracer method to quantify CUE and CUET along a north-south forest transect. Climate was the primary factor that affected CUE and CUET, predominantly through direct pathways, then by altering soil properties, carbon fractions, microbial structure and functions. Negative CUET (CUE decreases with measuring temperature) in cold forests (mean annual temperature lower than 10 °C) and positive CUET (CUE increases with measuring temperature) in warm forests (mean annual temperature greater than 10 °C) suggest that microbial CUE optimally operates at their adapted temperature. Overall, the plasticity of microbial CUE and its temperature sensitivity alter the feedback of soil carbon to climate warming; that is, a climate-adaptive microbial community has the capacity to reduce carbon loss from soil matrices under corresponding favorable climate conditions. The climate-dependency of microbial carbon use efficiency thermal sensitivity is demonstrated in a forest transect experiment, with implications for soil carbon feedbacks to climate warming. [ABSTRACT FROM AUTHOR]

In August 2022, an unprecedented compound heatwave and drought event (CHDE) lasting 24 days occurred in the Yangtze River valley (YRV), leading to a severe reduction of the crop, fresh water, and power supply. We constructed a joint cumulative probability distribution of heatwave and drought intensity, and found that the lowest probability-based index (PI) of 0.06 in 2022 was estimated as a 1-in-662-year event over the 1961–2022 climate. We then detected the fingerprint of greenhouse gas forcing to the observed PI in a generalized extreme value framework, but not the aerosol forcing, suggesting the leading contribution of greenhouse gas forcing on such extreme CHDE. Furthermore, anthropogenic influence had increased the probability of such CHDE by more than 10 times compared to the counterfactual climate. Also, the PI decreased from about 0.30 at the present climate to about 0.14 at the 3 °C global warming level, indicating that CHDE will become more extreme over YRV. [ABSTRACT FROM AUTHOR]

Highway shoulder rocks are exposed to continuous erosion force due to extreme rainfall that could be caused by global warming to some extent. However, the logical design method for erosion-resistant highway shoulder is not well-researched yet. This study utilized a large-scale UNLETB (University of Nebraska Lincoln–Erosion Testing Bed) with a 7.6 cm nozzle width and a 4000 cm3/sec flow rate to study the erosion characteristics of highway shoulder rocks. Test results showed that different shoulder materials currently used had vastly diverse erosion resistance. However, the clear criteria between the erosion-resistant gradation and other gradation could not be determined easily. Then, this study trained ANN (Artificial Neural Network) with test results to conveniently distinguish the erosion resistance of rocks from other rocks. The ANN predicted the acceptable/non-acceptable erosion characteristics of shoulder rocks with close to 99% accuracy based on the three gradation parameters (D10, D30, and D60). [ABSTRACT FROM AUTHOR]

The Paris Agreement and the Special Report on Global Warming of 1.5 °C from the Intergovernmental Panel on Climate Change (IPCC) highlighted the potential risks of climate change across different global warming levels (GWLs). The increasing occurrence of extreme high-temperature events is linked to a warmer climate that is particularly prevalent in the Arabian Peninsula (AP). This study investigates future changes in temperatures and related extremes over AP, under four GWLs, such as 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C, with three different Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The study uses high-resolution datasets of 27 models from the NASA Earth Exchange Global Daily Downscaled Projections of the Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6). The results showed that the NEX-GDDP-CMIP6 individual models and their multi-model means reasonably captured the extreme temperature events. The summer maximum and winter minimum temperatures are projected to increase by 0.11–0.67 °C and 0.09–0.70 °C per decade under the selected SSPs. Likewise, the projected temperature extremes exhibit significant warming with varying degrees across the GWLs under the selected SSPs. The warm temperature extremes are projected to increase, while the cold extremes are projected to decrease under all GWLs and the selected SSPs. Overall, the findings provide a comprehensive assessment of temperature changes over AP in response to global warming, which can be helpful in the development of climate adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

As global warming's impact on humanity surpasses initial predictions, numerous countries confront heightened risks associated with escalating urban carbon footprints. Concurrently, digital finance has flourished, propelled by advancements in digital technology. This convergence underscores the urgency of exploring digital finance's role in mitigating urban carbon footprint pressures. This study analyzes data spanning 277 Chinese cities from 2011 to 2020, yielding several key findings: Firstly, we developed a dataset detailing the carbon footprint pressures in these cities, revealing that variations in these pressures predominantly correlate with economic growth. Secondly, our analysis indicates that digital finance has a significant impact on reducing urban carbon footprint pressures, through mechanisms such as reducing the number of physical bank branches and enhancing residents' environmental awareness. Thirdly, the study identifies that the efficacy of digital finance in reducing carbon footprint pressures varies according to factors like sunshine duration and geographic location. The insights from this research aim to contribute substantively to strategies for sustainable urban development. [ABSTRACT FROM AUTHOR]

In recent years, climate change as a consequence of global warming, has garnered significant attention. Therefore, serious measures must be considered in the development planning process to adapt to and reduce effects of climate change. This research evaluates six development plans in Isfahan, Iran in the face of climate change effects using a framework consisting of three components of the analytical Awareness-Analysis-Action (A-A-A) approach and using quantitative and qualitative content analysis methods. In fact, the evaluation of the level of attention of the development plans from the perspective of the level of reflection and attention to raising awareness about the issues of climate change, the ability to analyze the available climate information in a useful way to support planning decisions and the level of special actions to deal with these changes. Finally, out of the three elements of the approach, the highest amount of attention in the plans is related to the element of action with 67/70% and the lowest is related to the element of awareness with 39/10%. The overall evaluation of the development plans shows that their role in integrating climate change issues into urban planning in Iran is still limited and insufficient. On the other hand, air pollution and climate change are closely related, as chemicals that cause air quality deterioration often enter together with greenhouse gases. Therefore, it can be said that although indicators of the transportation dimension (A3-J) with 80.66%, resource management have been given special attention under the action component, but carbon sequestration dimension (A2-F) with 14.63%, under the analysis component that seeks to evaluate the amount of air pollutants, classification of the type and sources of emission of pollutants could not reflect more than half of the total percentage in all development plans. [ABSTRACT FROM AUTHOR]

Large-scale geological sequestration of CO2 is one of the most effective strategies to limit global warming to below 2 °C, as recommended by the Intergovernmental Panel on Climate Change (IPCC). Therefore, identifying and characterizing high-quality storage units is crucial. The Surma Basin, with its four-way dip closed structures, high-quality reservoirs, and thick regional cap rocks, is an ideal location for CO2 storage. This study focuses on the Bokabil Formation, the most prominent reservoir unit in the Surma Basin. Detailed petrographic, petrophysical, XRD, and SEM analyses, along with mapping, have been conducted to evaluate the properties of the reservoir and cap rock within this formation. The Upper Bokabil Sandstone in the Surma Basin ranges from 270 to 350 m in thickness and consists of fine- to medium-grained subarkosic sandstones composed of 70–85% quartz and 5–12% feldspar, with good pore connectivity. Petrophysical analysis of data from four gas fields indicates that this unit has a total porosity of 21–27.4% and a low shale volume of 15–27%. Cross plots and outcrop observations suggest that most of the shales are laminated within the reservoir. The regional cap rock, known as the Upper Marine Shale (UMS), ranges in thickness from 40 to 190 m and contains 10–40 nm nano-type pores. A higher proportion of ductile materials with a significant percentage of quartz in the UMS indicates higher capillary entry pressures, enhancing its capacity to hold CO2. Using the CSLF method with a 6% cut-off of the available pore volume, it is estimated that 103 Mt, 110 Mt, 205 Mt, and 164 Mt of CO2 can be effectively stored in the Sylhet, Kailashtila, Habiganj, and Fenchuganj structures, respectively. Due to the shallow depth of the storage unit and the thick cap rock, the southern Surma Basin is the optimal location for CO2 injection. [ABSTRACT FROM AUTHOR]

Climate warming is one of the facets of anthropogenic global change predicted to increase in the future, its magnitude depending on present-day decisions. The north Atlantic and Arctic Oceans are already undergoing community changes, with warmer-water species expanding northwards, and colder-water species retracting. However, the future extent and implications of these shifts remain unclear. Here, we fitted a joint species distribution model to occurrence data of 107, and biomass data of 61 marine fish species from 16,345 fishery independent trawls sampled between 2004 and 2022 in the northeast Atlantic Ocean, including the Barents Sea. We project overall increases in richness and declines in relative dominance in the community, and generalised increases in species' ranges and biomass across three different future scenarios in 2050 and 2100. The projected decline of capelin and the practical extirpation of polar cod from the system, the two most abundant species in the Barents Sea, drove an overall reduction in fish biomass at Arctic latitudes that is not replaced by expanding species. Furthermore, our projections suggest that Arctic demersal fish will be at high risk of extinction by the end of the century if no climate refugia is available at eastern latitudes. Using a joint species distribution model fitted to 61 species, this study shows that the habitat of Arctic fish might be hugely reduced in the next decades, and potentially eliminated from the Barents Sea. Boreal species are shown to expand their habitat, leading to increased species richness in the area and a diversification of dominance, but this might not increase overall biomass. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) have experienced poleward migration in recent years, but whether this exists in future projections with high-resolution climate models remains unclear. This study investigates the poleward migration of TCs over the western North Pacific (WNP) using CMIP6-HighResMIP models. We first assess the model performance in TC genesis frequency and latitude, which differ greatly from the observations, especially in winter and spring due to misinterpretation of extratropical storms. In this study, we put forward a revised constrained detection method based on the sea surface temperature (SST) and the atmospheric conditions to resolve this bias. Results indicate that the revised detection method has good performance in capturing the annual cycle of TC genesis frequency and latitude. Future projections constrained by this method show that the latitude of TC genesis and lifetime maximum intensity (LMI) both undergo a poleward shift, with the former being more significant. Spatial changes in the dynamic potential genesis index and large-scale environment could explain this shift. The regional changes of Hadley circulation and the role of global warming and internal variability are also discussed. [ABSTRACT FROM AUTHOR]

Background: Understanding the effects of climate change on agro-ecosystems is fundamental in order to select the optimum management practices to mitigate environmental pressures. There is a need to forecast greenhouse gas emissions (GHG) emissions of grassland systems under climate change scenarios whilst also accounting for SOC sequestration. The objective of this study is to assess the net GHG emissions over > 405,000 hectares (ha) of moist temperate Northern Spanish grasslands utilised for dairy production, under climate change conditions (i.e., RCP 4.5, and RCP 8.5), compared to a reference baseline scenario. It is hypothesised that net GHG will increase under climate change conditions and that implementing specific manure management practices (namely the anaerobic digestion (AD)) may mitigate the global warming effect. Methods: We used an integrated modelling framework comprising: (i) geographic information systems (GIS); (ii) a modified RothC version to simulate SOC changes in managed grasslands under moist temperate conditions; and (iii) Tier 2 recent IPCC methods to estimate GHG emissions. Results: Average net GHG emissions contributed to global warming potential with average emissions of 5.8 and 6.2 Mg CO2-e ha−1 year−1, under RCP 4.5 and RCP 8.5, respectively. Anaerobic digestion allowed net GHG under both climate change scenarios to equal net GHG under the baseline reference scenario. Conclusion: Under climate change conditions, implementing specific manure management practices, namely AD, will likely reduce the net GHG emissions of the grassland systems associated with dairy production in Northern Spain. [ABSTRACT FROM AUTHOR]

CO2 is the primary greenhouse gas emitted through human activities which cause global warming. Many countries and international regulations aim to reduce CO2 and encourage development of a net-zero society by 2050, thus, CCUS (carbon capture, utilization, and storage) can be considered as a key technology for achieving this goal. Among the many industrial processes, NaHCO3 production is a representative CCUS technology which satisfies both CO2 reduction and economic incentive. Recently, Na2SO4 waste, containing 15% impurities (i.e., various heavy metals), produced as a by-product generated from desulfurized processes in steel industry has received a great deal of attention since landfilling has been the only way to treat it. Na2SO4 could be a suitable source of NaHCO3 production as CCUS; however, there are no commercial processes for production of NaHCO3 using Na2SO4 as the raw material, since it has low production efficiency compared to other Na+ sources. This study evaluates the regeneration of NaHCO3 using Na2SO4 waste and our results show that a combination of Na2SO4 waste and the addition of 20% Na2CO3 can sharply increase the yield of NaHCO3 with minimizing the consumption of expensive NH3 since alkaline properties of Na2CO3. [ABSTRACT FROM AUTHOR]

Urban populations face heightened extreme heat risks attributed to urban heat islands and high population densities. Although previous studies have examined global urban population exposure to heatwaves, the influence of urbanization-induced warming is still not quantified. Here, leveraging satellite-derived near-surface air temperature data, we assess the impacts of urbanization-induced warming on heat exposure in 1028 cities worldwide. Additionally, we investigate its role in shaping disparities in heat exposure between global North and South cities. Our findings reveal that urbanization-amplified compound heatwaves exacerbate heat exposure risk in more than 90% of cities, and that this amplification is stronger in high urbanization areas. Moreover, our analysis highlights the potential for overestimating disparities between global North and South cities if urbanization-induced warming is overlooked. The inequality of higher heat exposure in the global South cities than in the global North cities will be narrowed in real scenarios due to more intense urbanization-induced warming in the global North cities. We emphasize the pivotal role of urbanization-induced heatwave intensification in heat exposure assessments and call for its inclusion in future population vulnerability evaluations to extreme heat. [ABSTRACT FROM AUTHOR]