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Many higher education institutions around the world are engaged in efforts to tackle climate change. This takes place by not only reducing their own carbon footprint but also by educating future leaders and contributing valuable research and expertise to the global effort to combat climate change. However, there is a need for studies that identify the nature of their engagement on the topic, and the extent to which they are contributing towards addressing the many problems associated with climate change. Against this background, this paper describes a study that consisted of a review of the literature and the use of case studies, which outline the importance of university engagement in climate change and describe its main features. The study identified the fact that even though climate change is a matter of great relevance to universities, its coverage in university programmes is not as wide as one could expect. Based on the findings, the paper also lists the challenges associated with the inclusion of climate change in university programmes. Finally, it describes some of the measures which may be deployed in order to maximise the contribution of higher education towards handling the challenges associated with a changing climate. [ABSTRACT FROM AUTHOR]

Our environment has been significantly impacted by climate change. According to previous research, insect catastrophes induced by global climate change killed many trees, inevitably contributing to forest fires. The condition of the forest is an essential indicator of forest fires. Analysis of aerial images of a forest can detect deceased and living trees at an early stage. Automated forest health diagnostics are crucial for monitoring and preserving forest ecosystem health. Combining Modified Generative Adversarial Networks (MGANs) and YOLOv5 (You Only Look Once version 5) is presented in this paper as a novel method for assessing forest health using aerial images. We also employ the Tabu Search Algorithm (TSA) to enhance the process of identifying and categorizing unhealthy forest areas. The proposed model provides synthetic data to supplement the limited labeled dataset, thereby resolving the frequent issue of data scarcity in forest health diagnosis tasks. This improvement enhances the model's ability to generalize to previously unobserved data, thereby increasing the overall precision and robustness of the forest health evaluation. In addition, YOLOv5 integration enables real-time object identification, enabling the model to recognize and pinpoint numerous tree species and potential health issues with exceptional speed and accuracy. The efficient architecture of YOLOv5 enables it to be deployed on devices with limited resources, enabling forest-monitoring applications on-site. We use the TSA to enhance the identification of unhealthy forest areas. The TSA method effectively investigates the search space, ensuring the model converges to a near-optimal solution, improving disease detection precision and decreasing false positives. We evaluated our MGAN-YOLOv5 method using a large dataset of aerial images of diverse forest habitats. The experimental results demonstrated impressive performance in diagnosing forest health automatically, achieving a detection precision of 98.66%, recall of 99.99%, F1 score of 97.77%, accuracy of 99.99%, response time of 3.543 ms and computational time of 5.987 ms. Significantly, our method outperforms all the compared target detection methods showcasing a minimum improvement of 2% in mAP. [ABSTRACT FROM AUTHOR]

The stochastic synthesis of extreme, rare climate scenarios is vital for risk and resilience models aware of climate change, directly impacting society in different sectors. However, creating high-quality variations of under-represented samples remains a challenge for several generative models. This paper investigates quantizing reconstruction losses for helping variational autoencoders (VAE) better synthesize extreme weather fields from conventional historical training sets. Building on the classical VAE formulation using reconstruction and latent space regularization losses, we propose various histogram-based penalties to the reconstruction loss that explicitly reinforces the model to synthesize under-represented values better. We evaluate our work using precipitation weather fields, where models usually strive to synthesize well extreme precipitation samples. We demonstrate that bringing histogram awareness to the reconstruction loss improves standard VAE performance substantially, especially for extreme weather events. [ABSTRACT FROM AUTHOR]

In this paper, a critical issue related to power management control in autonomous hybrid systems is presented. Specifically, challenges in optimizing the performance of energy sources and backup systems are proposed, especially under conditions of heavy loads or low renewable energy output. The problem lies in the need for an efficient control mechanism that can enhance power availability while protecting and extending the lifespan of the various power sources in the system. Furthermore, it is necessary to adapt the system's operations to variations in climatic conditions for sustained effectiveness. To address the identified problem. It is proposed the use of an intelligent power management control (IPMC) system employing fuzzy logic control (FLC). The IPMC is designed to optimize the performance of energy sources and backup systems. It aims to predict and adjust the system's operating processes based on variations in climatic conditions, providing a dynamic and adaptive control strategy. The integration of FLC is specifically emphasized for its effectiveness in balancing multiple power sources and ensuring a steady and secure operation of the system. The proposed IPMC with FLC offers several advantages over existing strategies. Firstly, it showcases enhanced power availability, particularly under challenging conditions such as heavy loads or low renewable energy output. Secondly, the system protects and extends the lifespan of the power sources, contributing to long-term sustainability. The dynamic adaptation to climatic variations adds a layer of resilience to the system, making it well-suited for diverse geographical and climatic conditions. The use of realistic data and simulations in MATLAB/Simulink, along with real-time findings from the RT-LAB simulator, indicates the reliability and practical applicability of the proposed IPMC strategy. Efficient load supply and preserved batteries further underscore the benefits of the fuzzy logic-based control strategy in achieving a well-balanced and secure system operation. [ABSTRACT FROM AUTHOR]

Global distribution of salt-affected soils (SAS) has remained at about 1 billion hectares in the literature over the years despite changes in climate, sea levels, and land use patterns which influence the distribution. Lack of periodic update of input soil data, data gaps, and inconsistency are part of the reasons for constant SAS distribution in the literature. This paper proposes harmonization as a suitable alternative for managing inconsistent data and minimizing data gaps. It developed a new harmonization service for supporting country-driven global SAS information update. The service contains a global library of harmonization models for harmonizing inconsistent soil data. It also contains models for identifying gaps in SAS database and for showing global distribution where harmonization of available data is needed. The service can be used by countries to develop national SAS information and update global SAS distribution. Its data availability index is useful in identifying countries without SAS data in the global database, which is a convenient way to identify countries to mobilize when updating global SAS information. Its application in 27 countries showed that the countries have more SAS data than they currently share with the global databases and that most of their data require SAS harmonization. [ABSTRACT FROM AUTHOR]

The major cause of soil degradation (contamination, erosion, compaction) is closely linked to agriculture, i.e., unsustainable agriculture practices, which are reflected in the depletion of the soil organic carbon pool, loss in soil biodiversity, and reduction of C sink capacity in soils. Therefore, the agricultural practice of applying carbon-rich materials into the soil is an attractive solution for climate change mitigation and soil ecosystem sustainability. The paper aimed to evaluate the effectiveness of the addition of organic-mineral mixtures to the mineral salts (NPK), including the exogenous organic matter (lignite) mixed with zeolite-carbon (NaX-C) or zeolite-vermiculite (NaX-Ver) composites in the restoration of soils contaminated with PAHs. The addition of zeolite composites to fertilizer resulted in a significant reduction in soil PAH levels and a corresponding reduction in plant tissue content, without compromising yields, compared to the control and separate application of NPK. A Significant correlation between PAHs and pHH2O, pHKCl, EC and dehydrogenase activity (DhA) was found in soils. The addition of zeolite composites with lignite significantly reduced the content of PAHs in straws, especially following the application of NaX-C. However, in the case of grains, the highest percentage reduction in comparison to NPK was observed for the highest dose of NaX-Ver. [ABSTRACT FROM AUTHOR]

A crucial aspect analysed during the last years, aiming to improve sugarcane production, is the impact of climate change on sugarcane productivity. One of the strategies to mitigate climate change's impact on sugarcane yield is the development of new varieties known to positively affect crop production. This paper analysed how climate change impacts sugarcane production regarding the different planted varieties. Data regarding sugarcane harvest were collected from a cooperative in the south of Goiás state—Brazil, the second biggest national sugarcane producer. Results indicate that climate impact on sugarcane yield is irrelevant when controlling for different varieties. Considering the results presented in this work, the Brazilian government should keep the incentives for the development of new sugarcane varieties and, at the same time, spur sugarcane producers to use the new sugarcane varieties. The results imply that if the variety is correctly chosen, sugarcane can be produced without harming the environment, contributing to reaching SDG 15. Moreover, it is less probable that an adverse climatic event will destroy the planted area, preventing sugarcane producers from severe loss and contributing to achieving SDGs number 1 and 2. [ABSTRACT FROM AUTHOR]

Due to the severe effects of climate change on the agricultural sector, urgent action is required on the part of farmers and is, indeed, critical to reducing climate change impacts. However, reports globally revealed farmers' engagement in climate change adaptation is still insufficient, ambivalent, and inconsistent and farmers do not consider adaptation to be urgent. Researchers have argued that this issue is rooted in psychological biases beside other factors. Therefore, the aim of this study is to evaluate how psychological distance determines climate change beliefs, risk perception and adaptation strategies among Iranian farmers. A cross-sectional paper-based survey was conducted in the Dasht-e Azadegan county of Khuzestan province in southwest Iran. The study sample consisted of 250 farmers selected through a multi-stage random sampling process. An expert panel review and a pilot study were conducted to confirm convergent validity and reliability of the scales. The results confirm that all four dimensions of psychological distance influence water management adaptation strategies and non-farm activities. Moreover, all psychological dimensions, except the temporal dimension, affect adaptation in farming management. Thus, making climate change more proximal to decision makers could be a strategic way of encouraging individuals to take adaptive actions. This study emphasizes that concepts of psychological distance can be applied to help organizations (e.g., agriculture extension services) to understand farmers' risk perceptions and responses to climate change impacts and improve risk communication to better engage farmers in climate action. [ABSTRACT FROM AUTHOR]

Urban surfaces are often covered by impermeable materials such as concrete and asphalt which intensify urban runoff and pollutant concentration during storm events, and lead to the deterioration of the quality of surrounding water bodies. Detention ponds are used in urban stormwater management, providing two-fold benefits: flood risk reduction and pollution load minimization. This paper investigates the performance of nine proposed detention ponds (across the city of Renton, Washington, USA) under different climate change scenarios. First, a statistical model was developed to estimate the pollutant load for the current and future periods and to understand the effects of increased rainfall on stormwater runoff and pollutant loads. The Personal Computer Storm Water Management Model (PCSWMM) platform is employed to calibrate an urban drainage model for quantifying stormwater runoff and corresponding pollutant loads. The calibrated model was used to investigate the performance of the proposed nine (9) detention ponds under future climate scenarios of 100-year design storms, leading to identifying if they are likely to reduce stormwater discharge and pollutant loads. Results indicated significant increases in stormwater pollutants due to increases in rainfall from 2023 to 2050 compared to the historical period 2000–2014. We found that the performance of the proposed detention ponds in reducing stormwater pollutants varied depending on the size and location of the detention ponds. Simulations for the future indicated that the selected detention ponds are likely to reduce the concentrations (loads) of different water quality constituents such as ammonia (NH3), nitrogen dioxide (NO2), nitrate (NO3), total phosphate (TP), and suspended solids (SS) ranging from 18 to 86%, 35–70%, 36–65%, 26–91%, and 34–81%, respectively. The study concluded that detention ponds can be used as a reliable solution for reducing stormwater flows and pollutant loads under a warmer future climate and an effective adaptation option to combat climate change related challenges in urban stormwater management. [ABSTRACT FROM AUTHOR]

Climate change is a critical issue of our time, and its causes, pathways, and forecasts remain a topic of broader discussion. In this paper, we present a novel data driven pathway analysis framework to identify the key processes behind mean global temperature and sea level rise, and to forecast the magnitude of their increase from the present to 2100. Based on historical data and dynamic statistical modeling alone, we have established the causal pathways that connect increasing greenhouse gas emissions to increasing global mean temperature and sea level, with its intermediate links encompassing humidity, sea ice coverage, and glacier mass, but not for sunspot numbers. Our results indicate that if no action is taken to curb anthropogenic greenhouse gas emissions, the global average temperature would rise to an estimated 3.28 °C (2.46–4.10 °C) above its pre-industrial level while the global sea level would be an estimated 573 mm (474–671 mm) above its 2021 mean by 2100. However, if countries adhere to the greenhouse gas emission regulations outlined in the 2021 United Nations Conference on Climate Change (COP26), the rise in global temperature would lessen to an average increase of 1.88 °C (1.43–2.33 °C) above its pre-industrial level, albeit still higher than the targeted 1.5 °C, while the sea level increase would reduce to 449 mm (389–509 mm) above its 2021 mean by 2100. [ABSTRACT FROM AUTHOR]

Coastal inundation is increasing globally. Changes in tidal water levels contribute to flood risk alongside rain and sea storm events. Unlike the latter, temporal variations in tides may be predicted and their patterns analyzed many years in advance. This paper explains two novel methods for characterizing monthly scale patterns in tidal water level variation: one simple qualitative method with restricted applicability; and another more complex quantitative method with global applicability to areas characterized by mixed, mainly semidiurnal and mixed, mainly diurnal tide regimes (~ 65% of global oceans). We reveal that in some areas tidal high and low waters are balanced in near symmetrical patterns, while elsewhere tides are skewed towards upper or lower tidal height envelopes. Areas characterized by tidal patterns skewed towards upper envelopes are at heightened risk of extreme event inundations during certain periods each year, event scale risks that will increase with climate changes. Those skewed towards lower tidal envelopes are prone to frequent flooding and are potentially at greater risk of chronic inundation with ongoing mean sea level rise. Our findings and the novel tidal pattern classification approaches offered contribute to understanding the time varying nature of tidal contributions to coastal inundation risks. [ABSTRACT FROM AUTHOR]

The present paper aims to quantify how human-made changes in the upstream exacerbate climate change impacts on water birds' habitat in the downstream. To reduce climate change effects and design adaptation policies, it is important to identify whether human activities understate or overstate the effects of climate change in a region on its inhabitants. This paper also shows how human activities may magnify climate change impacts both locally and regionally. Land-use/land-cover change as the important sign of human-made destruction in an ecosystem was detected in the upstream of the Helmand basin over 40 years. Owing to conflicts in Afghanistan, studies on this basin are rare. The water bird's habitat suitability maps during the study period were created using the maximum entropy model and the multi-criteria evaluation method. The post-classification method was applied to show the land-use/land-cover change over 40 years. These results were compared to the area of suitable habitat for water birds. The findings of these analyses indicated that the irrigated farming was expanded in the upstream despite climate change and water limitation, while the water birds' habitat in the downstream was declined. These results revealed that the unsustainable pattern of farming and blocking water behind dams in the upstream exacerbated the negative effects of climate change on water birds' habitat in the downstream. The significance of this study is to demonstrate the role of human in exacerbating climate change impacts both locally and regionally. [ABSTRACT FROM AUTHOR]

Influenced by climate change and human activities, especially the completion and operation of cascade reservoirs in the middle and lower reaches of Jinsha River since 2012, new changes have taken place in the water and sediment characteristics of the Three Gorges Reservoir (TGR) in recent years. In this paper, a one-dimensional unsteady water and sediment mathematical model of the main and tributary rivers of the TGR is established, and the main calculation parameters of the model are calibrated with the measured water and sediment data from January 1, 2008 to December 31, 2017. In view of the different combinations of inflow water and sediment that may occur in the TGR under the condition of new water and sediment, the long-term changes of sediment erosion and deposition and the balance of reservoir deposition in the TGR are studied using the model. The results show that: (1) Under the new conditions of water and sediment, the amount of sediment in the TGR accounts for only 14.8% and 35.8% of that in 1956–1990 and 2003–2012, respectively; (2) The variation process of water level, discharge and sediment concentration of each station along the route calculated by the model is basically consistent with the measured results, and the calculated values of total deposition amount and deposition distribution are also basically consistent with the measured results. The verification results of the model are in accordance with the measured values; (3) Under the water-sediment conditions during 1961–1970 and 1991–2000, the model predicted the estimates of 320 and 430 years for the TGR to reach a sedimentation balance, respectively. Under the new water-sediment conditions, it takes 560 years at most and 450 years at least to reach the sedimentation balance for the TGR, and the corresponding condition is the typical year with less water-less sediment and more water-more sediment, respectively. The research results of this paper can provide a new reference for the long-term safe operation and operation optimization of the TGR. [ABSTRACT FROM AUTHOR]

A large range of climate change impacts is expected during the twenty-first century in vulnerable regions such as West Africa, where local populations largely rely on livestock systems as their main food production and income source. As climate change threatens livestock systems in various ways, here we assess how regional livestock could be exposed to cumulated climate-related stressors in the future. Using the world's largest multi-model climate impacts simulations database ISIMIP, we find that a large part of West Africa will experience at least 5–6 cumulated multiple climate stressors before the 2030s, including amplified severe heat stress conditions and flood risks. Consequently, about 30% of the current total regional livestock could be exposed to these cumulated stressors, with sheep and goat as the most affected species. This paper brings new quantifications that may help policy makers to prioritize decisions that could prepare local populations to face multiple climate-related impacts. [ABSTRACT FROM AUTHOR]

Environmental problems continue to intensify. Yet, despite scientific consensus on threats such as climate change, broadscale public engagement with the issue is elusive. In this paper, we focus on childhood formative experiences and the extent to which they are correlated with environmental engagement. We consider two forms of environmental engagement: civic engagement, measured in hours per month devoted to an environmental protection cause, and private-sphere green behavior. Past studies about significant life experiences have shown that formative experiences, especially in childhood, correlate with environmentally sensitive attitudes and vocations in later life. However, we know less about the formative life events experienced by contemporary environmentally engaged persons. Looking at a nationally representative sample of American adults (n = 449), we find that childhood trauma predicts both civic engagement and green behavior. We also find that childhood experiences in nature and childhood travel experiences predict green behavior but not civic engagement. [ABSTRACT FROM AUTHOR]

Climate change will have an impact on not only flood magnitude but also on flood timing. This paper studies the shifting in flood timing at 6167 gauging stations from 1970 to 2010, globally. The shift in flood timing and its relationship with three influential factors (maximum 7-day precipitation, soil moisture excess, and snowmelt) are investigated. There is a clear global pattern in the mean flooding date: winter (Dec–Feb) across the western Coastal America, western Europe and the Mediterranean region, summer (Jun–Aug) in the north America, the Alps, Indian Peninsula, central Asia, Japan, and austral summer (Dec–Feb) in south Africa and north Australia area. The shift in flood timing has a trend from − 22 days per decade (earlier) to 28 days per decade (delayed). Earlier floods were found extensively in the north America, Europe and northeast Australia while delayed floods were prevailing in the Amazon, Cerrado, south Africa, India and Japan. Earlier flood timing in the north America and Europe was caused by earlier snowmelt while delayed extreme soil moisture excess and precipitation have jointly led to delayed floods around the monsoon zone, including south Africa, India and Japan. This study provides an insight on the shifting mechanism of flood timing, and supports decisions on the global flood mitigation and the impact from future climate change. [ABSTRACT FROM AUTHOR]

Hybrid 2D/one-line shoreline models, which typically apply a finite volume approach to simulate sediment transport and the one-line theory to update the shoreline morphology, are being increasingly applied over meso timescales (101 to 102 years) to inform coastal management. The one-line theory assumption of a constant closure depth prevents these models from considering the effects of sea-level rise in the shoreline morphology update. Sea-level rise, an endogenous driving factor of meso timescale coastal behaviour, influences the closure depth through its effects on the wave climate. This paper presents a new hybrid 2D/one-line approach that enables a time-varying closure depth in response to annual variations in wave climate as a solution for mirroring the effects of sea-level rise on the coastal profile and associated shoreline evolution. This new hybrid approach is applied to hindcast meso timescale shoreline evolution in a sandy coastal system and compared against the traditional hybrid 2D/one-line approach. Results show that the traditional hybrid approach gives the most accurate predictions whereas the new hybrid approach overpredicts shoreline erosion. However, this overprediction is attributed to net closure depth overestimation. This attribution gives confidence that the shoreline response to the time-varying closure depth specified is within expectations since closure depth overestimation increases offshore sediment transport in shoreline models. Therefore, it is likely that enabling a time-varying closure depth in hybrid 2D/one-line models may improve meso timescale shoreline predictions under sea-level rise if closure depths can be accurately prescribed over time. [ABSTRACT FROM AUTHOR]

Eucalyptus plantations around the world have been largely used by the paper industry. Optimizing the management of resources is a common practice in this highly competitive industry and new forest growth models may help to understand the impact of climate change on the decisions of the optimization processes. Current optimized management plans use empirical equations to predict future forest stands growth, and it is currently impractical to replace these empirical equations with physiological models due to data input requirements. In this paper, we present a different approach, by first carrying out a preliminary assessment with the process-based physiological model 3PG to evaluate the growth of Eucalyptus stands under climate change predictions. The information supplied by 3PG was then injected as a modifier in the projected yield that feeds the management plan optimizer allowing the interpretation of climate change impacts on the management plan. Modelling results show that although a general increase of rain with climate change is predicted, the distribution throughout the year will not favor the tree growth. On the contrary, rain will increase when it is less needed (summer) and decrease when it is most needed (winter), decreasing forest stand productivity between 3 and 5%, depending on the region and soil. Evaluation of the current optimized plan that kept constant the relation between wood price/cellulose ton shows a variation in different strategic management options and an overall increase of costs in owned areas between 2 and 4%, and a decrease of cumulated net present value, initially at 15% with later stabilization at 6–8%. This is a basic comparison to observe climate change effects; nevertheless, it provides insights into how the entire decision-making process may change due to a reduction in biomass production under future climate scenarios. This work demonstrates the use of physiological models to extract information that could be merged with existing and already implemented empirical models. The methodology may also be considered a preliminary alternative to the complete replacement of empirical models by physiological models. Our approach allows some insight into forest responses to different future climate conditions, something which empirical models are not designed for. [ABSTRACT FROM AUTHOR]

With global climate change and the rapid urbanization, urban flood and drought disasters are frequent and urban water supply systems are facing a sea of serious challenges. It is crucial to assess the resilience of urban water supply systems and develop corresponding disaster mitigation and improvement strategies. Urban water supply systems include many subsystems, but existing researches generally focus on a single subsystem. Therefore, this paper proposes a correlation analysis method and a factor analysis method for the resilience evaluation index system of urban water supply systems by combining each subsystem and applying grey system theory. The method can reflect the four dimensions of the water supply process (water source, water plant, supply and distribution network and users) and the five dimensions of the urban management system (society, natural environment, economy, physics and organization). Taking Qingdao as an example, a multi-level integrated evaluation model based on a cloud model is applied to simulate and analyze the resilience of Qingdao's water supply system. As a result, decision support is provided for planning and building resilience systems for urban water systems in the short and long term, based on four main factors. [ABSTRACT FROM AUTHOR]

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

This paper explores the abstraction of classical physics and applies several metrics that explore the evolution of social opinion. These metrics include an abstraction of Newtonian kinematics: mass, position, speed, acceleration, and Newtonian dynamics, an abstraction of force. Poll data is fit to a 2nd-order polynomial and a logistic function. These fits are used to understand the acceleration of opinion shift, and we explore recent social, cultural, and environmental trends, such as views on global climate change. We compare our results with the evolution of communication technologies and time spent on devices over the past 120 years. We show that the model connects the evolution in opinion with an abstraction of a Galilean concept: acceleration is independent of mass. Finally, we discuss the model of social polarization and the non-linear effect of media such as echo chambers. [ABSTRACT FROM AUTHOR]

The melting of glaciers and ice sheets is nowadays considered a symbol of climate change. Many complex mechanisms are involved in the melting of ice, and, among these processes, surface darkening due to organic material on bare ice has recently received attention from the scientific community. The presence of microbes on glaciers has been shown to decrease the albedo of ice and promote melting. Despite several studies from the Himalaya, Greenland, Andes, and Alaska, no quantitative studies have yet been conducted in the European Alps. In this paper, we made use of DNA sequencing, microscopy and field spectroscopy to describe the nature of glacier algae found at a glacier (Vadret da Morteratsch) of the European Alps and to evaluate their effect on the ice-albedo feedback. Among different algal species identified in the samples, we found a remarkable abundance of Ancylonema nordenskioeldii, a species that has never previously been quantitatively documented in the Alps and that dominates algal blooms on the Greenland Ice Sheet. Our results show that, at the end of the ablation season, the concentration of Ancylonema nordenskioeldii on the glacier surface is higher than that of other algal species (i.e. Mesotaenium berggrenii). Using field spectroscopy data, we identified a significant correlation between a reflectance ratio (750 nm/650 nm) and the algae concentration. This reflectance ratio could be useful for future mapping of glacier algae from remote sensing data exploiting band 6 (740 nm) and band 4 (665 nm) of the MultiSpectral Instrument (MSI) on board Sentinel-2 satellite. Here we show that the biological darkening of glaciers (i.e. the bioalbedo feedback) is also occurring in the European Alps, and thus it is a global process that must be taken into account when considering the positive feedback mechanisms related to glacier melting. [ABSTRACT FROM AUTHOR]

Over the past 50 years, temperatures on the Qinghai-Tibet Plateau (QTP) have risen roughly twice as fast as the global average, making it the most unpredictable region of environmental change due to global warming. In this paper, an Environmental Area Index model was developed using data from the Coupled Model Intercomparison Project to assess the ecological risk faced by QTP ecosystems under the influence of climate factors. The results show that ecological risk gradually decreases from northwest to the southeast, and there are different trends in ecological risk for each class in areas with different elevation gradients. As elevation increased, the proportion of potential risk areas gradually decreased, and the proportion of high- and higher-risk areas gradually increased. We predict that in the period 2021–2100, the overall ecological risk change trend on the QTP will not be obvious, but there will be a more obvious change on the vertical gradient. In general, under the existing global climate change scenario, the ecological risk faced by the QTP show a decreasing trend under the influence of climate factors, and the decrease in ecological risks is much higher at higher elevations than at lower elevations. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Public health is threatened by climate change and extreme temperature events worldwide. Differences in health predispositions, access to cooling infrastructure and occupation raises an issue of heat-related health inequality in those vulnerable and disadvantaged demographic groups. To address these issues, a comprehensive understanding of the effect of elevated body temperatures on human biological systems and overall health is urgently needed. In this paper we look at the inner workings of the human innate immunity under exposure to heat stress induced through exposure to environment and physical exertion. We couple two experimentally validated computational models: the innate immune system and thermal regulation of the human body. We first study the dynamics of critical indicators of innate immunity as a function of human core temperature. Next, we identify environmental and physical activity regimes that lead to core temperature levels that can potentially compromise the performance of the human innate immunity. Finally, to take into account the response of innate immunity to various intensities of physical activities, we utilise the dynamic core temperatures generated by a thermal regulation model. We compare the dynamics of all key players of the innate immunity for a variety of stresses like running a marathon, doing construction work, and leisure walking at speed of 4 km/h, all in the setting of a hot and humid tropical climate such as present in Singapore. We find that exposure to moderate heat stress leading to core temperatures within the mild febrile range (37, 38] ∘ C , nudges the innate immune system into activation and improves the efficiency of its response. Overheating corresponding to core temperatures beyond 38 ∘ C , however, has detrimental effects on the performance of the innate immune system, as it further induces inflammation, which causes a series of reactions that may lead to the non-resolution of the ongoing inflammation. Among the three physical activities considered in our simulated scenarios (marathon, construction work, and walking), marathon induces the highest level of inflammation that challenges the innate immune response with its resolution. Our study advances the current state of research towards understanding the implications of heat exposure for such an essential physiological system as the innate immunity. Although we find that among considered physical activities, a marathon of 2 h and 46 min induces the highest level of inflammation, it must be noted that construction work done on a daily basis under the hot and humid tropical climate, can produce a continuous level of inflammation triggering moieties stretched at a longer timeline beating the negative effects of running a marathon. Our study demonstrates that the performance of the innate immune system can be severely compromised by the exposure to heat stress and physical exertion. This poses significant risks to health especially to those with limited access to cooling infrastructures. This is due in part to having low income, or having to work on outdoor settings, which is the case for construction workers. These risks to public health should be addressed through individual and population-level measures via behavioural adaptation and provision of the cooling infrastructure in outdoor environments. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

This paper studies the oil spill, which occurred in the Norilsk and Taimyr region of Russia due to the collapse of the fuel tank at the power station on May 29, 2020. We monitored the snow, ice, water, vegetation and wetland of the region using data from the Multi-Spectral Instruments (MSI) of Sentinel-2 satellite. We analyzed the spectral band absorptions of Sentinel-2 data acquired before, during and after the incident, developed true and false-color composites (FCC), decorrelated spectral bands and used the indices, i.e. Snow Water Index (SWI), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI). The results of decorrelated spectral bands 3, 8, and 11 of Sentinel-2 well confirmed the results of SWI, NDWI, NDVI, and FCC images showing the intensive snow and ice melt between May 21 and 31, 2020. We used Sentinel-2 results, field photographs, analysis of the 1980–2020 daily air temperature and precipitation data, permafrost observations and modeling to explore the hypothesis that either the long-term dynamics of the frozen ground, changing climate and environmental factors, or abnormal weather conditions may have caused or contributed to the collapse of the oil tank. [ABSTRACT FROM AUTHOR]

Marine pollution impacts coastal nations around the world, and more so: (a) in confined maritime areas with significant marine traffic, (b) where exploitation of natural and mineral resources is taking place, or (c) in regions witnessing pressure from tourism, local population growth, and industry. In this work, Digital Elevation Models, hydrographic, and climatic data are used together with computer simulations to understand the control of climate change on marine pollution. The results show that different climate change signals can potentially alter the flow and concentration of pollution in the European Seas, when compared to the present day. Ultimately, this work identifies the main sources of marine pollution as: (1) rivers and streams near cities and industrialised areas, (2) coastal areas experiencing sudden demographic pressures, (3) offshore shipping lanes in which oil and other marine debris are released, and (4) areas of rugged seafloor where industrial fishing takes place. This paper finishes by describing new educational material prepared to teach school children around the world. It explains why how a new training curriculum and e-game developed by Sea4All can be crucial in future Environmental Education and Education for a Sustainable Development. [ABSTRACT FROM AUTHOR]

China's temperate glaciers have a relatively warm and humid climate and hydrothermal conditions at low latitudes. Temperate glaciers, however, have larger ablation, higher ice temperatures, relatively fast movement speeds, and a significant sliding process at the bottom. As a result, these glaciers are more significantly affected by climate change. On the basis of topographic maps, aerial photography, and Landsat OLI images, and combined with existing research results, this paper systematically analyzed the temporal and spatial dynamic characteristics of typical temperate glaciers. The results are as follows: (1) From the 1950s to the 1970s, compared with other types of glaciers, temperate glaciers showed strong retreat and ablation trends in terms of area, length, speed, and mass balance. (2) The reduction rates of glacier areas of Kangri Garpo, Dagu Snow Mountain, Yulong Snow Mountain (YSM), and Meili Snow Mountain (MSM) in China's temperate glacier areas all exceeded 38%, which was far above the national average of 18% from the 1950s to the 2010s. (3) The recent length retreat rates of Azha Glacier, Kangri Garpo, and Mingyong Glacier, MSM, Hailuogou Glacier (HG), Gongga Snow Mountain (GSM), and Baishui River Glacier No. 1 (BRGN1), YSM were above 22 m/a, which was faster than the retreat rates of other regions. (4) Consistent with glacier retreat, temperate glaciers also had a faster ice flow speed. The ice flow velocities of the BGN1, HG, Parlung River Glaciers No. 4 and 94, and Nyainqêntanglha were, respectively, 6.33–30.78 m/a, 41–205 m/a, 15.1–86.3 m/a, and 7.5–18.4 m/a, which was much faster than the velocity of other types of glaciers. (5) Mass loss of temperate glaciers was most dramatic during the observation period (1959–2015). The annual mass balance from eight typical temperate glaciers fluctuated between − 2.48 and 0.44 m w.e., and the annual average change rate of mass balance (− 0.037 m w.e./a) was much higher than that in China (− 0.015 m w.e./a, p < 0.0001) and globally (− 0.013 m w.e./a, p < 0.0001). [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Cetacean strandings (CS) have been reported in increasing numbers in coastal areas worldwide. Although the causes of these strandings are unknown, a number of anthropogenic and environmental factors have been suggested. This paper aims to characterize CS patterns and describe their fine-scale spatiotemporal dynamics. We analysed spatial and spatiotemporal CS patterns in Chile from January 1968 to January 2020. We identified a total of 389 CS events affecting eight cetacean families, 21 genera, and 35 species, which represent more than 85% of the reported species richness for the country. Most CS events (94.1%) were single (i.e., ≤two individuals). There were also 18 mass stranding (three to 24 individuals, 4.1%) and nine unusually large mass stranding events (>25 individuals, 2%). Purely spatial tests showed CS events appearing in random occurrence along the Chilean coast. Local tests for spatio-temporal clusters, however, identified a greater number of hotspots reported in the southernmost part of the country, namely, Chilean Patagonia. Specifically, significant spatio-temporal clusters were identified and defined as containing three or more individuals within a two-month period as a focal coastal event (<1 km radius). It is a cause of concern that CS events in Chile have been increasing consistently over the last decades, and although we were not able to identify their causes, we are able to highlight the importance of changes in climate conditions and of an increase in monitoring activities as primary drivers for such patterns, particularly important in Chilean Patagonia. [ABSTRACT FROM AUTHOR]

The heavily industrialised Kanpur region is the most polluted stretch of the Ganga river because of excessive pollutant discharge from the industries. Agricultural runoff along with climate change further adds to the pollution risk in this industrialised stretch of Ganga. In this paper, we analyse the potential impacts of climate change and land use change on the water quality in this stretch under hypothetical scenarios using the water quality model, QUAL2K. Water quality indicators of Dissolved Oxygen (DO), Biochemical Oxygen Demand, ammonia, nitrate, total nitrogen, organic-, inorganic- and total phosphorous and faecal coliform are assessed for eight climate change and six land use land cover scenarios. Eutrophic conditions are observed in this stretch of the river for all scenarios, implying severe impacts on aquatic life. DO is identified as the most sensitive indicator to the climate change scenarios considered, while nutrients and faecal coliform are more sensitive to the land use scenarios. Increase in agricultural land area leads to larger nutrient concentration while increase in built-up area causes an increase in faecal coliform concentration. Results from this hypothetical study could provide valuable guidance for improving the water quality of the Ganges in future climate change and land use change scenarios. [ABSTRACT FROM AUTHOR]

The time of emergence (TOE) of climate change is defined as the time when a new climate state emerges from a prior one. TOE assessment is particularly relevant in West Africa, a region highly threatened by climate change and urgently needing trustworthy climate predictions. In this paper, the TOE of precipitation change in West Africa is assessed for the first time, by analyzing 6 precipitation metrics (cumulated precipitation, number of wet and very wet days, onset and length of the rainy season) computed from the output of 29 state-of-the-art climate models. In West Sahel, climate conditions characterized by reduced occurrence of wet days are likely to emerge before 2036, leading to the possible emergence of a dryer climate in 2028–2052. In East Sahel, a wetter precipitation regime characterized by increased occurrence of very wet days is likely to emerge before 2054. Results do not provide a clear indication about a possible climate shift in the onset and length of the rainy season. Although uncertainty in climate model future projections still limits the robust determination of TOE locally, this study provides reliable time constraints to the expected climate shift in West Africa at the sub-regional scale, supporting adaptation measures to the future change in the precipitation regime. [ABSTRACT FROM AUTHOR]

This paper presents estimates of the effects of changing climate on crop yields for grain corn and soybeans in Ontario, Canada, for 1959–2013. We were able to use a database that is more comprehensive with respect to explanatory variables than some previous efforts had available. Our model includes climate variables, prices, land quality, groundwater level, CO2 concentration, and a time trend. Our results indicate that trends in temperature and precipitation during our study period have not yet resulted in appreciable threats to crop yields in the region. [ABSTRACT FROM AUTHOR]

The determination of the effects of cadmium and mercury on the growth, biomass productivity and phytoremediation potential of Miscanthus × giganteus (MxG) grown on contaminated soil was the main aim of this paper. The use of bioenergy plants as an innovative strategy in phytotechnology gives additional benefits, including mitigation and adaptation to climate change, and soil remediation without affecting soil fertility. An experiment was set up as a randomized complete block design with the treatments varied in concentrations of Cd (0, 10 and 100 mg kg−1 soil) and Hg (0, 2 and 20 mg kg−1 soil) added to the soil. Three vegetative years were studied. Yield values ranged from 6.3–15.5 tDM ha−1, cadmium concentration in plants varied from 45–6758 µg kg−1 and Hg varied from 8.7–108.9 µg kg−1. Values between treatments and years were significantly different. MxG can accumulate and remove very modest amount (up to 293.8 µg Cd and 4.7 µg Hg) per pot per year in aboveground biomass. Based on this data it can be concluded that MxG, as a valuable energy crop, is a potential candidate for the phytostabilization and biomass production on soils contaminated with Cd and Hg moderately. [ABSTRACT FROM AUTHOR]

The coincidence of flood flows in a mainstream and its tributaries may lead to catastrophic floods. In this paper, we investigated the flood coincidence risk under nonstationary conditions arising from climate changes. The coincidence probabilities considering flood occurrence dates and flood magnitudes were calculated using nonstationary multivariate models and compared with those from stationary models. In addition, the "most likely" design based on copula theory was used to provide the most likely flood coincidence scenarios. The Huai River and Hong River were selected as case studies. The results show that the highest probabilities of flood coincidence occur in mid-July. The marginal distributions for the flood magnitudes of the two rivers are nonstationary, and time-varying copulas provide a better fit than stationary copulas for the dependence structure of the flood magnitudes. Considering the annual coincidence probabilities for given flood magnitudes and the "most likely" design, the stationary model may underestimate the risk of flood coincidence in wet years or overestimate this risk in dry years. Therefore, it is necessary to use nonstationary models in climate change scenarios. [ABSTRACT FROM AUTHOR]

The Municipal Solid Waste (MSW) Sector is a major source of Methane (CH4) emission, a Greenhouse Gas (GHG) that contributes to Climate Change. However, governments of developing countries have not been able to address the challenges posed by this sector due to inadequate funding and technical requirement. The objective of this study was to determine how seasonal variation influences the CH4 gas emission. The First Order Decay (FOD) Tier 1 Model was used to estimate CH4 emission from four Solid Waste Disposal Sites (SWDS) in Lagos namely: Ewu-Elepe (Ewu), Abule-Egba (A/E), Soluos (Sol), and Olushosun (Olu) covering the dry and wet seasons, respectively for the inventory year 2020. A known weight of the wet waste deposited was characterized. The study revealed that the Degradable Organic Carbon (DOC) for the dry season was 12.897 GgC/kgWaste while that of the wet season was 12.547 GgC/kgWaste. But, the methane gas generated during the wet season was 0.331 Gg higher than that of the dry season which was 0.134 Gg for the study period. This is an appreciable quantity of methane that can contribute to the global Climate Change impact if not addressed. Therefore, these waste types should be segregated from other recyclables and processed into compost or energy resource. [ABSTRACT FROM AUTHOR]

Sustainable and effective means to control flying insect vectors are critically needed, especially with widespread insecticide resistance and global climate change. Understanding and controlling vectors requires accurate information about their movement and activity, which is often lacking. The Photonic Fence (PF) is an optical system that uses machine vision, infrared light, and lasers to identify, track, and interdict vectors in flight. The PF examines an insect's outline, flight speed, and other flight parameters and if these match those of a targeted vector species, then a low-power, retina-safe laser kills it. We report on proof-of-concept tests of a large, field-sized PF (30 mL × 3 mH) conducted with Aedes aegypti, a mosquito that transmits dangerous arboviruses, and Diaphorina citri, a psyllid which transmits the fatal huanglongbing disease of citrus. In tests with the laser engaged, < 1% and 3% of A. aegypti and D. citri, respectfully, were recovered versus a 38% and 19% recovery when the lacer was silenced. The PF tracked, but did not intercept the orchid bee, Euglossa dilemma. The system effectively intercepted flying vectors, but not bees, at a distance of 30 m, heralding the use of photonic energy, rather than chemicals, to control flying vectors. [ABSTRACT FROM AUTHOR]

According to the guidelines of the Intergovernmental Panel on Climate Change, carbon emissions are attributed to the producers of goods and services. This approach has been challenged by recent literature, advocating an attribution criterion based on consumers, i.e. accounting for the carbon embedded into the goods imported by each country. Quantifying the effectiveness of such a consumption-based accounting requires understanding the complex structure of the graph induced by the flows of emissions between world countries. To this aim, we have considered a balanced panel of a hundred of countries and constructed the corresponding Carbon Trade Network for each of the past twenty years. Our analysis highlights the tendency of each country to behave either as a 'net producer'—or 'net exporter'—of emissions or as a 'net consumer'—or 'net importer'—of emissions; besides, it reveals the presence of an unexpected, positive feedback: despite individual exchanges having become less carbon-intensive, the increasing trade activity has ultimately risen the amount of emissions directed from 'net exporters' towards 'net importers'. Adopting a consumption-aware accounting would re-distribute responsibility between these two groups, possibly reducing disparities. [ABSTRACT FROM AUTHOR]

The agricultural and rural development policy seeks to facilitate the transition towards environmentally sustainable and climate-neutral agricultural practices, with a focus on human capital, knowledge, and innovation. Gender equality can play a significant role in promoting environmentally sustainable practices in the agricultural sector, particularly through the adoption and implementation of agri-environment-climate schemes (AECS) in the context of farm, agricultural, and rural development. We examine the presence of gender bias in the adoption intensity of AECS by utilising farm-level data from Slovenia. We find that women on Slovenian farms engage in the adoption of AECS and receive subsidies, despite the presence of a gender gap in various agricultural factor endowment variables that typically favour men. The results of this study provide evidence in favour of promoting greater involvement and empowerment of women in the fields of green technology applications and green entrepreneurship, particularly with AECS practices. [ABSTRACT FROM AUTHOR]

In order to tackle the global increase in overweight and obesity prevalence, several nutrient profiling systems have been developed; among others, Food Compass Score (FCS) has been designed to encompass multiple domains of food healthfulness. However, environmental sustainability of healthy diets is another crucial dimension which should not be overlooked in the context of human health. The aim of the present study is to assess the association between healthiness and environmental sustainability of food items, using the FCS and Agribalyse databases, respectively. A total of 806 matching food items were identified, grouped in 12 food categories; within each category, differences in median Z-scores between FCS and Single Environmental Footprint (EF) Score were assessed. While Fruits, Legumes and Nuts, Mixed foods, Meat Poultry and Eggs (MPE), Savory and Sweets, and Vegetables showed statistically significant differences (all p < 0.001), Beverages (p = 0.361), Dairy (p = 0.092), Fats and Oils (p = 0.594), Grains (p = 0.436), Sauce and Condiments (p = 0.093), and Seafood (p = 0.241) had similar Food Compass and Single EF Z-scores distributions. These findings underscore a relevant lack of difference between healthfulness and environmental impact of some prominent food categories, such as Grains and Seafood. Therefore, we suggest matching nutrient profiling systems with adequate environmental sustainability indices. [ABSTRACT FROM AUTHOR]

Water is a scarce, strategic resource and the most important input for economic development, especially in agricultural countries such as Brazil. Cocoa production is directly related to water availability, and, as climate changes, selecting drought-tolerant genotypes is vital to keep cacao crops sustainable. Here, we evaluated cacao genotypes under irrigated and water-stressed conditions and selected drought-tolerant ones based on nutritional and physiological traits. Thirty-nine genotypes were monitored for three years for agronomic traits and higher fruit yield. After this evaluation, the 18 most promising genotypes were evaluated in a randomized block design, under a 2 (with and without irrigation) × 18 (genotypes) factorial arrangement, with three replicates and five plants per plot. We evaluated seven physiological and 11 nutritional traits, selecting genotypes based on the Genotype-by-Trait Biplot approach. Significant effects (p < 0.05) were observed for the nutritional traits N, P, Mg, S, Zn, Cu, Mn and for the physiological traits CO2 assimilation rate (A), stomatal conductance (gs), transpiration (E), intercellular and atmospheric CO2 concentrations (Ci/Ca), intrinsic water use efficiency (A/gs), instantaneous water use efficiency (A/E), and instantaneous carboxylation efficiency (A/Ci), as determined by analysis of variance. The genotype × irrigation treatment interaction was significant (p < 0.05) for the traits A, gs, and E. Genotypes CP 41, CP 43, and CCN 51 exhibited superior performance for both nutritional and physiological traits (A, gs, and E). In the irrigated environment, CP 41 showed superiority in traits such as P, A/E, A/gs, Mn, S, and Zn. Conversely, under non-irrigated conditions, CP 43 exhibited better performance in nutritional properties, specifically Mn, Mg, and Zn. Notably, in both irrigated and non-irrigated environments, CCN 51 excelled in key physiological traits, including A/Ci, A/E, and A/gs. This robust performance across diverse conditions suggests that these three genotypes possess physiological mechanisms to endure water-stressed conditions. Our research can generate valuable insights into these genotypes informing suitable choices for cocoa cultivation, especially in the context of global climate change. [ABSTRACT FROM AUTHOR]

The upper tropospheric water vapor is a key component of Earth's climate. Understanding variations in upper tropospheric water vapor and identifying its influencing factors is crucial for enhancing our comprehension of global climate change. While many studies have shown the impact of El Niño-Southern Oscillation (ENSO) and global warming on water vapor, how they affect the upper tropospheric water vapor remains unclear. Long-term, high-precision ERA5 specific humidity data from the European Centre for Medium-Range Weather Forecasts (ECMWF) provided the data foundation for this study. On this basis, we successfully obtained the patterns of global warming (Independent Component 1, IC1) and ENSO (Independent Component 2, IC2) by employing the strategy of independent component analysis (ICA) combined with non-parametric optimal dimension selection to investigate the upper tropospheric water vapor variations and responses to ENSO and global warming. The results indicate that global warming and ENSO are the primary factors contributing to water vapor variations in the upper troposphere, achieving the significant correlations of 0.87 and 0.61 with water vapor anomalies respectively. Together, they account for 86% of the global interannual variations in water vapor. Consistent with previous studies, our findings also find positive anomalies in upper tropospheric water vapor during El Niño years and negative anomalies during La Niña years. Moreover, the influence extent of ENSO on upper tropospheric water vapor varies with the changing seasons. [ABSTRACT FROM AUTHOR]

The bamboo-coral Isidella elongata is a key habitat-forming species in the deep Mediterranean Sea. This alcyonacean is listed as an indicator of Vulnerable Marine Ecosystems (VMEs) and as Critically Endangered due to bottom trawling impacts. In this work, a modeling approach was used to predict and map the habitat suitability of I. elongata in the Mediterranean Sea under current environmental conditions. Occurrence data were modeled as a function of environmental parameters. Using climate change scenarios and fishing effort data, the risk of climate change and fisheries impacts on habitat suitability were estimated, and climate refugia were identified. A drastic loss of habitat is predicted, and climate change scenarios suggest a loss of 60% of suitable habitats by 2100. In the central Mediterranean, climate refugia overlapped with active fishing grounds. This study represents the first attempt to identify hot spots for the protection of soft bottom Vulnerable Marine Ecosystems for the entire Mediterranean Sea, and highlights areas most at risk from trawling. This work is relevant to the objectives of the EU Marine Strategy Framework and Maritime Spatial Planning Directives, the Biodiversity Strategy for 2030 regarding priority areas for conservation. [ABSTRACT FROM AUTHOR]

Maerl beds are listed as a priority marine feature in Scotland. They are noted for creating suitable benthic habitat for diverse communities of fauna and flora and in supporting a wide array of ecosystem services. Within the context of climate change, they are also recognised as a potential blue carbon habitat through sequestration of carbon in living biomass and underlying sediment. There are, however, significant data gaps on the potential of maerl carbon sequestration which impede inclusion in blue carbon policy frameworks. Key data gaps include sediment thickness, from which carbon content is extrapolated. There are additional logistical and financial barriers associated with quantification methods that aim to address these data gaps. This study investigates the use of sub-bottom profiling (SBP) to lessen financial and logistical constraints of maerl bed sediment thickness estimation and regional blue carbon quantification. SBP data were cross validated with cores, other SBP data on blue carbon sediments, and analysed with expert input. Combining SBP data with estimates of habitat health (as % cover) from drop-down video (DDV) data, and regional abiotic data, this study also elucidates links between abiotic and biotic factors in determining maerl habitat health and maerl sediment thickness through pathway analysis in structural equation modelling (SEM). SBP data were proved to be sufficiently robust for identification of maerl sediments when corroborated with core data. SBP and DDV data of maerl bed habitats in Orkney exhibited some positive correlations of sediment thickness with maerl % cover. The average maerl bed sediment thickness was 1.08 m across all ranges of habitat health. SEM analysis revealed maerl bed habitat health was strongly determined by abiotic factors. Maerl habitat health had a separate positive effect on maerl bed sediment thickness. [ABSTRACT FROM AUTHOR]

Using data from Twitter (now X), this study deploys artificial intelligence (AI) and network analysis to map and profile climate change denialism across the United States. We estimate that 14.8% of Americans do not believe in climate change. This denialism is highest in the central and southern U.S. However, it also persists in clusters within states (e.g., California) where belief in climate change is high. Political affiliation has the strongest correlation, followed by level of education, COVID-19 vaccination rates, carbon intensity of the regional economy, and income. The analysis reveals how a coordinated social media network uses periodic events, such as cold weather and climate conferences, to sow disbelief about climate change and science, in general. Donald Trump was the strongest influencer in this network, followed by conservative media outlets and right-wing activists. As a form of knowledge vulnerability, climate denialism renders communities unprepared to take steps to increase resilience. As with other forms of misinformation, social media companies (e.g., X, Facebook, YouTube, TikTok) should flag accounts that spread falsehoods about climate change and collaborate on targeted educational campaigns. [ABSTRACT FROM AUTHOR]

The intensification of heatwaves dues to climate change is a significant concern, with substantial impacts on ecosystems and human health, particularly in developing countries. This study utilizes NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) and projected population data accounting for China's population policies to project changes in various grades of heatwaves (light, moderate, and severe) and the population exposure to heatwaves (PEH) in Xinjiang under three shared socioeconomic pathways (SSP1–2.6, SSP2-4.5, and SSP5-8.5). The results show that the number of days and intensity of heatwaves in Xinjiang are projected to increase. Heatwaves occurring in Xinjiang will predominantly be severe heatwaves (SHW) in the long-term under the SSP5-8.5 scenario, and the number of SHW days projected to increase by 62 ± 18.4 days compared to the reference period. Changes in heatwaves are anticipated to influence PEH, estimating population exposure to light, moderate, and severe heatwaves (LPEH, MPEH, and SPEH) at 534.6 ± 64 million, 496.2 ± 43.5 million, and 1602.4 ± 562.5 million person-days, respectively, in the long-term under the SSP5-8.5 scenario. The spatial distribution of PEH is projected to be consistent with that of the reference period, with high values persisting in Urumqi, Kashgar and Hotan. Changes in PEH are primarily driven by climate effects, followed by interactive effects, while population effects contribute the least. Therefore, mitigating climate change is crucial to reduce the PEH in Xinjiang. [ABSTRACT FROM AUTHOR]