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This paper is a review of research undertaken, and subsequent policy change enacted, in the years 2018 to 2022 regarding the integration of cooking loads and needs into modern energy planning. Building on an earlier paper which described how the dominant global approaches to tackling the enduring problem of biomass-fuelled cooking was failing, and how a new UK Aid programme (Oct 2018) would be seeking to intentionally change international energy policy towards cooking and enable a significant transition in energy use, in this paper we review whether this strategy is being adopted by researchers, governments, and the private sector across the world and whether it is likely to make a significant contribution to the fulfilment of Sustainable Development Goal 7. In particular, the call is for integrated planning of modern energy inclusive of cooking loads—the potential 'Mutual Support' that both can lend to each other. The review considers the international commitments made by donors and governments to this end, the research that positions the use of modern energy as a cost-effective proposition, the urbanisation and societal changes reinforcing such planning, and positions the review in the light of climate change and the need to reach net zero carbon by 2050. [ABSTRACT FROM AUTHOR]

Pakistan is among the countries that are highly vulnerable to climate change. The country has experienced severe floods and droughts during recent decades. The agricultural sector in Pakistan is adversely affected by climate change. This systematic review paper set out to analyze the existing literature on adaptation measures at the farm level toward climate change in Pakistan. Adopting a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, a total of 62 articles were identified from the Web of Science and Scopus databases. The review paper indicates that the main adaptation strategies adopted by farmers are as follows: changing cropping practices, changing farm management techniques, advanced land use management practices, and nonagriculture livelihood options. Further, this review shows the factors influencing the farmer's adaptation measures to climate change. Influencing factors were examined and classified into three groups: demographic, socioeconomic, and resources and institutional. Barriers hindering farmers' adaptive capacity were identified as lack of access to information and knowledge, lack of access to extension services, lack of access to credit facility, and lack of farm resources. [ABSTRACT FROM AUTHOR]

Simple Summary: This article examines the relationship between twentieth- and twenty-first-century paleobiology. After summarizing the disciplinary problem of paleontology in the mid-twentieth century, I focus on five representative research topics in contemporary paleontology. In doing so, I outline twenty-first-century paleontology as a science that seeks more data, more technology, and more integration. At the end of the paper, I highlight a possible new paleobiological revolution: it would give paleontologists strong political representation to deal with issues such as expanded evolutionary synthesis, conservation of the Earth's environment, and global climate change. In this paper, I will briefly discuss the elements of novelty and continuity between twentieth-century paleobiology and twenty-first-century paleontology. First, I will outline the heated debate over the disciplinary status of paleontology in the mid-twentieth century. Second, I will analyze the main theoretical issue behind this debate by considering two prominent case studies within the broader paleobiology agenda. Third, I will turn to twenty-first century paleontology and address five representative research topics. In doing so, I will characterize twenty-first century paleontology as a science that strives for more data, more technology, and more integration. Finally, I will outline what twenty-first-century paleontology might inherit from twentieth-century paleobiology: the pursuit of and plea for a new synthesis that could lead to a second paleobiological revolution. Following in the footsteps of the paleobiological revolution of the 1960s and 1970s, the paleobiological revolution of the twenty-first century would enable paleontologists to gain strong political representation and argue with a decisive voice at the "high table" on issues such as the expanded evolutionary synthesis, the conservation of Earth's environment, and global climate change. [ABSTRACT FROM AUTHOR]

The European transition to green economy is based on long-term strategies. The Europe 2020 Strategy was launched in 2010 in order to promote smart, sustainable, and inclusive growth in the region. Later, the ambitions regarding this strategy were followed by the Green Deal and Sustainable Development Goals. Now, the effort of countries towards the green economy is even more relevant than ever because of the context of today's global energy crisis and economic uncertainty due to many challenges such as the COVID-19 pandemic or Russia invasion of Ukraine. This paper seeks to assess the countries' achievements in seeking climate change and energy targets of the Europe 2020 Strategy by applying the innovative multi-criteria decision-making (MCDM) technique. The kernel-based comprehensive assessment (KerCA) method was applied for the calculations of the progress achieved and countries' rankings. It allows to evaluate countries' achievements and compare them using the mathematical models. The analysis of the national target implementation in the countries allows to determine the compliance of countries with their commitments and liability towards other countries and the European Union (EU). An analysis of the implementation of the strategy can serve as a guide to further develop climate change and energy policy in the region. Furthermore, the added value of the article is systematic overview of scientific studies proposing different methodologies for the analysis of target implementation at the whole region level. The novelty of this paper also relies on the approach, which considers not only the level of achievement of the target, but also assesses the excess. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper analyzed the different relationships between earlywood and latewood as well as total tree-ring growth and the climate factors and reconstructed 106 years of May–June mean temperature (TMJ) in the Tongbai Mountains based on the earlywood width chronology of Pinus taiwanensis Hayata. It also analyzed the linkages to the Indian and Pacific Oceans. This paper found that earlywood width chronology has better response to the climate factors than latewood width and total tree-ring width. This study also found that the main limiting factors that restrained radial growth of Pinus taiwanensis Hayata in the Tongbai Mountains were May–June mean temperature and mean maximum temperature. The reconstructed TMJ series have a better reliability and are significantly negatively correlated with sea surface temperature (SST) over the tropical Western Pacific Ocean and Indian Ocean and are significantly positively correlated with SST over the subtropical Pacific Ocean. Finally, the periodic fluctuations of TMJ in the Tongbai Mountains might be related to the quasi-biennial interannual oscillation of SST over the Indo-Pacific equatorial region (QBO). The results of this study are significant for further understanding and exploring forest growth and climate change in the climatic transition zone. The Tongbai Mountains are an ecologically sensitive region to climate change, where there lies a climatic transitional zone from a subtropical to a warm–temperate monsoon climate. The northern boundary of Pinus taiwanensis Hayata is here; thus, climate information is well recorded in its tree rings. Based on developed earlywood width (EWW), latewood width (LWW) and total ring width (RW) chronologies (time period: 1887–2014 year) of Pinus taiwanensis Hayata in the Tongbai Mountains in central China, this paper analyzed characteristics of these chronologies and correlations between these chronologies and climate factors. The correlation results showed that earlywood width chronology contains more climate information than latewood width chronology and total ring width chronology, and mean temperature and mean maximum temperature in May–June were the main limiting factors for radial growth of Pinus taiwanensis Hayata. The highest significant value in all correlation analyses is −0.669 (p < 0.05) between earlywood width chronology and May–June mean temperature (TMJ) in the pre-mutation period (1958–2005) based on mutating in 2006. Thus, this paper reconstructed May–June mean temperature using earlywood width chronology from 1901 to 2005 (reliable period of earlywood width chronology is 1901–2014). The reconstructed May–June mean temperature experienced eight warmer periods and eight colder periods and also showed 2–3a cycle change over the past 105 years. The spatial correlation showed that the reconstructed series was representative of the May–June mean temperature variation in central and eastern China and significant positive/negative correlation with the sea surface temperature (SST) of the subtropical Pacific Ocean and the tropical Western Pacific Ocean and Indian Ocean from the previous October to the current June. This also indicated that May–June mean temperature periodic fluctuations might be related to the quasi-biennial oscillation (QBO) in the tropical Western Pacific Ocean and Indian Ocean. The results of this study have extended and supplemented the meteorological records of the Tongbai Mountains and have a guiding significance for forest tending and management in this area. [ABSTRACT FROM AUTHOR]

Simple Summary: Spring in Europe has been trending earlier for almost half a century. Long-distance migrant birds, such as the Willow Warbler and Pied Flycatcher, which breed in Europe, have arrived earlier too. It is broadly accepted that warming springs in temperate regions explain the earlier arrival of migrants. However, migration started weeks earlier and thousands of kilometres away. There must be additional cues elsewhere triggering migration. Meteorologists have developed measures of atmospheric circulation which are related to climate variability in wide regions. One of them is the Southern Oscillation Index, which reflects El Niño/La Niña that cause droughts and floods in the southern hemisphere. Other atmospheric circulation patterns, measured by the North Atlantic Oscillation Index and Indian Ocean Dipole, help predict total rainfall for a whole season in various parts of Africa and Europe. Good rains are associated with plant growth and with insect abundance. Insects provide food for most of these migrants. Therefore, this paper asks the question: "Is the timing of arrival of long-distance migrants in spring related to the climates they experience in the places where they are over the year prior to arrival in Europe?" This paper says the answer is "Yes". Earlier springs in temperate regions since the 1980s, attributed to climate change, are thought to influence the earlier arrival of long-distance migrant passerines. However, this migration was initiated weeks earlier in Africa, where the Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation drive climatic variability, and may additionally influence the migrants. Multiple regressions investigated whether 15 indices of climate in Africa and Europe explained the variability in timing of arrival for seven trans-Saharan migrants. Our response variable was Annual Anomaly (AA), derived from standardized mistnetting from 1982–2021 at Bukowo, Polish Baltic Sea. For each species, the best models explained a considerable part of the annual variation in the timing of spring's arrival by two to seven climate variables. For five species, the models included variables related to temperature or precipitation in the Sahel. Similarly, the models included variables related to the North Atlantic Oscillation (for four species), Indian Ocean Dipole (three), and Southern Oscillation (three). All included the Scandinavian Pattern in the previous summer. Our conclusion is that climate variables operating on long-distance migrants in the areas where they are present in the preceding year drive the phenological variation of spring migration. These results have implications for our understanding of carry-over effects. [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia is experiencing a surge in electricity demand, with power generation increasing 4 times in 25 years from 1990 to 2014. Despite the abundant primary renewable energy sources, the country has overlooked them in the past in national energy policies. However, in recent years, renewable energy has become a part of the Kingdom of Saudi Arabia's energy conservation policy due to climate changes, technological progress, economies of scale, and increased competitiveness in supply chains. The Saudi government has created the King Abdullah City for Atomic and Renewable Energy (KACARE) to develop national strategies for effectively utilizing renewable and nuclear energy. This paper reviews the current state of the art of the renewable energy technologies available on the market and evaluates the installation of renewable energy plants near Saudi Arabia's East Coast for a new town, focusing on technical rather than economic aspects. The paper provides a wide review of the possible technical solutions to exploit the producibility of different renewable sources, considering the challenging climate conditions typical of desert areas. The analysis of a real case study shows a high availability of wind and solar irradiance that allow a net energy production of 354 and 129 GWh, respectively. In addition, the comparison between a typical ground-mounted photovoltaic (PV) system and an emerging floating PV reveals that for the same installed power, occupied area, and environmental conditions, the latter has a 4% greater performance ratio due to the cooling effect of water. [ABSTRACT FROM AUTHOR]

The decarbonization of energy matrices is crucial to limit global warming below 2 °C this century. An alternative capable of enabling zero or even negative CO2 emissions is bioenergy with carbon capture and storage (BECCS). In this sense, the Brazilian sugar–energy sector draws attention, as it would be possible to combine the production of fuel and electricity from renewable biomass. This paper is the final part of a study that aimed to research carbon capture and storage (CCS) in energy systems based on sugarcane. The case studied is CCS in thermal power plants considering two different technologies: the steam cycle based on the condensing–extraction steam turbine (CEST) and the combined cycle integrated to biomass gasification (BIG-CC). The results for the thermal power plant indicate that the CO2 capture costs may be lower than those in cogeneration systems, which were previously studied. The main reasons are the potential scale effects and the minimization of energy penalties associated with integrating the CCS system into the mills. In the best cases, capture costs can be reduced to EUR 54–65 per ton of CO2 for the CEST technology and EUR 57–68 per ton of CO2 for the BIG-CC technology. [ABSTRACT FROM AUTHOR]

Floods occur throughout the world and are becoming increasingly frequent and dangerous. This is due to different factors, among which climate change and land use stand out. In Mexico, they occur every year in different areas. Tabasco is a periodically flooded region, causing losses and negative consequences for the rural, urban, livestock, agricultural, and service industries. Consequently, it is necessary to create strategies to intervene effectively in the affected areas. Different strategies and techniques have been developed to mitigate the damage caused by this phenomenon. Satellite programs provide a large amount of data on the Earth's surface and geospatial information processing tools useful for environmental and forest monitoring, climate change impacts, risk analysis, and natural disasters. This paper presents a strategy for the classification of flooded areas using satellite images obtained from synthetic aperture radar, as well as the U-Net neural network and ArcGIS platform. The study area is located in Los Rios, a region of Tabasco, Mexico. The results show that U-Net performs well despite the limited number of training samples. As the training data and epochs increase, its precision increases. [ABSTRACT FROM AUTHOR]

Polar-orbiting satellite observations are of fundamental importance to explore the main scientific challenges in the Arctic Ocean, as they provide information on bio-geo-physical variables with a denser spatial and temporal coverage than in-situ instruments in such a harsh and inaccessible environment. However, they are limited by the lack of coverage near the North Pole (Polar gap), the polar night, and frequent cloud cover or haze over the ocean and sea ice, which prevent the use of optical satellite instruments, as well as by the limited availability of external validation data. The satellite sensors' coverage and repeat cycles may also have limitations in properly identifying and resolving the dominant spatial and temporal scales of atmospheric, ocean, cryosphere and land variability and their interactive processes and feedback mechanisms. In this paper, we provide a state of the art of contribution of satellite observations to the understanding of the polar environment and climate scientific challenges tackled within the Arktalas Hoavva project funded by the European Space Agency. We identify the current limitations to the wider use of polar orbiting remote sensing data, as well as the observational gaps of the existing satellite missions. A comprehensive overview of all satellite missions and applications is given provided with a primary focus on the European satellites. Finally, we assess the expected capability of the approved future satellite missions to answer today's scientific challenges in the Arctic Ocean. [ABSTRACT FROM AUTHOR]

Simple Summary: During the last glaciation, the nature of the northern hemisphere of the Earth underwent significant changes. Nonetheless, it underwent no less serious changes after the melting of the glacier, when, under the conditions of climate mitigation, the gradual formation of modern landscapes began in the spaces freed from ice. This study is devoted to the reconstruction of the post-glacial environment in one of the regions of Eastern Europe, in the south-eastern part of the Baltics. The uniquely preserved deposits of one of the post-glacial basins discovered here made it possible to reconstruct in detail the changes in climate, vegetation, and aquatic organisms in the time interval of 14–13.4 thousand years ago. The study revealed that during this period there were short-lasting climate fluctuations (warmings and coolings), which caused repeated changes in all components of the local nature. The results of the study contribute to understanding the complex processes of planetary climate formation, as well as the impact of climate on nature both at local and global levels, which is necessary not only for understanding the past, but also for predicting the future of all living organisms on the planet. This paper presents the results of a study on the Kulikovo section (south-eastern Baltic Sea coast), a sediment sequence exposing deposits of a post-glacial basin that existed along the edge of the glacier in the Late Pleistocene. The research was targeted at the reconstruction of the dynamics of the local environmental systems in response to climatic oscillations of the Lateglacial (the Older Dryas—first half of the Allerød). The evolution of the local biotic components on the territories of the Baltic region after the ice retreat is still poorly understood. Data from geochronological, lithological, diatom, algo-zoological and palynological analyses provide a reconstruction of local aquatic and terrestrial biocenoses and their response to short-term warmings and coolings that took place 14,000–13,400 cal yr BP. This study has demonstrated that, during the Older Dryas and first part of the Allerød (GI-1d and GI-1c), the aquatic and terrestrial environment of the Kulikovo basin underwent several changes, resulting in eight stages of the basin evolution, most probably related to the short-term climatic fluctuations that could have had a duration of several decades. The data obtained in this study have revealed the fairly dynamic and complex evolution of the pioneer landscapes, as indicated by the changes in the hydrological regime of the area and by the traced successions of plant communities from the pioneer swampy vegetation to park and real forests towards the middle of the Allerød. [ABSTRACT FROM AUTHOR]

The increase in the concentration of geological gas emissions in the atmosphere and particularly the increase of methane is considered by the majority of the scientific community as the main cause of global climate change. The main reasons that place methane at the center of interest, lie in its high global warming potential (GWP) and its lifetime in the atmosphere. Anthropogenic processes, like engineering geology ones, highly affect the daily profile of gasses in the atmosphere. Should direct measures be taken to reduce emissions of methane, immediate global warming mitigation could be achieved. Due to its significance, methane has been monitored by many space missions over the years and as of 2017 by the Sentinel-5P mission. Considering the above, we conclude that monitoring and predicting future methane concentration based on past data is of vital importance for the course of climate change over the next decades. To that end, we introduce a method exploiting state-of-the-art recurrent neural networks (RNNs), which have been proven particularly effective in regression problems, such as time-series forecasting. Aligned with the green artificial intelligence (AI) initiative, the paper at hand investigates the ability of different RNN architectures to predict future methane concentration in the most active regions of Texas, Pennsylvania and West Virginia, by using Sentinel-5P methane data and focusing on computational and complexity efficiency. We conduct several empirical studies and utilize the obtained results to conclude the most effective architecture for the specific use case, establishing a competitive prediction performance that reaches up to a 0.7578 mean squared error on the evaluation set. Yet, taking into consideration the overall efficiency of the investigated models, we conclude that the exploitation of RNN architectures with less number of layers and a restricted number of units, i.e., one recurrent layer with 8 neurons, is able to better compensate for competitive prediction performance, meanwhile sustaining lower computational complexity and execution time. Finally, we compare RNN models against deep neural networks along with the well-established support vector regression, clearly highlighting the supremacy of the recurrent ones, as well as discuss future extensions of the introduced work. [ABSTRACT FROM AUTHOR]

Agriculture is the second-highest, after energy use, source of greenhouse gas emissions, which are released from soils and animal digestion processes and as a result of energy consumption at various stages of agricultural production. However, changes in the management of agricultural systems may mitigate the negative impact of this sector on the atmosphere and climate. This paper presents a literature review on energy consumption in agriculture and the potential of agricultural crop production to assist in mitigation of global warming by increasing absorption of CO2 from the atmosphere. The issue was considered in the context of managing the cultivation of main, catch and cover crops. The potential of carbon sequestration in the above- and below-ground biomass of selected crops was analyzed. It was stated that, depending on the species, main crops can sequester up to 113 CO2 ha−1 yr−1 in whole biomass, while catch or cover crops can sequester up to 14.80 CO2 ha−1 yr−1 and 0.17 CO2 ha−1 yr−1 in the above- and below-ground biomass, respectively. The benefits of the spread of catch or cover crops, such as improvement of soil quality (leading to an increase in primary crop yield by even as much as 65%) and a phytosanitary effect, as well as the barriers that limit the use of catch crops, including the problems with matching crop species to climate and soil conditions and the risk of reducing farmers' income, were considered. The results of the review show that catch crops can assimilate an additional amount of 4 to 6 tonnes CO2 ha−1 yr−1, and thus, spreading of catch crops is an effective way to reduce the climate impact of agriculture. [ABSTRACT FROM AUTHOR]

This paper presents an overall performance assessment of hybrid-electric medium-range transport aircraft, with the aim to evaluate the potential of such a propulsion technology towards the reduction in the environmental impact of aviation transport, in terms of both local air quality degradation in airport areas and climate change. The proposed approach presents distinct analyses of the environmental impact of transport aircraft, distinguishing climate-changing effects from local pollution effects so that the integration of hybrid-electric propulsion is carried out to face the two issues specifically. The proposed analysis, although of conceptual nature, presents a clear scenario in which, given the technological limitations of batteries, the use of hybrid-electric propulsion on medium-haul aircraft can only be useful to reduce local pollution. In contrast, other solutions are needed to mitigate the climate-changing impact. [ABSTRACT FROM AUTHOR]

This paper examines the long-term changes in temperature and precipitation in the karst region of Imotski, Croatia, which is of particular interest due to its abundance of karst phenomena. This study analyses temperatures and precipitation on monthly and annual scales at two climatological stations in the region, Imotski and Ričice. Linear regression, the Theil–Sen estimator (β), and the Mann–Kendall test were used to determine the trends and statistical significance. The homogeneity of the data was checked using the Standard Normal Homogeneity Test (SNHT), and the F-test and t-test were used to test the significance of the mean shift between the two subseries. Additionally, the coefficient of variability, standardized rainfall anomaly, and precipitation concentration index were employed to analyze the precipitation variability. The study found a statistically significant (p < 0.05) upward trend in the mean (β = 0.0437) and maximum (β = 0.0590) annual air temperature at the Imotski station and the mean (β = 0.0387) annual temperature at the Ričice station. The SNHT test showed a statistically significant (p < 0.05) shift in the mean annual temperatures after 2007 and maximum annual temperatures after 1998 at the Imotski station. Similarly, a statistically significant (p < 0.05) shift in the mean annual temperatures after 2011 and the maximum annual temperatures after 1998 was found at the Ričice station. A seasonal distribution of precipitation is observed at both the Ričice and Imotski stations, with a downward trend (β = −2.7693) at Ričice and an upward trend (β = 6.0575) at Imotski; however, neither trend is statistically significant (p > 0.05). An increase in the intensity of dry periods and the occurrence of extreme events was also noted. The climatological analysis, conducted for the first time in this area, is a crucial step toward understanding local climate patterns and making informed decisions toward sustainable development and adaptation strategies. [ABSTRACT FROM AUTHOR]

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area's precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen's Slope in the baseline and future periods with all RCPs. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

Under rapid urbanization-induced global warming and resource depletion, growing interest in zero-energy building (ZEB) and zero-emission building (ZEB) technologies have emerged globally to improve energy performance in homes and shape sustainable cities. Although several countries have released ZEB-enhanced strategies and set national standards and policies to promote ZEBs, construction projects are still limited to demonstration projects. This paper reviews global ZEB activities and state-of-the-art technologies for energy-efficient residential building technologies [based on an evaluation of 40 residential buildings]. Over 40 residential buildings on different continents were reviewed, and their technical details and performance were evaluated. Our results show that 62.5% of the buildings achieved the +ZEB standard, 25% of the buildings were net-zero energy buildings, and only 12.5% of the buildings were near-zero energy buildings. Solar PV is the most widely used renewable energy source in the studied cases, while in warmer climates, advanced cooling technologies and heat pumps are the preferred technologies. A building envelope and thermal ventilation with heat recovery are essential in cold climates. Our systematic analysis reveals that the thermal performance of the building envelope and solar energy are the most effective mechanisms for achieving energy efficiency and shaping sustainable cities. [ABSTRACT FROM AUTHOR]

Blackbrush (Coleogyne ramosissima Torr.) is the dominant shrub on three million hectares across the transition zone between the western North American warm and cold deserts. This paper presents a study of blackbrush population structure at the stand level at sixteen sites across the species range. New stand-level information is then integrated with what is already known about blackbrush population ecology to explore the stand-level consequences of several unusual features of blackbrush life history, including its masting reproductive strategy, its interactions with heteromyid rodents that are both seed predators and dispersers, and its ability to form 'seedling banks' of growth-suppressed individuals, often within the crowns of adult conspecifics. It complements earlier work showing that blackbrush stands are organized at both the inter-clump and intra-clump levels. Each clump represents an establishment nexus where younger individual genets replace older genets over an extended time period. Inter-clump structure is thus determined by the rate of establishment of new clumps rather than new individuals. This has resulted in contrasting stand structures in response to rodent community composition, disturbance regimes, and climatic variability at the leading and trailing edges of current blackbrush distribution in the eastern Mojave Desert and Colorado Plateau regions. Because blackbrush likely disperses too slowly to track anthropogenic climate change, assisted migration with wild-collected seeds may be necessary to promote its continued survival and dominance. [ABSTRACT FROM AUTHOR]

This paper presents a review of concepts related to wildfire risk assessment, including the determination of fire ignition and propagation (fire danger), the extent to which fire may spatially overlap with valued assets (exposure), and the potential losses and resilience to those losses (vulnerability). This is followed by a brief discussion of how these concepts can be integrated and connected to mitigation and adaptation efforts. We then review operational fire risk systems in place in various parts of the world. Finally, we propose an integrated fire risk system being developed under the FirEUrisk European project, as an example of how the different risk components (including danger, exposure and vulnerability) can be generated and combined into synthetic risk indices to provide a more comprehensive wildfire risk assessment, but also to consider where and on what variables reduction efforts should be stressed and to envisage policies to be better adapted to future fire regimes. Climate and socio-economic changes entail that wildfires are becoming even more a critical environmental hazard; extreme fires are observed in many areas of the world that regularly experience fire, yet fire activity is also increasing in areas where wildfires were previously rare. To mitigate the negative impacts of fire, those responsible for managing risk must leverage the information available through the risk assessment process, along with an improved understanding on how the various components of risk can be targeted to improve and optimize the many strategies for mitigation and adaptation to an increasing fire risk. [ABSTRACT FROM AUTHOR]

Rapid Arctic warming is expected to result in widespread permafrost degradation. However, observations show that site-specific conditions (vegetation and soils) may offset the reaction of permafrost to climate change. This paper summarizes 43 years of interannual seasonal thaw observations from tundra landscapes surrounding the Marre-Sale on the west coast of the Yamal Peninsula, northwest Siberia. This robust dataset includes landscape-specific climate, active layer thickness, soil moisture, and vegetation observations at multiple scales. Long-term trends from these hierarchically scaled observations indicate that drained landscapes exhibit the most pronounced responses to changing climatic conditions, while moist and wet tundra landscapes exhibit decreasing active layer thickness, and river floodplain landscapes do not show changes in the active layer. The slow increase in seasonal thaw depth despite significant warming observed over the last four decades on the Yamal Peninsula can be explained by thickening moss covers and ground surface subsidence as the transient layer (ice-rich upper permafrost soil horizon) thaws and compacts. The uneven proliferation of specific vegetation communities, primarily mosses, is significantly contributing to spatial variability observed in active layer dynamics. Based on these findings, we recommend that regional permafrost assessments employ a mean landscape-scale active layer thickness that weights the proportions of different landscape types. [ABSTRACT FROM AUTHOR]

The growth history of the Tibetan Plateau provides a valuable natural laboratory to understand tectonic processes of the India–Asia collision and their impact on and interactions with Asian and global climate change. However, both Tibetan Plateau growth and Asian paleoenvironments are generally poorly documented in pre-Pliocene times and reflect limited temporal coverage for different parts of the plateau. In this paper, the 238 m thick Cenozoic sediments in the Hongzhuang section of the Xunhua Basin were tested and analyzed via paleomagnetic and environmental magnetic methods. The formation age was determined, and the evolution history of the regional climate environment was analyzed. The magnetostratigraphy study shows that the sediments record a continuous sequence of geomagnetic polarity changes from C5ACn to C10r, which spans an interval of approximately 30~14.3 Ma from the early Oligocene to the middle Miocene. The magnetic susceptibility of the Hongzhuang section is basically similar to the deep-sea oxygen isotope fluctuation, indicating that the monsoon climate change indicated by the magnetic susceptibility is affected by global temperature. It is worth noting that at ~27 Ma and ~15 Ma, there is a negative correlation between magnetic susceptibility and deep-sea oxygen isotope, and magnetic susceptibility lags behind the increase in deep-sea oxygen isotope. Combined with the change in the sedimentary rate curve, we explain the asynchrony between the magnetic susceptibility and the deep-sea oxygen isotope around ~27 Ma and ~15 Ma. As the uplift of the plateau leads to the enhancement of the East Asian summer monsoon, the soil formation in the region is strengthened, resulting in an increase in magnetic susceptibility. At the same time, the rapid uplift of the plateau caused the erosion of the surrounding mountains to strengthen, and the input of near-source materials may promote the increase in magnetic susceptibility. [ABSTRACT FROM AUTHOR]

In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

The primary aspiration of this paper is to learn about the effects of economic growth, energy consumption, agriculture and irrigation water consumption and agriculture productivity on environmental pollution in five countries of Central Asia. The data cover the period from 1992 to 2020 by applying panel data models, namely the Panel FMOLS, Panel DOLS and Panel ARDL-PMG approaches. The results indicate that there is a positive long-term impact of economic growth, water productivity, energy consumption and electricity production on CO2 emissions while agriculture value added and trade openness have a negative and statistically significant influence on CO2 emissions in Central Asia. Country specific short-run coefficients from Panel ARDL reveal that energy consumption is the main driver for rise in the level of CO2 emissions in the countries under the study. Indeed, country level analysis generates unique nexus correlation among agriculture, energy and environmental degradation in each country of Central Asia. [ABSTRACT FROM AUTHOR]

In the last 20 years, research on the observed and projected impacts of climate change on cultural heritage has led to significant developments regarding damage quantification and risk assessment, which unfortunately are not yet exhaustively transferred to practical applications and to the sector of policy and decision making. One of the major reasons for this still lacking alignment remains with the inadequate handover of quantitative data, which is a prerequisite for the development of measures and strategies for the mitigation of the impacts and risk reduction. In this paper, we focus on the methods and approaches put in place for the production of projections providing quantitative assessments of climate change-induced impacts in the near and far future (up to the 21st century) on outdoor built heritage mainly constituted by stone and stone-like materials. Our critical study found that different approaches have been applied for quantifying slow cumulative damage due to the ongoing variations of climate and air pollution parameters and to risk assessment caused by hydrometeorological extreme events induced by variations of temperature and precipitation. There is clear evidence that efforts are still needed for directing research to provide concrete solutions and tools addressed to meet the requirements of stakeholders and to solve the existing challenges in the field: selected effective models and tools are illustrated. The discussion is structured in order to highlight the driving role of research in supporting the definition of priorities for heritage managers and the development of strategies by decision and policy makers for the prevention and safeguarding of cultural heritage at risk. [ABSTRACT FROM AUTHOR]

Simple Summary: Anthropogenic climate change is one of the greatest threats to biodiversity. Extreme temperature events associated with longer-term climate change are increasing in frequency, duration and intensity. The effects of climatic extremes on ectotherms, such as insects, have been well-studied in recent years. However, the effects of extreme temperatures on other arthropod groups, such as spiders, has received much less attention. Spiders are important organisms as predators in natural and agricultural ecosystems. In this paper, we describe spider responses to extreme temperatures and highlight the most important knowledge gaps that urgently need to be filled to better understand how vulnerable spiders are to climate change and climatic extremes. Unlike insects, traits such as body size and niche breadth may differ markedly in male and female spiders. Therefore, we argue that research needs to address the effects of heat exposure on the physiology, behavior and ecology of male and female spiders across multiple taxa. Observed declines in some terrestrial insects have been widely reported in recent years, with climate change, along with other anthropogenic threats, being implicated. Longer-term data on trends in spider abundance, where available, may also shed possible light on the role of climate change. Climatic extremes, such as heat waves, are increasing in frequency, intensity and duration under anthropogenic climate change. These extreme events pose a great threat to many organisms, and especially ectotherms, which are susceptible to high temperatures. In nature, many ectotherms, such as insects, may seek cooler microclimates and 'ride out´ extreme temperatures, especially when these are transient and unpredictable. However, some ectotherms, such as web-building spiders, may be more prone to heat-related mortality than more motile organisms. Adult females in many spider families are sedentary and build webs in micro-habitats where they spend their entire lives. Under extreme heat, they may be limited in their ability to move vertically or horizontally to find cooler microhabitats. Males, on the other hand, are often nomadic, have broader spatial distributions, and thus might be better able to escape exposure to heat. However, life-history traits in spiders such as the relative body size of males and females and spatial ecology also vary across different taxonomic groups based on their phylogeny. This may make different species or families more or less susceptible to heat waves and exposure to very high temperatures. Selection to extreme temperatures may drive adaptive responses in female physiology, morphology or web site selection in species that build small or exposed webs. Male spiders may be better able to avoid heat-related stress than females by seeking refuge under objects such as bark or rocks with cooler microclimates. Here, we discuss these aspects in detail and propose research focusing on male and female spider behavior and reproduction across different taxa exposed to temperature extremes. [ABSTRACT FROM AUTHOR]

Natural-language processing is well positioned to help stakeholders study the dynamics of ambiguous Climate Change-related (CC) information. Recently, deep neural networks have achieved good results on a variety of NLP tasks depending on high-quality training data and complex and exquisite frameworks. This raises two dilemmas: (1) the networks are highly reliant on powerful hardware devices and processing is time-consuming, which is not only inconducive to execution on edge devices but also leads to resource consumption. (2) Obtaining large-scale effective annotated data is difficult and laborious, especially when it comes to a special domain such as CC. In this paper, we propose a CC-domain-adapted BERT distillation and reinforcement ensemble (DARE) model for tackling the problems above. Specifically, we propose a novel data-augmentation strategy which is a Generator-Reinforced Selector collaboration network for countering the dilemma of CC-related data scarcity. Extensive experimental results demonstrate that our proposed method outperforms baselines with a maximum of 26.83% on SoTA and 50.65× inference time speed-up. Furthermore, as a remedy for the lack of CC-related analysis in the NLP community, we also provide some interpretable conclusions for this global concern. [ABSTRACT FROM AUTHOR]

High concentration levels of air pollutants may cause damage to plants, animals, and the health of some groups of human beings. Therefore, it is important to investigate different topics related to the high air pollution levels and to find reliable answers to the questions about the possible damages, which might take place when these levels exceed some limits. A few of the numerous questions, the answers of which are highly desirable, are listed below: (a) When are the air pollution levels dangerous? (b) What is the reason for the increased air pollution levels? (c) How can the air pollution levels be decreased? (d) Will the future climate changes result in higher and more dangerous air pollution levels? It is necessary to study carefully many issues connected with the distribution of air pollutants in a given region and with the reasons for the increases of the concentrations to high levels, which might be damaging. In order to do this, it is necessary to develop a Digital Twin of all relevant physical processes in the atmosphere and to use after that this tool in different applications. Such a tool, its name is DIGITAL AIR, has been created. Digital Twins are becoming more and more popular). Many complex problems, arising taking place in very complicated surroundings, can be handled and resolved successfully by applying Digital Twins. The preparation of such a digital tool as well as its practical implementation in the treatment of a special problem, the increase of some potentially dangerous ozone levels, will be discussed and tested in this paper. The Unified Danish Eulerian Model (UNI-DEM) is a very important part of DIGITAL AIR. This mathematical model, UNI-DEM, can be applied in many different studies related to damaging effects caused by high air pollution levels. We shall use it in this paper to get a reliable answer to a very special but extremely important question: will the future climatic changes lead to an increase in the ozone pollution levels in Bulgaria and Europe, which can potentially become dangerous for human health? [ABSTRACT FROM AUTHOR]

While the UN recognizes the right of individuals "to take risks and make mistakes", there are reasons to question whether this right can be universal. In the context of a changing climate, it is imperative that individuals have access to a safe and sustainable environment; yet we must ask if this covenant is broken if people choose to place themselves in harm's way. In its first part, this paper explores outcomes of climate change denial, manifested as continued migration to dangerous locations, and skepticism for adaptive strategies. The second half of the paper explores how localities can create a false narrative concerning risks, and asks whether communities also have a right to make mistakes? [ABSTRACT FROM AUTHOR]

The spatio-temporal variogram is an important factor in spatio-temporal prediction through kriging, especially in fields such as environmental sustainability or climate change, where spatio-temporal data analysis is based on this concept. However, the traditional spatio-temporal variogram estimator, which is commonly employed for these purposes, is extremely sensitive to outliers. We approach this problem in two ways in the paper. First, new robust spatio-temporal variogram estimators are introduced, which are defined as M-estimators of an original data transformation. Second, we compare the classical estimate against a robust one, identifying spatio-temporal outliers in this way. To accomplish this, we use a multivariate scale-contaminated normal model to produce reliable approximations for the sample distribution of these new estimators. In addition, we define and study a new class of M-estimators in this paper, including real-world applications, in order to determine whether there are any significant differences in the spatio-temporal variogram between two temporal lags and, if so, whether we can reduce the number of lags considered in the spatio-temporal analysis. [ABSTRACT FROM AUTHOR]

Leaders on the forefront of the rapidly escalating climate crisis continually seek effective strategies to help communities stay engaged without burning out or spiraling into despair. This paper examines the concept of adaptive change for its potential to reframe disruption and intentionally harness its potential for building resilience in both practical and psychological ways. In particular, social science suggests that secure communal bonds lay the foundation for the adaptive ability to build resilience through and from disruption. Swiss history offers an intriguing example of this phenomenon: held up as a model for its social, political, and ecological resilience, Swiss democracy evolved as part of the restructuring of society after a series of disruptive historical pandemics. This paper uses the Swiss example and the current COVID-19 (Coronavirus Disease) pandemic in order to explore the potential of transcendent and adaptive sociological and theological frameworks for the development of robust concepts of resilience in the face of climate destabilization. It further argues that a wide theological interpretation of Eucharistic abundance offers a lens through which to claim the liberative resurrection of disruptions, even, or perhaps especially, in the extreme case of human or planetary annihilation. [ABSTRACT FROM AUTHOR]

Among the several methods investigated over the past few years for the thermal mitigation of buildings in urban areas, green roof systems seem to be one of the most suitable solutions for several reasons, and researchers encourage the further study and implementation of these roofing techniques because of the potential benefits that they offer. So far, intensive, extensive and semi-intensive green roofs are considered to be a better option in terms of both energy efficiency and green area increase. However, there are some aspects that cause green roofs not to be suitable to every application, preventing their use from spreading, such as high maintenance and costs required by these sophisticated systems. Few studies aimed at overcoming the limits of green roofs have hinted at the possibility of implementing hydroponic cultures in green roof systems. This soil-less technology might overcome some issues, such as identifying the suitable substrate to support the growth of the vegetation. This paper aims to provide a systematic review of hydroponic green roof systems (HGRS), based on the rigorous analysis of the evidence gathered from the thorough evaluation of the available literature on the subject, in order to assess their potential use as an alternative to traditional green roofs. The review was carried out by analyzing studies that have assessed the performance of hydroponic green roofs as well as those of comparable systems, such as pond roofs and green roofs. The results of these studies show that HGRS provide similar performances to the above-mentioned systems in terms of the passive conditioning effect, lowering the cooling/heating load of buildings, with slight changes depending on the climatic conditions. However, they offer other significant properties such as higher efficiency in water runoff management, alongside others discussed in this paper, while also requiring minor maintenance. Significant results have been provided; however, gaps in the knowledge have also emerged, and further studies need to be conducted to provide exhaustive information. [ABSTRACT FROM AUTHOR]

The paper discusses existing trends and prospects for decarbonization in the Commonwealth of Independent States (the CIS), an international organization that regroups Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, and Uzbekistan. The CIS occupies a significant share of Eurasia, representing a large share of global energy consumption and production with a corresponding carbon footprint. These countries and their decarbonization prospects are rarely discussed in the English-language scientific literature. This paper fills in this gap by offering a comprehensive analysis based on statistical data, policy documents, and scenario-based future projections. The results underline that revisiting Nationally Determined Contributions, increasing energy efficiency, and decoupling GDP growth from greenhouse gas emissions are essential to the implementation of the Paris Agreement. The future energy mix should include larger shares of renewable energy, hydrogen, fossil fuels (highly efficient with carbon capture), and nuclear energy to achieve energy security and decarbonize the economy of the region in the long term. [ABSTRACT FROM AUTHOR]

The current geopolitical landscape of the European Union has made it clear that the energy sector must be a top priority in EU policy, especially in light of the sudden escalation of Russian–Ukrainian conflicts. Energy efficiency has been used as the first tool of EU policy to tackle energy and climate crises, given the issues surrounding energy vulnerability and the need to limit gas emissions that contribute to climate change. The white certificate mechanism in Italy has played a pivotal role in encouraging measures to achieve the country's energy-saving goals. Given the high energy requirements of Wastewater Treatment Plants (WWTPs), especially for aeration in the biological section, this paper examines the replacement of the air distribution system for a large WWTP as a viable intervention. In order to provide economic perspective for the plant, both the discounted Payback Period (dPBP) and the Net Present Value (NPV) were calculated for the investment. When viewed through an economic lens, the dPBP metric exhibits values that span from less than 1 year to nearly 4.5 years. Additionally, the investment's cost-effectiveness was emphasized by the NPV, which, depending on the factors considered, can exceed 17.5 million euros. Finally, given the centrality of the theme of climate change, the avoided greenhouse gas emissions generated by the efficiency intervention were calculated, according to the GHG Protocol, resulting in a quantity of avoided emissions equivalent to over 57,770 tonnes of CO2e. These results highlight important achievements in terms of both the cost-effectiveness of the plant and the reduction of greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

The increasingly severe effects of climate change have resulted in a shift in countries' approach to climate policy. From an initial focus on mitigation efforts, adaptation to climate change is now given equal importance. Adaptation policies in individual countries provide for different sets of instruments owing to different natural conditions and climate change impacts and their resulting problems as well as different approaches related to the sociopolitical characteristics of the country. In the paper, we identify and classify adaptation policy instruments and then look for the differences and similarities in the adaptation instrument mixes included in the national adaptation strategic documents of selected European countries. We focused on Western European (WE) and Central and Eastern European (CEE) countries, as the latter are underrepresented in studies on adaptation policies. Based on text-mining methods, i.e., categorisation of policy instruments using a set of criteria and clustering, we looked for similarities and differences between the adaptation instrument mixes in the chosen European countries. We found similarities between the two CEE countries studied—Poland and Lithuania. These countries are also different from WE countries in this regard. The results indicate that CEE countries have a sectoral rather than systemic approach to adaptation policy, and instruments from the management sphere are less prominent. [ABSTRACT FROM AUTHOR]

Climate change has increased agricultural drought risk in arid/semi-arid regions globally. One of the common adaptation strategies is shifting to more drought-tolerant crops or switching back to grassland permanently. In many drought-prone areas, groundwater dynamics play a critical role in agricultural production and drought management. This study aims to help understand how groundwater level decline affects the propensity of cropland switching back to grassland. Taking Union County of New Mexico (US) as a case study, field-scale groundwater level projections and high-resolution remote sensing data on crop choices are integrated to explore the impact of groundwater level decline in a regression analysis framework. The results show that cropland has been slowly but permanently switching back to grassland as the groundwater level in the Ogallala Aquifer continues to decline in the area. Specifically, for a one-standard-deviation decline in groundwater level (36.95 feet or 11.26 m), the average likelihood of switching back to grassland increases by 1.85% (the 95% confidence interval is [0.07%, 3.58%]). The findings account for the fact that farmers usually explore other options (such as more drought-tolerant crops, land idling, and rotation) before switching back to grassland permanently. The paper concludes by exploring relevant policy implications for land (soil) and water conservation in the long run. [ABSTRACT FROM AUTHOR]

Drought poses a serious threat to agricultural production and food security in the context of global climate change. Few studies have explored the response mechanism and lag time of agricultural drought to meteorological drought from the perspective of cultivated land types. This paper analyzes the spatiotemporal evolution patterns and hysteresis relationship of meteorological and agricultural droughts in the middle and lower reaches of the Yangtze River in China. Here, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products and surface temperature products were selected to calculate the Temperature Vegetation Dryness Index (TVDI) from 2010 to 2015. Furthermore, we obtained the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) for the same period. Based on these indices, we analyzed the correlation and the hysteresis relationship between agricultural and meteorological drought in rainfed and irrigated arable land. The results showed that, (1) compared with SPEI, the high spatial resolution PDSI data were deemed more suitable for the subsequent accurate and scientific analysis of the relationship between meteorological and agricultural droughts. (2) When meteorological drought occurs, irrigated arable land is the first to experience agricultural drought, and then alleviates when the drought is most severe in rainfed arable land, indicating that irrigated arable land is more sensitive to drought events when exposed to the same degree of drought risk. However, rainfed arable land is actually more susceptible to agricultural drought due to the intervention of irrigation measures. (3) According to the cross-wavelet transform analysis, agricultural droughts significantly lag behind meteorological droughts by about 33 days during the development process of drought events. (4) The spatial distribution of the correlation coefficient between the PDSI and TVDI shows that the area with negative correlations of rainfed croplands and the area with positive correlations of irrigated croplands account for 77.55% and 68.04% of cropland areas, respectively. This study clarifies and distinguishes the details of the meteorological-to-agricultural drought relationship in rainfed and irrigated arable land, noting that an accurate lag time can provide useful guidance for drought monitoring management and irrigation project planning in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Heterosigma akashiwo is a golden-brown unicellular phytoflagellate with a high potential to create harmful algal blooms (HABs) and kill fish in many coastal regions worldwide, resulting in significant economic losses. Climate change and global warming have been introduced as triggers that impact the frequency and severity of H. akashiwo and other bloom-forming species in the past decades. In this review paper, the author tried to briefly discuss the morphology and taxonomy of H. akashiwo and show how environmental parameters can influence the physiology and toxicity of this species. Although the toxin production and mechanisms are still a conundrum, the proposed fish-killing mechanisms will be reviewed in the next step. [ABSTRACT FROM AUTHOR]

The building industry is responsible for a significant degree of energy consumption in the world, causing negative climate changes and energy supply uncertainties due to low energy efficiency as well as the high resource demand of construction. Consequently, energy design optimization has become an important research field. Passive design strategies are one of the most definitive factors concerning energy-related building development. The given architectural problem calls for a method that can create all potentially feasible building geometries, thus guaranteeing the optimal solution which is addressed in the current paper. To reach this requirement, the necessity of a modular space arrangement system and architectural selection rules were determined, focusing on the relationship between the rules and the generation of geometries with mathematical rigor. Next, the architecture-based congruency analysis performed, further reduced the number of simulation cases. With the simulations, it is illustrated how the building shape versions affect the heating energy demands: the performance of the configurations themselves. Results clearly illustrate the importance of the synthesis step of the architectural design. [ABSTRACT FROM AUTHOR]

One of the most crucial solutions to the issues of climate change and global warming is clean energy. However, creating intelligent, resilient, and sustainable systems is a worldwide problem, particularly for grid-connected Renewable Energy Systems (RES). Therefore, it is important to investigate how prospective changes in electricity pricing, renewable energy sources, and load demand could affect system performance during the projects. This paper presents a techno-economic analysis of a grid-connected wind energy system located in the Al-Jouf region in Saudi Arabia. To this end, the potential of renewable energy sources was assessed using Hybrid Optimization of Multiple Electric Renewables (HOMER) software, that also carried out the technical and economic study utilizing multi-year parameters. The novelty of this study is that it is the first-ever investigation of a grid-connected wind farm system in Saudi Arabia that considers the impact of multi-year parameters such as the grid price, system fixed operation, maintenance cost, and the AC electric load. The results showed that the proposed system in the chosen area recorded a very low Levelized Cost of Energy (LCOE) of around 0.06 USD/kWh compared to other systems. Also, running a multi-year model showed that the considered parameters have an impact on the system's performance, and this reflects the importance of considering these parameters in any such system that will increase the study's accuracy. [ABSTRACT FROM AUTHOR]

In Africa, switching to renewable energy sources with low carbon emissions is becoming more popular. In the Economic Community of West African states (ECOWAS), the low-carbon energy transition must overcome significant obstacles, including those posed by policies put in place and their implementation. In order to replace the current fossil fuel-driven economy with low-carbon development that also advances the regional aims and Sustainable Development Goals (SDGs), this paper analyzes the current policy landscape in the region. A total of 75 policies from four categories (energy access, energy efficiency, renewable energy, climate change) were chosen for the policy review. Multicriteria decision analysis and a thorough review of the literature have shed light on how well the policies of the ECOWAS countries could promote low-carbon development and what the main challenges to overcome are. The last step was the comparison of the progress of the two key policies in the region: the National Energy Efficiency Action Plan (NEEAP) and National Renewable Energy Action Plan (NREAP). The results illustrate the amount of work still needing to be done in the region, with only 26 of the 75 policies receiving a score above 50. However, the prospect of a better energy strategy that adequately considers the difficulties of the energy transition is possible, given the progress made by the region's nations since the creation of national action plans for energy efficiency (EE) and renewable energy (RE). Our analysis has also shown that countries like Senegal have obtained quite promising results, as evidenced by the best scores of 76.88 and 73.25, respectively, obtained by its NREAP and NEEAP policies. [ABSTRACT FROM AUTHOR]

As one of the best indicators of the periglacial environment, ice-wedge polygons (IWPs) are important for arctic landscapes, hydrology, engineering, and ecosystems. Thus, a better understanding of the spatiotemporal dynamics and evolution of IWPs is key to evaluating the hydrothermal state and carbon budgets of the arctic permafrost environment. In this paper, the dynamics of ground surface deformation (GSD) in IWP zones (2018–2019) and their influencing factors over the last 20 years in Saskylakh, northwestern Yakutia, Russia were investigated using the Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE). The results show an annual ground surface deformation rate (AGSDR) in Saskylakh at −49.73 to 45.97 mm/a during the period from 1 June 2018 to 3 May 2019. All the selected GSD regions indicate that the relationship between GSD and land surface temperature (LST) is positive (upheaving) for regions with larger AGSDR, and negative (subsidence) for regions with lower AGSDR. The most drastic deformation was observed at the Aeroport regions with GSDs rates of −37.06 mm/a at tower and 35.45 mm/a at runway. The GSDs are negatively correlated with the LST of most low-centered polygons (LCPs) and high-centered polygons (HCPs). Specifically, the higher the vegetation cover, the higher the LST and the thicker the active layer. An evident permafrost degradation has been observed in Saskylakh as reflected in higher ground temperatures, lusher vegetation, greater active layer thickness, and fluctuant numbers and areal extents of thermokarst lakes and ponds. [ABSTRACT FROM AUTHOR]

Citrus are the most produced fruits worldwide. It is expected that these crops will be severely affected by climate change. However, the literature lacks works that attempt to understand the influence of climate change on citrus. For this reason, a bibliometric analysis was conducted on climate change and citrus to investigate its development and current trends in this research domain. The main trends, keywords, and their relations were identified. The period from 1992 to 2022 was analyzed, resulting in 178 documents in the Scopus database. The most significant publishers' countries were also the largest citrus producers in the world besides being G7 members. Three main research areas were identified: modeling, socio-political issues, and plant physiology. A tendency to change interest from modeling and risk analysis to physiology and stress studies was observed. Additionally, some of the most cited papers observed the positive impacts of climate change on certain citrus crops. Despite the multidisciplinary publications, two main gaps were identified: (i) the lack of investigations with combined stresses (abiotic and biotic) instead of isolated studies, and (ii) the lack of studies of predictive models for citrus production in different conditions and climate change scenarios. Finally, there was a tendency toward studying water use and irrigation alternatives due to water scarcity and management solutions to improve the production system's resilience, considering the potential impacts of climate change. [ABSTRACT FROM AUTHOR]

Simple Summary: Climate change-induced trophic mismatch poses a challenge to nestling survival. This paper presents a physiological adaptation of nestlings to poor food conditions. Some indicators related to the immunity (IFN-γ, TNF-α, and IL-1β) and growth (IGF-1, body mass growth rate) of wild Asian short-toed lark nestlings were studied. The relationships between these indicators and food abundance are analyzed. The results indicate that the plasticity of immunity and growth in nestlings may buffer the challenge of trophic mismatch in birds. Passerine nestlings frequently suffer from sub-optimal food conditions due to climate change-induced trophic mismatch between the nestlings and their optimal food resources. The ability of nestlings to buffer this challenge is less well understood. We hypothesized that poor food conditions might induce a higher immune response and lower growth rate of nestlings, and such physiological plasticity is conducive to nestling survival. To test this, we examined how food (grasshopper nymphs) abundance affects the expression of interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), interleukin-1 β (IL-1β) genes, plasma IGF-1 levels, body mass, and fledging rates in wild Asian short-toed lark (Alaudala cheleensis) nestlings. Linear mixed models revealed that nymph biomass significantly influenced the expression of IFN-γ, TNF-α, and IL-1β genes, and the level of plasma IGF-1. The expressions of IFN-γ, TNF-α, and IL-1β genes were negatively correlated with nymph biomass and plasma IGF-1 level. Plasma IGF-1 level, nestling body mass growth rate, was positively correlated with nymph biomass. Despite a positive correlation between the nestling fledge rate and nymph biomass, more than 60% of nestlings fledged when nymph biomass was at the lowest level. These results suggest that immunity and growth plasticity of nestlings may be an adaptation for birds to buffer the negative effects of trophic mismatch. [ABSTRACT FROM AUTHOR]

Simple Summary: Micronesia is an ethnogeographic region within the continent of Oceania that represents an underserved area of the world. Cancer is the second leading cause of death among the people of Micronesia and indigenous Pacific Islanders share an unequal burden of the disease. Many factors come into play when discussing the adverse health outcomes of Micronesian people. Our paper intends to review these factors that have led to the ongoing health crisis among indigenous Pacific Islanders. It is well appreciated that the social determinants of health are intimately related with health outcomes. However, there is a paucity of literature that explores these themes comprehensively for the indigenous people within Micronesia. Certain Micronesia-specific factors, such as transitions from traditional diets, the consumption of betel nut, and exposure to radiation from the nuclear bomb testing in the Marshall Islands, have predisposed certain Micronesian populations to an increased risk of developing a variety of malignancies. Furthermore, severe weather events and rising sea levels attributed to climate change threaten to compromise cancer care resources and displace entire Micronesian populations. The consequences of these risks are expected to increase the strain on the already challenged, disjointed, and burdened healthcare infrastructure in Micronesia, likely leading to more expenses in off-island referrals. A general shortage of Pacific Islander physicians within the workforce reduces the number of patients that can be seen, as well as the quality of culturally competent care that is delivered. In this narrative review, we comprehensively underscore the health disparities and cancer inequities faced by the underserved communities within Micronesia. [ABSTRACT FROM AUTHOR]

Any element that enables higher education institutions (HEIs) to set themselves apart in a positive and superior way in terms of their performance would be advantageous given the competitive climate in which they operate. The Erasmus+ Programme provides HEIs with yet another option to become more competitive and to contribute to the Sustainable Development Goals (SDGs) via the improvement of educational quality (SDG 4), reducing inequalities (SDG 10), climate action (SDG 13), and peace and justice (SDG 16). The goal of this work was to explore the potential relationships and synergies between HE sustainability and Total Quality Management (TQM) issues through the SDGs. The methodological approach was concentrated on the qualitative study of academic papers on TQM, sustainability, and the SDGs in HE as well as on the analysis of Regulation (EU) 2021/817, which established Erasmus+. We concluded that TQM and sustainability have synergies related to the SDGs, and the Erasmus+ Programme can support the sustainability of HEIs by promoting these SDGs. Leadership; education and training; the participation of staff members; measurement, evaluation, and control; and other stakeholders are essential factors for the effective implementation of TQM and sustainability in HEIs. [ABSTRACT FROM AUTHOR]

The increasing demand for food, the lack of natural resources and arable land, and the recent restrictions on energy consumption require an immediate solution in terms of agricultural activities. This paper's objective was to review hydroponics (a new soilless cultivation technology) and compare it with conventional agriculture (soil cultivation) regarding its environmental impact and water and energy consumption. The soil loss, the crop/soil contamination, and the greenhouse gas emissions were the criteria for the environmental comparison of conventional agriculture and hydroponics. As for resource consumption, the water consumption rates (L/kg), energy consumption rates (kWh), and energy required (kW) were the criteria for comparing conventional agriculture with hydroponics. Tomato and cannabis cultivation were used as case studies in this review. The review results showed that the advantages of hydroponics over conventional cultivation include zero-soil cultivation, land-use efficiency, planting environment cleanliness, fertilizer and resource saving, water consumption reduction, and conservation. The disadvantages of hydroponics versus conventional cultivation were found to include the high investment costs, technical know-how requirements, and higher amount of demanded energy. [ABSTRACT FROM AUTHOR]

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

Global climate change affects biodiversity patterns, especially in arid and semi-arid regions such as the Mongolian plateau, one of the most ecologically fragile regions in the world. Three dynamic habitat indices (DHIs) were related to the productivity hypothesis and calculated based on FAPAR, including cumulative productivity ( D H I c u m indicates the availability of resources such as food supply and habitat in a year, representing available energy), minimum productivity ( D H I m i n indicates the limitations of food and habitat resources in a year, representing environmental stress), and seasonal productivity ( D H I s e a denotes the change in productivity in a year, representing environmental stability). In this paper, we investigated the distribution pattern of species richness on the Mongolian Plateau based on the productivity hypothesis. We constructed models of the richness of three species (mammals, birds, and amphibians) using DHIs and climate variables to explain patterns of species richness on the Mongolian Plateau. The results revealed that, on the Mongolian plateau, there is a relatively high correlation between DHIs and species richness, especially with D H I c u m (R = 0.59 for mammals, R = 0.73 for birds, and R = 0.58 for amphibians). There was a significant non-linear relationship between DHIs and species richness, as the model predictive power was significantly enhanced with GAM and RF. The inclusion of climate variables significantly improved the explanatory power of various models for the mammal, bird, and amphibian species richness on the Mongolian Plateau, with the best results for RF (0.89, 0.94, and 0.91, respectively). The influence of climate variables on species richness patterns in the importance ranking was higher than that of DHIs. Climate also has an influence on species richness. Vegetation productivity and climatic factors are good determinants of species richness on the Mongolian Plateau and should be carefully considered in future studies. [ABSTRACT FROM AUTHOR]

With the continuous development of financial markets worldwide to tackle rapid changes such as climate change and global warming, there has been increasing recognition of the importance of financial time series forecasting in financial market operation and management. In this paper, we propose a new financial time series forecasting model based on the deep learning ensemble model. The model is constructed by taking advantage of a convolutional neural network (CNN), long short-term memory (LSTM) network, and the autoregressive moving average (ARMA) model. The CNN-LSTM model is introduced to model the spatiotemporal data feature, while the ARMA model is used to model the autocorrelation data feature. These models are combined in the ensemble framework to model the mixture of linear and nonlinear data features in the financial time series. The empirical results using financial time series data show that the proposed deep learning ensemble-based financial time series forecasting model achieved superior performance in terms of forecasting accuracy and robustness compared with the benchmark individual models. [ABSTRACT FROM AUTHOR]