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Energy efficiency is one of the most powerful strategies to mitigate the impacts of climate change by reducing energy demand, which in turn reduces the emissions of Green House Gases (GHG), as well as reducing the burden on the supply side renewable generation expansion. Because electric motors systems represent such a large share of the overall electricity consumption (over 50%), large savings potential could be made available by the use of energy-efficient motor systems both in new installations and by accelerating the replacement of old inefficient motors. Since electric motors are very reliable, their lifetime is long (according to recent studies it may exceed 20 years) which translates into a very inefficient existing stock despite worldwide policy efforts. This paper analyzes the current efficiency of the installed stock and the causes for its low efficiency, possible policy options to increase its the efficiency, the role of new technologies and improvements possible by targeting the entire motor system at the time of motor replacement. The paper presents an innovative analysis of the estimated impact of increasing the uptake of high-efficiency motors and motor systems; effective policies could translate into 100 TWh/year in the European Union if additional measures, such as addressing oversizing, proper controls (VSDs) and digitisation, are also implemented. If similar measures were adopted globally, the savings triggered could be at least tenfold reaching over 1000 TWh/year. [ABSTRACT FROM AUTHOR]

Digital objects are now pervasively used across the heritage sciences, often as 3D models. However, the theoretical discussion of what these objects are, ontologically speaking, can be diverse, ranging, and inconclusive. This paper will focus on the Cherish Project, a European research initiative that used a range of methods—including drone-based photogrammetry and laser scanning— to create 3D models of coastal heritage landscapes that are at risk due to climate change. In specifically attending to the database storage schemes and software/platforms employed by Cherish, this paper explores how digital heritage objects can more broadly be discussed in terms of their ontological multiplicity, the multi-sitedness of their production and circulation, and their mobility across interfaces as they are formalised and circulated. In tracing these specific factors, this paper arrives at epistemological insights about how digital heritage objects factor into knowledge producing practices like Cherish, foregrounding critical questions about how these practices might be differently discussed, pursued, or imagined. [ABSTRACT FROM AUTHOR]

In this paper, the patterns of the occurrences of fire incidents over sub-Saharan Africa are studied on the basis of satellite data. Patterns for the whole sub-Saharan Africa are contrasted with those for northern sub-Saharan Africa and southern-hemisphere Africa. This paper attempts to unravel linear trends and overriding oscillations using regression and spectral techniques. It compares fire patterns for aggregated vegetation with those for specific types, which are savannahs, grasslands, shrublands, croplands, and forests, to identify key trend drivers. The underlying cyclic trends are interpreted in light of climate change and model projections. Considering sub-Saharan Africa, northern sub-Saharan Africa, and southern-hemisphere Africa, we found declining linear trends of wildfires with overriding cyclic patterns that have a period of ∼5 years, seemingly largely driven by savannahs, grasslands, and croplands. [ABSTRACT FROM AUTHOR]

Natural hazards are increasingly threatening our communities; hence it is imperative to provide communities with reliable information on possible impacts of such disasters, and on resilience measures that can be adopted to recover from disasters. To increase the engagement of various stakeholders in decision-making processes related to resilience to natural hazards, problem-specific information needs to be presented to them in a language understandable to non-experts in the field. To this end, this paper illustrates experimentation with low-code platforms for fast digitalization of resilience reports, incorporating the perspectives of various stakeholders in the analysis, thus making informed decision-making practicable. We present a co-creation-based approach to develop GIS-based user-friendly dashboards in support to the identification of resilience strategies against natural hazards; this approach has been developed within the framework of the European project ARCH. Urban areas are regarded as complex social-ecological systems whose various dimensions should be considered in this resilience endeavor, during all phases of the Disaster Risk Reduction and Climate Change Adaptation cycle. The work presented in this paper specifically targets the possible impacts and risks that might affect the cultural heritage subsystems of our cities, generally underrepresented in the international literature related to urban resilience assessment. We describe how we applied our approach to the Camerino municipality, a historic Italian town exposed to seismic risk, which was struck by a severe earthquake sequence in 2016–2017 and discuss the results of our experience. [ABSTRACT FROM AUTHOR]

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

This paper explores the potential of ground-penetrating radar (GPR) monitoring for an advanced understanding of snow cover processes and structure. For this purpose, the study uses the Hansbreen (SW Spitsbergen) records that are among the longest and the most comprehensive snow-cover GPR monitoring records available on Svalbard. While snow depth (HS) is frequently the only feature derived from high-frequency radio-echo sounding (RES), this study also offers an analysis of the physical characteristics (grain shape, size, hardness, and density) of the snow cover structure. We demonstrate that, based on GPR data (800 MHz) and a single snow pit, it is possible to extrapolate the detailed features of snow cover to the accumulation area. Field studies (snow pits and RES) were conducted at the end of selected accumulation seasons in the period 2008–2019, under dry snow conditions and HS close to the maximum. The paper shows that although the snow cover structure varies in space and from season to season, a single snow pit site can represent the entire center line of the accumulation zone. Numerous hard layers (HLs) (up to 30% of the snow column) were observed that reflect progressive climate change, but there is no trend in quantity, thickness, or percentage contribution in total snow depth in the study period. HLs with strong crystal bonds create a "framework" in the snowpack, which reduces compaction and, consequently, the ice formation layers slow down the rate of snowpack metamorphosis. The extrapolation of snow pit data through radar profiling is a novel solution that can improve spatial recognition of snow cover characteristics and the accuracy of calculation of snow water equivalent (SWE). [ABSTRACT FROM AUTHOR]

Climate change is directly linked to a broad array of changes because of disorganized activities within the economic system and human intervention. Climate change affects the well-being status of both non-living and living things. Relevant policies to mitigate and adapt to climate change conditions concentrate on solutions that intend to use renewable energy instead of fossil fuels or other conventional energy sources. This study aims to process a review focused on how renewables advance environmental quality and create relevant benefits within severe economic activities. This study elaborates on the case of China for two main reasons. First, China has a pivotal role in the economic system worldwide. Second, China is making serious attempts to transition into a low-carbon economy. An integrative review was processed to receive selected publications. The advantage of this process is that it considers empirical and non-empirical studies, policy papers, and conceptual frameworks. Inclusion and exclusion criteria were applied to retrieve the final number of publications. Review results from 39 well-acknowledged Journals provided 180 selected publications categorized into seven study groups: data analyses, model optimization studies, market issues, renewable energy technology publications, nuclear energy publications, ocean energy publications, and policy-related studies. Policy implications concern China's efforts to accelerate the integration of renewables in the energy mix. Hence, the country should increase energy efficiency in consumption and process investment plans based on robust research and development efforts. [ABSTRACT FROM AUTHOR]

The Philippines is one of only a few countries where Coffea liberica is commercially produced. Two infra-species, C. liberica liberica (also locally known as 'liberica') and C. liberica var dewevrei (also known as 'excelsa') comprise 1.1% and 5.7% of the national coffee production, respectively. These rare varieties are produced widely in the provinces of Batangas and Cavite mainly because of historical affinity, a local market, and more recently the renewed interest from importers. Aside from its unique flavor profile, renewed interest comes from the potential of the larger beans and deeper root systems of the species to thrive on a warming planet. In this paper, we present work that has been performed in evaluating bean morphology, chlorogenic acid, caffeine content and genetic variability of C. liberica varieties from different areas of the country. The initial efforts to predict areas for increased production were based on a maximum entropy model. Combining these data provides insights into development areas for increased production in the Philippines. [ABSTRACT FROM AUTHOR]

One fifth of the world's population and critical infrastructures are close to the coast and regions of high-risk sea level rise elevation. The last decades have been characterized by increasing extreme events, including storm surges, flooding, coastal erosion, enhanced coastal vulnerability with associated livelihood, and economic losses. Nature-based engineering solutions are being adopted as sustainable solutions for helping existing technologies live their design life and providing climate change adaptation and resilience for coastal and riverine communities. This paper involves the investigation of nature-based eco-hydraulic soft coastal engineering to cultivate seaweed for coastal protection. In this context, the present study involves an advanced risk evaluation performed by conducting an extreme bore interaction with seaweed as a soft engineering coastal protection measure. The load reduction on the inland structure during extreme flooding conditions, incorporating seaweed, is addressed. The present study indicates that the load on inland structures can be reduced by as much as 14% in extreme flooding conditions in the presence of seaweed with two rows of seaweed, indicating the usage of seaweed as a part of coastal protection over existing site protection infrastructure for improved coastal mitigation. [ABSTRACT FROM AUTHOR]

This paper analyzed the variations of two air temperature indices, diurnal temperature range (DTR) and annual temperature range (ATR), calculated based on observations at the Zagreb Grič Observatory over a period of 133 years (1887–2019). In intense climate changes strongly manifested by the increased air temperature, these two climate indices were determined to significantly impact human health and the environment. This effect is especially evident in urban areas. The Zagreb Grič Observatory is located in the center of Zagreb and has not changed its location during the observed period. It has a long homogeneous series of climatological observations, enabling a detailed study of climate variation in the city, which is strongly influenced by various urbanization processes. In 133 years, both of the analyzed indicators showed a statistically insignificant downward trend. The Rescaled Adjusted Partial Sums (RAPS) method revealed statistically significant differences in DTR's time series between three sub-periods: 1887–1953, 1954–1989, and 1990–2019. The time series of ATR during 133 years behaved statistically differently in four sub-periods: 1887–1905; 1906–1926; 1927–1964; and 1965–2019. The analysis of monthly values of DTR showed that the DTR values are the highest in the warm part of the year, from May to August, when they are twice as high as those during the cold period from November to December. With an increase in precipitation, the DTR values decrease, while they increase as the mean annual temperature increases. [ABSTRACT FROM AUTHOR]

Definition: Climate change is a shift in the climate's condition that lasts for an extended period, usually decades or longer, and that may be detected by changes in the mean and variability of its parameters. The full spectrum of players and their related value-adding activities, that are a part of the food supply chain, including the disposal of food items derived from agriculture, forestry, or fisheries, are collectively called food systems. Food systems are a component of their larger economic, social, and environmental contexts. Finally, food security is the condition in which all individuals consistently have physical and financial access to adequate safe, nutritious food that satisfies their dietary needs and food choices for an active and healthy life. Climate change and its relationships with food systems and security are complex since food systems significantly contribute to climate change. However, climate change impacts food systems unpredictably, leading to food insecurity through adverse impacts on the four dimensions of food security: utilization, access, food availability, and stability. Climate change adaptation plans are urgent and include measures such as flood and climate protection, waste management and recycling, climate-smart agriculture, and analytical climatic conditions innovation equipment on agricultural processes and activities. Nevertheless, addressing the climate crisis and its adverse impacts on food security through the activation and promotion of innovation needs reliable information and intervention in many different but interconnected fields, such as institutional design, philanthropy, novel partnerships, finance, and international cooperation. In this context, this paper analyses the relationship between climate change, agriculture, and global–local strategies to ensure food security and also discusses policies' role in fostering innovation for supporting local agro-food systems and their capacity to sustain societal needs. [ABSTRACT FROM AUTHOR]

Considering the negative effect of anthropological activities on climate in recent decades, all countries entailed a universal commitment to fight against climate change by boosting innovation and introducing new technologies. In this context, our paper aimed to investigate the impact of innovation input in terms of research and development (R&D) costs and technology expressed as technical equipment and machinery (TEM) on the reported greenhouse gas (GHG) emissions in chemical industry companies in five Central and Eastern European countries. This study employed a panel regression model with fixed effects and covered data from 2015 to 2020. The empirical results emphasize a negative relationship between R&D costs and GHG emissions, indicating the companies' commitment to developing innovative solutions that contribute to lower destructive emissions. Additionally, the findings related to the influence of TEM on GHG emissions reveal a positive impact, highlighting the need to improve manufacturing technologies. The practical implications of our findings can be meaningful for both policymakers and businesses operating in the chemical industry in developing countries. Policymakers should offer financial incentives to support research and investments in clean technologies, while businesses should prioritise such investments to mitigate GHG emissions. [ABSTRACT FROM AUTHOR]

Energy keeps the global economy alive, while also being extensively exposed to various climate change impacts. In this context, severe business competition (e.g., the building sector) and the unwise use of natural resources and ecosystem services (e.g., fossil fuel energy sources) seem to sharpen the relevant effects of climate change. Indicatively, contemporary issues at the interface of building energy performance and environmental quality levels include consequences from global warming, the increasing release of carbon dioxide to peak electrical loads, power grids, and building planning, and energy demand and supply issues. In light of such concerns, the present review paper attempts to disclose the multifaceted and multidisciplinary character of building energy use at the interface of the economy, the environment, and society against climate change. This review highlights energy efficiency concepts, production, distribution, consumption patterns, and relevant technological improvements. Interestingly, the reviewed contributions in the relevant literature reveal the need and necessity to alter the energy mix and relevant energy use issues. These include developments in climate-proof and effective systems regarding climate change impacts and shocks. Practical implications indicate that the sustainable development goals for clean energy and climate action should be followed if we wish to bring a sustainable future closer and faster to our reality. [ABSTRACT FROM AUTHOR]

The citizen's carbon footprint is affected by various factors, but mostly by electricity consumption, daily transportation, travelling habits, as well as municipal solid waste management, a critical factor that is not frequently incorporated in carbon footprint estimations. This paper proposes a new carbon footprint calculator, the Carbon Footprint Simulation Dashboard—COMPAIR's CO2 calculator. The CO2 calculator employs Citizen Science (CS) information in order to assist citizens in understanding and comparing how future carbon emissions will be modified in accordance with changes in their daily routines. The calculator offers several statistics, e.g., the country's average carbon footprint and comparisons between EU members with respect to sectors that shape it, along with several recommendations for those domains where carbon footprint is significantly higher than the desired limits. The novelty of this tool is the integration of waste management strategies as a dimension of the total CO2 calculation. In this framework, the study presents the development of the Carbon Footprint Simulation Dashboard while two different waste management scenarios are applied with different citizen behaviours on recycling and composting. The applications highlighted the consumption in buildings that account for almost 50% of the total CO2 emissions, while the crucial role of transportation is also a key parameter. The different waste management scenarios showed a correlation between the CO2 footprint and the overall consumption/disposal habits of citizens. In the case of advanced recycling and composting, waste management accounted for up to 7% of the CO2 emissions, and this highlights the significance of behavioural choices. [ABSTRACT FROM AUTHOR]

The SSS (sea surface salinity) is an important factor affecting global climate changes, sea dynamic environments, global water cycles, marine ecological environments, and ocean carbon cycles. Satellite remote sensing is a practical way to observe SSS from space, and the key to retrieving SSS satellite products is to establish an accurate sea surface brightness temperature forward model. However, the calculation results of different forward models, which are composed of different relative permittivity models and SSR (sea surface roughness) brightness temperature increment models, are different, and the impact of this calculation difference has exceeded the accuracy requirement of the SSS inversion, and the existing SSR brightness temperature increment models, which primarily include empirical models and theoretical models, cannot match all the relative permittivity models. In order to address this problem, this paper proposes a universal DNN (deep neural network) model architecture and corresponding training scheme, and provides different SSR brightness temperature increment models for different relative permittivity models utilizing DNN based on offshore experiment data, and compares them with the existing models. The results show that the DNN models perform significantly better than the existing models, and that their calculation accuracy is close to the detection accuracy of a radiometer. Therefore, this study effectively solves the problem of SSR brightness temperature correction under different relative permittivity models, and provides a theoretical support for high-precision SSS inversion research. [ABSTRACT FROM AUTHOR]

Cultural heritage is one of the most exceptional resources characterizing the Italian territory. Archaeological heritage, i.e., the archaeological sites with different types of archaeological artifacts, strongly contributes to enriching the national and international cultural heritage. Nevertheless, it is constantly exposed to external factors, such as natural deterioration, anthropic impact, and climate-related hazards, which may compromise its conservation. In Italy, many archaeological areas are affected by significant soil settlements that involve a large part of monuments. This paper focuses on the landslide hazard assessment of the archaeological site of Pietrabbondante (Molise region, Italy). The impact of the expected rainfall regimes, according to the EURO-CORDEX projections, on slope stability conditions were evaluated through the application of a physically based model that couples a hydraulic and a mechanical model to evaluate slope stability evolution due to pore pressure changes. Given the unavoidable lack of knowledge of the geotechnical soil properties in an archaeological heritage area, the proposed method considered the random uncertainty of soil parameters by means of a probabilistic approach in order to assess the stability conditions in terms of probability of occurrence of a landslide. The results of this study provide a reference for the safety assessment and preventive conservation of archaeological areas characterized by high cultural value. [ABSTRACT FROM AUTHOR]

The constantly growing demand for energy, the need to ensure the security of its supply, and the progressing climate changes related to the emission of carbon dioxide and other pollutants have caused, in recent years, an increase in interest in offshore wind energy. This paper presents all the work that needs to be done to build a wind farm in the Baltic Sea. The work focuses on the description of the equipment and the necessary tests to perform in order to analyze the obtained data. The data will allow for unambiguous interpretation and the selection of a convenient location for the construction of a wind farm. The final product of the work is a cost estimate, in which the costs of undertaking such an undertaking are shown. [ABSTRACT FROM AUTHOR]

In recent years, the importance of energy efficiency in the agricultural sector has become increasingly apparent. As the world faces challenges such as climate change, resource scarcity, and population growth, the need for sustainable and efficient agricultural practices has intensified. Energy plays a crucial role in agricultural production, from powering machinery and irrigation systems to processing and transportation. Therefore, understanding the scientific advancements and collaborative efforts in the field of energy efficiency in agriculture is essential for devising effective strategies, promoting innovation, and achieving global sustainability goals. The aim of this study is to provide insight into and a comprehensive overview of global publications on energy efficiency in agriculture and examine its scientific productivity. The paper explores the research areas and trending topics within the field, as well as the extent of collaboration among authors, institutions, and countries involved in this scientific domain. This investigation is crucial in order to address the current energy shocks and the numerous problems they generate, highlighting the importance of a holistic approach and the need for multiple regions to work together. Only by offering rapid and viable solutions can we effectively overcome this situation. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a crucial role in the climate change of China as well as global climate change. It is therefore of great practical significance to study vegetation and its dynamic changes for regional ecological protection. The combination of a dry climate and notable temperature disparities can lead to intricate effects on the region's vegetation. However, there are few studies exploring the complex effects of diurnal temperature variations on vegetation growth that differ from the effects of mean temperature on the TP, especially under different frozen ground types. Based on the long-time series maximum temperature (Tmax), minimum temperature (Tmin), and Normalized Difference Vegetation Index (NDVI) of the TP, we conducted a comparative study of the warming effects on plant growth under different frozen types. The results exhibit that it warms up faster at night (0.223 °C de−1; p < 0.01) than during the day (0.06 °C de−1; p < 0.01), resulting in a significant decrease in the temperature difference between day and night (−0.078 °C de−1; p < 0.01) in the past few decades. The principal finding of this paper is that Tmin is the dominant temperature indicator for vegetation growth on the TP, which dominates 63.3% of the area for NDVI and 61.4% of the area for GPP, respectively. The results further identify a stronger correlation between air temperature and vegetation growth in seasonal frozen grounds (R = 0.68, p < 0.01) and permafrost regions (R = 0.7, p < 0.01) compared to unfrozen grounds (R = 0.58, p < 0.01). Moreover, the physiological mechanism underlying the asymmetric influence of Tmin and Tmax on vegetation growth is further elucidated in this study. Given that future climate changes are expected to exacerbate these changes, it is imperative to explore additional avenues in pursuit of potential mechanisms that can offer adaptive strategies for safeguarding the ecology of the TP. [ABSTRACT FROM AUTHOR]

Physically based hydrologic models require significant effort and extensive information for development, calibration, and validation. The study explored the use of the random forest regression (RFR), a supervised machine learning (ML) model, as an alternative to the physically based Soil and Water Assessment Tool (SWAT) for predicting streamflow in the Rio Grande Headwaters near Del Norte, a snowmelt-dominated mountainous watershed of the Upper Rio Grande Basin. Remotely sensed data were used for the random forest machine learning analysis (RFML) and RStudio for data processing and synthesizing. The RFML model outperformed the SWAT model in accuracy and demonstrated its capability in predicting streamflow in this region. We implemented a customized approach to the RFR model to assess the model's performance for three training periods, across 1991–2010, 1996–2010, and 2001–2010; the results indicated that the model's accuracy improved with longer training periods, implying that the model trained on a more extended period is better able to capture the parameters' variability and reproduce streamflow data more accurately. The variable importance (i.e., IncNodePurity) measure of the RFML model revealed that the snow depth and the minimum temperature were consistently the top two predictors across all training periods. The paper also evaluated how well the SWAT model performs in reproducing streamflow data of the watershed with a conventional approach. The SWAT model needed more time and data to set up and calibrate, delivering acceptable performance in annual mean streamflow simulation, with satisfactory index of agreement (d), coefficient of determination (R2), and percent bias (PBIAS) values, but monthly simulation warrants further exploration and model adjustments. The study recommends exploring snowmelt runoff hydrologic processes, dust-driven sublimation effects, and more detailed topographic input parameters to update the SWAT snowmelt routine for better monthly flow estimation. The results provide a critical analysis for enhancing streamflow prediction, which is valuable for further research and water resource management, including snowmelt-driven semi-arid regions. [ABSTRACT FROM AUTHOR]

Analyzing the future changes in runoff is crucial for efficient water resources management and planning in arid regions with large river systems. This paper investigates the future runoffs of the headwaters of the Tarim River Basin under different emission scenarios by forcing the hydrological model SWAT-Glacier using six regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) project. Results indicate that compared to the period of 1976~2005, temperatures are projected to increase by 1.22 ± 0.72 °C during 2036~2065 under RCP8.5 scenarios, with a larger increment in the south Tianshan mountains and a lower increment in the north Kunlun Mountains. Precipitation is expected to increase by 3.81 ± 14.72 mm and 20.53 ± 27.65 mm during 2036–2065 and 2066–2095, respectively, under the RCP8.5 scenario. The mountainous runoffs of the four headwaters that directly recharge the mainstream of the Tarim River demonstrate an overall increasing trend in the 21st century. Under the RCP4.5 and RCP8.5 scenarios, the runoff is projected to increase by 3.2% and 3.9% (amounting to 7.84 × 108 m3 and 9.56 × 108 m3) in 2006–2035. Among them, the runoff of the Kaidu River, which is dominated by rainfall and snowmelt, is projected to present slightly decreasing trends of 3~8% under RCP4.5 and RCP8.5 scenarios. For catchments located in the north Kunlun Mountains (e.g., the Yarkant and Hotan Rivers which are mix-recharged by glacier melt, snowmelt, and rainfall), the runoff will increase significantly, especially in summer due to increased glacier melt and precipitation. Seasonally, the Kaidu River shows a forward shift in peak flow. The summer streamflow in the Yarkant and Hotan rivers is expected to increase significantly, which poses challenges in flood risk management. [ABSTRACT FROM AUTHOR]

In the context of anomalous global climate change and the frequent occurrence of droughts and floods, studying trends in the conversion rate between precipitable water vapor (PWV) and actual precipitation in a certain region can help in analyzing the causes of these natural disasters. This paper examines the variation trend in the conversion rate between PWV and actual precipitation on a monthly scale in Hubei from 1960 to 2020. To estimate historical PWV data, we propose a new method for estimating PWV using water vapor pressure based on the RF algorithm. The new method was evaluated by radiosonde data and improved the accuracy by 1 mm over the traditional method in Hubei. Based on this method, we extrapolate the monthly average PWV in Hubei from 1960 to 2020 and analyze the conversion rate between PWV and precipitation during this period. Our results showed that there was no obvious cyclical pattern in the conversion rate in either the longitude or latitude directions. In Hubei, where the topography varies significantly in the longitude direction, the conversion rate is influenced by topography, with the smallest conversion rate being in the transition zone between the mountainous region of western Hubei and the Jianghan Plain. In the latitudinal direction, the conversion rate decreases with increasing latitude. [ABSTRACT FROM AUTHOR]

Diseases that are transmitted from vertebrate animals to humans are referred to as zoonotic diseases. Although microbial agents such as bacteria and parasites are linked to zoonotic events, viruses account for a high percentage of zoonotic diseases that have emerged. Worryingly, the 21st century has seen a drastic increase in the emergence and re-emergence of viral zoonotic disease. Even though humans and animals have coexisted for millennia, anthropogenic factors have severely increased interactions between the two populations, thereby increasing the risk of disease spill-over. While drivers such as climate shifts, land exploitation and wildlife trade can directly affect the (re-)emergence of viral zoonotic disease, globalisation, geopolitics and social perceptions can directly facilitate the spread of these (re-)emerging diseases. This opinion paper discusses the "intelligent" nature of viruses and their exploitation of the anthropogenic factors driving the (re-)emergence and spread of viral zoonotic disease in a modernised and connected world. [ABSTRACT FROM AUTHOR]

Huge amounts of carbon being sequestered in forest ecosystems make them an important land carbon sink at the global scale. Their ability to withdraw carbon dioxide (CO 2 ) from the atmosphere, whose concentration is gradually increasing due to anthropogenic emissions, renders them important natural climate-mitigation solutions. The urgent need for transition from high to zero net emission on country, continental, and global scales, to slow down the warming to an acceptable level, calls for the analysis of different economic sectors' roles in reaching that ambitious goal. Here, we examine changes in CO 2 emission and sequestration rates during recent decades focusing on the coal-dominated energy sector and Land Use, Land-Use Change, and Forestry (LULUCF) as well as wood production at the country level. The main purpose of the presented study is to examine the potential of storing carbon in standing forest biomass and wood products in Poland as well as the impact of disturbances. The ratio of LULUCF absorption of CO 2 to its emission in Poland has ranged from about 1% in 1992 to over 15% in 2005. From a climate-change mitigation point of view, the main challenge is how to maximize the rate and the duration of CO 2 withdrawal from the atmosphere by its storage in forest biomass and wood products. Enhancing carbon sequestration and storage in forest biomass, via sustainable and smart forestry, is considered to be a nature-based climate solution. However, not only forests but also wood-processing industries should be included as important contributors to climate-change mitigation, since harvested wood products substitute materials like concrete, metal, and plastic, which have a higher carbon footprint. The energy perspective of the paper embraces two aspects. First, CO 2 sequestration in forests and subsequently in harvested wood products, is an effective strategy to offset a part of national CO 2 emissions, resulting largely from fossil fuel burning for energy-production purposes. Second, wood as biomass is a renewable energy source itself, which played an important role in sustaining energy security for many individual citizens of Poland during the unusual conditions of winter 2022/2023, with a scarce coal supply. [ABSTRACT FROM AUTHOR]

Climate change represents an important cause of subsidence, especially in coastal cities affected by changes in surface water level and water table. This paper presents a complementary study of Interferometric Synthetic Aperture Radar (InSAR) and Ground Penetrating Radar (GPR) for the early detection of subsidence and sinkhole phenomena. The methodology was applied to a coastal urban area in Galicia, northwest Spain (humid region), showing apparent signs of subsidence and building settlement during the last two years. Two different InSAR methods are compared for the period from June 2021 to March 2022: PSI (Persistent Scatterer Interferometry) and SBAS (Small Baseline Subsets), and the average deformation velocities obtained resulted in −3.0 mm/yr and −4.1 mm/yr, respectively. Additional GPR data were collected in January 2022 to validate the InSAR results, which detected subsidence in agreement with the persistent scatters obtained from the PSI method. This is crucial information to plan preventive maintenance. [ABSTRACT FROM AUTHOR]

Global drylands, covering about 41% of Earth's surface and inhabited by 38% of the world's population, are facing the stark challenges of water scarcity, low water productivity, and food insecurity. This paper highlights the major constraints to agricultural productivity, traditional irrigation scheduling methods, and associated challenges, efforts, and progress to enhance water use efficiency (WUE), conserve water, and guarantee food security by overviewing different smart irrigation approaches. Widely used traditional irrigation scheduling methods (based on weather, plant, and soil moisture conditions) usually lack important information needed for precise irrigation, which leads to over- or under-irrigation of fields. On the other hand, by using several factors, including soil and climate variation, soil properties, plant responses to water deficits, and changes in weather factors, smart irrigation can drive better irrigation decisions that can help save water and increase yields. Various smart irrigation approaches, such as artificial intelligence and deep learning (artificial neural network, fuzzy logic, expert system, hybrid intelligent system, and deep learning), model predictive irrigation systems, variable rate irrigation (VRI) technology, and unmanned aerial vehicles (UAVs) could ensure high water use efficiency in water-scarce regions. These smart irrigation technologies can improve water management and accelerate the progress in achieving multiple Sustainable Development Goals (SDGs), where no one gets left behind. [ABSTRACT FROM AUTHOR]

Kañawa/Cañihua (Chenopodium pallidicaule Aellen) is the lesser-known cousin of the domesticated Andean pseudocereal quinoa (Chenopodium quinoa Willd.). In 1970, Daniel Gade hypothesized that Andean farmers may have domesticated volunteer wild kañawa plants that occupied quinoa or potato fields after observing that they could survive harsh climatic events such as drought or frost. To revisit this question of kañawa domestication, this paper provides an overview of the current botanical, genetic, and archaeological knowledge of kañawa domestication. It then provides patterns in the presence of wild and domesticated kañawa seeds from archaeological sites in the southern Lake Titicaca Basin of Bolivia, spanning the Formative and Tiwanaku periods from approximately 1500 BCE to 1100 CE. This archaeobotanical evidence supports Gade's hypothesis that kañawa was a later domesticate, not appearing until after 250 CE. Regional paleoclimatic evidence of frequent climatic fluctuations lends support to the argument that kañawa contributed to a diversified food supply, which could provide a buffer against climate risks. [ABSTRACT FROM AUTHOR]

Despite decades of literature and practice with community-engaged research along with advancements in the recognition of environmental injustices, the application of equity-/justice-based and collaborative approaches between government agencies and community-based organizations has been limited. The toxic legacies of environmental racism, redlining, displacement, and segregation combined with the accelerating human-caused climate crisis warrant an increased need for consultation and collaboration between frontline communities and power brokers to markedly improve quality of life and health outcomes in environmental justice neighborhoods. This paper describes the processes and progress to date from a community-led collaboration between local community-based organizations and the Enforcement Division of the California Air Resources Board to assess and address air pollution in South Stockton, particularly from heavy-duty diesel trucks. South Stockton is one of the most polluted neighborhoods in California's San Joaquin Valley, one of the most disparate and polluted regions in the United States. Some of the most significant components integrated into this project thus far include taking an equity-, justice-, and youth-oriented approach to community development that intentionally emphasizes a historical understanding of root causes of social and environmental injustices and provides pathways to workforce development. Including these elements has been essential in building the trust necessary to transform disparate power relations between the state and environmental justice communities, and to put multiple ways of knowing into conversation with each other to co-learn and co-power solutions to air pollution in South Stockton. [ABSTRACT FROM AUTHOR]

The increasing prevalence of wicked problems, such as climate change, requires a transformation in education that equips students with the skills, competencies and knowledge to address these complex challenges. Wicked problems are characterised by their incomplete, contradictory, and ever-changing requirements, rendering them difficult to resolve due to intricate interdependencies. Nexus thinking offers a valuable approach to these problems, as it emphasises the interconnectedness of various systems, fostering a more comprehensive understanding of the challenges at hand. In this paper, we propose the use of Climate, Land, Energy, and Water (CLEWs) modelling as an innovative pedagogical strategy tool to cultivate nexus thinking among students. Building upon the pioneering CLEWs pedagogical work of Shivakumar et al., in their 'Introduction to CLEWs' Open Learn course, we demonstrate how this approach can be utilised in a Higher Education (HE) setting in the form of a Masters' module for geography students. [ABSTRACT FROM AUTHOR]

Holmes Rolston, III examined the significance of Asian thought for Western evaluations of nature and questioned if Asian Romanticism can inform the realistic decision making required for practice. However, Rolston's general evaluation of Asian thought ignored Confucianism. This study launches a dialogue between Rolston and contemporary Confucianism on environmental philosophy and highlights the following points in response to Rolston: First, Confucianism is grounded on an "anthropocosmic" worldview and bases its environmental ethics on its affirmation of the "virtue of life and growth" and the related vision of "unity of heaven and human beings"; it is thus an objective environmental virtue ethics with the characteristics of sacred humanism that avoids anthropocentrism. Second, Confucian ethics is built on the premise of "one principle with various manifestations" and advocates for practicing benevolence through "love with gradations", which avoids an excessively idealistic ecocentrism. Furthermore, Confucianism may adopt Rolston's recommendation for Asian thought concerning the incorporation of evolutionary biology into Asian traditions to facilitate their own transformation and thus contribute to environmental philosophy. Upon an exploration of the compatibility and possible reciprocal illumination between Confucianism and Rolston, this paper points out the implications of the above dialogue for theology in the planetary climate crisis. [ABSTRACT FROM AUTHOR]

The impact of climate change on the physical environment, ecosystems, and human societies is increasingly recognized as the most important global challenge. Climate change may alter, among others, the thermal environment, the occurrence of extreme weather events, and the human exposure to physical, chemical, and biological pollutants, thus affecting human health with several potential outcomes. The impact of climate change on occupational health and safety has been receiving increasing attention in last years. In the European Union, the health and safety of workers is under the rule of Directive 89/391 and its daughters. In a changing climate, compliance with all requirements of the existing EU regulation entails an additional effort to implement preventive and protective measures. A central role in workers' health protection is played by proper workers' information and training, which is partly in charge of the occupational physicians. This paper provides a basic proposal on topics related to climate change to update workers' information and training and to integrate the curricula of occupational physicians. Importantly, suitable information and training may contribute to promoting workers' health and to implement adaptation measures, which are part of the individual, societal, and global responses to climate change. [ABSTRACT FROM AUTHOR]

The rainfall distribution in southwest China is uneven, and the rainstorm threshold cannot use in a unified standard. This paper synthesizes a calculation method for the extremely heavy precipitation threshold and the provision of the rainstorm threshold in meteorological operation. It calculates the daily precipitation rainstorm threshold at 400 national ground stations in southwest China. The rainstorm events from 1961 to 2021 were statistically analyzed using the rainstorm threshold and analyzing the spatial-temporal variation characteristics. The results show that the number of single-station rainstorm events and the average precipitation of single-station rainstorm events in southwest China decreased from east to west. The number and frequency of single-station rainstorm events in Guizhou, Sichuan, Tibet, and Chongqing are increasing, while the number of single-station rainstorm events in Yunnan is decreasing. There is no apparent spatial distribution pattern for the continuous rainstorm events in the southwest region. From 1961 to 2021, the number and frequency of rainstorm events at a single station in southwest China followed an upward trend. The number of rainstorm events at a single station increased by 16.7 times · (10a)−1, and the frequency of rainstorms increased by 9.9% · (10a)−1. The continuous rainstorm events show an increasing trend, with an increase of 0.1 times · (10a)−1. Using the rainstorm threshold in southwest China, the early warning threshold for rainstorm disasters can be adjusted. The temporal and spatial characteristics of rainstorm events since 1961 can analyze the changes occurring in rainstorm events under global warming and provide data to support the response of southwest China to climate change. [ABSTRACT FROM AUTHOR]

The Earth's weather and climate are strongly influenced by synoptic-scale systems such as extratropical cyclones. From this point of view, extratropical cyclones are very important for Equator–Pole heat exchange, and their positions are relevant to the understanding of the behavior of this system under current conditions and in the context of climate change. Baroclinic instability (BI), meridional heat flux (MHF), and kinetic energy (KE) are among the ways of calculating storm tracks (the regions in which extratropical cyclones most often occur). Forecasting is important for predicting the evolution of these phenomena and preparing future political decisions. In this study, we used ERA5 reanalysis data and BESM model forecasts to calculate BI, MHF, and KE. Overestimation of the BESM BI at lower and higher latitudes and underestimation of BI at medium latitudes were observed. In general, KE and MHF were underestimated and were displaced southward in the BESM. The analyses show a tendency towards poleward displacement of these tracks for all variables studied in in this paper. The scenarios show the same bias, with RCP8.5 having more extreme changes in all situations. [ABSTRACT FROM AUTHOR]

The objective of this paper is to present a novel design of intelligent neuro-supervised networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson's disease illness (PDI), governed with three differential classes to represent the rhythms of brain electrical activity measurements at different locations in the cerebral cortex. The proposed INSNs are constructed by exploiting the knacks of multilayer structure neural networks back-propagated with the Levenberg–Marquardt (LM) and Bayesian regularization (BR) optimization approaches. The reference data for the grids of input and the target samples of INSNs were formulated with a reliable numerical solver via the Adams method for sundry scenarios of PDI models by way of variation of sensor locations in order to measure the impact of the rhythms of brain electrical activity. The designed INSNs for both backpropagation procedures were implemented on created datasets segmented arbitrarily into training, testing, and validation samples by optimization of mean squared error based fitness function. Comparison of outcomes on the basis of exhaustive simulations of proposed INSNs via both LM and BR methodologies was conducted with reference solutions of PDI models by means of learning curves on MSE, adaptive control parameters of algorithms, absolute error, histogram error plots, and regression index. The outcomes endorse the efficacy of both INSNs solvers for different scenarios in PDI models, but the accuracy of the BR-based method is relatively superior, albeit at the cost of slightly more computations. [ABSTRACT FROM AUTHOR]

Wind patterns can change due to climate change, causing more storms, hurricanes, and quiet spells. These changes can dramatically affect wind power system performance and predictability. Researchers and practitioners are creating more advanced wind power forecasting algorithms that combine more parameters and data sources. Advanced numerical weather prediction models, machine learning techniques, and real-time meteorological sensor and satellite data are used. This paper proposes a Recurrent Neural Network (RNN) forecasting model incorporating a Dynamic Fitness Al-Biruni Earth Radius (DFBER) algorithm to predict wind power data patterns. The performance of this model is compared with several other popular models, including BER, Jaya Algorithm (JAYA), Fire Hawk Optimizer (FHO), Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Particle Swarm Optimization (PSO)-based models. The evaluation is done using various metrics such as relative root mean squared error (RRMSE), Nash Sutcliffe Efficiency (NSE), mean absolute error (MAE), mean bias error (MBE), Pearson's correlation coefficient (r), coefficient of determination (R2), and determination agreement (WI). According to the evaluation metrics and analysis presented in the study, the proposed RNN-DFBER-based model outperforms the other models considered. This suggests that the RNN model, combined with the DFBER algorithm, predicts wind power data patterns more effectively than the alternative models. To support the findings, visualizations are provided to demonstrate the effectiveness of the RNN-DFBER model. Additionally, statistical analyses, such as the ANOVA test and the Wilcoxon Signed-Rank test, are conducted to assess the significance and reliability of the results. [ABSTRACT FROM AUTHOR]

Cities have always been places that generate problems, but also places where solutions are born. In recent years, cities have become a testing ground for finding and testing solutions to overcome the climate crisis. The subject of the paper is Nature-based Solutions (NbSs) that strengthen the resilience to climate change, influence urban spaces, and improve the quality of life of residents. The study focusses on the identification of NbSs, the diagnosis of its participation in local adaptation activities, and a comparative analysis of the activities planned and implemented in 44 large Polish cities in 2017–2023. The authors analyse data from 44 Polish cities, based on the types of NbSs implemented in European cities that carried out the URBAN GreenUP project. The results of the study show that Polish cities, while introducing sustainable urban lifestyles through NbSs, do not take advantage of all the opportunities inherent in these solutions. They focus on greening urban spaces and implement water interventions and singular green infrastructure measures to a lesser extent. There is negligible use of innovative and energy-using activities. The quantitative data obtained can be used to identify the gaps and potentials in the use of nature-based solutions in the adaptation of Polish cities to climate change and energy transformation. The aim of this work is also to identify recommendations to incorporate NbSs into urban adaptation policies in Poland. The authors conclude that the research conducted can serve to improve the knowledge on the links between NbS planning in adaptation activities and their implementation in urban spaces. An awareness of NbS gaps can influence the intensification of research on the implementation of innovative adaptation solutions, including energy-based solutions. The results obtained can also contribute to a better organisation of urban policies that aim to increase the resilience of cities to climate change. [ABSTRACT FROM AUTHOR]

Achieving a good level of resilience to extreme events caused by severe weather conditions is a major target for operators in modern power systems due to the increasing frequency and intensity of extreme weather phenomena. Moreover, regulatory authorities are pushing transmission and distribution operators to prepare resilience plans suitably supported by Cost–Benefit Analyses (CBAs). In this context, this paper proposes a CBA framework based on Optimization via Simulation (OvS) for the selection of the optimal portfolio of resilience enhancement measures. Starting from a comprehensive set of candidate grid hardening and operational measures, the optimal mix is identified by applying a novel two-step procedure based on an efficient application of the generalized pattern search heuristic technique. Risk indicators for the CBA are quantified, accounting for probabilistic models of climate changes. Moreover, the potential cascading outages due to multiple component failures provoked by extreme events are simulated on selected scenarios. The examples carried out on an IEEE test system show the effectiveness of the approach in identifying the best portfolio of resilience enhancement measures depending on climate change projections and costs of the measures, while the application to the model of a large portion of the Italian EHV transmission system demonstrates the practicability of the approach in real-world studies to support operators in different power system management phases, from planning to operation. [ABSTRACT FROM AUTHOR]

In recent years, the demand and requirement for renewable energy have significantly increased due to concerns regarding energy security and the climate crisis. This has led to a significant focus on wind power generation. As the deployment of wind turbines continues to rise, there is a growing need to assess their lifespan and improve their stability. Access to accurate load data is crucial for enhancing safety and conducting remaining life assessments of wind turbines. However, maintaining and ensuring the reliability of measurement systems for long-term load data accumulation, stability assessments, and residual life evaluations can be challenging. As a result, numerous studies have been conducted on load prediction for wind turbines. However, existing load prediction models based on 10 min statistical data cannot adequately capture the short-term load variations experienced by wind turbines. Therefore, it is essential to develop models capable of predicting load with a high temporal resolution to enhance reliability, especially with the increasing scale and development of floating wind turbines. In this paper, we developed prediction models with a 50 Hz resolution for the bending strain at the tower bottom of offshore wind turbines by combining SCADA data and acceleration data using machine learning techniques and analyzed the results. The load prediction models demonstrated high accuracy, with a mean absolute percentage error below 4%. [ABSTRACT FROM AUTHOR]

The province of Jaén (Andalusia, Spain), despite being declared the European territory with the largest number of defensive constructions (castles, fortifications, etc.), has few conservation plans, with many remains included on the Red List of Spanish Heritage lying abandoned. This poses a challenge for landscape conservation and the optimal use of the province's tourism potential. In this paper, we present the early implementation of an ongoing methodological approach designed to alleviate this situation. It takes advantage of data from the Sentinel 2A and 2B satellites, HBIM, RPAS, GIS, and fieldwork that will be applied across five archaeological case studies. It was tested for the first time in the village of Magaña. Three main objectives and phases of this methodological approach were designed: 1. Preparation of an environmental risk chart with which to answer such questions as "How have climate change, anthropic alterations and environmental characteristics affected the state of conservation of certain heritage sites?" 2. Preparation of HBIM models to foster monitorisation and conservation policies for the main archaeological remains and improving their protection based on digital and technological tools. 3. Building a smart tourism app for mobile devices aimed at promoting smart tourism by digitalising and virtualising tourist itineraries and archaeological remains. Finally, public administrations will be apprised of the need to implement a conservation policy for cultural assets and their surroundings in a simple, quick, and cost-effective manner. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms of responses to high temperatures in Arabidopsis will provide insights into how plants may mitigate heat stress under global climate change. And exploring the interconnections of different modification levels in heat stress response could help us to understand the molecular mechanism of heat stress response in Arabidopsis more comprehensively and precisely. In this paper, we combined multiomics analyses to explore the common heat stress-responsive genes and specific heat-responsive metabolic pathways in Arabidopsis leaf, seedling, and seed tissues. We found that genes such as AT1G54050 play a role in promoting proper protein folding in response to HS (Heat stress). In addition, it was revealed that the binding profile of A1B is altered under elevated temperature conditions. Finally, we also show that two microRNAs, ath-mir156h and ath-mir166b-5p, may be core regulatory molecules in HS. Also elucidated that under HS, plants can regulate specific regulatory mechanisms, such as oxygen levels, by altering the degree of CHH methylation. [ABSTRACT FROM AUTHOR]

Tea (Camellia sinensis L.), as one of the most important cash crops in China, plays an important role in increasing farmers' incomes and guaranteeing a high quality of life. Tea production has been greatly influenced by both climate change and economic development in China. However, without a scientific understanding of the interaction mechanism of climate change and the impetus from rapid economic development on tea production practices in China, it is difficult to take adaptive actions to meet the climate change challenges for the tea industry. In this paper, we firstly assessed the potential impacts of climate change on tea climate suitability by empirical formula calculation using meteorological data; then, the effects from the additional climatic stress due to warming on tea production were detected with the annual statistical tea yield record on a municipal level. The contribution of socioeconomic development to the tea industry was evaluated with the comparison of the movement of China's national economy's and tea industry's gravity center during the period of 1987–2017. Finally, a conceptual adaptation framework was built to demonstrate the interaction mechanisms between climate change, tea production, and the economic development. The results showed that there was a negative impact of climate change on tea production in mainland China, with the percentage of high tea climate suitability (>0.9) areas dropping by 45% to 32%, while opportunities of enlarging the tea cultivating area emerged in the north tea production region where the tea climate suitability increased. We found that the tea planting area expanded northwards from 33° N in 1987 to 35° N in 2017 to take advantage of the favorable climatic resources due to warming, and tea planting decreased at an altitude of 100–400 m while increasing to higher altitude of 400–2000 m to avoid hot temperature damage and seek the optimum environment in high mountainous areas for tea production. In addition, the tea production moved westward along the longitude, decreasing obviously at 117–121° E while increasing significantly at 98–104° E and 107–110° E. Meanwhile, the tea production gravity center showed a westward movement consistent with the national economic gravity center moving trend, which means that tea industry development was driven by multiple socioeconomic factors and climatic forcings. A conceptual framework was built in this paper, aiming to show a robust adaptation mechanism for the tea system to maximize the benefits and minimize the damages from the altered climatic resources under rapid economic development in mainland China. The results in this study would help deepen the understanding of the adaptation process and practices for tea production in mainland China. [ABSTRACT FROM AUTHOR]

Crop quality is directly related to national food security and people's living standards, and it is also key to the improvement of agricultural quality and efficiency. According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), climate change has already exerted a negative impact on crop quality. To address climate change scientifically, this paper reviews the latest progress in studies on the impact of climate change on crop quality, and points out limitations of existing studies: (1) Climate factors affecting crop quality are not yet clearly identified; (2) The climate change influencing mechanism and disaster-inducing critical meteorological conditions for crop quality are not clearly established; and (3) No climatic suitability model for crop quality has been constructed to reflect the synergy of multiple climate factors. To ensure food quality and security, and to adjust and optimize the industrial planning of grain crops, promote a high crop quality and yield, and address climate change scientifically, this paper argues that subsequent studies should discuss the following topics, focusing on the climatic suitability of crop quality and resistance mechanisms: (1) changing laws involving the climate sensitivity of crop quality in the context of climate change; (2) response mechanisms of crop quality to climate change; (3) crop quality monitoring and assessment modelling; (4) climatic suitability zoning of crop quality; (5) spatiotemporal evolution trends of crop quality and its responses; and (6) crop quality and its legal measures in the world. [ABSTRACT FROM AUTHOR]

The emergence of new transformational technology, known as the fourth industrial revolution, has crucially opened a new window to green economic growth. The transition to low carbon, green economy, and green sustainability has gained momentum simultaneously in developed and developing countries. The greening policy echoes the pending climate change and its entrenching disruptions. Financial technology, or FinTech seems to be a promising direction in unlocking the green dilemma; to be concrete, FinTech and the green economy are separately documented in the literature. Against this background, the current study investigates the intersection between green economic growth and FinTech by conducting a systematic-cum-bibliometric analysis of published papers in the Scopus database with the goal of first examining the role and opportunities of implementing green FinTech as a stimulus for transition towards green economic growth in African countries and, second, identifying knowledge gaps and future policy and research directions by developing an integrated framework to help African countries in the transition to green economic growth and green FinTech. The results illustrate an increasing trend in research attention towards the green FinTech concept and its relationship with green economic growth, climate change, and greening rules and standards. A deep inspection of the mined papers indicates that future research trajectories are oriented into five different mainstreams: technology and instruments in digital finance; regulation, policies, and green FinTech; climate risk mitigation through FinTech; FinTech and environmental quality; green finance and climate change mitigation. Based on these research directions, an integrated framework was conceptualised that aims to deliver green economic growth using FinTech as a vehicle of transition for African countries. [ABSTRACT FROM AUTHOR]

As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

Simple Summary: Vector-borne diseases (VBDs) are a major threat to human health. Climate change has a significant impact on VBDs. To clarify the complex effects of climate change on VBDs, we concluded the effects of climate on the transmission and spread of VBDs from an ecological perspective and summarized VBD changes in response to climate change, specifically including: the nonlinear effects of local climate (temperature, precipitation and wind) on VBD transmission, especially temperature showing n-shape effects; regional climate (the El Niño–Southern Oscillation and North Atlantic Oscillation) has time-lag effects on VBD transmission through indirect impact on local climate; and the u-shaped effect of extreme climates can lead to the geographical spread of VBDs. In terms of non-climatic factors, land use and human mobility through the interactions with climatic factors, will affect transmission and spread of VBD. We further explored the uncertainty of the impact of climate change on VBDs under the COVID-19 pandemic. A systematic understanding of the impact of climate change on the transmission and spread of VBD can provide insights and suggestions for future research on VBD prevention and control. Climate change affects ecosystems and human health in multiple dimensions. With the acceleration of climate change, climate-sensitive vector-borne diseases (VBDs) pose an increasing threat to public health. This paper summaries 10 publications on the impacts of climate change on ecosystems and human health; then it synthesizes the other existing literature to more broadly explain how climate change drives the transmission and spread of VBDs through an ecological perspective. We highlight the multi-dimensional nature of climate change, its interaction with other factors, and the impact of the COVID-19 pandemic on transmission and spread of VBDs, specifically including: (1) the generally nonlinear relationship of local climate (temperature, precipitation and wind) and VBD transmission, with temperature especially exhibiting an n-shape relation; (2) the time-lagged effect of regional climate phenomena (the El Niño–Southern Oscillation and North Atlantic Oscillation) on VBD transmission; (3) the u-shaped effect of extreme climate (heat waves, cold waves, floods, and droughts) on VBD spread; (4) how interactions between non-climatic (land use and human mobility) and climatic factors increase VBD transmission and spread; and (5) that the impact of the COVID-19 pandemic on climate change is debatable, and its impact on VBDs remains uncertain. By exploring the influence of climate change and non-climatic factors on VBD transmission and spread, this paper provides scientific understanding and guidance for their effective prevention and control. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: Existing food production systems and dietary behaviours are not healthy nor sustainable due to the higher environmental footprint of animal-derived foods. Alternative dietary choices could provide better outcomes. We investigated Generation Z (Gen Z)'s alternative food preferences within a planetary health framework which combines human and ecological well-being. The paper is based on data from a 2021 cross-national survey conducted in the main Australian cities, which explored Gen Z's attitudes towards meat consumption in relation to climate change and alternatives to animal-based proteins. Climate change is seen as a result of human activities by 86% of the survey participants. More than a third (38%) of them believe that livestock production and the consumption of animal-sourced foods are contributing significantly to climate change and environmental deterioration. The remaining majority (62%), however, has a low awareness and understanding of the food systems' impacts, disbelieving that diet is a major contributor to climate change. We discuss how these findings will shape Australia's Gen Z, climate change and the future of alternative proteins. Scientific evidence shows that current food systems are impacting the planet in ways that are unsustainable and detrimental to human health. Various technological advances have been made in response, one of them being the development of new food products known as novel alternative proteins, including cultured meat, plant-based meat analogues, algae- and insect-based foods. The future of these alternative proteins to a large extent depends on consumer acceptance from young people. This study investigates the attitudes of Australia's adult Generation Z (Gen Z), born between 1995 and 2003, regarding climate change and more sustainable food choices. Gen Z is a diverse, important and trendsetting group known for organising globally on causes related to climate, social justice and health. The study of Australia's Gen Z is based on a 2021 cross-national survey in the main Australian cities. It shows that, although 86% of the participants perceive climate change as anthropogenic, only 38% believe that livestock-based foods are contributing significantly to global warming and environmental deterioration. The paper discusses the implications for Gen Z and novel alternative proteins given that the majority of Australia's young people has low awareness of the environmental impacts of food systems and dietary choices. [ABSTRACT FROM AUTHOR]

This article is a response to comments made by researchers from the Universidad de Sevilla regarding a paper on extending climate justice to animals. The authors of the response agree with the commenters that the Iberian Lynx population has increased due to conservation efforts, but they clarify that their paper was not intended as a critique of these measures. The purpose of their paper is to discuss how to help wild animals cope with climate change, using the Iberian Lynx as an illustrative case. They argue that while the population has increased, the species is still at risk of extinction due to climate change. The authors also address the commenters' mention of the lack of originality in their proposed conservation measures, stating that their intention was to examine the moral implications of intervention strategies. Overall, the authors emphasize the importance of climate justice for animals, including the Iberian Lynx. [Extracted from the article]

Climate change is progressing faster than previously envisioned. Efforts to mitigate the challenges of greenhouse gas emissions by countries through the establishment of the Intergovernmental Panel on Climate Change has resulted in continuous environmental improvements in the energy efficiency and carbon emission signatures of products. In this paper, an energy–carbon emissions nexus causal model was applied using the Leontief Input–Output mathematical model for low-carbon products in future transport-manufacturing industries., The relationship between energy savings, energy efficiency, and the carbon intensity of products for the carbon emissions signature of the future transport manufacturing in South Africa was established. The interrelationship between the variables resulted in a 29% improvement in the total energy intensity of the vehicle body part products, 7.22% in the cumulative energy savings, and 16.25% in the energy efficiency. The scope that has been examined in this paper will be interesting to agencies of government, researchers, policymakers, business owners, and practicing engineers in future transport manufacturing and could serve as a fundamental guideline for future studies in these areas. [ABSTRACT FROM AUTHOR]

This paper reviews and assesses India's energy policy in the context of its commitment to achieve the target of net-zero carbon emissions by 2070. It emphasizes the central role of green electrification, particularly through the expansion of solar power capacity. It discusses policies outside the energy sector that need to be part of a strategy of achieving this target, including the use of information technology, infrastructure development, and transportation. Furthermore, it examines possible policy options for accelerating the target date to 2050, especially with the use of carbon capture to manage the transition from the current heavy use of coal. The paper also discusses the possible financial and growth implications of various strategy options, arguing that feasible external financing commitments can allow India to achieve net-zero goals without sacrificing economic growth. [ABSTRACT FROM AUTHOR]