The response of boreal vegetation to global warming has shown a weakening trend over the last three decades. However, in previous studies, models of vegetation activity responses to temperature change have often only considered changes in mean daily temperature (Tmean), with the diurnal temperature range (DTR) being neglected. The goal of this study is to evaluate the temporal trends of the relationships between two temperature factors (Tmean and DTR) and vegetation activity across the boreal regions on both annual and seasonal timescales, by simultaneously employing satellite and climate datasets. We found that the interannual partial correlation between growing season (GS) NDVI and Tmean (RNDVI−Tmean) showed a significant decreasing trend over the last 34 years. At the seasonal scale, RNDVI−Tmean shows a significant upward trend in the spring, while in the summer and autumn, RNDVI−Tmean exhibits a significant downward trend. The temporal trend characteristics of the partial correlation between NDVI and DTR (RNDVI−DTR), at both the GS and seasonal scales, are fully consistent with RNDVI−Tmean. The area with a significant decrease in GS RNDVI−Tmean and RNDVI−DTR accounted for approximately 44.40% and 41.21% of the boreal region with the 17-year moving window, respectively. In stark contrast, the area exhibiting a significant increasing trend in GS RNDVI−Tmean and RNDVI−DTR accounted for only approximately 14.65% and 13.59% of the boreal region with the 17-year moving window, respectively. With respect to the seasonal patterns of RNDVI−Tmean and RNDVI−DTR, the area with a significant upward trend in spring was greater than that with a significant downward trend. Nevertheless, more areas had a significant downward trend of RNDVI−Tmean and RNDVI−DTR in summer and autumn than had a significant upward trend. Overall, our research reveals a weakening trend in the impact of temperature on vegetation activity in the boreal regions, and contributes to a deeper understanding of the vegetation response to global warming.

Psychiatric patients are particularly vulnerable to strong weather stimuli, such as foehn, a hot wind that occurs in the alps. However, there is a dearth of research regarding its impact on mental health. This study investigated the impact of foehn wind among patients of a psychiatric hospital located in a foehn area in the Swiss Alps. Analysis was based on anonymized datasets obtained from routine records on admission and discharge, including the Brief Symptom Checklist (BSCL) questionnaire, as well as sociodemographic parameters (age, sex, and diagnosis). Between 2013 and 2020 a total of 10,456 admission days and 10,575 discharge days were recorded. All meteorological data were extracted from the database of the Federal Office of Meteorology and Climatology of Switzerland. We estimated the effect of foehn on the BSCL items using a distributed lag model. Significant differences were found between foehn and non-foehn admissions in obsession-compulsion, Interpersonal Sensitivity, depression, Anxiety, Phobic Anxiety, Paranoid Ideation, and General Severity Index (GSI) (p <.05). Our findings suggest that foehn wind events may negatively affect specific mental health parameters in patients. More research is needed to fully understand the impact of foehn’s events on mental health.

There is accumulating evidence that prenatal exposure to air pollution disturbs fetal growth and development, but little is known about these effects in cold climates or their season-specific or joint effects. Our objective was to assess independent and joint effects of prenatal exposure to specific air pollutants on the risk of low birth weight (LBW). We utilized the 2568 children of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo. We conducted stratified analyses for births during warm and cold seasons separately. We analyzed the effect estimates using multi-pollutant Poisson regression models with risk ratio (RR) as the measure of effect. The risk of LBW was related to exposure to CO and (adjusted RR 1.44, 95% CI: 1.04-2.00) and exposure to O3 in the spring-summer season (1.82, 1.11-2.96). There was also evidence of synergistic effects between CO and O3 (relative risk due to interaction, RERI, all year 1.08, 95% CI: 0.27-4.94, spring-summer 3.97, 2.17-25.85) and PM2.5 and O3 (all year 0.72, -0.07-3.60, spring-summer 2.80, 1.36-19.88). We present new evidence of both independent and joint effects of prenatal exposure in a cold climate on the risk of LBW at low levels of air pollution.

The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015-2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements in MERRA-2 reanalyses and the full revisit capacity of Sentinel-2.

Fungi constitute a diverse group with highly positive and negative impacts in different envi-ronments, having several natural roles and beneficial applications in human life, but also caus-ing several concerns. Fungi can affect human health directly, but also indirectly by being detri-mental for animal and plant health influencing food safety and security. Climate changes are al-so affecting fungal distribution, prevalence, and their impact on different settings. Searching for sustainable solutions to deal with these issues is challenging due to the complexity of the inter-actions among fungi and agriculture, animal production, environment, and human health. In this way, the “One Health” approach may be useful to get some answers since it recognizes that human health is closely connected to animal and plant health, as well as to the shared environ-ment. This review aims to explore and correlate each of those factors influencing human health in this “One Health” perspective.

Oncomelania Hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of its habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB), and the ecological stability. Therefore, it is crucial to analyse the influence of climate change on the distribution of O. Hupensis in order to achieve accurate control over its population. This study utilised the MaxENT model to forecast possible snail habitats by utilising snail distribution data obtained from historical literature. The subsequent outcomes were achieved: The primary ecological factors influencing the distribution of O. Hupensis are elevation, minimum temperature of coldest month, and precipitation of wettest month; Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution centre for O. hupensis; Specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest; These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, resulting in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

This study examined local communities' perceptions of mangroves in coastal southeastern Cuba. A variety of methods were employed, including mixed and structured questionnaire surveys, interviews with key informants, and document reviews. Data were gathered from 334 respondents living in communities adjacent to four mangrove social-ecological systems (SESs). The analysis focused on five variables: community use of mangrove resources, ecosystem services, threats to the ecosystem, management activities, and social-ecological relationships. To qualitatively assess the influence of social-ecological relationships and governance, a matrix was created based on anthropogenic activities identified by respondents and their perceptions of ecosystem services. The results indicated that while local people recognize the uses and ecosystem services of mangroves, they do not rely on them for their livelihoods. They also showed moderate to full awareness of management responsibilities and activities at each site. The most commonly identified threats were climate change, drought, and deforestation. Three types of social-ecological relationships were identified based on the characteristics of the communities, their economic activities, and their impacts on the mangroves: urban-industrial, rural-agricultural, and rural-agricultural/tourism. Finally, the research proposed a set of five recommendations and eight associated indicators to ensure that mangrove management framework become more inclusive and participatory, thereby contributing to the articulation of mangrove SES governance in the southeastern region of Cuba.

Emerging countries in Southeast Asia are facing considerable challenges in addressing rising motorisation and its negative impact on air quality, traffic, energy security, liveability, and greenhouse gas emissions. Indeed, even as initial policies to address these issues are being agreed and implemented, current trends are incompatible with sustainable development and long-term climate change targets. This paper presents a comparative analysis of the approach and status of sustainable, low-carbon transport policy in ASEAN countries and identifies differences and similarities, with the aim of helping assessment of feasibility of future policies and informing future studies on policy innovations and cross-country learning. The methodology is based on the taxonomy of policy components developed by Howlett and Cashore, and our data on comprehensive country studies for Indonesia, the Philippines, Thailand and Vietnam and interviews. We find that each country has a specific set of goals, objectives and targets that support sustainable transport, and, directly or indirectly, climate change mitigation. In terms of specific instruments and calibrations, which we analyse based on the Avoid-Shift-Improve approach, there are notable differences between the countries, for example in fuel economy policy.

Climate change and net zero are expected to have a significant impact on eco-nomic activity in developing countries, and thus, on the financial cash flow of organizations. In this paper, we propose a procedure for assessing the financial impact of climate change on organizational cash flow in developing countries. Our study contributes to the research on scenario-based climate change impact analysis. The applied research design is exploratory and mainly qualitative, constructing financial impact scenarios combined with narratives to determine the impact of climate change on individual cash flow line items. The narra-tives rationalize cash flow variations and enrich the estimates by adding expert knowledge, in the form of financial micro-stories and descriptions to the pro-posed procedure. We present a hypothetical citrus farming company in a de-veloping country to demonstrate the application of the proposed measurement procedure. The results obtained suggest that (1) the procedure is practical be-cause financial cash flows are known and widely used in financial analysis and because they can be implemented in a spreadsheet; that (2) the procedure pro-vides flexibility because it can be adapted to suit the specific needs of different companies, depending on a selected climate change scenario, the company’s exposure to climate change, its resilience and vulnerability; (3) that the prac-tice of thinking in terms of financial worst-case, base-case and best-case sce-narios, which reflect different levels of uncertainty, helps to model the finan-cial impacts of climate change and provides a forward-looking perspective on how much a company’s cash flow could change.

Recently, NOAA has included GNSS (Global Navigation Satellite System) Radio Occultation (RO) data as one of the crucial long-term observables for weather and climate applications. To include more GNSS RO data in the numerical weather prediction system, the NOAA Commercial Weather Data Pilot program (CWDP) started to explore the commercial RO data available on the market. After two rounds of pilot studies, the CDWP decided to award the first Indefinite Delivery Indefinite Quantity (IDIQ) contract to GeoOptics and Spire Incs. in 2020. This study examines the quality of Spire data products for weather and climate applications. Spire RO data are collected from commercial CubeSats through careful comparison with the data from Formosa Satellite Mission 7–Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), ERA-5, and high-quality radiosonde data. The results demonstrated that although with lower Signal-Noise-Ratio (SNR) in general, the pattern of the lowest penetration height for Spire is similar to those for COSMIC-2. The Spire and COSMIC-2 penetrate heights are between 0.6 and 0.8 km altitude at the tropical oceans. Although using different GNSS RO receivers, the precision of Spire STRASP receivers is of the same quality as those of COSMIC-2 Global Positioning System - GPS, GALILEO, and GLObal NAvigation Satellite System – GLONASS (TGRS) receivers. The retrieval accuracy from Spire is very compatible with those from COSMIC-2. We validated Spire temperature and water vapor profiles by comparing them with collocated radiosonde data. Generally, over the height region between 8 km and 16.5 km, the Spire temperature profiles match those from RS41 RAOB very well with temperature biases < 0.02 K. Over the height range from 17.8 to 26.4 km, the temperature differences are ~-0.034 K with RS41 RAOB being warmer. We also estimated the error covariance matrix for Spire, COSMIC-2, and KOMPSAT-5. Results showed that the COSMIC-2 estimated error covariance values are slightly more significant over the oceans at the mid-latitudes (45oN-30oN and 30oS-45oS), which may also be owing to COSMIC-2 SNR being lower at those latitudinal zones.

The assessment of ecosystem quality and the maintenance of optimal ecosystem function requires understanding vegetation area dynamics and its relationship with climate variables. This study aims to detect vegetation area changes over a downstream dam and to understand the influence of the dam as well as climatic variables on the region’s vegetation areas. The case study is located in an arid area with an average rainfall amount of 50 to 100 mm/year. An analysis of seasonal changes in vegetation areas was conducted using the Normalized Difference Vegetation Index (NDVI), and supervised image classification was used to evaluate changes in vegetation areas using Landsat imagery. Pearson correlation and multivariate linear regression were used to assess the response of local vegetation areas to both hydrologic changes due to dam construction and climate variability. The NDVI analysis reveals a considerable vegetation decline after the dam construction in the dry season. This is primarily associated with the impoundment of the seasonal water by the dam and the increase in cropland areas due to dam irrigation. A significantly stronger correlation between vegetation changes and precipitation and temperature variations is observed before the dam construction. Furthermore, multivariant linear regression was used to evaluate the variations of equivalent water thickness (EWT), climate data, and NDVI before and after the dam construction. The results suggest that 85 percent of the variability in the mean NDVI was driven by climate variables and EWT before the dam construction. On the other hand, it was found that only 42 percent of the variations in NDVI were driven by climate variables and EWT after the dam construction for both dry and wet seasons.

The increase in the production and entry of greenhouse gases into the earth's atmosphere has disturbed the balance of the environment. The signs of climate change (caused by global warming) are clearly visible and its effects are tangible. According to the United Nations, if the current trend continues, the global average temperature will increase by 3.2°C by the end of the century, which will have terrible consequences if it happens. This research aimed to investigate the effects of greenhouse gases and climate changes resulting from them on Hyrcanian forests. The Hyrcanian forests, as one of the oldest forest areas (remaining from the Paleogene era), were studied by telemetry from 2013 to 2021. The analysis of the images taken from the Landsat 8 satellite showed that during 9 years, the NDVI index decreased by 0.6 units and the average air temperature increased by 0.5°C. Although the average relative humidity has only increased by 2%, the average annual rainfall has recorded an increase of 25mm. The analysis of the statistics showed that the rains occur irregularly and are often torrential. Therefore, it is predicted that as the average temperature continues to increase, the NDVI index will further decrease, and as a result, the forest cover will become weaker and the soil will lose more water absorption power, and due to the increase in average rainfall. successive floods will occur. Therefore, soil erosion increases and the extinction and migration of plant and animal species increase significantly.

The impacts of climate change on shrimp aquaculture can vary widely and can have environmental and socioeconomic consequences. This study assessed the vulnerability to climate change impacts of selected small-scale shrimp farms of Penaeus vannamei and shrimpfish market vendors in Davao region, Philippines using a modified Fisheries Vulnerability Assessment Tool (FishVool). Shrimp farmers and vendors were interviewed using two separate semi-structured questionnaires. A total of thirty-nine (N=39) shrimp farmers and forty-eight (N=48) market vendors from various market areas within the region were interviewed. Data regarding exposure (E), sensitivity (S), and adaptive capacity (AC) were collected following the FishVool parameters with modifications. Results revealed that overall climate change vulnerability of the shrimp farmers was medium (M), where both exposure and adaptive capacity were low (L) while sensitivity was medium (M). In addition, the shrimp market vulnerability of the various sites examined revealed medium (M) scores for markets in Pantukan, Mabini, Tagum, Maco, Lupon, Davao City, and Digos. But high (H) vulnerability scores for the markets in Panabo and Sta Cruz. Overall, the study provided a better understanding about shrimp farming in relation to climate change impacts and vulnerability and provided information for future shrimp farm management, marketing and climate change adapation in the region.

An increase in air temperature leads to a significant transformation of the relief and landscapes of the Arctic. The rate of permafrost degradation, posing a profound change in the Arctic landscape, depends on air temperature, vegetation cover, type of soils, surface and ground waters. The existing international circumpolar programs dedicated to monitoring the temperature state of permafrost TSP (Thermal State Permafrost) and active layer thickness CALM (Circumpolar Active Layer Monitoring) are not sufficient for a comprehensive characterization of geocryological conditions. Yet, no standardized protocol exists for permafrost monitoring and related processes. Here, we propose a novel multi-parameter monitoring protocol and implement for two sites in the European part of the Russian Arctic: the Yary site along the coast of the Baydaratskaya Bay in the Kara Sea (68.9°N) within the continuous permafrost area and the Hanovey site in the Komi Re-public (67.3°N) within the discontinuous permafrost one. The protocol includes drilling boreholes, determining the composition and properties (vegetation cover and soils), snow cover measure-ment, geophysical imaging, active layer estimation and continuous ground temperature meas-urements. Ground temperature measured in 2014 – 2020 revealed that amplitudes of surface tem-perature fluctuation had no significant difference between the Yary and Hanovey sites, while that the mean annual temperatures between the areas had a considerable difference of greater than 3.0 °C. The period of the presence of the active layer changed with the year (e.g., ranging between 135 and 174 days in the Yary site), showing longer when the air temperatures in summer and the preceding winter were higher. Electrical resistivity tomography (ERT) allowed determining the permafrost distribution and active layer thicknesses. Thermometry results were consistent with our geophysical data. Analyzing the composition and properties of frozen soils helped better interpret the data of geophysical and temperature measurements. Our work by integrating the study of the soil properties, ground temperatures, and ERT allowed fully characterize these sites, suggesting that it helps better understand the thermal state in any other research sites in the European north of Russia. Our suggested monitoring protocol enables calibrating and verifying the numerical and analytical models of the heat transfer through the earth’s surface.

Climate change is one of the biggest challenges of our times. Its impact on human populations is not yet completely understood. Many studies have focused on single aspects with contradictory observations. However, climate change is a complex phoenomenon that cannot be adequately addressed from a single discipline's perspective. Hence, we propose a comprehensive conceptual framework on the relationships between climate change and human responses. This framework includes biological, psychological and behavioural aspects, and provides a multidisciplinary overview and critical information for focused interventions. The role of tipping points and regime shifts is explored, and a historical perspective is presented to describe the relationship between climate evolution and socio-cultural crisis. Vulnerability, resilience and adaptation are analyzed from an individual and a community point of view. Finally, emergent behaviours and mass effect phenomena are examined that account for mental maladjustment and conflicts.

Regional Climatic Comfort Index (CCI) deteriorated significantly due to the climate change and anthropogenic interference. Knowledge regarding the long-term temporal dynamics of CCI in typical regions should be strengthened. In this study, we analyze the temporal and spatial evolution of CCI from 1969 to 2018 in Guangdong Province, based on meteorological indicators, including heat, humidity, wind and cloth loading etc.. Additionally, the population exposure to climate unconformity was examined since 1990 with the help of population data. Our study found that: (1) the warming and humidifying of the summer climate served as the main driving force for the continuous deterioration of CCI, with the comfortable days decreased by 1.06d/10a and the extremely muggy days increased by 2.83d/10a; (2) spatially, the lowest climate comfortability concentrated in southwestern Guangdong with more than 50 uncomfortable days each year, while the climate comfortability in northeastern Guangdong tends to deteriorated whit higher rate, which can reach as high as 6d/10a; (3) in summer, the population exposure to uncomfortable climate highly centralized in the Pearl River Delta, Shantou, Jieyang, and the surrounding areas, and both area and population exposure showed increasing trends. Particularly, Shenzhen held the highest growth rate of population exposure with an increase rate of 2.94 million/10a; (4) although the discomfort distribution and deterioration rate vary across the province, the spatial heterogeneity of comfortability is diminishing in Guangdong Province. This study will provide scientific reference for regional urban planning, thermal environment improvement, local resident health risk analysis, and key strategy implementation, etc.

Zimbabwe has ambitious and laudable GHG mitigation targets. Compared to a coal based future emissions reductions by 33% per capita by 2030 are targeted, by implementing a set of identified nationally determined contributions (NDCs). If historical climate conditions continue, it can do this at low or negative cost. However, anticipated conditions may not continue, and of the planned emissions reductions in the NDCs, 88% would come from the expansion of hydropower, which is driven by rainfall. If climate change causes the extreme droughts witnessed in recent years to become more frequent, embarking on Zimbabwe’s NDC future (underpinned by its official system development plan) may be expensive and further cripple the economy. Note that the economy is already being strangled by constrained power supplies due to unusually dry conditions in the Zambezi river basin. If the NDC Future is pursued, but the climate becomes drier, proactive efforts might be made to overcome the power shortages. However, this may result in a rapid ramp up of greenhouse gas emissions if the country turns to coal to reinforce its system and increase its resilience against hydropower vulnerability and the costs that would otherwise ensue. If the country were to keep its NDC investments and supplement them with more aggressive deployment of clean adaptation options, strongly positive outcomes appear possible. Specifically, this would require increased deployment of renewable energy technologies, a restructured power market, and deep increases in energy efficiency investments. In so doing, the country would not only exceed its NDC targets, but also reduce costs in a manner that is climate resilient. This would not remove the country's need for hydropower and some level of coal reliance. However, it will introduce requirements to ensure flexibility in both hydropower and coal power production. For hydropower, power stations will need to provide and be recompensed for providing ‘balancing services’, that is, storing water and producing electricity when the wind is not blowing, nor sun shining. In order to ensure continuous output from mines, it may require intelligent stockpiling combined with dynamic forecasting. This would apply not only to production in Zimbabwe, but potentially for neighboring countries. Doing so would allow predictable mining activities, but allow electricity systems to absorb low cost, low carbon hydropower at high rainfall periods. To make the NDCs resilient via clean adaptation, strong institutional restructuring is required. However, internalizing those costs and moving to advanced market structures and business cases may strain the capacity of current institutions.

The Greenland ice sheet is a major contributor to sea level rise, adding an estimated 0.47 +/− 0.23 mm/yr to global mean sea level between 1991 and 2015 (van den Broeke et al., 2016). Making sea level rise projections for the future and understanding the processes controlling current observed rates of sea level rise are crucially dependent on understanding the present-day state of the ice sheet. Here, we provide an overview of the current state of the mass budget of Greenland based on satellite gravimetry and remote sensing observations of surface elevation change, ice sheet velocity and calving front positions. We also combine these essential climate variables with a regional climate model (RCM) output from an ice sheet model (ISM) to gain insight into poorly understood ice sheet dynamical and surface mass processes. On average from 1992 to 2017 the ice sheet in some locations has lost up −2.65 m/yr in elevation based on ESA Radar altimetry analysis. Calving fronts have retreated all around Greenland since the 1990s and in only two out of 28 study locations have they remained stable. The locations of grounding lines at 5 key glaciers with floating ice tongues have remained stable over the observation period. However a detailed case study at Petermann glacier with an ice fracture model shows the sensitivity of these floating ice shelves to future climate change. GRACE gravimetric mass balance (GMB) data allows us to tie together disparate lines of evidence showing that Greenland has lost about 265 +/− 25 Gt/yr of ice over the period 2002 to 2015. RCM and ISM simulations show that surface mass processes dominate the overall Greenland ice sheet mass budget except for areas of fast ice sheet flow but marked differences between models and between models and observations indicate that not all processes are captured accurately, indicating areas of greater uncertainty and directions of future research for future sea level rise projections.

Climate change represents a major threat to lotic freshwater ecosystems and their ability to support the provision of ecosystem services. England’s chalk streams are in a poor state of health, with significant concerns regarding their resilience, the ability to adapt, under a changing climate. This paper aims to quantify the effect of climate change on hydroecological response, the health of the river, for the River Nar, a SSSI in the south-east of England. To this end, we apply a coupled hydrological and hydroecological modelling framework, with the UKCP09 probabilistic climate projections serving as input (A1B high emissions scenario). Results show that, from 2021 to the end of the century, hydroecological response becomes more heterogeneous. Despite the limited range of the functional feeding groups on the baseline, the River Nar has been able to adapt to extreme events due to inter-annual variation. In the future, this variation is greatly reduced, raising real concerns over the resilience of the river ecosystem under climate change. These new insights into the health of the River Nar, and chalk streams more generally, highlights the necessity of further study and the real need to for changed river management practices.

Multi-cropping can solve the energy and GHG balance problems, but the emergence, development and productivity of such mixed crops are at risk due to increasing drought periods. For this reason, single maize crops with inter-row mellowing and weed-mulching practices were compared with faba bean, crimson and Persian clover, and alfalfa intercropped maize cultivations. Tests were performed at the Experimental Station of Vytautas Magnus University, Lithuania. Results showed that by the 30% higher energy inputs were calculated in technologies with intercropped crimson, Persian clover, and alfalfa than in monocropped maize. Single maize crops produced by the 23-40% higher biomass yields compare to clover and alfalfa intercropped maize because, due to the drought periods, intercrops weakly sprouted and developed. Lower harvests reduced the energy output by up to 38%, energy efficiency ratio - by up to 2.5 times and net energy - by up to 42%. All tested technologies were environmentally friendly and similar according to the CO2 equivalent. Long-term drought periods during vegetative season due to climate change make us think about the improvement of intercropping technologies. Sowing intercrops at the same time with maize could solve the problem of its germination but highlight the problem of abundant weed spread. Therefore, this takes us to another sphere of agrotechnologies - the effective non-chemical weed control.

Modern engineering faces challenges in ensuring technical standards for service, durability, and sustainability. Political, administrative, and budgetary factors, coupled with climate change, pose tasks to structural integrity, affecting industries and economies. Marine infrastructures represent a strategic asset of the country as it handles a large part of the economic exchanges. This article analyzes five essential factors that play a fundamental role in the performance analysis of coastal structures: Chloride-induced corrosion, degradation models, maintenance strategies, monitoring, and climate change. Starting with reinforcement corrosion, considered as the main cause of distress, particularly in coastal zones for the long-term behavior of structures. Additional pressure from the influences of climate change is becoming evident and extreme, leading to reduction in capacity. To guarantee the lifespan, degradation models contribute by estimating the long-term performance of the asset as a strategic piece to the development of effective maintenance solutions. Additionally, quantifying the condition of the structure from monitoring data, plays a crucial part that provides information on the current situation of the structure. Finally, this review summarizes the challenges associated with the maintenance of aging marine structures considering aspects such as corrosion, monitoring, and the future challenges this area will face due to climate change.

In the field of climate change adaptation, the future matters. Amongst others, river futures justify the way adaptation projects materialize in rivers. In this paper, we challenge the ways in which dominant paradigms and expert claims monopolise the truth concerning policies and designs of river futures, side-lining and delegitimizing alternative river futures. Currently, limited work is done to critically reflect on the power of river futures in the context of climate change adaptation. We conceptualized the power of river futures through river imaginaries: collectively performed and publicly envisioned reproductions of riverine socionatures, mobilized through truth claims of social life and social order. Through the Border Meuse project case study, a climate change adaptation project in a stretch of the river Meuse in the south of the Netherlands and a proclaimed success story of climate adaptation in Dutch water management, we elucidated how three river imaginaries: a modern river imaginary, a market-driven imaginary and an eco-centric river imaginary, merged and materialized as an eco-modern river imaginary. Importantly, not only the river futures merged, also their aligned truth regimes merged. To this end, we argue that George Orwell’s famous quote “Who controls the past, controls the future: who controls the present, controls the past” can be extended to ‘Who controls the future, controls how we see and act in the present, and how we rediscover the past’.

Context and aim: Environmental awareness is the first step to climate change risk perceptions and environmental behaviour. However, this pathway is not always possible within different population segments and trust contexts. This study explores the conditional effect of trust on environmental behaviour in the Zed Generation in Albania. The consideration of the Zed generation due to two opposing traits, such as social courage and anti-social, make them an interesting topic to understand, especially for their importance in online communities. Method: The youth engagement environmental programme and the climate change risk perceptions framework are adopted in an input-output design. Environmental awareness (input) is the initiating factor, and climate change risk perception and community engagement as mediators of environmental behaviour(output). Individual and institutional trust is the moderating factor that inhibits/enhances engagement and environmental behaviour. Results: The moderation-mediation show that climate change risk perceptions did not mediate environmental behaviour. Environmental awareness directly affects it. However, low institutional trust inhibits the general trust that, in turn, lowers the impact of awareness in climate change perceptions and community engagement toward environmental protection. Practical recommendation: The application of the input-output model shows that the pathway that directly affects environmental behaviour among Zed Generation in Albania is not Climate change risk perception. In low-trust contexts, positive environmental behaviour can be generated through community engagement. Policymakers and educational programmes in low-middle-income countries might consider community engagement to mitigate trust issues and effectively deal with environmental problems with a global segment such as the Zed generation.

Scenario analysis is a widely employed method for addressing uncertainties when assessing the physical and socio-economic impacts if climate change. Global scenarios have been extensively used in this context. However, these scenarios are in most cases not suitable for supporting local analyses. On the other hand, locally developed scenarios may lack the global context, thus having limited comparability with or transferability to other locations. The Shared Socioeconomic Pathways, which have been primarily developed for climate impact research, provide the possibility to extend the existing global narratives and adapt them to local characteristics in order to develop locally relevant scenarios. Here, we propose a methodological framework for producing harmonized scenarios across different case studies. This framework was developed in the EVOKED project and combines elements of top-down and bottom-up approaches to develop local scenarios for five regions in northern Europe. We employ the SSP as boundary conditions and, in cooperation with stakeholders from these five regions, develop local scenarios for a range of SSP. The developed sets of scenarios are consistently informed by global developments and are therefore comparable with other downscaled scenarios developed in different regions. At the same time, they have been based on local participatory processes, thus being locally credible and relevant to the needs of stakeholders. The local scenarios constitute a climate service per se as they can raise stakeholder awareness of the processes that will drive risk, exposure, and adaptive capacity in the future and inform discussions on mitigation strategies and adaptation pathways.

Asphalt pavement temperature has several applications, including pavement structural design and evaluation, asphalt mixture design, asphalt binder grade determination and material aging characterization. However, available asphalt pavement temperature prediction models were mostly developed for temperate climatic conditions, outside of the tropics. Before such models are adopted for use in a tropical climate, their applicability must be evaluated. This study evaluated five empirical asphalt pavement temperature prediction models developed by Lukanen et al. [1], Park et al. [2], Diefenderfer et al. [3], Taamneh [4] all in the United States and Asefzadeh et al. [5] in Canada to ascertain their prediction accuracy in tropical climate, using Ghana as a case study. In-situ asphalt pavement temperature data were measured at two sites for eight months: Kumasi and Tamale in the Forest and Savannah climatic zones, respectively. The measured pavement temperature data were statistically compared with predicted temperatures, and it was found that the Park et al. [2] model provided a more accurate pavement temperature prediction in both climatic zones. The other models either over-predicted or under-predicted asphalt pavement temperature with significant error margins. However, there is a need to improve the prediction accuracy of the Park et al. [2] model or a local model developed.

The main purpose of this article is to identify key areas of research on climate change in the context of the SDGs, focusing on the potential development impacts on Bolivia and Paraguay. Application of the Delphi technique with the involvement of a panel of experts allowed the consolidation of different perspectives and knowledge on climate change, focusing on those that experts considered to have the greatest potential impact on the regions. The results of this study constitute a valuable guide for decision-makers and funding bodies, highlighting research areas that could have a significant impact at the national and regional levels, as well as for researchers, identifying specific research areas crucial for regional development and climate change mitigation.

Aflatoxins (AFs) contamination of cereals is considered one of the greatest food safety concerns worldwide. Occurrence of AFs in maize, wheat, rice and sorghum is highly prevalent with each commodity accounting for more than 10% of world’s AF exposure. Their occurrence as food contaminants is also associated with huge economic losses. AFs are highly stable compounds that cannot be eliminated by regular processing of grains. Hence, prevention of AFs in food and feed is now considered more important than the subsequent interventions to mitigate the deleterious health effects of AFs in human and animals. However, the development of an effective preventive strategy hinges on a clear understanding of the underlying factors influencing AFs production. Therefore, the present review aims to highlight the most significant factors influencing AFs contamination of cereals at pre-and post-harvest stages. This is crucial for effective monitoring of critical control points and optimisation of preventive strategies in food and feed supply chains. Several intrinsic and extrinsic factors have been reported of which nutritional composition, environmental factors (temperature, water activity and relative humidity) and climate change have been identified as primary factors, while pH of the substrate, carbon dioxide (CO2) levels in the gaseous environment, and agronomic and socioeconomic status are the main secondary factors promoting AFs biosynthesis in cereals. Additionally, an overview of global occurrence of AFs in cereals, with their health impacts and various preventive measures have also been highlighted.

In Nigeria, desertification has become one of the most pronounced ecological disasters, with the impacts mostly affecting eleven frontline States. This has been attributed to a range of both nat-ural and man-made factors. This study applied a remote sensing-based change detection and indicator analysis to explore land use/land cover changes and detect major conversions from ecologically active land covers to sand dunes. Results indicate that areas covered by sand dunes (a major indicator of desertification) have doubled over the 25 years under consideration (1990 to 2015). Although about 0.71 km2 of dunes have been converted to vegetation, indicative of the success of various international, national, local, and individual afforestation efforts, conversely about 10.1 km2 of vegetation were converted to sand dunes, implying around 14 times more de-forestation compared to afforestation. Juxtaposing the progression of sand dune with climate records of the study area and examining the relationship between indicators of climate change and desertification suggested a mismatch between both processes as increasing rainfall and lower temperatures observed in 1994, 2005, 2012, and 2014 did not translated into positive feedbacks for desertification in the study area. On average, our results reveal that sand dune is progressing at a mean annual rate of about 15.2 km2 in the study area. Based on this study’s land cover change, trend and conversion assessment, visual reconciliation of climate records with land cover data, statistical analysis, observations from ground-truthing, as well as previous literature, it can be inferred that desertification in Nigeria is less a function of climate change, but more a product of human activities driven by poverty, population growth and failed government policies. Further projections by this study also reveal a high probability of more farmlands being converted to sand dunes by the year 2030 and 2045 if current practices prevail.

The province of Jaén (Andalusia, Spain), despite being declared the European territory with the largest number of defensive constructions (castles and fortifications), has few conservation plans, with many remains included on the Red List of Spanish Heritage lying abandoned. This presents a problem for the conservation of the landscape and the optimal use of the province’s tourism potential. Through the study case of Magaña hamlet two actions are proposed to alleviate this situation: The creation of an archaeological and environmental risk chart with which to answer such questions as “How have climate change, anthropic alterations and environmental charac-teristics affected the state of conservation of certain heritage sites?” and to put forward proposals for improving their protection using as a basis digital and technological tools, such as remote sensing (SAR), taking advantage of data from the Sentinel 2A and 2B satellites, HBIM, RPAS and GIS. To foster the promotion of smart tourism by digitalising and virtualising tourist routes and archaeological remains by building a Smart Tourism App for mobile devices. Finally, public administrations will be apprised of the need to implement a conservation policy for cultural as-sets and their surroundings in a simple, quick and cost-effective manner.

Multicropping can solve the energy and GHG balance problems, but the emergence, development and productivity of such mixed crops are at risk due to uneven distribution of precipitation. For this reason, investigations were performed at the Experimental Station of Vytautas Magnus University, Lithuania. Single maize crop was compared with Crimson/red clover, Persian clover, and alfalfa intercropped maize cultivations. Results showed that under arid conditions, the intercrops biomass was about 4 times less than under humid. Humid conditions were less suitable for maize and when growing with intercrops they produced about 3-5 t ha-1 less dried biomass, and when growing sole - about 6 t ha-1 less biomass than in arid conditions. Due to the higher yield of maize biomass in arid season, better energy indicators of the crop were obtained in arid conditions than in humid. The difference between net energy was about 122-123 MJ ha-1 in all treatments, except for the maize crop with intercropped alfalfa, where the difference was 62 MJ ha-1. All tested technologies were environmentally friendly, CO2 equivalent varied between treatments from 804 to 884 kg ha-1. Uneven distribution of precipitation during vegetative season makes us think about the improvement of intercropping technologies. Sowing intercrops at the same time with maize could improve its germination but increase the problem of weed spread.

Mosquito-borne diseases (MBDs) are a group of illnesses transmitted by mosquitoes and can be caused by bacteria, viruses, or parasites. These diseases represent a significant global burden of infectious diseases, including morbidity and mortality. This systematic review delves into the multifaceted factors contributing to the spread of mosquito-borne diseases (MBDs) in the Middle East and North Africa (MENA) region. Following PRISMA guidelines, a thorough analysis of peer-reviewed articles from May 1990 to Jan 2023 was conducted, highlighting the interplay of population, environmental, disease, and mosquito factors in disease transmission and prevalence. The review incorporated 31 studies that revealed a complex relationship between various risk factors and the presence of MBDs. Significant associations were observed with age, certain occupations, environmental conditions such as rainfall and temperature, sanitation practices, specific pathogen variants, clinical symptoms, and Aedes aegypti mosquitoes. Conversely, gender, socioeconomic status, educational status, and certain sanitation-related factors showed inconsistent association with the spread of MBDs. The review underscores the need for targeted interventions, including vector control, improved sanitation, and educational campaigns to mitigate the spread of MBDs in the MENA region. This review could guide research studies to address data gaps and assist in developing effective surveillance programs in the MENA region. This work emphasizes the need for region-specific public health strategies and further research to understand and curb the burden of these diseases effectively.

Tree decline resulting from climate change results in physiological weaknesses, attack by harmful pests and pathogen, and threatens forest ecosystem stability. In the work described here, the effects of drought on wood density, tree ring width, and variations in vessel morphology were investigated in Persian oak (Quercus brantii) in the forests of the Zagros Mountains, Ilam province, western Iran. Radial discs were cut from trunks of declined and healthy trees and wood blocks cut radially from the sapwood, heartwood, and juvenile core. Observations were made on transverse sections from the blocks using microscopy. In trees with decline symptoms, wood density was greater than the healthy trees. Furthermore, declining trees had the narrowest ring width, reduced vessel diameter, vessel area, and highest number of vessels and tylose in pith towards bark. It was concluded that changes in anatomical features are associated with the weakening of the trees and are components in declining tree health.

Solar radiation is closely related to the energy buildings consume for cooling, heating, and lighting purposes. Glazing is the only material of the building envelope that transmits solar radiation and needs to be appropriately designed to reduce energy cㅈonsumption. Currently, smart glass technology is being actively investigated and developed for effective solar radiation control. Among the various types of smart glass, electrochromic glazing is one of the most promising technologies, as it can adjust transmittance on its own, has a wider transmittance range in both the clear and darkened states, and consumes less electricity. Considering the importance of solar radiation adjustment in electrochromic glazing technology, this study attempted to develop an optimal control method for electrochromic glazing. Toward this goal, the solar radiation incident on vertical surfaces and outdoor temperature conditions were controlled in three regions with different climatic characteristics, and the annual cooling, heating, and lighting loads, discomfort glare, and interior illumination were analyzed. This approach enabled the optimal conditions with respect to visual comfort to be determined. Subsequently, the EDPI (Energy and daylight performance index) was used to optimize control conditions for each region, thereby producing integrated evaluations from results with different units and properties. The proposed control method will be utilized to develop a control algorithm and a control system to reduce building energy consumption.

Greenhouse Gases (GHG) emissions from dairy farms are significant contributors to global warming. However much of the published work on GHG reduction is focused on either Methane (CH4) or Nitrous Oxide (N2O), with few, if any, considering the interactions that changes to farm systems can have on both gases. This paper takes the raw data from a year of activity on a 300 cow commercial dairy farm in Northern Ireland to more accurately quantify the GHG sources by use of a simple predictive model based on IPCC methodology. Differing herd management policies are examined together with the impact of integrating Anaerobic Digestion (AD) into each farm system. Whilst significant success can be predicted in capturing CH4 and Carbon Dioxide (CO2) as biogas and preventing N2O emissions, gains made can be lost in a subsequent process negating some or all of the advantage. The process of extracting value from the captured resource is discussed in the light of current farm parameters together with indications of other potential revenue streams. However, this study has concluded that despite the significant potential for GHG reduction, there is little incentive for widespread adoption of manure based farm scale AD in the UK at this time.

This paper delves into the essential role of local communities in mitigating climate change in the post-pandemic landscape, with a specific focus on Barangay Acmac, Iligan City, Philippines. Employing a qualitative research approach, the study integrates in-depth literature reviews, informal interviews with participants (B-Part 1 to B-Part 20), meticulous observations, and thematic analysis. The research has uncovered crucial insights, including variations in community climate change awareness that emphasize the necessity of comprehensive education and awareness campaigns. It highlights the significance of community-driven initiatives, adaptation, and resilience as key elements in addressing climate change. Collaborative efforts between local government officials and the community are showcased as effective instruments of climate change mitigation, yet challenges persist, including addressing the perceived powerlessness of some community members. The methodology, participants, and theoretical framework offer a robust foundation for exploring community responses to climate change. Drawing from a diverse theoretical framework, this study presents a comprehensive understanding of the climate change and pandemic intersection. The findings firmly establish that local communities are pivotal players in the global endeavor to mitigate climate change, underscoring the need for collective action, extensive education, and shared responsibility. The post-pandemic era presents a unique opportunity for local communities, policymakers, barangay officials, and residents to champion climate education, foster community-driven initiatives, and empower individuals to enact change at the grassroots level. The collaborative spirit observed in Barangay Acmac in 2022 serves as a model for communities worldwide, offering a blueprint for addressing similar challenges. Overall, this paper concludes with a resounding call to action, advocating for the recognition of local communities as the driving force in climate change mitigation, stressing that the power to combat climate change resides within these communities. The time for action is now, and local communities are the catalysts of this essential mission.

To estimate The potential inventory of natural gas hydrates in the Levant Basin we correlated the gas hydrate stability zone (GHSZ), modeled with locally estimated thermodynamic parameters, with seismic indicators of gas. Compilation of oceanographic measurements define the deep-water temperature and salinity to 13.8°C and 38.8‰ respectively, predicting the top GHSZ at a water depth of 1250±5 m. Assuming beneath the seafloor a hydrostatic pore-pressure, the water body salinity, and geothermal gradients ranging between 20 to 28.5°C/km, yields a useful first-order base-GHSZ approximation. Our model predicts that the entire northwestern half of the Levant Basin lies within the GHSZ, with a median thickness of ~150 m. High amplitude seismic reflectivity (HASR) imaged on an extensive 3D seismic dataset, consistently correlates with verified active seafloor gas seepage and is pervasively distributed across the deep-sea fan of the Nile within the Levant. Two main trends observed for the distribution of HASR are suggested to represent: (1) shallow gas and possibly hydrates, within buried channel-lobe systems 25 to 100 m beneath the seafloor; and (2) a regionally discontinuous bottom simulating reflection (BSR) broadly matching the modeled base GHSZ. We therefore estimate the potential methane hydrates reserve within the Levant Basin at ~4 Tcf.

Global climate change primarily affects the spatiotemporal variation of physical quantities such as relative humidity, atmospheric pressure, ambient temperature, and notably, precipitation levels. Accurate precipitation predictions remain elusive, necessitating tools for detailed spatiotemporal analysis to better understand climate impacts on the environment, agriculture, and society. This study compares three learning models: ARIMA (Autoregressive Integrated Moving Average), RF-R (Random Forest Regression), and LSTM-NN (Long Short-Term Memory Neural Network), utilizing monthly precipitation data (in millimeters) from 757 locations in Boyacá, Colombia. The LSTM-NN model outperformed others, precisely replicating precipitation observations in both training and testing datasets, significantly reducing the root mean square error (RMSE) with average monthly deviations of approximately 19 mm per location. Evaluation metrics (RMSE, MAE, R², MSE) underscore the LSTM model’s robustness and accuracy in capturing precipitation patterns. Consequently, the LSTM model was chosen to predict precipitation over a 16-month period starting from August 2023, offering a reliable tool for future meteorological forecasting and planning in the region.

The Vu Gia - Thu Bon River Basin (VG-TB) is confronting numerous challenges related to water security (WS), particularly in the face of the impacts of climate change. These challenges manifest in salinity intrusion, altered rainfall patterns, and reduced water supply in downstream areas. To assess the current state of water security in the basin, the study employed statistical analysis methods, Process Analysis Method (PAM), SMART, and Analytic Hierarchy Process (AHP) to develop a comprehensive Assessment Framework for Water Security (AFWS) in the VG-TB. The AFWS encompasses five key dimensions, 17 indicators, and 28 variables, aligning with the UN-Water definition of water security and addressing the Sustainable Development Goal 6 (SDG6) criteria for global water sustainability. It also adheres to the Asian Development Bank's (ADB) approach to water security assessment as outlined in the Asian Water Development Outlook (AWDO) reports. This allows for the computation of a comprehensive Water Security Index (WSI) for specific regions, serving as a foundation for decision-making and policy formulation aimed at enhancing water security in the context of climate change and facilitating sustainable basin development in the future.

Purpose: The study investigates soil pores' impact on carbon dynamics and sequestration processes, examining their physical and chemical characteristics and their mechanisms for carbon sequestration.Research Method: Existing literature and research on soil pores, carbon dynamics, and carbon sequestration are analyzed. The interrelationships between soil pore structure, water movement, microbial activity, root penetration, carbon input, soil aggregation, and gas exchange are examined. Traditional techniques and advanced imaging methods are used to quantify and characterize soil pores.Findings: Soil pores play a critical role in facilitating carbon sequestration through various mechanisms. They affect water movement, microbial activity, root penetration, carbon input, soil aggregation, and gas exchange. Understanding these relationships is crucial for sustainable soil management.Research Limitations: This study relies on existing literature and research, which may have limitations and uncertainties. Further research is needed to address these gaps and enhance understanding.Originality Value: This research enhances the existing knowledge by comprehensively examining the significance of soil pores in carbon dynamics and sequestration. It incorporates both traditional and advanced methods, providing insights for soil management and contributing to climate change mitigation efforts.

Insecticide testing facilities that evaluate a variety of vector control products may generate large amount of hazardous wastes from routine operations. These wastes originate from degraded technical grade materials, sprayed substrates, redundant stock or working insecticidal solutions. The washing of Long-Lasting Insecticidal Nets (LLINs) during preparation for laboratory and experimental hut trials also contribute to waste water with insecticide content. Human and environmental exposure to insecticidal waste can occur during transport, categorization, storage and disposal in resulting in environmental pollution and potential health effects. Various national and international guidelines have been devised for safe disposal and should be strictly followed to avoid adverse effects on humans or environment. The current paper describes a case study from insecticide test facility in north-eastern Tanzania in management of insecticidal waste.

Urban ecology is a factor that significantly affects the urban landscape. Proper management and sustainable planning of ecosystems in cities can help urban landscapes to increase biodiversity and contribute to the efficient use of natural resources. In this framework, the integration of green spaces and ecosystem services can improve the quality of urban landscapes by increasing the health and resilience of urban ecosystems. This paper, which examines the effects of ecological factors on urban landscape in Antalya-Muratpaşa, presents a detailed analysis using various data sets. Within the scope of the research, the number of vehicles, carbon emissions by years, the ratio of green areas to population, CORINE data and land surface temperatures were analyzed. In addition, the change in land use from 1990 to 2018 and the land surface temperature forecast for 2040 and 2041 shed light on the evolutionary processes in the city. In an effort to understand the ecological status of Antalya-Muratpaşa, the paper highlights the potential impacts on the sustainability of the urban landscape. In particular, predicting the possible impacts of future land use on the urban landscape with population growth offers a strategic approach in planning processes. This study can be an important resource for urban planners, researchers and local governments because the data in the Antalya-Muratpaşa case provides a comprehensive overview that can guide those who want to consider sustainability and environmental factors in urban landscape planning. In line with this perspective, it is recommended to encourage green roof and green facade practices, rainwater harvesting, gray water recycling, etc. in new constructions.

This paper explores the emergence of Sustainability-Linked Bonds (SLBs) as an innovative instrument to finance sustainability objectives. SLBs have emerged as a transformative financial instrument, establishing an explicit link between cost of funding and sustainability objectives. SLBs were first launched in 2019 and represent 7% of labelled bonds, still dominated by the more established green bonds. Issuance of SLBs now exceeds $250 billion. Following initial enthusiasm, they are now facing criticism. In the context of the growth of sustainable finance and concerns of greenwashing, this paper investigates ways to enhance the design of SLBs. Drawing on literature and expert interviews, the findings highlight the strong potential of SLBs to contribute to sustainability financing, especially in hard-to-abate sectors. The paper identifies the key positive attributes of SLBs and their limitations in five areas: key performance indicators’ (KPI) selection, sustainability performance targets’ (SPT) calibration, bond characteristics, reporting practices, and resource requirements. Recommendations to financial intermediaries, issuers and policy makers include defining standardized KPIs based on a materiality assessment, requesting SPTs to be supported by science and in line with an issuer’s core strategy, tailored step-up mechanisms and avoidance of call loopholes, and stricter reporting. SLBs represent an opportunity to add rigor to sustainable finance and better price externalities, where material topics have an explicit impact on cost of funding and credit ratings.

This paper focuses on environmental policies for mitigating the impacts of climate change on the Taj Mahal, an iconic structure built on the banks of the Yamuna River from 1632 to 1653 with a blend of Persian and Indian architectural styles. The Taj Mahal is threatened by damage caused by climate change, including air pollution resulting in acid rain and floods that lead to erosion and discoloration of the main marble material of the Taj Mahal. This study employs a Systematic Literature Review (SLR) of peer-reviewed journal articles with a primary focus on environmental policy, the impacts of climate change, and the preventive measures undertaken by the Indian government. Based on the analysis of 270 papers, it is concluded that out of the total, 30 papers specifically address objectives relevant to this research. The study period spans from 2014 to 2024. The research findings reveal that air pollution has a significantly adverse impact on the Taj Mahal. Furthermore, nine policies are generally identified from the journal literature review aimed at preserving and protecting the Taj Mahal from the negative effects caused by air pollution.

We investigated the response of leaf photosynthetic capacity to climate warming and its variation among provenances of Larix gmelinii (Dahurian larch). Seedlings of 11 L. gmelinii provenances were transplanted into two common gardens with different climate conditions (control and warming climate). We measured the leaf photosynthetic capacity and explored its influencing factors. The warming treatment significantly increased the maximum net photosynthetic rate (Pmax-a), photosynthetic nitrogen use efficiency (PNUE), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), triose phosphate utilization rate (TPU), mesophyll conductance (gm), leaf nitrogen content (Narea), and chlorophyll content (Chlm). The Pmax-a was significantly positively associated with Vcmax, Jmax, TPU, gm, and Narea, and the slope of the correlations between Pmax-a and Vcmax, Jmax, and TPU was steeper in the warming treatment. The responses of Pmax-a, PNUE, Vcmax, Jmax, TPU, Narea, and Chlm to warming differed among provenances. The effects of warming on Pmax-a, Vcmax, Jmax, and TPU increased and then decreased as the aridity index of the original site increased. Overall, the warming treatment improved the photosynthetic capacity of L. gmelinii, but the extent of the improvement varied among provenances. These findings provide insights into the mechanisms underlying the responses of L. gmelinii to climate warming.

Polar stratospheric clouds (PSCs) form in polar regions typically between 15 and 25 km, when the local temperature is sufficiently low. PSCs play an important role in the ozone chemistry and the dehydration and denitrification of the stratosphere. Lidars with a depolarization channel may be used to detect and classify different classes of PSCs. The main PSC classes are water ice, nitric acid trihydrate (NAT) and supercooled ternary solutions (STS), the latter being liquid droplets consisting of water, nitric acid and sulphuric acid. PSCs have been observed at the lidar observatory at Concordia Station from 2014 on. The harsh environmental conditions at Concordia during winter render successful lidar operation difficult. In order to facilitate the operation of the observatory several measures have been put in place to achieve an almost complete remote control of the system. PSC occurrence is strongly correlated with local temperatures and is affected by dynamics, as the PSC coverage during the observation season shows.

The Earth's fresh water resources predominantly is groundwater that is pumped out due to rapid urbanization and aggravated by climate change. Groundwater modeling is a crucial tool for understanding aquifer systems, employing 1D, 2D, and 3D numerical models with distinct applications. One-dimensional models focus on vertical dynamics, examining aquifer properties and simulating vertical contaminant transport. Two-dimensional models extend to regional scales, considering horizontal variations and assessing groundwater-surface water interactions, making them valuable for watershed-scale studies. Three-dimensional models provide a comprehensive representation of hydrogeological systems, capturing intricate flow patterns and aiding site-specific assessments. Comparative analysis reveals model strengths and limitations, emphasizing the importance of calibration for reliable results. Case studies showcase practical applications, such as 1D models in flooding analysis and 2D models for simulating debris flows. Three-dimensional modeling proves essential for understanding complex river-aquifer exchange fluxes. Future directions call for a global groundwater platform to address data variability and technical challenges. Despite substantial investments required, the anticipated returns in scientific advancements, societal benefits, and economic gains are expected to outweigh the initial costs. This review aims in highlighting the significance of advancing all three-dimension groundwater modeling for sustainable water resource management and environmental protection.

In 2021, the American Association of Colleges of Nursing (AACN) added “the impact of climate change on environmental and population health” into The Essentials: Core Competencies for Professional Nursing Education. Presently, little guidance exists for nursing faculty new to climate education. The year prior, the Nurses Climate Challenge (NCC) - a campaign to educate 50,000 health professionals about health impacts of climate change - launched the School of Nursing Commitment through a series of focus groups and collaborative content development. With an aim of increasing access to knowledge and tools to support education about the health impacts of climate change, the NCC Commitment partners with nursing schools and provides a community of practice. Partner schools use NCC resources in courses and report the number of students educated. Within three years, 61 nursing schools in 30 states joined the Commitment. Participants included academic health centers, research institutions, multi-state schools, and small private colleges, and programs ranged from AD to PhD. Faculty 1) integrated resources into didactic and clinical settings such as population or organ-system content, leadership, and policy and 2) used resources to support assignments. In four years, faculty reported educating over 37,700 students using NCC resources in 439 educational sessions. The Commitment may be valuable for faculty fulfilling AACN Essentials by bringing climate change to the classroom, community, and bedside. Furthermore, the Commitment may be a replicable model for health professional education and inspiring action on climate change.

In this study, we employ the GARCH-MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to explore the predictability of commodity return volatility in relation to US climate policy uncertainty (CPU). Our analysis utilizes the 20-day annualized realized commodity volatility returns of nine global commodities (Aluminium, Cocoa, Coffee, Copper, Cotton, Rice, Soybean, Sugar, and Wheat) to construct the GARCH-MIDAS model, with Climate Policy Uncertainty (CPU) serving as the predictive variable. The outcomes of our investigation reveal a consistently positive and statistically significant relationship between CPU and the selected commodities. This implies that CPU effectively serves as a robust predictor of volatility in commodity returns. The implications drawn from our results suggest that climate change policies play a pivotal role in influencing economic activities within the commodity market. This underscores the substantial impact of climate change considerations on investment decisions and further emphasizes the integral role of climate change in shaping economic choices.

This paper aims to explore how climate change affects electricity generation (fossil-fueled power plants, hydroelectric stations, wind systems and photovoltaics) and energy demand in residential buildings in Greece for the period up to 2050. In both cases RCP scenarios results are considered in the appropriate spatial and temporal dimension. Energy supply technologies were examined through statistical regression models and/or mathematical equations correlating climatic parameters with energy productivity. With respect to energy demand, bottom-up models were developed that integrate behavioral and policy aspects. The analysis showed that climate change is expected to mainly affect electricity generation from hydro and thermal power plants, while the impacts on solar and wind energy are significantly lower. The range of impacts on hydro potential and electricity generation depends on the geographical location of the power plants and shows significant uncertainty due to the corresponding uncertainty in climate models estimates regarding precipitation and runoff changes while showing significant geographical variations. With respect to energy demand, climate change is expected to affect energy consumption, but the expected range of effects depends on both the implementation and the characteristics (deep vs. shallow renovation) of measures for upgrading the thermal performance of the building stock and the intensity of climate change.

Climate change is one of the most concerning global issues and has the potential to influence every aspect of human life. Like different components of society, it can impose significant adverse impacts on pavement infrastructure. Although several research efforts have focused on studying the effects of climate change on natural and built systems, its impact on pavement performance has not been studied extensively. Due to the weather effect the lifetime of pavement is getting lower on the other hand maintenance cost is getting higher and higher. The data has been collected from LTTP website and as a site The State of Texas has been considered. The primary objective of this project is to quantify the effect of temperature as well as precipitation changes on pavement response and performance prediction using the ARIMA model and develop a logistic regression model to analyze the forecast data.

The Earth's water resources, totaling 1.386 billion cubic kilometers, predominantly consist of saltwater in oceans. Groundwater, plays a pivotal role, with 99% of usable freshwater supporting 1.5–3 billion people as drinking water source and 60–70% for irrigation. Climate change, with temperature increase and altered precipitation patterns, directly impacts groundwater systems, affecting recharge, discharge, and temperature. Hydrological models are crucial for assessing climate change effects on groundwater, aiding in management decisions. Advanced hydrological models, incorporating data assimilation and improved process representation, contribute to understanding complex systems. Recent studies, employ numerical models to assess climate change impacts on groundwater recharge that could help in management of Groundwater. Groundwater vulnerability assessments vary with the spatial and temporal considerations, as well as assumptions in modelling groundwater susceptibility. The review assesses the vulnerability of groundwater to climate change and stresses the importance of accurate assessments for sustainable water resource management. It highlights challenges in assumptions related to soil and aquifer properties, multiple stressors, adaptive capacity, topography, aquifer properties, and groundwater contamination processes and gradual sea level rise scenarios and realistic representations of the region of study. The advancements in hydrological modelling, including the integration of uncertainty quantification and remote sensing data, artificial intelligence, could assist in the efforts to improve models for assessing the impacts of climate change on hydrological.

The impact of climate change on water resources is a global issue with significant regional implications. The Ghba subbasin has experienced a higher socioeconomic change. In this paper, we assess the potential impact of climate change and human activity on water supply and demand in the Ghba subbasin of Ethiopia. We then evaluate the effectiveness of regional adaptation strategies for water supply management under these conditions. To do this, we use the statistical downscaling model (SDSM) and the water assessment and planning tool (WEAP) to simulate and analyse future water conditions. After running the model through a calibration and validation process, minimum (Tmin) and maximum (Tmax) temperatures, water demand and unmet water demand were projected for 2100 horizon, using different climate change scenarios. The results showed that the model's performance, calibration, and validation were all satisfactory. The analysis showed that, under A2 and B2 emission scenarios of the Intergovernmental Panel on Climate Change (IPCC), the mean precipitation will increase by 31% and 26%, respectively. The projected mean Tmax and Tmin will be warmer than the baseline period, with Tmax increasing by 1.5°C (A2) and 1.3°C (B2), and Tmin by 1.7°C (A2) and 1.5°C (B2) by 2100. The results also illustrate that in all scenarios, water consumption would rise and that this need will not be satisfied, and the pressure on water resources will intensify, resulting in a water shortage. The findings show that future water demand under the influence of climate change is projected to exceed 210 million cubic meters (MCM) by 2100. The findings show that while the evaluations of the recommended adaption techniques are effective, they are not enough to guarantee the Ghba subbasin's water sustainability.

Climate change not only affects weather conditions, patterns, and the frequency and severity of extreme weather events but also changes how governments spend money. Agriculture is an important sector of the European Union (EU), and it is projected to decrease by 16% by 2050, therefore a third of the EU budget has been spent on agricultural funding, adaptation, and climate action. The effect of climate change on agriculture is mixed and dependent on the country and its location. The southern EU is adversely affected while the northern EU is positively affected by the changes in weather patterns. The main goal of this paper is to gain insight regarding the effect that climate change has on public spending in relation to the agricultural sector of the EU, by using the pooled OLS and GMM methods. The study concluded that agriculture has a significant impact on public spending in the southern countries of the EU, where it represents a significant portion of the GDP. Inflation influences public spending in the whole EU region, the northern and southern countries of the EU. Rain has a moderately significant impact on public spending in the whole EU region. It is advised that governments maintain a controllable level of inflation using fiscal and monetary policy that will implicitly control public spending.

Tropical forest and savanna biomes are pivotal in the functioning of the Earth system. Tropical forests are one of the largest terrestrial biosphere carbon pools, whereas savannas exchange carbon between the biosphere and atmosphere via frequent and extensive landscape fires. Both are biodiverse and under increasing threat due to land clearing and anthropogenic climate change. Reliable mapping of tropical forest and savanna is essential to provide understanding of how anthropogenic impacts are affecting the extent of these biomes. Using Google Maps satellite imagery, we manually classified 24,239 random points as forest, savanna, or anthropogenic landscapes within the tropics. Because fire and climate are correlated, we developed separate geospatial models to rank the importance of climate, topography, and human influence on vegetation present. This modelling confirmed that those areas with more fires had lower probabilities of tropical forest, that forest was most likely in areas with high mean annual rainfall with little seasonal variation in precipitation, and that anthropogenic factors disrupt this environmental predictability. We found there were environments where tropical forest and savanna were equally probable are geographically restricted. These relationships suggest that future drier climates projected under anthropogenic climate change, combined with clearing and burning that have reduced tropical forest extent to a subset of its theoretical distribution, will lead to irreversible loss of tropical forests. Our modelling provides global mapping that can be used track further changes to distribution of rainforests.

The migratory life history of anadromous salmonids requires successful migration between nursery, feeding and spawning habitats. Smoltification is the major transformation anadromous salmonids undergo before migration to feeding areas and prepares juvenile fish for downstream migration and entry to seawater. We reviewed the effects of climate change on smolt ecology from growth of juveniles in freshwater to early post-smolts in sea. Shift in the suitable thermal conditions by climate change is causing Atlantic salmon to expand their range northwards, while in the southern edge of their distribution populations struggle with high temperatures and occasional droughts. Climatic conditions, particularly warmer temperatures, are affecting growth during freshwater phase in the river. Better growth in the northern latitudes leads to earlier smoltification. Thermal refuges, the areas of cooler water in the river, are especially important for salmonids impacted by climate change. Restoring and maintaining connectivity and suitable diverse mosaic habitat in rivers are important for survival and growth throughout the range. The start of the smolt migration has shifted earlier as a response to increasing water temperatures, which has led to concerns of mismatch with optimal conditions for post-smolts in the sea decreasing their survival. A wide smolt window allowing all migrating phenotypes from early to late migrant’s safe access to sea is important in changing environmental conditions. This is true also for regulated rivers, where flow regulation practices cause selection pressures on migrating salmonid phenotypes. Life history in freshwater affects also marine survival, and there is a need for better collaboration across life stages and habitats among researchers and managers to boost the smolt production in rivers.

We investigated rainfall patterns in India over during the 60-year period from 1951 to 2010 and predicted changes for the next century (2051-2100) with an assumed 4K warming from large ensemble experiments (190 members). We focused on rainfall patterns during two periods of present-day climate (1951-1980 and 1981-2010) and their projected changes for the near and far future (2051-2080 and 2081-2110). Our analysis revealed that the northeastern region of India and some southern regions received higher rainfall during the period of 1951-2010. This finding is consistent with daily observations from the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE). In a warming climate, rainfall events in India are predicted to carry more precipitation, with the northeast and southern regions experiencing stronger rainfall events. The frequency and intensity of these events (with more than 20mm of rainfall per day, on average) are also expected to increase. Overall, our study suggests that water-related disasters such as flooding and landslides could be much worse in India in the future due to climate warming.

The objective was to estimate the monetary loss of potato producers up to the year 2100 as a result of temperature and precipitation impacts, taking into account the A2 and B2 scenarios of the IPCC (Intergovernmental Panel on Climate Change). The Pooled Production Panel Model was used, whose database was prepared taking into account climatic variables (temperature and precipitation) and agricultural variables (production, harvested area, farm-gate price) for the period 1996 - 2020, which form the independent variables of the study. The estimations used 60 observations and a total of 38 estimations were run in the econometric software EViews8, of which Equation 05 of the Production Pooled Panel Model was chosen as the best. The model obtained used temperature and precipitation forecasts from Brazil's INPE (National Institute for Space Research), validated for the study area. The results indicate a concave function between potato production (t/ha), temperature and precipitation. Finally, based on the A2 climate scenario, which is the most pessimistic and using the period 2021 - 2100, a loss for potato producers of approximately 8'927,521.48 million soles was estimated.

Each year, the global population and agriculture suffer critical agricultural output losses as a result of severe drought devastation. Physiological drought occurs when plants are unable to extract water from the soil, even though it is available in the root zone. Apart from having a significant effect on plant physiology, drought stress has the effect of reducing crop yield. Drought stress influences plant metabolism both directly and indirectly. Drought stress alters the morpho-anatomical, physiological, and biochemical composition of plants, thereby decreasing transpiration water loss and increasing the efficiency with which plants use their water. Constant water loss through transpiration, combined with previously lost water, results in leaf water deficits. Nonetheless, drought stress has a wide variety of effects, ranging from lesions to confusion. Plant health is harmed when their ability to absorb water and nutrients, interact with their environment, and breathe is harmed. Apart from oxidative damage to plants, it may also result in cell death, which can occur under certain conditions when cells are exposed to their environment. Drought induces a plethora of physiological and molecular changes in plants, the majority of which assist them in adapting to the harsh environment. To mitigate drought's adverse effects, we must first gain a better understanding of how drought affects plant physiology. The purpose of this research is to better understand how drought affects plant development by examining the causes and effects of drought stress.

Climate change is a major threat to agricultural food production globally and locally. It poses both direct and indirect effects on soil functions. Thus, agricultural management practices has evolved to adaptation strategies in order to mitigate the risks and threats from climate change. The study concludes with a recommendation the coconut farmers should explore the idea of soil biodiversity in a bid to mitigate the potential negative impact of climate related risk on the farming. The study proffers the need for adopting sustainable agricultural practices to boost local coconut production. This can contribute to the simultaneous realisation of two of the Sustainable Development Goals (SDGs) of the United Nations: SDG 2 on food security and sustainable agriculture and SDG 13 on action to combat climate change and its impacts. The study findings has implications for tackling climate change in Sub-Saharan Africa and in particular Nigeria in order to boost local agricultural production and coconut in particular without negative environmental consequences and an ability to cope with climate change related risks.

The main purpose of this research is to analyze the perception of climate change impacts on human health in Bangladesh through data from nationality representative surveys conducted in some district of Bangladesh. In Bangladesh there have a few research has been conducted on public perceptions about the impact of climate change on human health. A structured questionnaire method was conducted, and data collected from 615 respondents. The findings of this study reveal that out of 615 respondents, 76.0% of the respondents replied positively while remaining 24.0%, almost one-fourth of total respondents, indicated that they have not heard the term climate change before. Knowledgeable in climate change, 92.5% of respondents agreed that climate change has an impact on human health while only 7.5% respondents disagreed with this statement. 90.5% of respondents argued that they are agreed with the opinion that climate change is a serious threat to human health.

There is growing awareness that “Nature-based Solutions” (NbS) can help to protect us from climate change impacts whilst slowing further warming, supporting biodiversity and securing ecosystem services. However, the potential of NbS to provide the intended benefits has not been rigorously assessed. There are concerns over their reliability and cost-effectiveness compared to engineered alternatives, and their resilience to climate change. Trade-offs can arise if climate mitigation policy encourages NbS with low biodiversity value, such as afforestation with non-native monocultures. This can result in maladaptation, especially in a rapidly changing world where biodiversity-based resilience and multifunctional landscapes are key. Here we highlight the rise of NbS in climate policy—focussing on their potential for climate change adaptation as well as mitigation—and discuss barriers to their evidence-based implementation. We outline the major financial and governance challenges to implementing NbS at scale, highlighting avenues for further research. As climate policy turns increasingly towards greenhouse gas removal approaches such as afforestation, we stress the urgent need for natural and social scientists to engage with policymakers. They must ensure that NbS can achieve their potential to tackle both the climate and biodiversity crisis while also contributing to sustainable development. This will require systemic change in the way we conduct research and run our institutions.

The Global Carbon Budget is the cumulative carbon emissions that human activities can generate while limiting the global temperature increase to less than 2°C. On this basis, most countries ratified the Paris Agreement 2015, pledging to reduce national emissions and the impacts of climate change. The European Union has planned to reduce emissions by 80% of their 1990 value by 2050 but such a target needs to be coupled with a further constraint on the cumulative greenhouse gases released along the path to 2050. The aim and the novelty of this study are to propose, for the first time, a carbon budget for the European Union, which represents the most significant physical characteristic to assess the feasibility of current EU-28 greenhouse gas reduction objectives under the goals of the 2015 Paris treaty

Soybean yields are often indicated as an interesting case of climate change mitigation due to the beneficial effects of CO₂ fertilization. In this paper we econometrically study this effect using a time series model of yields in a multivariate framework for a main producer and exporter of this commodity, Argentina. We have to deal with the upward behavior of soybean yields trying to identify which variables are the long-run determinants responsible of its observed trend. With this aim we adopt a partial system approach to estimate subsets of long-run relationships due to climate, technological and economic factors. Using an automatic selection algorithm we evaluate encompassing of the different obtained equilibrium correction models. We found that only technological innovations due to new crop practices and the use of modified seeds explain soybean yield in the long run. Regarding short run determinants we found positive effects associated with the use of standard fertilizers and also from changes in atmospheric CO₂ concentration which would suggest a mitigation effect from global warming. However, we also found negative climate effects from periods of droughts associated with La Niña episodes, high temperatures and extreme rainfall events during the growing season of the plant.

Flooding is a prevalent natural disaster with both short and long-term social, economic, and infrastructure impacts. Changes in intensity and frequency of precipitation (including rain, snow, and rain on snow) events create challenges for the planning and management of resilient infrastructure and communities. While there is general acknowledgement that new infrastructure design should account for future climate change, no clear methods or actionable information is available to community planners and designers to ensure resilient design considering an uncertain climate future. This research used climate projections to drive high-resolution hydrology and flood models to evaluate social, economic, and infrastructure resilience for the Snohomish Watershed, WA, U.S.A. The proposed model chain has been calibrated and validated. Based on the established model chain, the peaks of precipitation and streamflows were found to shift from spring and summer to earlier winter season. The nonstationarity of peak discharges was discovered with more frequent and severe flood risks projected. The peak discharges were also projected to decrease for a certain period in the near future, which might be due to the reduced rain-on-snow events. This research was expected to provide a clear method for the incorporation of climate science in flood resilience analysis and to also provide actionable information relative to the frequency and intensity of future precipitation events.

The present study aims at investigating the potential impact of agricultural policies on GHG emissions from agriculture across the European Union. The study begins with a brief analysis of the context of implementation of the 2014-2022 Common Agricultural Policy (CAP), within which many interventions were designed to improve sustainability and increase competitiveness. It follows a description of the structural changes the European agriculture is witnessing, that are both influenced and contribute influencing policies. The method of Qualitative Comparative Analysis (QCA) is used to investigate possible causalities and to cluster observations based on similar combinations of conditions (i.e., drivers) and outcomes (i.e., positive or negative variations in GHG emissions from agriculture between the end and the begin of the CAP programming period). The results reveal that the increase in GHG emissions from agriculture over the study period is mainly attributable to the low share of agricultural land under management contracts targeting climate change mitigation and carbon sequestration through the CAP. CAP payments coupled with the production is found to contribute to further increasing GHG emission from agriculture in some eastern and northern EU countries. Livestock concentration, income support payments and the high price of agricultural land drive the increase in GHG emissions for other central and eastern EU countries. The paper concludes addressing existing shortcomings due to conflicting interventions in the current CAP Strategic Plans.

Transitioning towards net zero emissions is critical in the chemical and process industries to combat climate change and ensure environmental sustainability. Key focus areas of this review include the reduction of carbon emissions, the efficient utilization of energy resources, and the adoption of sustainable practices. Cutting-edge technologies such as biomass utilization, biotechnology applications, and waste management strategies are crucial in achieving this transition. Industries, including cement production, encounter unique challenges in their quest for sustainability and must actively seek innovative solutions to mitigate their carbon footprint effectively. The role of hydrogen as a clean fuel and its potential to revolutionize the chemical and process sectors is also discussed. The European Green Deal and Sustainable Development Goals (SDGs) are significant for the chemical industry. They provide a clear roadmap and framework for promoting sustainability, driving innovation, and reducing the industry's environmental impact. By aligning with these initiatives, the chemical industry can enhance its competitiveness, contribute to societal well-being, and foster collaboration across sectors to achieve shared sustainability objectives.

Due to an increase of the monocrystalline PV systems installations, for a drive towards the sustainable smart cities in the hot arid developing country such as Pakistan, pose challenges of the performance and degradation issues. Monocrystalline PV module efficiencies are declining and damaging under the continuous exposure to higher surface day-time temperatures in the different parts of the country. A MATLAB simulations were performed based on the validated mathematical approach. This paper investigates the hot arid surface temperature impacts on the performance of PV modules during the summer and winter seasons in Pakistan. The investigations are performed examining the power generating efficiency of the PV system. This paper also investigates the influence of installations of PV-system in the North, South, East and West regions of Pakistan. It was examined that the northern areas of Pakistan are more suitable for maintaining the long-term durability of the PV system. Investigations are performed for the peak summer and peak winter days. During summer months, cooling strategies have to be implemented to overcome the heating effects whilst reducing degradation effect on installed PV-system.

Climate change is affecting the production of temperate fruit crops. Freeze damage, particularly in spring, has resulted in significant economic losses in peach production in the southeastern United States. Research efforts in peach and other Prunus species have primarily focused on dormancy-related traits associated with bloom time, such as chill and heat requirement, with fruitlet freeze tolerance not equally represented. This study reports fruitlet freeze tolerance in 75 peach and nectarine accessions at six freezing temperatures (0 to -10ºC) using electrolyte leakage method over two seasons (2022-2023). Fruitlet freeze tolerance ranged from -3.94 to -10.22 °C with an estimated damage ranging from 16-48% with the majority of the accessions showing tolerance to cold temperatures in the -4 to -6ºC and 25-35% range. Variability in tolerance was noted across years, including some inconsistencies between tolerance group assignments. Grouping based on the estimated damage showed better stability and some accessions changed their grouping from the extremes to an intermediate tolerance group. Interestingly, nectarine accessions were among most tolerant in both seasons. Broad-sense heritability of 0.52 and 0.85, for freeze tolerance and estimated damage, respectively, suggested genetic control of this trait with a potential for improvement via breeding.

Environmental tax is the climate policy that offers, in theory, the easiest way for carbon reduction. But in practice, implementation has proven complicated despite public demand for policy action on climate change. This research investigates to reframe environmental taxes in ways more personally engaging to create a moral foundation, and massive participation. As people show rising demand, we aimed to design a tool that responds to public expectations and operates directly at source on emission reducers, viz the trees. Drawing on research from environmental taxes and the evidence of measures taken, we reasoned that an environmental fiscal policy may not intend necessarily to punish the “bads”, but rather might reward the positive attitude and direct it to act. Consequently, we focused on tax reliefs and designed Green Aid, that can address people’s attitude to take active participation into account by incorporating virtuous behaviours into tax relief. Green Aid Tax relief works embedded in the Green Aid Participation Scheme that bears directly on a source of environmental recovery and organizes the global call to public action in a sustained, structured, and collective participation to forestation. Green Aid bridges the action of contributing to carbon reduction with immediate, tangible, and direct benefits. It can be an alternative environmental tax, able to address and operate directly at source on emission reducers and secure effectiveness in carbon reduction and efficiency in terms of public acceptance and viability at a global level.

Conventional methods of climate change (CC) mitigation have not ‘bent the curve’ of steadily rising annual anthropic CO2 emissions or atmospheric concentrations of greenhouse gases. This study reviews the present position and likely future of such methods, using recently published literature with a global context. It particularly looks at how fast they could be implemented, given that the limited time available for avoiding catastrophic CC (CCC). The study then examines solar geoengineering, an approach often viewed as complementary to conventional mitigation. The review next introduces equity considerations, and shows how this will shorten even further the time available for effective action for CC mitigation. The main findings are as follows. Conventional mitigation approaches will be implemented too slowly to be of much help in avoiding CCC, partly because some suggested technologies are infeasible, while others are either of limited technical potential, or, like wind and solar energy, cannot be introduced fast enough. Because of these problems, solar geoengineering is increasingly advocated as a quick-acting and effective solution. However, it could have serious side effects, and given that there will be winners and losers at the international as well as the more regional level, political opposition may make it difficult to implement. The conclusion is that global energy consumption itself must be rapidly reduced to avoid catastrophic climate change.

Accurate assessment and projections of extreme climate events requires the use of climate datasets with no or minimal error. This study uses quantile mapping bias correction (QMBC) method to correct the bias of five Regional Climate Models (RCMs) from the latest output of Rossby Climate Model Center (RCA4) over Kenya, East Africa. The outputs were validated using various scalar metrics such as Root Mean Square Difference (RMSD), Mean Absolute Error (MAE) and mean Bias. The study found that the QMBC algorithm demonstrate varying performance among the models in the study domain. The results show that most of the models exhibit significant improvement after corrections at seasonal and annual timescales. Specifically, the European community Earth-System (EC-EARTH) and Commonwealth Scientific and Industrial Research Organization (CSIRO) models depict exemplary improvement as compared to other models. On the contrary, the Institute Pierre Simon Laplace Model CM5A-MR (IPSL-CM5A-MR) model show little improvement across various timescales (i.e. March-April-May (MAM) and October-November-December (OND)). The projections forced with bias corrected historical simulations tallied observed values demonstrate satisfactory simulations as compared to the uncorrected RCMs output models. This study has demonstrated that using QMBC on outputs from RCA4 is an important intermediate step to improve climate data prior to performing any regional impact analysis. The corrected models can be used for projections of drought and flood extreme events over the study area. This study analysis is crucial from the sustainable planning for adaptation and mitigation of climate change and disaster risk reduction perspective.

The escalating concerns over climate change have propelled industries worldwide to seek innovative strategies for mitigating greenhouse gas emissions. Within the energy sector, Carbon Capture and Storage (CCS) technology emerges as a promising solution to curtail emissions and foster sustainable development aims for net zero approach. The research delves into the role of government support in expediting CCS adoption for the maximum potential of 9.79 MtCO2 storage from six major refinery plants. The refineries mentioned above are anticipated to necessitate an initial capital investment of approximately 18,307 million THB. This research focuses on potential business model proposals appropriate for a country's context, specifically applying CCS technology to Thai oil refining sector. To achieve the realization of CCS within the context of this study, a combination of three essential measures will be required: tax incentives, carbon credits, and grants. This process will commence with the implementation of tax incentives, followed by an increase in the carbon price within the country. Finally, the establishment of a dedicated fund, funded through deductions from oil excise tax revenue, will play a pivotal role in facilitating the necessary financial support for the emergence of CCS.

The virtual airport hub business model is an innovative solution supported by digital technologies, the implementation of which in continental air transport may lead to a reduction in energy consumption and to a reduction in greenhouse gas emissions. The prerequisites for the implementation of the described solution are: striving to implement the GHG emission reduction strategy laid out in the Paris Agreement (2015) and the European Green Deal (2019) as well as the EU digitalization strategy (2020). The use of predictive analitics to identify the mobility needs of population and operational capabilities of the sector, gives an opportunity to plan travel flows and to create an appropriate set of direct connections among regional airports every day. The results of the analysis of data from 2019 on the amount of energy consumption and GHG emissions indicate that in Europe, it would be possible to achieve reduce GHG emissions by 5% without reducing the number of passengers using air transport. The study was prepared after conducting literature studies, data analysis and using the method of formulating scenarios. The proposed solution has the features of an innovative business model, the implementation of which allows for obtaining more favorable effects using already available resources.

An indisputable fact about our planet is that its atmospheric temperature has risen dramatically during the past century. Combustion of fossil fuels and their subsequent greenhouse gas emissions are thought to be the main contributors to recent changes within the Earth’s ecosystem. The transportation sector and electricity generating power plants are each responsible for approximately one-third of these emissions. Shifting towards a cleaner and renewable resources to generate electricity is believed to omit a big portion of polluting substances. Improvements in vehicles’ fuel efficiency and the introduction of alternative fuels besides strategic plans to control travel demand are among the most promising approaches to alleviate emissions from the transportation sector. Recent technology advancements, however, drew much attention to the production and manufacturing of alternative fuel vehicles, electric vehicles in particular. Since these vehicles use electricity as part of or all their powertrain, assessing the amount of emissions they produce is closely tied to the cleanliness of the electricity source. In order for a valid comparison to be made between internal combustion and electric vehicles, hence, a life cycle assessment procedure needs to be followed from production stages to terminal life of vehicles. Involvement of numerous affecting factors during the lifetime of a vehicle on one hand, and the ambiguity in the exact source of electricity used to charge electric vehicles on the other hand bring about more complexities. The latter case is more commonly known as the marginal grid problem, which deals with how a combination of sources used to generate electricity can influence the life cycle emissions. There are also other concerns regarding the growth in fuel-efficient and electric vehicles. Transportation planners argue that new developments in the vehicle industry may attract more people to owning and driving cars. This phenomenon which is better known as a rebound effect not only will result in increased traffic congestion, but it can also outpace the environmental benefits from utilizing electric vehicles. Moreover, since fuel taxes comprise the majority of Highway Trust Funds, alternative ways to compensate for state and federal revenues should be devised. This paper is an attempt to review the existing literature to better elaborate on the role of the transportation sector in controlling climate change threats. More specifically, issues around the use of electric vehicles and how they can contribute to more environmentally friendly communities are discussed.

The overwhelming evidence supports the assertion that the climate is undergoing change. Understanding the perception of locals of the magnitude of climate change and its influence on non-timber forest products (NTFPs) challenge at a global scale. Although studies on climate change, value addition, and the multiple uses of NTFPs and their impact on local livelihoods have been conducted, locals' perceptions of these factors have not been fully explored. This study aims to assess various social factors, including education, gender, and religion, and their influence on locals' perceptions of the abovementioned factors. The research focused on five regions where NTFPs are prevalent in Ghana (Western North, Bono, Ahafo, Ashanti, and Eastern regions). To investigate the impact of social factors on local perceptions of climate change, value addition, and the multiple values of NTFPs within rural communities, a total of 732 interviews with a team of interviewers across these five regions in Ghana were carried out. We applied a logistic regression model to assess the social factors and their influencing locals’ perceptions of the mentioned variables. It was revealed that age, gender, education, and occupation did not significantly influence locals' perceptions of climate change. However, religion was found to influence locals' perceptions of climate change. Furthermore, the results demonstrated that gender (P<0.000328) and education (P<0.00426) strongly influenced locals' perceptions of value addition to NTFPs. In contrast, religion and constraints (related to time, finance, and skills) did not significantly influence locals' perceptions. Additionally, it was observed that gender (0.00132), education (0.00692), and religion (8.12e-05) significantly influenced how locals perceive and use NTFPs. In conclusion, this study provides valuable insights into the intricate interplay among local perceptions, climate change, value addition, multiple uses of NTFPs, and the capacity of NTFPs to enhance the well-being of forest fringe communities. These findings underscore the importance of comprehensive, tailor-made interventions that consider local perspectives and adhere to sustainable approaches, with the aim of optimising the positive impacts of NTFPs in poverty alleviation and overall community development.

Land and climate are strongly connected through multiple interface processes and climate change may lead to significant changes in land use. In this study, high-resolution observational gridded datasets are used to assess modifications in the Köppen-Geiger and Worldwide Bioclimatic (WBCS) Classification Systems, from 1950‒1979 to 1990‒2019 in Portugal. A compound Bioclimatic-Shift Exposure Index (BSEI) is also defined to identify the most exposed regions to recent climatic changes. The temporal evolution of land cover with vineyards and olive groves between 1990 and 2018, as well as correlations with areas with bioclimatic shifts, are analyzed. Results show an increase (decrease) of CSa Warm Mediterranean climate with hot summer (CSb, warm summer) of 18.1% (‒17.8%). The WBCS Temperate areas also reveal a decrease of ‒5.11%. Arid and semi-arid ombrotypes areas increased, conversely to humid to sub-humid ombrotypes. Thermotypic horizons depict a shift towards warmer classes. BSEI highlights the most significant shifts in northwestern Portugal. Vineyards have been displaced towards regions that are either the coolest/humid, in the northwest, or the warmest/driest, in the south. For oliviculture, the general trend for a relative shift towards cool/humid areas suggests an attempt of the sector to adapt, despite the cover area growth in the south. As vineyards and olive groves in southern Portugal are commonly irrigated, options for the intensification of these crops in this region may threaten the already scarce water resources and challenge the future sustainability of these sectors.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Aim: Utilizing the subjective experience of nurse executives who have supervised nurses during a major disaster in a hospital setting, this study aims to describe the subjective experience of nurse executives (NE) who have supervised nurses’ response to major disaster. This paper will focus on strategies to support nursing response to disaster, specifically to strengthen resiliency and the ability to maintain function despite the shock of disaster, including those caused by climate changes. Methods: Semi-structured interviews were conducted with 11 hospital-based nurse executives who supervised nurses during some of the worst natural and human-made disasters in different regions of the United States. A phenomenological approach was used to analyze and describe emerging themes from qualitative data. Results: Three Nurse Executives demonstrated theme saturation for mitigation steps to augment traditional disaster readiness activities: 1.) Assessment of Human Infrastructure: Daily Skills Needed During Disaster Response, 2.) Identification and Study of Failure Points & Metrics, 3.) Strengthening Human Infrastructure: Rectifying Deficiencies), and 4.) Monitoring Metrics & Making Corrections During Conventional Periods. Conclusion: Mitigation steps may improve outcomes in hospital function during conventional times; therefore, may improve resiliency and the ability to maintain functions during major disasters, including climate change.

This study assesses the perception and vulnerability of the farming communities to climate change in the southwestern parts of Ethiopia. Data were collected from 442 households in four districts: Jimma Arjo, Bako Tibe, Chewaka, and Sekoru. The vulnerability of the farming communities was assessed using the households’ livelihood vulnerability index. A total of 40 indicators were applied to calculate household livelihood vulnera-bility to climate change, which were categorized into five major capitals: natural, social, financial, physical, and human. The household percep-tions of climate change results showed that there existed a statistically significant relationship between climate change perceptions and changes in rainfall pattern (75.6%, p<0.001), temperature pattern (69.7%, p<0.001), drought (41.6%, p=0.016), flood (44.1%, p=0.000), and occurrence of early (53.2%, p<0.001) and late rain (55.9%, p<0.001). The results showed that households in Sekoru district were the most vulnerable (0.61), while Jimma Arjo district were less vulnerable (0.47) to the effect of climate change. The vulnerability of the households in the study areas is mainly related to the occurrence of drought, lack of much-needed infrastructure facilities and weak institutional support. Links with the financial organization are also lacking among the household. The findings of this study will support policymakers to design climate change adap-tation strategies to combat climate change impacts. To support disaster risk management on the one hand and increase the resilience of vulnera-ble societies to climate change on the other hand, we recommend a detailed assessment in the remaining districts of the region.

We developed an artificial neural network as an air quality model and estimated the scope of the impact of climate change on future (until 2064) summertime trends of hourly Ozone (O3) concentrations at an urban air quality station in Tehran, Iran. Our developed scenarios assume that present-time emissions conditions of O3 precursors will remain constant in the future. Therefore, only the impact of climate change on future O3 concentrations is investigated in this study. GCM projections indicate more favorable climate conditions for O3 formation over the study area in the future: the surface temperature increases over all months of the year, solar radiation increases, and precipitation decreases in future summers, and summertime daily maximum temperature increases about 1.2 ∘C to 3 ∘C until 2064. In the scenario based on present-time O3 conditions in 2012 summer without any axceedances, the summertime exceedance days of 8-hr O3 standard are projected to increase in the future by about 4.2 days in the short term and about 12.3 days in the mid-term. Similarly, in the scenario based on present-time O3 conditions in 2010 summer with 58 days of exceedance from 8-hr O3 standard, exceedances are projected to increase about 4.5 days in the short term and about 14.1 days in the mid-term. Moreover, the number of Unhealthy and Very Unhealthy days in 8-hr AQI is also projected to increase based on pollution scenarios of both summers.

Development of the continental shelf has accelerated significantly as nations around the world seek to harness offshore renewable energy. Many areas marked for development align with submerged palaeolandscapes. Poorly understood and difficult to protect, these vulnerable, prehistoric landscapes provide specific challenges for heritage management. Indeed, there now appears to be a schism between what underwater cultural heritage policy intends and what it is achieving in practice. Shortcomings in international and national legislature ensures that large parts of the continental shelf, including areas under development, may have little or no legal protection.

Colombia has initiated the process of participating in the environmental projects of the United Nations global agenda for the mitigation of climate change and the protection of biodiversity. Consequently, organizations within the solidarity sector have devised projects with the objective of aligning themselves with regional programs and of promoting leadership in the rural development through solidarity-based environmental initiatives. These include the organizations Canapro Ambiental, Cooperación Verde and Cootregua, which have participated in and accompanied local environmental projects. This study has identified the common elements related to the principles of organizational design proposed by Elinor Ostrom as a result of the adoption of Corporate Social Responsibility (CSR) for the purpose of a sustainable growth. The above findings serve to corroborate the relevance of the principles of organizational design as a qualitative assessment methodology for environmental solidarity initiatives. In particular, the methodology demonstrates the value of supporting the objectives of environmental sustainability and governance in the long term, by means of the strengthening of Corporate Social Responsibility (CSR) for the purposes of the solidarity ecosystem.

In a rapidly evolving global landscape characterized by increased international travel, migration, and ecological shifts, this study sheds light on the emergence of protozoal and helminthic infections targeting the central nervous system (CNS) within Europe. Despite being traditionally associated with tropical regions, these infections are progressively becoming more prevalent in non-endemic areas. By scrutinizing the inherent risks, potential outcomes, and attendant challenges, this study underscores the intricate interplay between diagnostic limitations, susceptibility of specific population subsets, and the profound influence of climate fluctuations. The contemporary interconnectedness of societies serves as a conduit for the introduction and establishment of these infections, warranting comprehensive assessment. This study emphasizes the pivotal role of heightened clinician vigilance, judicious public health interventions, and synergistic research collaborations to mitigate the potential consequences of these infections. Though rare, their profound impact on morbidity and mortality underscores the collective urgency required to safeguard the neurological well-being of the European populace. Through this multifaceted approach, Europe can effectively navigate the complex terrain posed by these emergent infections.

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 ly-ing 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 has been tested for the first time in the village of Magaña. Three main objectives and phases of this methodological approach have been designed: 1. Preparation of an Environmental Risk Chart with which to answer such ques-tions as “How have climate change, anthropic alterations and environmental characteris-tics 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 man-ner.

The Congo River Basin is the second-largest watershed globally, flowing through nine countries before reaching the Atlantic Ocean. The Kasai River Basin (KARB), containing about one-fourth of Congo’s freshwater resources, plays a strategic role in sustaining navigation, food production, and hydroelectricity generation in Central Africa. A multi-model framework suited for data scarce regions is applied for climate change impacts on water availability in the KARB to propose effective development plans in the future. This includes consideration of two conceptual hydrological models calibrated using four reanalysis datasets and fed with bias-corrected outputs of 19 climate models under two future Representative Climate Pathways (RCPs). Changes in mean annual discharge in the KARB from -18% to +3% are projected depending on the considered modeling configuration. This shows the sensitivity of impact assessment to the choice of models as well as input data. Moreover, about 9%, 18%, and 13% decline in streamflow signatures (Q10, Q50 and Q90) are projected based on the ensemble of models under RCP 8.5. A decrease of 14% and 5% in annual hydropower potential of the mainstream is estimated under RCPs 4.5 and 8.5, respectively. These changes in flows conditions should be considered in decision-making around constructing reservoirs and hydroelectricity generation.

How hands-on gardening impacts behaviors including healthy eating and physical activity during early childhood can be of critical importance for preventing early onsets of obesity. This research investigates how participating in hands-on gardening impacts preschoolers’ (3-5 years old) physical activity (measured by accelerometers) in childcare centers in the Semi-Arid Climate Zone. The research was conducted in eight licensed childcare centers located in West Texas with 149 children (n=149). Four childcare centers in the experimental group received hands-on garden interventions; the other four in the control group did not. In both experimental (intervention) and control (non-intervention) centers, children wore Actigraph GT3X+ accelerometers continuously for 5 days before and for 5 days after intervention (a total of 10 days). Results show that the duration of sedentary behavior of children in the experimental (intervention) group significantly decreased compared to children in the control (non-intervention) group. The finding suggests that the positive effects of childcare hands-on gardening on physical activity extend to semi-arid climate zones where gardening is challenging due to high temperatures and lack of annual rainfall. The research emphasizes the critical need to incorporate hands-on gardening in childcare centers as an obesity prevention strategy nationally in the U.S. and beyond.

The global carbon neutrality challenge places a spotlight on forests as carbon sinks. However, greenhouse gas (GHG) balances of wood for material and energy use often reveal GHG emission savings in comparison with a non-wood reference. Is it thus better to increase wood production and use, or to conserve and expand the carbon stock in forests? GHG balances of wood products mostly ignore the dynamics of carbon storage in forests, which can be expressed as the carbon storage balance in forests (CSBF). For Germany, a CSBF of 0.25 to 1.15 t CO2/m³ wood can be assumed. When the CSBF is integrated into the GHG balance, GHG mitigation substantially deteriorates and wood products may even turn into a GHG source, e.g. in the case of energy wood. Here, building up the forest carbon sink would be the better option. We conclude that it is vital to include the CSBF in GHG balances of wood products if the wood is extracted from forests. Only then can GHG balances provide political decision-makers and stakeholders in the wood sector with a complete picture of GHG emissions.

Under the “Korean emission trading system in the forestry sector (KETSF)” initiative, the South Korean government has developed several greenhouse gas (GHG) emissions reduction programs that include forestry activities as the cornerstones of the initiative. Forest management is deemed to be a major strategy to implement KETSF; this has been confirmed by most participants in the program, who have shown their preference for forest management projects as the most effective and encouraging strategy to participate in the KETSF program. For a successful implementation of KETSF projects is essential to explore methods that optimize the positive impacts of such strategies, thereby maximizing the economic returns and carbon stocks that result from the implementation of forest management activities. Thus, this study investigated several value-added KETSF projects in South Korea, which included simulated scenarios under two main forest management strategies: one based on an extension of the rotation age, and a second one based on reforestation with new species. Five forest management scenarios were examined and evaluated in their ability to maximize carbon stocks and economic returns. Based on the results, Scenarios 2 and 4 were identified as the best KETSF projects in terms of carbon stock increments. Additionally, the results indicated that projects including reforestation with new species added more economic value than projects that considered an extension of the rotation age. The study also revealed that KETSF projects generated revenue in both scenarios, by either extending the rotation age or by implementing reforestation with new species.

COVID‑19 pandemic, also known as the coronavirus pandemic, has spread rapidly across the globe since the end of 2019 and brought impressive changes in our life and living through partial or full lockdown and reduced anthropogenic activities. Hence, it is imperative to investigate the impacts and consequences of COVID-19 on global eco-system and environment. The present study accordingly addresses the impacts and consequences of COVID-19 by ten environmental indicators; viz., global warming (or greenhouse gas emission), stratospheric ozone depletion, ozone formation (on human health), fine particulate matter formation, smog, ionizing radiation, human carcinogenic toxicity, human non-carcinogenic toxicity, water resource consumption, and effect on human health. The overall study has been performed in agreement with the standard principle and guidelines of life cycle assessment. Worldwide changes in consumption of fossil fuels, viz., petroleum, coal and natural gas, as a result of COVID-19 pandemic, has been the core theme of the study. Outcomes from the study show that COVID-19 has been a ‘blessing in disguise’ for the global environment with most of the above-mentioned indicators declining by approximately 20-30% in 2020 in comparison to the 2019 level.

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature (LST), SUHI and urban design factors were achieved by using Landsat satellite data, GIS database and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that in the summer daytime under the clear sky condition, the LST varied greatly from 26 °C to 40 °C and the SUHI changed in a wide range of -6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZ of LCZs 1-5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.697, RMSE of 1.21 °C, and the d value of 0.81 for the model of LCZs 1-5, and the values of 0.666, 1.66 °C, and 0.76 for the model of the mixed LCZ, indicating that the models can predict the changes of SUHI with LCZs to a large and satisfactory extent. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs in the largely urbanized cities, and provides information beneficial to the urban designs and regenerations in the humid subtropical region.

The increase in tobacco production while ameliorating the condition of the participant households has caused challenges to stakeholders particularly those in the governance of forest resources upon which the sector is hinged. Massive deforestation has proceeded at an alarmingly high level, in a way that threatens the long term viability of the tobacco sector and sustainability of natural forest resources. The entrance of previously disadvantaged majority into the once minority-dominated tobacco sector (and economy) in a quest to improving their livelihoods, is driving forest landscape changes that pose inherent environmental challenges including climate change. This article adopts institutional and landscape approaches to explore and explain the drivers, nexus and implications of smallholder tobacco as a livelihood strategy to the forest landscape changes and the subsequent imperative for governance of the sustainable utilization of forest resources in Zimbabwe. Drawing on documentary evidence the paper concludes that this situation poses a dilemma to forest and livelihood policies, hence the need to examine new institutional and livelihood initiatives.

Temporal changes of population densities and species richness of three main pollinator groups: moths and butterflies (Lepidoptera), bees, wasps and sawflies (Hymenoptera) and hoverflies, horse-flies, tachninids and bee flies (Diptera) were investigated in the Carpathian Basin. Maintaining pollinator divesrity is a crucial factor for preserving our biodiversity and ecosystems, furthermore several pollinator species has strong economic role in maintaning crop and fruit cultures. Our conclusions are based on our three or four decades of faunistic surveys in various regions of the Carpathian Basin. Analysing and comparing our data with the historical data of the last 50 years, we concluded, densities of some pollinators were declined during the past decade and the half (Symphyta, hoverflies), although populations of several species of Mediterranean-origin were grown (Aculeata) and even new species were migrated from the warmer regions. In numerous cases, this decrease was dramatic: more than 90% decrease of certain butterfly species were detected. On the other hand, the composition of pollinator fauna significantly changed due to the disappearance of some montaneous or mesophyle species. The main reason of decrease of pollinator communities is partly the climatic change and partly anthropogenic factors. Our conclusion: in our region, the pollinator crisis is present, but moderate; however, there is clear sign of the gradual transition of our pollinator fauna towards the Mediterranean type.

For the water bodies of the Lena Delta Nature Reserve, 413 taxa were known. In 14 small tundra reservoirs in its vicinity, we identified 385 taxa, which in the compilatory list made up a significant diversity (666 taxa including definitions to the genus level) of diatoms. Thus, the species composition of diatoms in the reserve and adjacent territories was replenished by 278 species. The predominance of species of the genera Pinnularia (57) and Eunotia (51) at the family and generic levels was revealed. Index of intraspecific variability Ssp./Sp. for the lakes of the reserve was 1.11, and for the lakes of the Tiksi region 1.14, which is typical for high-latitude and high-mountain communities. The number of rare or endangered species varied in different lakes within 1-10, totaling 42 species for the entire study area. Bioindication has shown that potentially threatened species prefer moderate temperatures, slightly acidic or neutral environments free from organic pollution. A comparative analysis of the species composition of diatoms in the vicinity of the Lena Delta and other northern water bodies of Yakutia and the Arctic Islands showed that the species composition of each lake in the Arctic is strictly individual. The indicator characteristics show a certain response of the species composition of diatoms to changes in salinity, pH, and organic pollution. A number of regularities in the spatial distribution of diatoms in the study area were found in connection with the physicochemical parameters of their habitat, height above sea level, and relation to a particular catchment basin. Statistical mapping of indicators of community and habitat diversity revealed a strong reaction to point one-time pollution and made it possible to assume the influence of summer northeast winds on the species composition. We suggest that the high diversity inherent in the diatom lakes of the Tiksi coastal zone, which can even be replenished in further studies, can be considered as a property of coastal biota inherent in ecotones. Since it is in the coastal Tiksi region that a surge in the number of species is observed, this region can be considered not only an ecotone, but also a hotspot of diatom diversity. The results of the study are important for developing the basis for monitoring biodiversity under the conditions of anthropogenic and climatic changes in the Arctic.

Flood inundation causes socioeconomic losses for coastal tourism under climate extremes, progressively attracting global attention. Mapping, evaluating, and predicting the flood inundation risk (FIR) is significant for coastal tourism. The study develops a spatial tourism–aimed framework integrating a weighted k-Nearest Neighbors (WkNN), Geographic Information Systems, and flood-related spatially environmental criteria such as precipitation, elevation, soil, and drainage systems. These model inputs were standardized and weighted using distance, and integrated into WkNN to infer regional probability and distribution of FIR. Zhejiang province, China, was selected as a case study. The resulting map was pictured to denote the likelihood of the criteria at various risk categories, which was validated by historical Maximum Inundation Extent (MIE) extracted from World Environment Situation Room. The result indicates 80.59% of WkNN results reasonably confirm the MIE. Precipitation and elevation make a negative contribution to high-medium risk, and drainage systems positively alleviate the regional stress of FIR. The results can help stakeholders make suitable strategies to protect coastal tourism, and also weigh WkNN is superior to kNN in FIR assessment. The framework provides a productive way to yield a reliable assessment of FIR and can also be extended to other risk-related environmental studies under climate change.

Agroecology is a holistic approach to farming that emphasizes the use of local resources and ecological processes to increase productivity, reduce environmental impact, and enhance resilience. Despite its potential benefits, the adoption of agroecological practices in Sub-Saharan Africa has been slow. This paper examines the opportunities for promoting agroecology in the region, including the growing demand for organic and sustainable food, the availability of local knowledge and resources, and the potential for agroecology to improve rural livelihoods and support climate change adaptation. The premise is that the promotion of agroecology faces several challenges. which include, inadequate policy and institutional support, lack of access to credit and markets, limited extension services, and weak land tenure systems. The paper draws on case studies from across Sub-Saharan Africa to illustrate the opportunities and challenges of promoting agroecology in the region. These case studies highlight the diversity of agroecological practices and the importance of context-specific approaches. Overall, the paper maintains that agroecology has the potential to transform agriculture in Sub-Saharan Africa, but that realizing this potential will require concerted efforts from governments, civil society, and the private sector.

Due to rising global warming and climate change, biodiversity protection has become a critical ecological concern. The rich biodiversity zones are under threat and are deteriorating, necessitating national, regional, and provincial efforts to safeguard these natural areas. The effective conservation of National Parks and Nature-protected Areas helps to improve biodiversity conservation, forest, and urban air quality. The continuous encroachment and abuse of these protected areas have degraded the ecosystem over time. While exploring the geophysical ecology and biodiversity conservation of these areas in West Africa, Kainji National Park was selected for this study because of its notable location, naturalness, rich habitat diversity, topographic uniqueness, and landmass. The conservation of national parks and nature-protected areas is a cornerstone of biodiversity conservation globally. This study is aimed at the target of United Nations Sustainable Development Goal 13, 2030- Climate Action, targeted at taking urgent action towards combating climate change and its impacts. The study captures both flora and fauna that are dominant in the study area. The 15 identified tree species were selected from over 30 species with 563,500,000 (an average of 3,700,000 in each sample frame) trees for every tree species/type with a total of 63% tree green canopy cover. The study areas divided into three zones were randomly sampled within a stratum of 25x25km frames divided into 150 sample frames for proper analyses using the i-Tree Eco v6.0.23. The following microclimatic data were captured and analyzed; photosynthetically active radiation, rain/precipitation, temperature, transpiration, evaporation, water intercepted by trees, avoided a runoff by trees, potential evaporation by trees, isoprene and monoterpene by trees. This study also further discusses the tree benefits of a green, low carbon, and sustainable environment within the context of biodiversity conservation considering carbon storage, carbon sequestration, hydrology effects, pollution removal, oxygen production, and volatile organic compounds (VOCs). There is a quick need for remotely-sensed information about the protected areas at regular intervals and government policies must be strict against illegal poaching, logging activities and other hazardous human impacts.

Countless disasters have resulted from climate change, causing severe damage to infrastructure and the economy. These disasters have significant societal impacts, necessitating mental health services for the millions affected. To prepare for and respond effectively to such events, it is crucial to understand people's emotions and the life incidents they experience both before and after a disaster strikes. In this case study, we mined the emotions and life incidents expressed on Twitter during the 2017 Hurricane Harvey. Between August 20 and August 30, we collected a dataset of approximately 400,000 public tweets related to the storm. Using a BERT-based model, we predicted the emotions associated with each tweet. Following emotion prediction, we applied various natural language processing techniques to analyze the content of the tweets, aiming to uncover the 'topics' discussed alongside specific 'emotions.' To efficiently identify these topics, we utilized the Latent Dirichlet Allocation (LDA) technique for topic modeling, which allowed us to bypass manual content analysis and extract meaningful patterns from the data. However, rather than stopping at topic identification, we further refined our analysis by integrating Graph Neural Networks (GNN) and Large Language Models (LLM). The GNN was employed to generate embeddings and construct a similarity graph of the tweets, which was then used to optimize clustering. This step ensured that related tweets were accurately grouped together based on their content and context. Subsequently, we used an LLM to automatically generate descriptive names for each event cluster. This advanced approach allowed us to identify and label life incidents automatically, providing a nuanced understanding of the key issues faced by the community during the hurricane. The results revealed significant emotional shifts as the hurricane reached its most devastating phase. These shifts coincided with pressing concerns and demands from the population, such as evacuation plans, animal safety, safety updates, public policy, help requests, flood impacts, and the spread of fake news. By combining GNN and LLM for automatic event name prediction, our study not only mapped out the emotions but also accurately categorized the specific life incidents that were most relevant during the disaster, offering critical insights for disaster preparedness and response strategies.

Observations collected during cold season precipitation periods at Utquagvik, Alaska and at the mul-tidisciplinary drifting observatory for study of Arctic climate (MOSAiC) are used to statistically ana-lyze relations among the atmospheric water cycle parameters including the columnar supercooled liq-uid and ice amounts (expressed as liquid water and ice water paths, i.e., LWP and IWP), the integrated water vapor (IWV) and the near-surface snowfall rate. Data come from radar and radiometer-based retrievals and from optical precipitation sensors. While correlation between snowfall rate and LWP is rather weak, correlations coefficients between radar-derived snowfall rate and IWP are high (~ 0.8), which is explained, in part, by generally low LWP/IWP ratios during significant precipitation. Corre-lation coefficients between snowfall rate and IWV are moderate (~0.45). Correlations are generally weaker if snowfall is estimated by optical sensors, which is, in part, due to blowing snow. Correlation coefficients between near-surface temperature and snowfall rates are low (r<0.3). Results from the Alaska and MOSAiC sites are generally similar. These results are not very sensitive to the amount of time averaging (e.g., 15-minute averaging versus daily averages). Observationally-based relations among the water cycle parameters are informative about atmospheric moisture conversion processes and can be used for model evaluations.

The promotion of active travel is deemed a crucial component of the transition to sustainable urban mobility. Several barriers hinder its policy implementation and uptake. Some evidence suggests that capacity building could be a useful tool for deepening sustainability efforts. However, a clear framework for understanding the dimensions of capacity building for active travel is lacking. Most research and findings use cases within a Global North context, constricting implications and transferability to the Global South, especially to African cities. This study responds to the dearth of scholarly work exploring Global South cases and fills a knowledge gap regarding capacity building in the case of active travel. Through a literature review, this study examines the dimensions of capacity building that are necessary to improve active travel in selected African countries. We focus on multilevel trans-portation governance, with highlights from five (5) African cities. Our findings suggest that the literature and policies on transport in Africa have key dimensions for capacity building for active travel but lack the introduction of key instruments and strategic pathways to meet these requirements for improved sustainable mobility. We propose a thematic guiding framework under three (3) levels of governance for integrating capacity building for active travel policies and implementation at institutional, individual, and environmental levels.

Species diversity has been shown to be influenced by environmental factors, but the mechanism underlying their relationship remains unclear across spatial scales. Based on field investigation data collected from 3,077 sample plots in temperate forest ecosystems, we compared tree species richness, evenness and dominance at 10 km × 10 km, 30 km × 30 km and 90 km × 90 km spatial scales. Then, we detected the scale dependence of changes in tree species composition on climate, topography and forest structure using variation partitioning and quantified their contribution to tree diversity with gradient boosted models (GBMs) and fitted their relationships. The magnitude of tree richness, evenness and dominance significantly increased with spatial scale. Ecological factors jointly accounted for 24.3%, 26.5% and 38.5% of the variation in tree species composition at the three spatial scales, respectively. Annual mean temperature had a strong impact on tree richness, evenness and dominance and peaked at an intermediate scale. Tree evenness and dominance increased with the variation of temperature but had upper and lower limits. Tree richness obviously increased with annual precipitation on multiple scales and decreased with annual sunshine duration at large spatial scale. Tree richness, evenness and dominance obviously increased with the variation elevation and diameter at breast height at large scales and small scales, respectively. Tree dominance decreased with tree height in a hump at small scale. The dependence of tree diversity on ecological factors increased with spatial scales. Furthermore, different factors exert various controls on tree diversity at different spatial scales, representing a comprehensive mechanism regulating tree diversity.