The commonly used words ‘transformation’ and ‘transition’ tend to lose their edge when used for any significant change process as is rather often the case. Partners and wider stakeholders in initiatives related to ‘sustainability transitions’ therefore often entertain different perspectives on what the strategic orientation of an initiative is or is meant to be. Common planning and design processes such as situation analysis and theories of change, however, often do not sufficiently cater to this dynamic. As a result, different actors may be pulling the initiative in different directions, undermining the overall partnership efforts. In this short contribution a strategic scoping canvas and an associated facilitation process are presented as a way of addressing such situations. Illustrations are provided of initial application in three cases related to food system transitions in Peru, Ethiopia, and Bangladesh, exploring the connectivity with approaches commonly used in the context of system transformations, including the Multi-Level Perspective on sustainability transitions, the Leverage Points approach, Capability Approach, and the theory of Large System Change. We conclude that the canvas and associated facilitation approach has proved useful in different contexts, offering opportunities for complementing existing methodologies, and potentially enhancing their efficacy in facilitated multi-stakeholder processes.

Farming systems prevalent in sub-Saharan Africa are exposed and vulnerable to climate change due to their high dependence on rainfall. However, most studies have only estimated the impacts of climate change on agricultural productivity at a regional or national level. We add to this literature by focussing on the sub-national impacts. This study uses 30 years (1981–2011) of yield and weather data in Zambia and applies the Just and Pope model to determine how rainfall and temperature affect yield and yield variability of maize and beans at the national and subnational levels. Results show a negative impact of temperature rise on yield and a positive impact of rainfall rise on yield, above the current mean levels. These results differ by agro-ecological region. Worst-case-scenario predicted impacts using HadGEM-ES2 global circulation model show that major yield decreases (25% for maize and 34% for beans) by 2050 will be in region II and will be driven mainly by temperature increase offsetting the positive gains from rainfall increase. The model mainly under-predicts yield for maize and overpredicts yield for beans. These findings call for agro-ecological region-specific adaptation strategies and well-planned policy interventions to make agriculture more resilient to climate change.

We consider the propagation of electromagnetic waves in the Friedman – Lemaître – Robertson – Walker metric. The exact solutions for plane and spherical wave are written down. The corresponding redshift, amplitude change, and dispersion are discussed. We also speculate about the connection of the electromagnetic wave equation to the Klein–Gordon equation.

This research analyses extreme precipitation events in the Huaihe River Basin in China, a densely populated region with a history of human settlements and agricultural activities. This study aims to explore the impact of extreme precipitation index changes and provide decision-making suggestions for flood early warning and agricultural development in the Huaihe River Basin. The study utilises the NEX-GDDP-CMIP6 climate models dataset and the daily value dataset (V3.0) from China's national surface weather stations to investigate temporal and spatial changes in extreme precipitation indices from 1960 to 2014 and future projections. At the same time, this study adopted the RclimDex model, Taylor diagram and Sen+Mann-Kendall trend analysis research methods to analyse the data. The results reveal a slight increase in extreme precipitation indices from northwest to southeast within the basin, except for CDD, which shows a decreasing trend. Regarding spatial, the future increase of extreme precipitation in the Huaihe River Basin will show a spatial variation characteristic that decreases from northwest to southeast. These findings suggest that extreme precipitation events are intensifying in the region. Understanding these trends and their implications is vital for adaptation strategy planning and mitigating the risks associated with extreme precipitation events in the Huaihe River Basin.

Worldwide, it is estimated that at least 1 in 4 adults suffers from hypertension, and this number is expected to increase as populations grow and age. Blood pressure (BP) possesses substantial heritability, but is also heavily modulated by lifestyle factors. As such, digital, lifestyle-based in-terventions are a promising alternative to standard care for hypertension prevention and man-agement. In this study we assessed the prevalence of elevated and high BP in a Dutch general pop-ulation cohort undergoing a health screening, and observed the effects of a subsequent self-initiated, digitally-enabled lifestyle program on BP regulation. Baseline data were available for 348 participants, of which 56 had partaken in a BP-focused lifestyle program and got re-measured 10 months after the intervention. Participants with elevated SBP and DBP at baseline showed a mean decrease of 7.2 mmHg and 5.4 mmHg, respectively. Additionally, 70% and 72.5% of participants showed an improvement in systolic and diastolic BP at remeasurement. These improvements in BP are superior to those seen in other recent studies. The long-term sustainability and the efficacy of this and similar digital lifestyle interventions will need to be estab-lished in additional, larger studies.

Wildfires are a rising environmental threat which health impact remains poorly documented, in particular beyond the fire period. This ecological study investigates changes in health conditions before, during, and after two consecutive wildfires that occurred in France´s Gironde district in the summer 2022. Electronic records from the district´s emergency medical communication centre were used to identify calls with respiratory and cardiovascular diseases, and two specific subgroups of those, asthma (all ages and 0-5 years) and cardiac arrest, respectively. Compared to before the fires, respiratory disease cases were fewer during each fire (OR = 0.85, 95% CI: 0.79, 0.90 and OR = 0.62, 95% CI: 0.58, 0.67, respectively), cardiovascular disease cases, more common during the second fire, and asthma cases, higher following the fires (ORall ages= 1.85, 95% CI: 1.56, 2.21 and ORchildren= 3.52, 95% CI: 2.62, 4.80). Asthma cases also rose during the same calendar time in 2021, but to a lesser extent. In sum, except for asthma, emergency calls data in Gironde reveal few significant potentially smoke-related symptoms around fire periods, apart from post-fire asthma. Whether the effects are smoke- or season-related remains to be determined, preferably using additional data sources.

The study examines projected changes in dry- and wet-spell probabilities in West Africa using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. The results show an increase in the probability of having a dry day, a dry day preceding a wet day and a dry day preceding a dry day, and a decrease in the probability of wet days in the Sahel region under anthropogenic forcing scenarios RCP4.5 and RCP8.5. The decrease in wet days is stronger in the far future and under the RCP8.5 scenario (up to -30%). The study also finds that the probability of consecutive dry days (lasting at least 7 days and 10 days) is expected to increase in the Western Sahel, the Central Sahel, and the Sudanian Area under both scenarios, with stronger increases in the RCP8.5 scenario. In contrast, the decrease is expected over the Guinea Coast, with the changes more important under the RCP4.5. These changes in dry- and wet-spell probabilities are important for water management decisions and risk reduction in the energy and agricultural sectors. The study also highlights the need for decision-makers to implement mitigation and adaptation policies to minimize the adverse effects of climate change.

Evaluating of long-term satellite-derived ocean color products using in-situ measurements is essential to ensure data quality and integrity. In this study, the Visible Infrared Imaging Radiometer Suite (VIIRS) remote sensing reflectance (Rrs) products were evaluated and analyzed by using long-term OC-CCI in-situ data from 2012 to 2021. The results demonstrate that the root mean square difference of VIIRS Rrs product accuracy in most bands is better than 0.002 (sr-1) when considering its average life span of 12 years. However, the VIIRS Rrs products in shorter wavelength bands (e.g., at 412 nm) had significantly lower accuracy in general and a long-term bias over the recent years. The annual precision of VIIRS Rrs products showed a declining trend especially in coastal or eutrophic waters. This accuracy deterioration of the VIIRS Rrs products suggests a strong need for continuous monitoring of its performance and further efforts on improving the atmospheric correction algorithm to specifically deal with satellite records at high SZAs and OZAs.

Deforestation brings vast and detrimental impact on the environment, economy, and social aspects of community. Thus, it is important to assess and analyze deforestation to inform the decision maker that oversees issued policy and development strategies. The present study aims to characterize deforestation in Central Kalimantan between 2006 - 2020. Utilized land cover map issued by Indonesian Ministry of Environment and Forestry, we analyzed the change in natural forest cover using Remote Sensing and Geographical Information System (GIS) to find the rate the trend, location, and land cover replacement of deforestation in Central Kalimantan Province, Indonesia. The research found that during the period Central Kalimantan lost 1.5 million ha of natural forest with the rate of deforestation 117,000 ha/year. In general, the deforestation shown decrease trend and fluctuated during the period. Deforestation majority takes place at secondary swamp and dry forest that are located at south part of the island. Most of deforestation resulted shrubs, plantations, and agriculture land. The finding of this research could be used as a base to determine the target location for rehabilitation strategy and approach to prevent further deforestation.

Decapod assemblages in Zostera marina beds from two bays adjacent to unvegetated habitats were investigated to assess their influence on decapod assemblages. Thirty-eight decapod species belonging to 4 taxa were collected using a small beam trawl at four habitat types from two different locations off the coast of Namhae Island, southern Korea. Dominant decapod taxon at all habitats was the caridean shrimps, with Eualus leptognathus, Heptacarpus pandaloides, Latreutes anoplonyx, La. laminirostris and Palaemon macrodactylus being the most abundant caridean species. Crabs were characterized by the highest biomass, but moderate species richness and abundance. Penaeoids and sergestoids shrimps only accounted for <1% of the total decapod abundance. The number of species, their abundance, and the diversity of decapod assemblages varied greatly by habitat type, season, and diel patterns. Species number and abundance peaked in seagrass beds of southern exposed bays during the autumn, and were lowest in unvegetated habitats during the summer months. Diel decapod species and catch rates were higher at night. Dense seagrass vegetation and nighttime supported greater decapod species richness and higher mean densities, but not diversity. Multivariate analyses revealed that habitat type and season significantly affected the structure of decapod assemblages, but diel patterns had a minor influence. Among decapod species, Pa. macrodactylus and Pugettia quadridens characterized the decapod assemblages in seagrass beds at the northern semi-closed bay, while Telmessus acutidens, Crangon affinis, Cr. hakodatei, Charybdis japonica and Portunus sanguinolentus were significantly associated with both vegetated and unvegetated habitats at the southern exposed bay, with the former two species more abundant during winter and spring.

The once near-extinct Russell’s viper has recently come back to the area beyond its historical range. A couple of decades ago, its distribution was confined to 11 districts of Bangladesh. Hence, the study aims to update the distributional map of Russell’s Viper (Daboia russelii) across the country and find out the surges' causal factors. Both primary and secondary data were utilized in this study. It revealed that the distributional range of this snake was expanded from 22 to 33 districts in 2024. The respondents noted that climatic stressors like high humidity accompanied by hot weather, increased salinity, and increased frequency of flooding facilitated the spreading of the viper across the country. The cropping pattern and crop diversification were another major contributing factor. The shifting of the single-cropped area to a multi-cropped area in the Barind tract increased its main prey rats. Contrarily, the killing of natural predators such as foxes, monitor lizards and mongoose led to the rise in the snake population. The destruction of vegetation coverage in the upper part of the Padma Basin facilitated the movement of Russell's vipers downstream.

In the case of indigenous grapevine varieties, the aim of clonal selection is twofold: to improve their technological cultivation problem while preserving the varietal character. As the sensitivity of perennial crops to climate change becomes more pronounced, clonal selection, which is already very time-consuming for perennial woody crops, may take even longer. In Badacsony, clonal selection breeding of the ‘Kéknyelű’ and ‘Juhfark’ varieties was started in the early 2000s. The problem mentioned above in cultivation technology is the poor fertility of ‘Kéknyelű’ (functionally female-flowered variety), while in the case of ‘Juhfark’ the high susceptibility to grey rot (Botrytis). Based on 11 years of data significant difference in yield between clone B.2. and the base variety was found. In this comparison the year clusters also gave different values, as in years belonging to cluster 1 the ’Kéknyelű’ yielded more than in another year. Both clones of ‘Kéknyelű’ matured with significantly lower pH compared to the base variety. ‘Kéknyelű' is renowned for the distinctive variety character of its wine, which is said to be acidic. Given the acidic nature of ‘Kéknyelű’ wine and the expected increase in must degrees and pH due to climate change, these distinctions may be beneficial in the future. Daily meteorological parameters were also recorded in the years under study, and different indexes were calculated for both of varieties for different phenological periods. The years were classified into 3 clusters and the harvest data were analyzed within each cluster. In the case of 'Kéknyelű' our results revealed significant differences in yield between vintage clusters for clone B.2. However, clone B.1 demonstrated distinct KMW and pH values. Both 'Kéknyelű’ clones have produced a substantially higher incidence of Botrytis infection in cluster 2 years than in cluster 3 years. Botrytis infection only showed statistically significant differences between year clusters for ‘Juhfark’. It is intriguing that in most years, the rotting rate was lower in both clones, especially in year clusters 1 and 3 when the overall rate of Botrytis infection was quite low. Our results highlighted the year-round sensitivity of the two varieties studied and the difficulties of clonal selection.

Training supervised machine learning models requires labeled examples. A judicious choice of examples is helpful when there is a significant cost associated with assigning labels. This article improves upon a promising extant method – Batch-mode Expected Model Change Maximization (B-EMCM) method – for selecting examples to be labeled for regression problems. Specifically, it develops and evaluates alternate strategies for adaptively selecting batch size in B-EMCM. By determining the cumulative error that occurs from the estimation of the stochastic gradient descent, a stop criteria for each iteration of the batch can be specified to ensure that selected candidates are the most beneficial to model learning. This new methodology is compared to B-EMCM via mean absolute error and root mean square error over ten iterations benchmarked against machine learning data sets. Using multiple data sets and metrics across all methods, one variation of AB-EMCM, the max bound of the accumulated error (AB-EMCM Max), showed the best results for an adaptive batch approach. It achieved better root mean squared error (RMSE) and mean absolute error (MAE) than the other adaptive and non-adaptive batch methods while reaching the result in nearly the same number of iterations as the non-adaptive batch methods.

Indirect effects of global change via changing species interactions have been largely ignored in studies predicting global change impacts on ecosystems. Antagonistic biotic interactions, however, can strongly affect ecosystems and are likely to be affected by global change drivers themselves. We synthesize current knowledge on the impact of invertebrate herbivores and pathogens on plant productivity, diversity and community composition, and outline theory and expectations on how important global change drivers – nitrogen enrichment, climate change and elevated CO², and plant and insect diversity loss, may affect enemy impact on plant communities. We illustrate that our ability to predict global change impact requires a holistic perspective, taking into account direct as well as indirect effects via the biotic component of ecosystems.

Dioscorea composita is a plant native to México and Central America with a high concentration of diosgenin precursors. Currently, México is one of the two most important countries producers of this yam; however, climate change is altering the environmental conditions of its natural habits, threatening its preservation and productivity. This is why this research was focused to characterize the eco-geography of D. composita and predict its potential geographic distribution under climate change scenarios in México-Central America. A collection of 408 geo-referenced accessions was used to determine its climatic adaptation, ecological descriptors, and the current and future potential geographic distribution, which was modeled with MaxEnt model through the Kuenm R-package. For future climate scenarios, an ensemble of the GCMs HadGEM-ES and CCSM4 was used. Results showed that D. composita adapts to warm humid and very humid agro-climates and that the most contributing variables for its presence are annual and seasonal moisture availability indices, seasonal photoperiod, annual thermal range, Bio14 and Bio11. The year 2050 RCP 4.5 climate scenario would contract the potential distribution of D. composita, whilst the 2050 RCP 8.5 scenario would expand it, indicating that this species could be a good crop option under this scenario of emissions.

Large ruminant production in developing countries is inefficient with low growth rates and likely high greenhouse gas emissions (GHGe) per unit of meat or milk produced. Trials conducted in Lao PDR from 2017-2020, studied ad-libitum supplementation for 12 weeks with 20kg high quality molasses nutrient blocks (MNB; Four Seasons Pty Ltd, Brisbane, Australia), that were either: non-medicated (NMB); fenbendazole-medicated (FMB5, Panacur100®, Coopers Australia, @ 5g/kg); triclabendazole-medicated (TMB5 or TMB10, Fasinex®, Novartis Australia, @ 5g/kg or @ 10g/kg, respectively); or formulated with urea (UMB8 or UMB10 @ 8% or 10% urea, respectively). Average daily gains (ADG) were determined for access to all MNB’s and compared with access to NMB’s, no supplementation, or previously determined free-grazing baseline ADG’s (55–84g in cattle; 92–106g in buffalo). ADGs were significantly improved following access to all MNBs for periods up to 12wks. ADGs following access to UMB8 or NMB were calculated for three age cohorts of cattle: young calves <8m (238-298g), growing cattle (143-214g) and lactating cows (179-191g). Modelling using IPCC Inventory software model V 2.69 of published data demonstrated a conservative net abatement of 350kg CO2e was achievable over a 200 day feeding period. An additional trial of Emissions control blocks (EMB’s, n = 200) distributed to farmers (n = 60) and two educational institutions, was conducted. Consumption rates (156g/day) and farmer and institutional acceptance of EMB’s were similar to published findings with other MNB’s, confirming all MNB’s and EMB’s improved animal productivity and body condition score, with healthier animals that were easier to manage. Modelling of changes in GHGe intensity identified an abatement of 470kg CO2e per EMB consumed, delivering a total project emissions abatement of 94t CO2e. Provision of MNBs and EMBs in smallholder large ruminant production systems is likely to achieve impressive abatement of GHGe due to improved efficiency of rumen fermentation and productivity.

Abstract: Floods can be defined as one of the most frequent and destructive disasters, that cause significant damage to people, while droughts present significant challenges in first place to most vulnerable communities. In consequence, state public policies are essential to manage the risk in the face of both phenomena and contribute to the construction of resilient communities. As a request of the National Water Commission of Mexico (CONAGUA) for the Regional Water Plan (PHR), we designed and applied a methodology based on virtual consultation fora in conjunction with digital survey tools to understand the population's perception of these phenomena. The workshops were organized in the five municipalities of Baja California Sur. Then, we performed an interdisciplinary analysis that combines hydrological considerations with the most critical social, economic, environmental, and law components, applying the PESTEL analysis. The results indicate that there is a clear and widespread awareness that floods and droughts increase the risk to the livelihoods of the population; however, there are deficiencies in different areas, which complicates risk management. Timely information and the inclusion of communities in mitigation and adaptation proposals would allow for achieving more successful cases with the efforts to minimize vulnerabilities and increase the resilience of the population in the face of a changing climate. This must be a collaborative work of the entire society, governmental, social, and private stakeholders.

The investigation of submerged speleothems for sea level studies has made significant contributions to the understanding of the global and regional sea level variations during the Middle and Late Quateranry. This has been especially the case for the Mediterranean Sea, where more than 300 submerged speleothems sampled in 32 caves have been analysed so far. Here, we present a comprehensive review of the results obtained from the study of submerged speleothems since 1978. The studied speleothems cover the last 1.4 Ma and are focused mainly on Marine Isotope Stages (MIS) 1, 2, 3, 5.1, 5.3, 5.5, 7.1, 7.2, 7.3 and 7.5. Results reveal that submerged speleothems represent extraordinary archives providing accurate information on former sea level changes, also considering that the Mediterranean Sea is devoid of any tropical corals since the Miocene. New results from a stalagmite collected at Palinuro (Campania, Italy) characterized by marine overgrowth are also reported. The measured elevations of speleothems are contaminated by the local response to glacial- and hydro-isostatic adjustment (GIA), and thus might significantly deviate from the global eustatic signal. Age and altitude comparation between Mediterranean speleothems, flowstone from Bahamas with local GIA provide a new scenario for MIS 5 and 7 sea level reconstrutions.

Oncology clinical pharmacists are uniquely positioned to make interventions to increase patient activation and engagement. To accomplish this goal, pharmacists can target health system-related, provider-related, and patient-related factors to help enhance patient-centered care and drive behavioral health changes. Interventions that pharmacists must tackle include educating team members and patients on the medication acquisition process, communicating urgency of treatment, optimizing workflows, facilitating guideline recommendations, preventing, and managing treatment toxicities, and promoting patient self-advocacy through education and shared decision-making. As crucial members of the healthcare team, oncology clinical pharmacists can simplify highly complex treatment regimens to facilitate and optimize patients’ ownership of their care. This review will focus on the example of venetoclax treatment in acute myeloid leukemia to demonstrate the impact that pharmacists provide that leads to behavioral change of patients and clinicians.

The necessity for precise and current data concerning the dynamics of land cover change in Indonesia is crucial for efforts to reduce natural vegetation cover due to agricultural expansion. The functionality of monitoring systems that incorporate Terra-MODIS is currently compromised by the limited availability of data for the immediate future. This study seeks to assess the potential of VIIRS satellite imagery in developing an early warning system for monitoring vegetation cover change in Indonesia. The Normalized Differential Open Area Index (NDOAI) computed from the 8-day’ VIIRS data was employed to detect changes in vegetation cover based on pixel-by-pixel subtraction in the NDOAI data time series. Evaluating the pixel-level accuracy of change detection is complicated due to the fact that we evaluate a change map at a coarser resolution than the Landsat-based reference map. The results revealed that increasing the threshold percentage is associated with improved accuracy. In change detection, there is often a trade-off between accuracy and sensitivity. A threshold that is too low may result in false positives, while a threshold that is too high may lead to missed changes. This study demonstrates that when a threshold value of less than 20% is applied, Landsat can identify vegetation cover changes at an earlier stage. Conversely, when a threshold value greater than 20% is employed, VIIRS will detect the change 4.5 days earlier than Landsat. Additionally, VIIRS is capable of detecting changes 25.4 days and 54.8 days faster than Landsat, respectively, when using thresholds of 40% and 75%.

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 &lt;.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.

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.

Based on the daily observation data of 2254 meteorological stations in China from 1961 to 2021 after homogenization and correction, the extreme value analysis method that combines relative threshold and absolute threshold was used to identify extreme climate events in the mainland of China, namely extreme high temperature, extreme low temperature, extreme drought, extreme precipitation and extreme typhoon events. The frequency and linear variation trends of individual extreme events in the past 60 years were investigated. On this basis, the multi extreme events composite risk grade index (MXCI) was constructed, which can objectively reflect the comprehensive characteristics of multi extreme climate events in different regions. The results show that the high value areas of MXCI were mainly located in Southeast China and Southwest China. The MXCI presented a decreasing trend in most of the western and southeastern regions of China, while an increasing trend from Southwest China to the south of Northeast China, due to the frequent occurrence of extreme high temperature, extreme drought and other extreme events in these regions.

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.

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.

The spatial segregation is a characteristic of Latin American cities, resulting in distinct dynamics of social inclusion and exclusion at both spatial and identity levels. Then, specific green spaces may convert into appreciated and contested territories, where various actors negotiate their uses and regulations. Considering a case-study in a green icon of the metropolitan city of Santiago de Chile, the main objective of the present study was to describe and comprehend the uses and meanings of the Quebrada Macul park among different social groups over the past two decades. We employed qualitative methods including six in-depth interviews with key informants (social and ecological leaders, historical neighbors, and park workers), five participant observations in the park, and statistical analysis of visitors. Results reveal that (1) the transition of being a popularly used hill to a metropolitan park rises tensions between public and private statuses of place; (2) conflicts emerge regarding who uses the space and how, reflecting power dynamics among different social groups; (3) the park, beyond being a public space, holds significant identity value for its historical residents, both for those who fought for its recovery and those who have lived closely, so processes of forgetfulness might be resentful. We conclude on enduring meanings of the park associated with the struggle for the place among different groups, highlighting the role of memory for the social integration of groups among natural spaces.

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.

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.

Monitoring lakes in high-latitude areas can provide a better understanding of freshwater systems sensitivity and accrete knowledge on climate change impacts. Phytoplankton are sensitive to various conditions: warmer temperatures, earlier ice-melt and changing nutrient sources. Satellite imagery can monitor algae biomass over large areas. The detection of chlorophyll a (chl-a) concentrations in small lakes is hindered by the low spatial resolution of conventional ocean colour satellites. The short time-series of the newest generation of space-borne sensors (e.g. Sentinel-2) is a bottleneck for assessing long-term trends. Although previous studies have evaluated the use of high-resolution sensors for assessing lakes' chl-a, it is still unclear how the spatial and temporal variability of chl-a concentration affect the performance of satellite estimates. We discuss the suitability of Landsat (LT) 30-m resolution imagery to assess lakes' chl-a concentrations under varying trophic conditions, across extensive high-latitude areas in Finland. We use in situ data obtained from field campaigns in 19 lakes and generate remote sensing estimates of chl-a, taking advantage of the long-time span of the LT 5 and 7 archives, from 1984 to 2017. Our results show that linear models based on LT data can explain approximately 50 % of the chl-a interannual variability. However, we demonstrate that the accuracy of the estimates is dependent on the lake's trophic state, with models performing in average twice as better in lakes with higher chl-a concentration (> 20 µg/l) in comparison with less eutrophic lakes. Finally, we demonstrate that linear models based on LT data can achieve high accuracy (R2 = 0.9; p-value < 0.05) in determining lakes' annual mean chl-a concentration, allowing the mapping of the trophic state of lakes across large regions. Given the long time-series and high spatial resolution, LT-based estimates of chl-a provide a tool for assessing the impacts of environmental change.

In this work commercial 18650 lithium-ion cells with LiMn₂O₄, LiFePO₄ and Li(Ni_0.33Mn_0.33Co_0.33)O₂ cathodes were exposed to external heating in an Accelerating Rate Calorimeter (es-ARC, THT Company) to investigate the thermal behavior under abuse conditions. New procedures for measuring external and internal pressure change of cells were developed. The external pressure was measured utilizing a gas-tight cylinder inside the calorimeter chamber in order to detect venting of the cells. For internal pressure measurements, a pressure line connected to a pressure transducer was directly inserted into the cell. During the thermal runaway experiments, three stages (low rate, medium rate and high rate reaction) have been observed. Both pressure and temperature change indicated different stages of exothermic reactions, which produced gases or/and heat. The onset temperature of thermal runaway was estimated according to temperature and pressure changes. Moreover, the different activation energies for the exothermic reactions could be derived from Arrhenius plots.

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.

Oenothera flower petals change color during senescence. When in full bloom, the flowers of O. tetraptera are white and those of O. laciniata and O. stricta are yellow; however, the colors change to pink and orange, respectively, when the petals fade. We analyzed the flavonoid components in these petals as a function of senescence using HPLC-DAD and LC-MS. In all three species, cyanidin 3-glucoside (Cy3G) was found in faded petals, and the content of Cy3G increased in senescence. In full bloom (0 h), no Cy3G was detected in any of the petals, but after 12 h, the content of Cy3G in O. tetraptera was 0.97 μmol/gFW and that in O. laciniata was 1.82 μmol/gFW. Together with anthocyanins, major flavonoid components in petals were identified. Quercitrin was detected in the petals of O. tetraptera, and isosalipurposide was found in the petals of O. laciniata and O. stricta. The content of quercitrin did not change during senescence, but that of isosalipurposide in O. laciniata increased from 3.4 μmol/gFW at 0 h to 4.8 μmol/gFW at 12 h. The color change in all the three Oenothera flowers was confirmed to be due to the de novo biosynthesis of Cy3G.

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.

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’.

The energy crisis is currently a major topic in scientific and managerial discussions in the building and construction industry. While employing low-cost strategies for reducing energy usage is beneficial for principals and decision-makers, the primary purpose of this study is to recommend the use of phase change materials (PCM) to improve cooling and heating load management in buildings. In order to accomplish this, the study applies design-builder simulations to a developing country case study. The results indicate that integrating PCM in buildings can reduce energy usage by around 6 percent. Although this value may be lower than other techniques, it is nevertheless important for reaching green building goals in both developed and developing nations. The case study, which takes place in a four-season region, demonstrates the significant potential of the PCM system for both cooling and heating energy management. In addition, the reciprocal performance improvement of PCMs is a remarkable characteristic, especially when contrasted to some conventional systems that focus on a single energy management objective in buildings. Lastly, it should be underlined that the suggested platform is consistent with Sustainable Development Goal 7 (Affordable and Clean Energy Targets).

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.

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.

As novel materials for carbon capture, phase change solvents can separate into two immiscible phases during the CO2 capturing procedure under a certain temperature. The solvent systems can significantly decrease the energy consumption since the solvents can be regenerated by only heating the rich-CO2 phase. In this work, amino acid ionic liquids (AAILs) were synthesized using quaternary ammonium salts and amino acids as raw materials, and the aqueous solutions were prepared as novel liquid-solid phase change solvents. The results showed that the solvents had excellent CO2 absorption capacity, and the AAILs functionalized by glycine and tryptophan exhibited significant phase change properties. The mechanism of phase-change of the solvent were mainly due to the lower solubility of the product after reaction between AAILs and CO2. The solvent with tryptophan as anion could be regenerated by only heating the CO2-riched solid phase, which might significantly decrease energy consumption of regeneration. And the absorbent could be reused with the regenerated absorption ratio up to 79%. The solvent system has great potential in industrial application due to the easy operation process and efficient recycling ability.

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.

According to the World Food Programme (WFP), the projected increase in the human population stands at 2 billion people by 2050. At the same time, world food production is witnessing a declining trend over recent years, and 690 million (8.9%) of the world's population are already in severe starvation. Climate variability and climate change impacts on food security are very eminent today. For this reason, this study explored the real effects of climate variability and change on food security in Africa by applying the system Generalized Method of Moments (GMM) and the Panel Corrected Standard Errors (PCSEs) estimators on data from 2001–2018 for 38 selected African countries. The findings reveal that higher amounts of precipitation positively influence food security along two dimensions (food availability and utilization). Hotter temperatures negatively impact food availability and utilization. However, it aids food accessibility in Africa. Similarly, carbon dioxide emissions improve food availability and are harmful to food accessibility and food utilization in Africa. Consequently, the effects of climate variability and change on food security in Africa are undesirable, thereby putting the continent at risk of food insecurity over the long run. Given these findings, the study made appropriate recommendations for policy change to address the negative effects of climate variability and change on food security in Africa.

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.

Background: Globally, women’s responsibility for unpaid care work (UCW) remains a barrier to gender equality and women’s empowerment. Rwanda, a low-income country, has a legal and policy framework for promoting gender equality but remains a patriarchal society with women responsible for UCW. Reseaux des Femmes, a local NGO, has been delivering a programme targeted at reducing and redistributing the UCW of women with the objective of gender transformational change. However, there has been no impact evaluation of their intervention to date. Methods/Design: The impact evaluation will be a proof-of-concept critical realist cluster control trial (CRcCT) to evaluate for which women, how and under what circumstances the intervention reduces and redistributes women’s UCW, promote gender equality and women’s empowerment, and improves women’s quality of life. Four clusters of villages in each of five districts in Rwanda will be randomly allocated to the intervention or control arms, and all eligible households, those headed by a couple with at least one child under 12 years, will be recruited. This will yield a sample of around 550 intervention households and 550 control. Discussion: This protocol describes the design of mixed-methods research to evaluate an intervention in Rwanda aimed at reducing and redistributing the time women spend on UCW, thereby promoting gender equality and women’s empowerment. This paper will contribute to our understanding of interventions for transforming gender relations from a scholarly perspective. From a policy perspective, it will act as a proof of concept of Reseaux des Femmes’ Programme.

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.

The phytoplankton community in 66 reservoirs ubicated at the hydrographic basin of the Ebro River (Spain) was analyzed. Samples were collected in the summer season during the period 2010-2015, with the main purpose of evaluate the Trophic State and Ecological Potential according to the Water Framework Directive of the European Union. In this work we presented a representative overview of several consecutive years of the state of the reservoirs and their associated trophic status; methodology was to obtain statistically significant relationships between the phytoplankton community and main physicochemical water quality variables (water transparency, pH, chlorophyll a, total and soluble phosphorus, anoxic zone depth, nitrite, nitrate and ammonium concentrations). We provide data for retrospective comparative of the state of the reservoirs with previous and current studies in order to improve the management of these reservoirs, and to serve as data reference for future works in a context of global change (climate and pollution).

Strategies implemented worldwide to contain COVID-19 outbreaks varied in severity across different countries, and established a new normal for work and school life (i.e. from home) for many people, reducing opportunities for physical activity. Positive relationships of physical activity with both mental and physical health are well recognised, therefore the aim was to ascertain how New Zealand’s lockdown restrictions impacted physical activity and mental health and wellbeing. Participants (n=4007; mean±SD: age 46.5±14.7y, 72% female, 80.7% New Zealand European) completed (10–26 April 2020) an online amalgamated survey (Qualtrics): International Physical Activity Questionnaire: Short Form; Depression, Anxiety and Stress Scale-9; World Health Organization-Five Well-being Index; Stages of Change Scale. Positive dose response relationships between physical activity levels and wellbeing scores were demonstrated for estimates that were unadjusted (moderate activity OR 3.79, CI 2.88-4.92; high activity OR 8.04, CI 6.07-10.7) and adjusted (confounding variables: age, gender, socioeconomic status, time sitting, co-morbidities) (moderate activity 1.57, CI 1.11-2.52; high activity 2.85, CI 1.97-4.14). The study results support previous research demonstrating beneficial effects of regular physical activity on mental health and wellbeing. Governments may use such results to promote meeting physical activity guidelines in order to protect mental health and wellbeing during the ongoing COVID-19 and future pandemics.

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.

Land use land cover (LULC) changes are highly pronounced in African countries, as they are characterized by an agriculture-based economy and a rapidly growing population. Understanding how land use/cover change (LULCC) influence watershed hydrology will enable local governments and policymakers to formulate and implement effective and appropriate response strategies to minimize the undesirable effects of future land use/cover change or modification and sustain the local socio-economic situation. The hydrological response of the Ethiopia Fincha’a watershed to LULCC happened during the last 30 years was investigated comparing the situation in three reference years: 1994, 2004 and 2018. The information was derived from Landsat sensors, respectively Landsat 5 TM, Landsat 7 ETM and Landsat 8 OLI/TIRS. The various LULC classes were derived via ArcGIS using a supervised classification system, and the accuracy assessment was done using confusion matrixes. For all the years investigated the overall accuracies and the kappa coefficients were higher than 80%, with 2018 as the more accurate year. The analysis of LULCC revealed that forest decreased by 19.99% between the years 1994-2004, and it decreased by 11.85% in the following period 2004-2018. Such decline in areas covered by forest is correlated to an expansion of cultivated land by 16.4% and 10.81%, respectively. After having evaluated the LULCC at the basin scale, the watershed was divided into 18 sub-watersheds, which contained 176 Hydrologic Response Units (HRUs), having a specific LULC. Accounting for such a detailed subdivision of the Fincha’a watershed, the SWAT model was firstly calibrated and validated on past data, and then applied to infer information on the hydrological response of each HRU on LULCC. The modelling results pointed out a general increase of average water flow, both during dry and wet periods, as a consequence of a shift of land coverage from forest and grass towards settlements and build-up areas. The present analysis pointed out the need of accounting for past and future LULCC in modelling the hydrological responses of rivers at the watershed scale.

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.

In Korea, laver (Gim) is the leading traded marine product and an important food source, accounting for 82.0% of the world’s exports. Laver exports reached $100 million in 2010 and steadily increased to $600 million in 2020. An increase in laver exports improves the income of laver farmers and promotes the growth of fisheries. However, marine algae are vulnerable to climate change. In this study, we aimed to predict changes in laver production due to climate change using environmental variables, including water temperature, rainfall, and sunlight duration. The results showed that water temperature considerably affected laver production; when water temperature increased by 1 °C, production decreased by 13.78% (t) in the same month. By contrast, when sunlight duration and rainfall increased by 1 h and 1 mm, respectively, 1 month before harvesting laver, production increased by 0.32% (t-1) and 0.13% (t-1), respectively. Using four scenarios based on climate change published by the Intergovernmental Panel on Climate Change in a modeling exercise, we found that laver production in 2100 in Wando in Korea may decline by 73.3% owing to water temperature changes (based on 2020 production), threatening food security. Accordingly, short-, mid-, and long-term countermeasures are needed for sustainable laver aquaculture. Appropriate water temperature (21–22 °C) during seeding is necessary to control environmental variables, based on scientific data and activation of land-based seeding methods. Moreover, mid- and long-term countermeasures should include development of high-temperature resistant laver seeds, identification of suitable new laver aquaculture grounds, and research on seeds that can adapt to climate change.

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.

It was believed that the construction of large dams in the upper tributary basin of the Chao Phraya River (CPR) has caused sediment load reduction in the CPR system by 75–85%. Based on historical and observed river flow and sediment data measured during 1922–2019, we investigated the effects of three large dams, the Sirikit, Naresuan, and Khwae Noi dams, on river runoff and sediment loads supplied to the CPR using Mann-Kendall (MK) test and the double mass curve (DMC). Results from this study revealed that the Nan River contributed approximately 40% and 57% of the runoff and total sediment load (TSL) to the CPR, respectively. The water regulation by the Naresuan diversion dam has mainly caused the reduction on annual runoff and TSL downstream of each dam. The results from this study also reveal that the sediment load observed at the headwater (C.2) of the CPR still increased after the construction of the Sirikit dam due to the expansion of irrigation areas downstream of the dam and the channel improvement in the lower reach of Nan River. After the three major dams were operated, the sediment load at C.2 reduced by 31% compared that discharging during the pre-construction period.

Coastal environments are complex systems that are influenced by a combination of natural processes and human activities. Scientific interest in the effects of coastal erosion/accretion and climatic change-related processes greatly increased in recent decades due to the growing human development along coastal areas. This paper investigates the state and evolution of beach-dune systems for the 1977-2001 and 2001-2019 periods of the Mediterranean coast of Andalusia (Spain) using two different proxies: the dune toe line, which was used to track foredunes evolution, and the high-water line, which was used to assess shoreline evolution. Results showed a general erosional behavior of the studied beach-dune systems and identified cases where the main trend was altered through human interventions. In the 1977-2001 period, 54% of foredunes showed erosion, 24% accretion and 22% stability while and 34% of shorelines showed erosion, 40% accretion and 34% stability. In the 2001-2019 period, 42% of foredunes showed erosion, 28% accretion and 30% stability, and 40% of shorelines showed erosion, 34% accretion and 26% stability. Combining the evolution classes of each proxy (dune toe/shoreline) allows the behavior of both shoreline proxies to be assed together and provides insights additional to those derive from the use of a single proxy. In this regard, Erosion/Erosion (EE) was the most frequent behavior, with 25% and 27% in the first and second periods respectively, and Accretion/Accretion (AA), with 17% in both periods. Erosion of foredunes combined with stability or accretion of the shoreline (ES and EA) were the most common pairings in the first period, while stability of dunes combined with accretion of the shoreline (SA) and Stability/Stability (SS) dominated in the second period. The results obtained provide additional insights on the nature and drivers of coastal change that aid local coastal managers and administrations in understanding erosion processes. The method can be applied at other areas around the world where a similar data base is available.

This paper attempts to alter a prevailing assumption that buildings use energy to an understanding that in fact, people use energy. Therefore, to successfully accelerate the transition to a low-carbon society and economy more emphasis should be on motivating people and increasing their awareness by making them energy conscious building users and therefore active players in the energy transition process. In this context, this paper provides insights from the Horizon 2020 MOBISTYLE project. It demonstrates research and development approaches, highlights the main project objectives, and presents findings of an ethnographic (qualitative) study of users’ habits, practices, and needs. The aim of the project is to motivate behavioural change by raising consumer awareness through the provision of attractive personalized information on user’s energy use, indoor environment and health, all enabled by an integrated information and communication technology (ICT) service. In this context, the anthropological people-centred approach is integrated into the MOBISTYLE approach putting users at the centre of the ICT tools development process. The main quantitative objective of the project is a reduction of energy use for at least 16 % prompted by the provision of combined information and feedback systems on energy, indoor environmental quality (IEQ) and health. The most relevant motivational factors and key performance indicators (KPIs) for encouraging a more energy conscious and healthy lifestyle were defined by means of a people-centred approach, adopting anthropological inquiries in different settings. Information about users’ lifestyles and their needs was collected in focus groups with potential users in five case studies, located in different European Union (EU) countries. Behaviour change is achieved through awareness campaigns, which encourage users to be pro-active about their energy consumption and to simultaneously improve health and well-being.

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.

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 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.

This paper describes an entropy equation that can be used for measuring energy. It originated from measuring economy in AI models, where the assumption would be that any organic system makes use of energy efficiency to form its structures. Looking at clustering and cohesion resulted in the equation E = (mean * variance). It was apparent however, that it was a very generic type of equation and it could be adjusted so that distance represents mean. This new version was applied to the domain of physics and the universe, when the equation can support the idea that work is done through the energy released by the 'change' in entropy. A comparison with Einstein's relativity equation is made and also the audacious suggestion that a black hole has only potential energy inside, which converts to kinetic energy after a Big Bang, for example. From that suggestion, a universal theory about state change can be made.

Climate change poses a significant threat to global food security, necessitating a thorough examination across multiple dimensions. Establishing appropriate food security evaluation indicators that align with the evolving concept of food security is imperative. This study enhances food security evaluation by refining a multi-dimensional framework and analyzing the impact of climate change across various regions from 2002 to 2021. By constructing an Food Security Index system composed of a three-tier indicator system and employing the entropy method for weighting, we assess the impacts of climate change on food security using a climate-economic model. Regression analysis reveals a negative linear relationship between mean temperatures and food security (p&lt;0.01), while precipitation impacts food security non-linearly, particularly exhibiting inverse U-shaped patterns in major grain-producing and grain-consuming areas. Extreme high temperatures consistently reduce food security, whereas extreme precipitation displays a complex, statistically significant inverse U-shaped association. In regions where production and consumption are balanced, mean temperatures have a negative effect on food security, while precipitation exhibits a positive correlation, but excessive precipitation can have adverse effects. These findings highlight the intricate interplay between climate change, regional disparities, and food security in China, emphasizing the need to consider multi-dimensional factors and regional variations in addressing food security challenges. These insights are invaluable for policy-making and planning aimed at enhancing food security in China.

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.

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.

This paper aims to study and analyze a new Peltier cell layout using a PCM in biphasic mode, with the liquid phase encapsulating the p-n junctions and the solid one playing the role of heat sink. The selected PCM is an organic compound that operates within a temperature range corresponding to the melting process. The phase change zone encompasses the working temperature of the Peltier cell, avoiding thermal gradient variation across the cell section and maintaining the operating conditions and the cell efficiency. PCM encapsulates the Peltier cell thermocouples, creating a layer that increases the power generation as the thickness reduces. We simulated the performance of the new configuration for different temperature gaps between both sides of the cell, obtaining an improvement in power generation from 1.65 to 7.93. This power increase ratio depends on the temperature gap and transient time to reach the steady working temperature. The control of the layer thickness, transient time, and working temperatures resides in the external heating power source, which varies the operating conditions regulating the heat power and the airflow. Maximum output power from the cell prototype is 36.5 W, while conventional Peltier cells operating in similar conditions produce 7.3 W, which represents a power gain of 500%.

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.

Outbreaks of the desert locust Schistocerca gregaria affect some of the poorest parts of Africa, causing devastating catastrophes. Key to understanding and dealing with this problematic adaptation to environmental changes is comparing locusts that are gregarious (associated with outbreak states) and solitarious (associated with non-outbreak states) either in nature or after experimental treatments in laboratories. Categorising locusts and detecting changes in their phase status is key to such comparisons. Such comparisons are hitherto based on applying mathematical models that use behavioural parameters and that each laboratory has to build a new for each experiment. All such models used thus far for research on locusts are different from each other. That implies differences in the tools used for the different experiments and by the different laboratories and, thus, potential noise in the scientific results and interpretations too. Standardizing the way how we categorise locusts between laboratories and experiments is needed if we want to reduce noise and errors. It is even a must if we are to make the results and interpretations transferable and comparable between experiments and laboratories that work in such an important research area. Here, we use samples from independent S. gregaria population in order to further test the two models that were suggested earlier as standardizing tools for S. gregaria categorization. The outcomes of both models were largely replicated and reproducible. We report on how successful the two models were at categorizing solitarious, intermediate (transient) and gregarious nymph and adult samples. We highlight shortcomings and make more specific recommendations on the use of these models based on the differences they show as to their precision when categorizing the solitarious and gregarious S. gregaria nymph and adult samples.

To explore impact of weight change (WC) on risk of atherosclerosis measured by cIMT, 20,700 participants from the CLSA follow-up were included in analysis. WC was defined as the difference of weight measured at follow-up and baseline, then quartered into four groups (Q1–Q4). cIMT>1.0 mm was defined as high-risk for atherosclerosis. Adjusted odds ratio (OR, [95% CI]) from logistic regression models were used to evaluate the association between WC and risk of atherosclerosis. At follow-up, participants have gained 0.118 kg weight, on average, and 16.4% of them were at high-risk for atherosclerosis. The mean levels of cIMT were comparable between participants from Q1 to Q4. Compared to Q2 (reference), the ORs (95% CI) were 1.00 (0.86, 1.15), 1.19 (1.03,1.38), and 1.25 (1.08,1.45) for Q1, Q3, and Q4, respectively. A similar pattern was observed when analyses conducted by <65 vs. 65+ years separately, but it was weaker for those aged 65+ years. Results from the jointed distribution analyses indicated that weight loss might increase risk for atherosclerosis among participants with obese at baseline, but not for those with cardiovascular events status at baseline. Weight gain, however, would increase risk for atherosclerosis regardless of cardiovascular events status, or overweight/obese at baseline.

While DNA serves as the fundamental genetic blueprint for an organism, it is not a static entity. Gene expression, the process by which genetic information is utilized to create functional products like proteins, can be modulated by a diverse range of environmental factors. Epigenetic mechanisms, encompassing DNA methylation, histone modification, and microRNAs, play a pivotal role in mediating the intricate interplay between the environment and gene expression. Intriguingly, alterations in the epigenome have the potential to be inherited across generations. Ethanol abuse poses significant health issues worldwide. Ethanol has the capability to induce changes in the epigenome, which can be inherited by offspring, thus impacting them even in the absence of direct ethanol exposure. This review article reviewed the alterations caused by ethanol on the epigenome. We thoroughly gathered all relevant papers investigating the behavioral and molecular consequences of parental ethanol exposure on their offspring. In conclusion, the comprehensive analysis of the literature supports the notion that ethanol exposure induces lasting epigenetic alterations, which can influence the behavior and health of future generations. This knowledge emphasizes the significance of addressing the potential transgenerational effects of ethanol and highlights the importance of preventive measures to minimize the adverse impact on offspring.

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.

Abstract: Climate change is one of the main barriers for agricultural production and productivity globally. Hence, understanding farmers’ adoption level of CSA practices and determinants is of highly important for policy decisions. Consequently, the study's purpose was to assess adoption level of multiple CSA practices and determinants of climate-smart agriculture practices in the study area. The study was conducted in Welmera Woreda, Oromia Region, Ethiopia. From the Woreda, three kebeles were identified, and 306 respondent farmers were selected. A cross-sectional household survey, focus group discussion, and key informant interviews were used. Multivariate probit model was used to examine adoption determinants of multiple climate-smart agriculture practices. According to the result, Conservation agriculture, integrated soil fertility management, and crop diversification are the most commonly practiced CSA techniques in the study area. Demographic factors result indicated that being male as compared with female farmers, has positive and significant effect on crop diversification and improved livestock feed and feeding practices. Age of farmers significantly and negatively affecting the probability of adoption of improved soil fertility management practices and crop diversification. However, it affects the adoption of agroforestry practices positively and significantly. Based on the result of economic factors, having relatively large farm land size significantly increases the adoption of conservation agriculture, improved soil fertility management, crop diversification, improved livestock feed and feeding practices, and postharvest technology practice. Better farm income increases the likelihood of uptake of improved livestock feed and feeding. Having a large number of livestock positively influences adoption of conservation agriculture and having access to credit services positively influences the implementation of agroforestry, crop diversification, and postharvest technology. In addition, institutional factors such as access to agricultural extension service and training found that significantly and positively influences the adoption of crop diversification; access to participation on farmers’ field day similarly significantly and positively influence the adoption of both conservation agriculture and improved soil fertility management practice. Awareness creation for farmers and experts about climate change and including location specific CSA practices in to agricultural program is crucial.

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.

In two sequential replicates (n=90 and n=96 feedlot finisher cattle, respectively) we measured the impact of an Enterococcus faecium-based probiotic (DFM) and an altered feedlot pen environment on antimicrobial resistance among fecal enterococci in cattle fed (or, not fed) the macrolide tylosin. Diluted fecal samples were spiral-plated on plain and antibiotic-supplemented m-Enterococcus agar. In the first replicate, tylosin significantly (p&lt;0.05) increased the relative quantity of erythromycin-resistant enterococci. This effect was diminished in cattle fed the DFM in conjunction with tylosin. A similar observed effect was not statistically significant (P &gt; 0.05) in the second replicate. Isolates were speciated and resistance phenotypes were obtained for E. faecium and E. hirae. E. faecium isolates were whole-genome sequenced, which yielded sequence types (ST), resistance genes and phylogeny. Samples of the DFM were sequenced and found to contain E. faecium ST296, which was not present on Day 0 of either replicate. This DFM sequence type was found in fecal samples after Day 0, the majority of which were isolated from cattle in one of the DFM-fed pens. Increased prevalence of ST296 occurred with a concomitant decrease in ST240; of importance, the latter typically harbored both ermB and tet(M) genes.

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.

With the increased use of laterite nickel ore, the impact of high Al2O3 slag on blast furnace smelting has gradually increased. In this paper, the effects of slag basicity and Al2O3 content on slag viscosity and enthalpy change under constant temperature conditions was investigated. The changes in slag structure were analyzed by activation energy and Fourier Transform Infrared (FT-IR) spectroscopy. The relationship between slag components and slag temperature and viscosity when slag heat is reduced was investigated. The results showed that the viscosity first slightly decreased and then significantly increased with increasing basicity at constant temperature. With the addition of Al2O3 content, the viscosity of the slag increases. The activation energy increases with increasing slag basicity and Al2O3. With increasing basicity, the [SiO4]4- tetrahedral unit trough depth becomes shallow, the [AlO4]5- asymmetric stretching band migrates to lower wave numbers, and the slag structure depolymerizes. With the increase of Al2O3 content, the trough of [SiO4]4- tetrahedra deepens and the center of the symmetric stretching band moves to a higher wave number. The [AlO4]5- asymmetric stretching band becomes obvious, indicating the complexity of the slag structure. When the heat decreases, the slag temperature increases as the basicity increases, and the slag thermal stability is better at the basicity of 0.95-1.05. As the Al2O3 content increases, the thermal stability of the slag becomes worse.

Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful applications in continuously deforming regions, much information is lost by simply fitting a line through the time series. Thanks to regular acquisitions across most of the the world by the ESA Sentinel-1 satellite constellation, we are now in a position to explore opportunities for near-real time deformation monitoring. In this paper we present a simple statistical approach for detecting offsets and gradient changes in InSAR time series. Our key assumption is that 5 years of Sentinel-1 data is sufficient to calculate the population standard deviation of the detection variables. Our offset detector identifies statistically significant peaks in the first, second and third difference series. The gradient change detector identifies statistically significant movements in the second derivative series. We exploit the high spatial resolution of Sentinel-1 data and the spatial continuity of geophysical deformation signals to filter out false positive detections that arise due to signal noise. When combined with near-real time processing of InSAR data these detectors, particularly the gradient change, could be used to detect incipient ground deformation associated with geophysical phenomena, for example from landslides or volcanic eruptions.

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.

The TanDEM-X mission is acquiring a new dataset to provide a temporally independent DEM, called "TanDEM-X Change DEM". This set of acquisitions taken between 2017 and 2020 has a clear temporal separation to the TanDEM-X global DEM data which were acquired between 2010 and 2015. Therefore, this new DEM aims to enable the characterization of terrain changes. Improvements in the acquisition planning and the data processing were necessary to generate this Change DEM with fewer acquisitions but still very high accuracy. For this, the use of an edited TanDEM-X DEM as a "starting point" for the interferometric processing is mandatory.

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.

Geospatial Information Systems (GIS) can provide a great environment for using machine learning algorithm for spatial data such as satellite images. Integrating this functionality with artificial intelligence algorithms for analyzing spatial data enables us to predict challenging disasters such as deforestation. Deforestation as an environmental problems has been recorded the most serious threat to environmental diversity and one of the main components of land-use change. In this paper, we investigate spatial distribution of deforestation using artificial neural networks and satellite imagery. We modeled deforestation process using various factors in determining the relationship between deforestation and environmental and socioeconomic factors. Hence, for this purpose, the proximity to roads and habitats, fragmentation of the forest, height from sea level, slope, and soil type are considered in the model. In this research, we modeled land cover changes (forests) to predict deforestation using an artificial neural network due to its significant potential for the development of nonlinear complex models. The procedure involves image registration and error correction, image classification, preparing deforestation maps, determining layers, and designing a multi-layer neural network to predict deforestation. The satellite images for this study are of a region in Hong Kong which are captured from 2012 to 2016. The results of the study demonstrate that neural networks approach for predicting deforestation can be utilized and its outcomes show the areas that destroyed during the research period.

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.

This paper is devoted to change-point detection using only the ordinal structure of a time series. A statistic based on the conditional entropy of ordinal patterns characterizing the local up and down in a time series is introduced and investigated. The statistic requires only minimal a priori information on given data and shows good performance in numerical experiments.

Sequential hypothesis test and change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. We show that for such problems, detection procedures based on sequential likelihood ratios with simple one-sample update estimates such as online mirror descent are nearly second-order optimal. This means that the upper bound for the algorithm performance meets the lower bound asymptotically up to a log-log factor in the false-alarm rate when it tends to zero. This is a blessing, since although the generalized likelihood ratio (GLR) statistics are optimal theoretically, but they cannot be computed recursively, and their exact computation usually requires infinite memory of historical data. We prove the nearly second-order optimality by making a connection between sequential analysis and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.

The Southwest Alpine Canyon Area of China was one of the regions in the world that suffered from severe soil erosion. The focus of this research was to understand the response of land use change on soil loss by water erosion in alpine canyon on Southeast Tibet, we analyzed the characteristics of temporal and spatial dynamics of land use in the Niyang River Basin from 1990 to 2020 using GIS and statistical methods, assessed the spatial and temporal change characteristics of soil erosion in the Niyang River Basin using RUSLE model. For this purpose, the meteorological, soil, topographic, remote sensing data were collected. The results showed the area of cropland and construction land in the Niyang River Basin increased to 2.4 and 6.1 times the original from 1990 to 2020, respectively, the area of forest and water continued to decrease. Grassland, unused land and forest have always been the dominant land types in the Niyang River Basin. Tolerable soil erosion was distributed in the flat areas of the valley terraces in the main stream and its tributaries, slight soil erosion was mainly distributed in the flat areas at high altitudes, and moderate, severe, very severe and destructive soil erosion was sporadically distributed in the Niyang River Basin. The areas of tolerable and slight soil erosion exceeded 82% of the total area, The area of severe, very severe and destructive soil erosion was less than 6%, but the total soil loss amount of severe, very severe and destructive erosion was more than 27%. From 1990 to 2020, the soil erosion area decreased from 9219.34 km2 to 8,090.84 km2 in Niyang River Basin, more than 85% of the soil erosion class has not changed, and the change of total soil loss amount also shows a significant reduction trend as a whole. 99% of the total soil loss amount in the Niyang River basin is generated by grassland, forest and unused land. The conversion of various land use types to cropland will cause the enhancement in soil erosion grade. We recommend that the focus of soil erosion control in the Niyang River Basin is to protect grassland, forest and carry out scientific farming.

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.