Evaluating the economic impact of airports is crucial for understanding the benefits they bring to a region. However, when an area has more than one airport, it becomes essential to analyze each airport's contribution to the local economy to make informed investment and policy decisions. Thus, studying economic models that can distinguish each airport's impact on the region's economy becomes essential. In this context, this paper aims to compare three different approaches to determine the economic contribution of airports in a given region and identify their social and economic benefits. The International Civil Aviation Organization recommends using Input-Output analysis in this context. The study considered three weight factors for the Input-Output basic model: circular buffer, displacement time, and Huff's gravitational model. The analysis was performed using the three largest airports in São Paulo's state, Brazil, due to their proximity and influence on the surrounding area. The models were compared based on their efficiency and accuracy in reflecting the reality of the case study context. The study identified the most suitable model for establishing correlations between investments made in airport infrastructure and the generation of gross domestic product, employment, and added value. This study fills a gap in the existing literature by proposing improvements to the methods for evaluating airports' economic and social benefits. In recent times, airport investors, both in the government and private sectors, have become increasingly demanding in their need for accurate analyses before making investments. Therefore, the results of this paper will provide valuable insights into the benefits of investing in airport infrastructure and help policymakers and investors make informed decisions.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

Poverty alleviation must be carried out in a planned and sustainable manner by the central government and regional governments, the private sector, and the entire community to achieve a prosperous society by getting special attention from the government. This study aims to analyze the impact of the non-cash food assistance program on poverty alleviation, stunting and economic problems using a public private partnership (PPP) approach that involves the role of the government, the private sector and the community. This study uses a qualitative-explorative research method to examine Indonesia's non-cash food assistance program as a national initiative to fight poverty in the form of food. Data were collected from interviews, field observations, and relevant literature, then Nvivo 12 Pro was used to analyze the results. The location of this research is in Indonesia, namely Takalar Regency. The results of the study show that the implementation of the non-cash basic food assistance program has been effective. The involvement of the government, the private sector, and the community shows this. The success factors for the basic food assistance program are alleviating poverty in Indonesia, reducing stunting rates, and increasing economic growth because people are given a place to be part of small businesses. From the results of this analysis it was concluded that the non-cash basic food assistance program is a special program that can overcome various social problems in society. So that poverty alleviation programs are expected to be sustainable and improved to provide benefits for people's welfare. The implementation of the food aid program also involved several cross-sectoral efforts to channel government assistance.

The size of the home is considered the most critical issue affecting the quality of life. This can be measured by the quality of the house and its environment. This paper highlights the housing quality index at the urban axis level in Bistrita-Nasaud county and the impact of socioeconomic activities on the index. The Household Quality of Life Index (HQLI) was calculated based on 11 variables. Household quality of life comprises two distinctive indices: the Housing Conditions Index (HCI) and the Asset Possession Index (API). The study found a variation in the housing condition variables across the urban focus areas. The impact of the socioeconomic environments is disproportionately dependent on the social-economic profile of the urban environments that make up the Urban Axis and the related economic activities that take place in the area of influence in the administrative-territorial units and the variability of the Housing Conditions Index This can be measured by the quality of the house and its environment. This paper highlights the housing quality index at the urban axis level in Bistrita-Nasaud county and the impact of socioeconomic activities on this index. The study area comprises territories in the municipality of Bistrita. The socio-economic context of the area has been the basis for understanding the patterns of evolution identified in the urban landscape, and being a driver in ongoing urban transformations and processes. The impact of the socio-economic is disproportionate to the socioeconomic profile of the urban environments that make up the Urban Axis and the economic activities related to the economic activities taking place in the catchment area in the administrative-territorial units, hence the variability of the Housing Conditions Index which is a system Housing Quality Indicator (HQI) is a tool for measuring and evaluating housing systems based on quality and not just cost.

The concept of green energy is now at the forefront of development discourse, with the United Nations Sustainable Development Goals (SDGs) 7, 11, and 12 all aimed at promoting green energy consumption to combat the three planetary crises: climate change, biodiversity loss, and pollution. Similarly, issues regarding Africa’s natural resource curse have caused a stir in the growth and development literature for some time now and there is no sign that it will die out. This study, the first of its kind, simultaneously assesses the impact of green energy consumption and Africa’s natural resources rents on economic growth by applying the Feasible Generalized Least Square (FGLS) estimator and the dynamic panel models of the Pooled Mean Group (PMG) and Mean Group (MG) estimators on data from 1990 to 2020 for 24 selected African countries. The results show that green energy consumption has a short-run growth-limiting effect and a long-run growth-enhancing effect in Africa. The study also found evidence of the natural resource curse phenomenon in Africa. The study, therefore, calls for the advancement and usage of green energy for both domestic and industrial production in Africa. The study further calls for a revamp in the global tax policy to curb illicit financial activities and strengthening institutional quality for transparency and accountability in the entire value chain of natural resource management in Africa.

This article aims to create the nexus between sustainable development and the quality of the political regime. The current social and political context is characterized by a series of crises generated by COVID-19 pandemic, economic imbalances and regional conflicts. In this context, sustainable development is affected by the economic dynamics and the “democratic recession”. The study aims to respond to the following research questions: “how could influence the quality of the democracy the dynamics of the Sustainable Development Goals (SDGs 17)?” and “what are the premises for sustainable development in the new political context, characterized by democratic recession?” The purpose of the study is to underline the fact that democratic regimes are inclined to create both participative and deliberative frames for achieving the SDGs in accordance with UN 2030 Agenda. The research methodology used in this study is based on descriptive and inferential statistics. The research data are collected from secondary sources in the years between 2015 and 2021, from 193 countries covering all the geographical areas. The empirical results suggest two models of development: the Asian model of sustainable development characterized by economic growth and the Western democratic model based on democratic institutions, fair justice and mechanisms for preserving peace. We noticed that the key-variables for explaining the dynamics of sustainability in correlation with democratic index are represented by the functioning of the governments and the political participation. Through civic engagement and political ac-countability, democracy could be seen as a pre-requisite for achieving an optimal level of the SDGs. All these empirical results could prove valuable for the scholars interested in the relation between democracy and sustainability and for the political decision makers involved in shaping strategies for social, economic and environmental development.

(1) Background: in epidemiological terms, it has been possible to calculate the savings in health resources and the reduction in health effects of COVID vaccines. From the point of view of economic evaluation, some studies have estimated its cost-effectiveness with the vaccination showing highly favorable results, which in some cases is cost-saving; (2) Methods: a cost-benefit analysis of the vaccination campaign in the North Metropolitan Health Region (Catalonia). An epidemiological model based on observational data and before and after comparison is used. The information on the doses used and the resources assigned (conventional hospital beds, ICU, number of tests) has been extracted from administrative data from the largest Primary Care provider in the region (Catalan Institute of Health). A distinction is made between the social perspective and the health system; (3) Results: the costs of vaccination are estimated at 137 million euros (€48.05/dose administered). This figure is significantly lower than the positive impacts of the vaccination campaign, which are estimated at 470 million euros (€164/dose administered). Of these, 18% corresponds to the reduction of ICU discharges, 16% to the reduction in conventional hospital discharges, 5% to the reduction in PCR tests and 1% to the reduction of RAT tests. Monetization of deaths and cases with sequelae avoided account for 53% and 5% of total savings, respectively. The benefit/cost ratio is estimated at 3.4 from a social perspective and 1.41 from a health system perspective. The social benefits of vaccination are estimated at €116.67 per dose of vaccine given (€19.93 from the point of view of the health system); (4) Conclusions: the mass vaccination campaign against COVID is cost-saving. From a social perspective, most of these savings come from the monetization of the reduction in mortality and cases with sequelae, although the intervention is equally widely cost-effective from the point of view of the health system thanks to the reduction in the use of resources. It is concluded that, from an economic perspective, the vaccination campaign has high social returns.

Concurrent waves of Coronavirus disease, Ebola virus disease, avian influenza A and black fungus are jeopardizing the lives in some parts of Africa and Asia. From this point of view, this review aims to summarize both socio-economic and public health implications of these parallel outbreaks along with their best possible management approaches. Various online databases were used to collect the necessary information regarding these outbreaks. Based on the reports published and analyses done so far, the long-lasting damages caused by these simultaneous outbreaks on global socio-economical and public health status can be conceived from the past experiences of outbreaks, especially the COVID-19 pandemic. Moreover, prolonged restrictions by the local government may lead to food insecurity, global recession, and an enormous impact on the mental health of people of all ages, specifically in developing countries. Such overwhelming effects already have been reported to be declining national growth of the economy as well as increasing political insecurity and shortage of basic needs. Although various actions have already been taken including vaccination, clinical management, and further research, social distancing, and lockdown, etc. to improve the situation, the emerging variants and associated genetic mutations may make the containment difficult worsening the situation again. Considering the current mutational dynamics of the pathogens and the past experiences, perpetual preparedness along with updated clinical management backed by epidemiological studies and innovating scientific effort are inevitable to combat the simultaneous waves of multiple infectious diseases.

Marine species are declining at an unprecedented rate, catalyzing many nations to adopt conservation and management targets within their jurisdictions. However, marine species and the biophysical processes that sustain them are naive to international borders. An understanding of the prevalence of cross-border species distributions is important for informing high-level conservation strategies, such as bilateral or regional agreements. Here, we examined 28,252 distribution maps to determine the number and locations of transboundary marine plants and animals. Over 90% of species have ranges spanning at least two jurisdictions, with 58% covering more than ten jurisdictions. All jurisdictions have at least one transboundary species, with the highest concentrations of transboundary species in the USA, Australia, Indonesia, and the Areas Beyond National Jurisdiction. Distributions of mapped biodiversity indicate that overcoming the challenges of multinational governance is critical for a much wider suite of species than migratory megavertebrates and commercially exploited fish stocks—the groups that have received the vast majority of multinational management attention. To effectively protect marine biodiversity, international governance mechanisms (particularly those related to the Convention on Biological Diversity, the Convention on Migratory Species, and Regional Seas Organizations) must be expanded to promote multinational conservation planning, and complimented by a holistic governance framework for biodiversity beyond national jurisdiction.

Nighttime lights (NTL) are a popular type of data for evaluating economic performance of regions and economic impacts of various shocks and interventions. Several validation studies use traditional statistics on economic activity like national or regional Gross Domestic Product (GDP) as a benchmark to evaluate the usefulness of NTL data. Many of these studies rely on dated and imprecise Defence Meteorological Satellite Program (DMSP) data and use aggregated units such as nation-states or the first sub-national level. Yet applied researchers who draw support from validation studies to justify their use of NTL data as a proxy for economic activity increasingly focus on smaller and lower level spatial units. This study uses a 2001-19 time-series of GDP for over 3100 US counties as a benchmark to examine the usefulness of the recently released version 2 VIIRS nighttime lights (V.2 VNL) products as proxies for local economic activity. Contrasts are made between cross-sectional predictions for GDP differences between areas and time-series predictions of GDP changes within areas. Disaggregated GDP data for various industries are used to examine what types of economic activity are best proxied by NTL data and comparisons are also made with the predictive performance of earlier NTL data products.

Economists have long been interested in examining inflation-growth nexus. Nevertheless, the nature of their relationship and the optimal level of inflation threshold for economic growth have still remained controversial in both theoretical and empirical works. Accordingly, this study investigates the existence of threshold effects of inflation on economic growth in Ethiopia over the period 1975-2018 using a Two-regime Threshold Auto-regressive (TAR) model. The study mainly departs from previous works since it estimates sector-specific inflation threshold level in food and non-food sectors. Our preliminary analyses clearly reveal that inflation in food sector has become more volatile, less-persistent and key contributor to the general inflation as compared to its non-food counterpart. Further, The TAR model results and robustness checks indicate the existence of inflation threshold in a range of 9-10%. In particular, the threshold level for food inflation is 10% and 8% for non-food inflation. In all cases, our results robustly confirm growth-detrimental effects of inflation after the threshold levels. After all, this study suggests the need for considering specific behaviors of food and non-food prices, and implementing appropriate fiscal and monetary policies to bring inflation down to a single-digit level.

(1)Background: To perform a simulation-based analysis of 2019 COVID-19 outbreak and how would the electronic commerce indursty help China’s economy resilient. (2)Methods: As the epidemic continues, it is possible to use Computable General Equilibrium model to simulate the economic consequences and analyse the role of electronic commerce industy in COVID-19 outbreak. (3)Results: Estimates and models produced at the time of the outbreak suggested that COVID-19 could have a catastrophic effect on China’s economy. National statistics were examined for anomalies that corresponded to the timing of COVID-19 outbreak and, where possible, the size of any gain or loss found estimated. Our analysis suggests that the electronic commerce industry could help China’s economy to recover by stimulating consumption, improving technological level and expanding investment. (4)Conclusions: This exercise holds important lessons for estimating the electronic commerce’s role of similar events – such as pandemic influenza – and measures to recover the economy. We suggest that electronic commerce industry should be paid more attention in economic development, especially in epidemic time. The implications of our findings are discussed in the light of a prospective epidemic.

In order to realize the sustainable utilization of water resources and the sustainable development of economy, the evaluation index system of water use efficiency system and economic development system was constructed. Entropy weight method and comprehensive evaluation method were adopted to determine the index weights and conduct comprehensive evaluation for the two systems. The coupling coordination model was used to calculate the coupling degree, coordination degree and coupling coordination degree of the two systems. The annual coupling stage and coupling coordination intensity of the two systems were analyzed and determined. The results showed that the comprehensive evaluation values of both water use efficiency system and economic development system in Jinan City increased greatly from 2008 to 2017, and showed a changing trend of ups and downs. The two systems were in the antagonistic stage, and were gradually approaching the running-in stage, indicating that they were in the state of common development. The coupling coordination degree of the two systems gradually increased in waves, progressed from the moderately to the highly coordinated coupling. In the future, if the water control path appropriate to Jinan City can be explored actively, the water-saving kinetic energy of economic development can be increased constantly, and the linkage effect between economic development and water resources utilization can be given full play to, the two systems will be in the orbit with the benign interaction and healthy harmonious development.

In this study, the prevalent methodology for design of the industrial policy in developing countries was critically assessed, and it was shown that the mechanism and content of classical method is fundamentally contradictory to the goals and components of the endogenous growth theories. This study, by proposing a new approach, along settling Schumpeter's economic growth theory as a policy framework, designed the process of entering, analyzing and processing data as the mechanism of the industrial policy in order to provide "theoretical consistency" and "technical and Statistical requirements" for targeting the growth stimulant factor effectively.

This research presents a solution to the problem of planning the optimum area for economic crops by developed mathematical models and developed an algorithm to solve the problem of planning the optimum area by considered economic value for the maximize profit of farmers. The data were collected from farmers in 8 provinces in the northeastern region of Thailand. The 3 economic crops studied were rice, cassava and sugarcane. The solving problem methods were 1) Created mathematical models and solved the problems with Lingo V.11. 2) Improved Differential Evolution algorithms (I-DE) to solve the problems, which had 3 local search methods included (Swap, Cyclic Move and K-variable moves). The results of this study showed that in the small and medium problems instances, Lingo V.11 and DE provided equal profit outcome but DE was faster but in the large size of test instances DE generated better solution than that of Lingo v.11 when Lingo simulation time is set to 250 hours and DE simulation time has set to maximum 21.82 minutes. 2) Comparing DE and I-DE , I-DE outperforms DE in finding the better solution for all size of test instances (small, medium and large).

The quality of an educational system is reflected not only in the instructive performances of the educational actors, but also in the degree in which it ensures an adequate professional integration. The undergraduate of today, the graduate of tomorrow needs an as accurate as possible information regarding the labour market, which cannot be achieved only by individual means, but also by resorting to carrier counselling services. The motivation of this research is closely connected to the improvement of the level of communication between the two aspects – on the one hand the academic one, by its finite products, and the economic one, on the other hand – and the opportunities that the cooperation between the two aspects might offer: adjusting the demand-supply ratio on the labor market and above all, stopping massive emigration of young graduates of higher education.

Declining water supply is the main cause of rising water fee for agricultural use. Moreover, in non-technical irrigation, poor irrigation infrastructure exacerbates water scarcity. Thus, the purpose of this study is to identify farmer willingness to pay for non-technical irrigation and its determinants. Structured questionnaire was used to collect data from 100 farmers. Contingent valuation method was employed to elicit farmer WTP and multiple linear regression was used to find its determinants. The result shows that farmer average WTP is Rp 3,055,168 /ha/year. It accounts for 20 percent of total farmer revenue and almost 20 times fee for technical irrigation. Economic and technical variables are the significant determinants of WTP while social variables seem insignificant to WTP. This result indicates high economic value of water, and to improve irrigation management we recommend establishing irrigation infrastructure gradually by mobilizing farmer resources (capital and management) and strengthening WUA.

This paper models the factors explaining households members economic well-being in Burkina Faso, with a focus on the relative influence of gender inequality in literacy status. It does so, using data from the 2014 survey on household living conditions and a semi-parametric bi-variate sample selection modeling approach. This approach compared to the classic Heckman two-step estimator is methodologically innovative because it deals simultaneously with non-random sample selection using conventional systems of two equations, non-linear covariates' effects using spline approach, and the non-normal bivariate distribution using copula functions. The graphical results from the Lorenz curves combined with the numerical Atkinson and Gini coefficients suggest that inequality in overall per-capita consumption spending among households headed by literates is higher than that of their illiterate counterparts in 2009 and 2014. However, independently of the head of household’s literacy status, the level of inequality in total economic well-being decreased from 2009 to 2014. Using the poverty indices of Watts, Sen, Foster ( alpha= 1)) we found that poverty among households headed by literates is lower than that of their illiterates counterparts for both years, although overall poverty decreased nationally between 2009 and 2014. The results also show that although the gender inequality in literacy status does not translate into inequalities in non-food wellness, it does however for food-wellness as female headed households have 38.9% less per-capita food consumption spending than their men counterparts. Combining both food and non-food consumption spending, total economic well-being also seems to exhibit gender inequality as female headed households now have relatively 26.7% less combined per-capita consumption spending.

This economic evaluation aims to support policy-making on the combined use of pre-exposure prophylaxis (PrEP) with HIV vaccines by evaluating the potential cost-effectiveness of implementation that would support the design of clinical trials for assessment of combined product safety and efficacy. The target study population is a cohort of men who have sex with men (MSM) in the United States. Policy strategies considered include standard HIV prevention, daily oral PrEP, HIV vaccine, and their combination. We constructed a Markov model based on clinical trial data and published literature. We used a payer perspective, monthly cycle length, a lifetime horizon, and a 3% discount rate. We assumed a price of $500 per HIV vaccine series in the base case. HIV vaccines dominated standard care and PrEP. At current prices,PrEP was not cost-effective alone or in combination. A combination strategy had the greatest health benefit but was not cost-effective (ICER=$463,448/QALY) as compared to vaccination alone. Sensitivity analyses suggest a combination may be valuable for higher-risk men with good adherence. Vaccine durability and PrEP drug prices were key drivers of cost-effectiveness. Results suggest that boosting potential may be key to HIV vaccine value.

The technologies influencing alternative ways of transportation are augmenting in recent years as the need for transportation is increasing rapidly due to urbanization and motorization. In this paper, a solar powered electric auto-rickshaw (SPEA) is designed and developed for Indian conditions. The developed vehicle is comprehensively analyzed techno-economically for its viability in the Indian market. The performance analysis of SPEA results in an optimal charging rate of 2 kWh per day with an average solar irradiance of 325 W/m2. The discharging characteristics are studied based on different loading conditions. The vehicle achieved a maximum speed of 21.69 km/h with battery discharge rate of 296W at 90kg load and also reached a maximum discharge rate of 540W at 390kg loading with a maximum speed of 12.11 km/h. The environmental analysis of SPEA displayed yearly CO2 emissions of 1,777 kg, 1,987 kg and 1,938 kg using Compressed Natural Gas, Liquefied Petroleum Gas and gasoline engines respectively can be mitigated using SPEA. The results of financial analysis of SPEA were welcoming as the investor gets 24.44% lesser payback duration compared to gasoline run vehicle. Socio-Economic analysis of SPEA discussed its significant advantages and showed 18.73% and 3.9% increase in yearly income over gasoline driven and battery driven vehicles.

This paper analyzes the causal effect between domestic private investment, public investment, foreign direct investment and economic growth in Tanzania during the 1970-2014 period. The modified neo-classical growth model is used to estimate the ieffect of investment on economic growth. Also, the economic growth models based on Phetsavong and Ichihashi (2012) [1], and Le and Suruga (2005) [2]are used to estimate the crowding out effect of public investment on domestic private investment on one hand and foreign direct investment on the other hand. In the same way, the crowding out effect of foreign direct investment on domestic private investment is estimated. A correlation test is applied to check the correlation among independent variables, and the results show that there is very low correlation suggesting that multicollinearity is not a serious problem. Moreover, the diagnostic tests including RESET regression errors specification test, Breusch-Godfrey serial correlation LM test, Jacque-Bera-normality test and white heteroskedasticity test reveal that the model has no signs of misspecification and that, the residuals are serially uncorrelated, normally distributed and homoskedastic. Broadly, the empirical results show that the domestic private investment and foreign direct investment play an important role in economic growth in Tanzania. Besides, a revealed negative, albeit weak, association between public and private investment suggests that the positive effect of domestic private investment on economic growth becomes smaller when public investment-to-GDP ratio exceeds 8-10 percent. Similarly, foreign direct investment tends to marginally reduce the impact of domestic private investment on growth. These results suggest that public investment and foreign direct investment need to be considered carefully in order to avoid a reduced positive impact of domestic private investment on growth. Domestic saving may be promoted to encourage domestic investment for economic growth.

The objective of the described activity is to develop technologies or proposals that can be implemented within the cycle to enhance the relationship between climate change, water, energy, and food. The focus is on analyzing natural treatment systems for wastewater (NTSW) within the context of Macaronesia, considering factors such as life cycle assessment (LCA), carbon footprint, impacts, and mitigation capacity. The analysis of real case data from the Canary Islands and Cape Verde will inform the development of appropriate technologies tailored to different areas and scales within Macaronesia. This work includes a comprehensive life cycle analysis of the Santa Catarina (Cape Verde) NTSW. This analysis encompasses: a) Inventory analysis of the construction phase: This involves the assessment of inputs and outputs associated with the construction of the NTSW, including materials, energy consumption, transportation, and waste generation. The maintenance and operation phase is then evaluated, with a focus on the ongoing maintenance and operation activities required for the NTSW, including energy consumption, water usage, chemical inputs (if any), labour, and equipment maintenance. Finally, the impacts of the NTSW are evaluated. The environmental, social, and economic impacts generated by the NTSW are assessed. This includes an analysis of factors such as carbon emissions, water usage, land use, ecosystem impacts, human health effects, and economic costs. By conducting a comprehensive analysis of the Santa Catarina NTSW, the document aims to provide insights into the environmental performance and sustainability of the system. This information can then be used to identify areas for improvement, develop mitigation strategies, and inform decision-making processes regarding wastewater treatment technologies in Macaronesia. Furthermore, lessons learned from real case studies in the Canary Islands and Cape Verde can be applied to similar regions within the Macaronesia archipelago.

This article examines the impact of climate change on the hydrometeorological state of some lakes and reservoirs in the Akmola and North Kazakhstan regions. Time series with values of various climate parameters for the period 1986-2023 are used for the climate analysis; the reliability of the results was assessed using the Fisher criteria. Hydrometric indicators were studied using the ArcGIG program. Using GIS to spatially analyze water climate data, 8-channel satellite images from 1995 to 2023 were used. During the study, it was found that the area of the main lakes has undergone changes.

CO2 emission activity of xylotrophic fungi response to an increase in temperature in the range of 10-30 °C on the example of pure dikaryotic cultures of Fomes fomentarius s. str., F. inzengae, Fomitopsis betulina, F. pinicola, Phellinus igniarius was analyzed. Emission activity was assessed by the difference in CO2 concentration in 0.5-liter exposure chambers with Petri dishes with mycelium growing on agar at the beginning of exposure and an hour later using a Gasmet DX-4030 FTIR spectrometer (Gasmet Technologies Oy, Finland), error measurements ±50 ppm. Specific (μg CO2/cm2/h) and total (μg CO2/h) emission activity and its relationship with temperature and size (area) of the mycelium were assessed. It has been shown that in the range of 10-30 °C, the specific and total CO2 emission activity of the mycelium is closely and positively related to temperature. Specific emission, which is an indicator of the respiratory activity of the mycelium, does not depend on its size; its only driver is temperature, the relationship with which is linear: an increase in temperature by 10 °C causes an increase in the specific emission activity of the mycelium by 1.7 times. The total CO2 emission activity, which is an indicator of the total amount of CO2 emitted, is directly proportional to the specific emission activity and the size of the mycelium. In the range of 10-30 °C, an increase in temperature causes an almost equal increase in both the specific emission activity of the mycelium (Q10 1.7) and its growth (Q10 1.5) and causes an exponential increase in the total emission of CO2. This must be taken into account when predicting CO2 emissions from woody debris under climate change, as it could potentially contribute to accelerating climate change.

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

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

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

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

The human landscape transforming activity contributes to the global change of vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We are investigating the vegetation dynamics over several years in in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). One important background factor is changes in precipitation and temperature. The novelty of our present study lies in the fact that the observation takes place with continuous disturbance, where the human influence is very large. Our results confirm that the weed infestation be detectable at bait sites over a long period, and the interannual changes were typical in every year, according to the fact that in August, more weed species are usually present with a greater cover at the bait sites. The main meteorological factors played a role in the degree of weed infestation in each year. There was a higher proportion of vegetation regeneration in wetter years, while dry periods do not favor successional processes. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. A more precise understanding of vulnerable systems and careful planning of treatment interventions is necessary.

Nanotechnology has become a popular topic in agricultural and animal research, generating sig-nificant global interest. Nanoparticles (NPs)-enabled agriculture and animal husbandry (AHs) products have three main principles: crop production, protection, and nutrient enrichment. Re-search on this topic has grown exponentially in recent years, with an increasing number of peer-reviewed literature and patents on NPs-enabled agriculture and AH products. This study examines and collects data on the various applications of NPs-enabled agricultural products for crop production, protection, and livestock improvement from the core nanotechnological database. The search returned several types of NPs and products used in agriculture and AH, countries that utilize these products at a commercial level, and analysis of these data by phyton, R-statistical software. Our findings show remarkable growth of nanotechnology in agriculture, AH, and re-search fields for future sustainability goals in the era of climate change

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

The increasing demand for transporting people and goods, rail system is needed for enhancement. An architectural design of train station can significantly impact investment from any government. However, a proper guideline for designing the train station in tropical climate is not publicized. This review examine railway station design through an analysis of student design theses in Thailand, from 1983 to 2022. Furthermore, the building analyses on architectural design theory were done in terms of service area, form, entrance structure, roof structure, style, and design development. The analysis reveals curved and gable roofs are most frequent, followed by 3D curved roofs. HSR stations' main entrances are designed to represent local culture and save walking distance. Curved and gabled porticos provide the most extravagant main entryway, a feeling of grandeur and beauty. A public building's overlapping portico or curving gabled portico lends majesty and refinement to its façade. Architects and designers strive to make buildings more attractive and practical. Besides, university-designed stations prioritize conceptual design and functional space over cost. Finally, railway station design should prioritize transparency, connectivity, movement, and cost- and time-efficiency. Research gaps are identified, such as designing user-friendly for thermal comfort and design-for-all the railway station in tropical climate, are critical for future evaluation.

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.

Môle Saint-Nicolas, like all other communes in the Republic of Haiti, faces increasing climate variability, impacting agricultural production and water resources. Consequently, there is a pressing need for adaptation to these climatic changes. This research aims to showcase the adaptation strategies deployed by farmers to cope with the increasing climate variability. Surveys were conducted through group and individual discussions with a randomly selected cohort of 150 farmers. Two types of analysis were performed: quantitative and qualitative. The quantitative data analysis was conducted using SPSS software. The findings reveal that farmers have perceived changes in rainfall patterns, temperature, wind, and their environment. These changes manifest as irregular rainfall, higher temperatures, prolonged drought periods, violent winds accompanied by rain, premature cessation of rains, and reduced flow from water sources. In response, the most common adaptation strategies developed include selecting new cultivars, early-maturing varieties, crop rotation and diversification, canal dredging, new soil preparation methods, upstream water source protection, and micro-watershed management. The significance of this research lies in its contribution to enhancing farmers' adaptive capacities by alerting stakeholders in the irrigated perimeters about the consequences of climate change, thereby incorporating the real needs of farmers in future projects.

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.

Due to the major impact of climate change on the world's environment, political and economic systems, climate change mitigation has become a pressing priority for the international community and requires rapid action from the whole society. With the continuous advancement of artificial intelligence research, the integration of AI and other technologies makes it more and more used in the whole society. It has become a promising and innovative avenue in the field of climate change mitigation. This paper comprehensively considers the key role of AI technology in the field of climate change mitigation, such as climate modeling, the optimization of renewable energy systems, the development of intelligent solutions for sustainable practices and CSS technology, and affirms its future prospects. It also describes the challenges of AI in the field of climate change mitigation. As researchers, policymakers, and industries collaborate to refine AI methodologies and integrate them into practical applications, a concerted effort is required to establish ethical guidelines, transparency standards, and inclusive governance frameworks.

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

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

The predominant management approach for municipal solid waste (MSW) remains disposal, given significant increases in generation and disposal rates of MSW in recent decades. In addition to the well-documented carbon emissions from disposal sites, these sites accumulate numerous elements, the masses of which are substantial globally yet inadequately quantified. The unique combinations of waste constituents, elements, diverse environments, and confined spaces in disposal sites create distinct biogeochemical conditions, setting them apart from any other infrastructure or geological feature on Earth. This review first presents a global summary of the cumulative masses and disposal rates of MSW constituents and associated elements. The five dominant transformation and transport processes influencing disposed elements are examined: biochemical degradation, physicochemical transformation, gas migration, leachate migration, and solid spillage. The magnitudes and rates of the processes corresponding to major disposed elements, including carbon, nitrogen, sulfur, chlorine, and several metals, are systematically summarized. We examine and quantify the potential environmental impacts and health risks associated with element transformation and transport. We also explore the existing knowledge and techniques for resource recovery and site remediation of disposal sites. The distilled compilation of measurements and insights herein serves as a valuable primer for researchers, practitioners, and decision-makers involved in MSW management.

The study combines two critical aspects of climate research in Nigeria. The first segment focuses on improving predictive performance of global circulation models (GCMs) employing ensemble techniques. ANN ensemble displayed significant improvement in the accuracy of climate projections, particularly in high-altitude geographic areas where traditional models exhibit limitations. Performance evaluation metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Nash–Sutcliffe Efficiency (NSE) demonstrate the effectiveness of the ANN multimodal ensemble. Building on the improved climate modelling, the second segment delves into a spatial and temporal analysis of rainfall and mean temperature patterns under climate change in Nigeria. By considering two Representative Concentration Pathways (RCPs), namely RCP4.5 and RCP8.5, the study utilizes dynamically downscaled GCMs obtained from the Coupled Model Intercomparison Project phase 5 (CMIP5). The Mann-Kendall test reveals significant spatiotemporal variations in climate trends across the country. The warming trend is particularly pronounced in the northern regions, with RCP8.5 showing more severe impacts compared to RCP4.5. This integrated approach not only highlights the importance of multimodal ensembles in climate modelling but also provides valuable insights into the spatial and temporal patterns of climate change to inform effective adaptation and mitigation strategies for Nigeria.

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.

Dengue is one of the most important arboviruses worldwide, with currently approximately 2.5 billion people at risk of becoming infected, mainly in tropical countries. The present study evaluated the influence of climatic variables on the incidence of dengue fever in an endemic urban area. A time series study of cases was carried out with all confirmed cases of dengue fever in the municipality of Belo Horizonte from 2001 to 2021. The climatic explanatory variables were obtained from the National Institute of Meteorology. The analysis was performed using a generalized linear regression model with three scenarios: a no-lag model, 1-month lag model (1 month earlier) and 2-month lag model (2 months earlier). In the no-lag model, the maximum temperature was associated with an increase in the monthly incidence of dengue (IRR: 1.5). In the 1- and 2-month lag models, the monthly average temperature was associated with an increase in incidence (IRR: 1.9 in both). Our results suggest that temperature contributed to the increase in the incidence of dengue, and an increase of 1 °C could increase the incidence of the disease by approximately 90%. Thus, temperature monitoring can direct efforts towards prevention and control of the disease.

The paper aims to introduce user-friendly modelling approaches to analyze how abiotic factors influence various trophic levels within the marine ecosystem, both naturally and through human impact. It specifically investigates the connections between environmental parameters (like temperature, salinity, and nutrients) and plankton along the Romanian Black Sea coast during the warm season (May-September) over a decade. Utilizing machine learning (ML) algorithms and data collected during this period, models were developed to project the proliferation of zooplankton. During the warm season, water temperature emerged as a significant factor affecting copepods and “other groups” zooplankton densities, while no discernible impact was noted on Noctiluca scintillans blooms. Salinity fluctuations notably influenced typical phytoplankton proliferation, with phosphate concentrations primarily driving widespread blooms. Two scenarios were explored for forecasting zooplankton growth: Business as Usual, predicting modest increases in temperature, salinity, and constant nutrient levels, and the Mild scenario, anticipating more substantial temperature and salinity increases while nutrients decrease significantly by 2042. The findings highlight that under both scenarios, Noctiluca scintillans displays notably high densities, with the second scenario projecting even higher values, surpassing the first by around 70%. These densities indicate characteristics of a eutrophic ecosystem, suggesting the potential implications of altered abiotic factors on ecosystem health.

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.

In this analysis, we assess the performance of GSMaP-GNRT6 data in capturing precipitation climatology and climate variability across China from 2001 to 2020. The evaluation involves comparing four precipitation indices of accumulated precipitation, the number of rainy days, rainstorm days, and precipitation maximum with the daily precipitation data from 2419 stations in China. The findings reveal that the GSMaP data effectively captures the overall spatial distribution of annual, summer, and monthly precipitation. However, it exhibits minor limitations in accurately depicting the spatial distribution of the number of rainy days from July to September and the precipitation maximum during wintertime in eastern China. While the GSMaP data depicts a coherent annual cycle consistent with the station observations, a general underestimation is observed. Notably, the GSMaP data presents a much smoother annual cycle in precipitation maximum. Regarding accumulated precipitation, the number of rainstorm days, and precipitation maximum, the GSMaP data shows an almost consistent interannual variation and increasing trends, aligning with station observations. However, it is noteworthy that the magnitude of the increasing trend based on the GSMaP data is greater, especially entering the early 21st century. Conversely, a significant discrepancy in the annual variation and an almost opposite changing trend are noticed in the number of rainy days between the GSMaP data and station observations.

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.

With the rapid development of artificial intelligence, machine learning is gradually becoming popular in predictions in all walks of life. In meteorology, It is gradually competing with traditional climate predictions dominated by physical models. This survey aims to consolidate the current understanding of Machine Learning (ML) applications in weather and climate prediction—a field of growing importance across multiple sectors including agriculture and disaster management. Building upon an exhaustive review of more than 20 methods highlighted in existing literature, this survey pinpointed eight techniques that show particular promise for improving the accuracy of both short-term weather and medium-to-long-term climate forecasts. According to the survey, while ML demonstrates significant capabilities in short-term weather prediction, its application in medium-to-long-term climate forecasting remains limited, constrained by factors such as intricate climate variables and data limitations. Current literature tends to focus narrowly on either short-term weather or medium-to-long-term climate forecasting, often neglecting the relationship between the two, as well as general neglect of modelling structure and recent advances. By providing an integrated analysis of models spanning different time scales, this survey aims to bridge these gaps, thereby serving as a meaningful guide for future interdisciplinary research in this rapidly evolving field.

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

In the era of persistent globalization, climate governance has emerged as a prominent concern within both the theoretical community and government departments of diverse nations. Of particular interest in academic research is the adverse effect of climate shocks on the global economy. This paper employs average temperature as a surrogate indicator for climate shocks and examines the influence of temperature fluctuations on inflation levels using a balanced panel dataset from 1995 to 2021. The findings indicate a positive association between temperature change and inflation within the country, which remains consistent even after subjecting the analysis to multiple robustness tests. Furthermore, accounting for heterogeneity reveals variations in the magnitude of response of inflation levels to temperature fluctuations. Regarding the analysis of underlying mechanisms, the study underscores the significance of energy demand as a pivotal pathway influencing inflationary pressures at the national level. Lastly, by incorporating GDP per capita as a threshold, the research reveals a nonlinear relationship between temperature change and inflation levels.

Rain-fed agriculture remains the source of employment for a majority of Ethiopian population, particularly in Dorebafana District, where annual rainfall is low. Perception of climate change and variability supported by local knowledge has helped to advance understanding of climate change and its impacts on agricultural land-use systems. Thus, the overall objective of this study was assessing farmers’ perception of climate change and variability and its impact on agriculture in Umbulo Kajima and Lebu Koromo kebeles of Dorebafana, Sidama region of Ethiopia. A total of 88 sample households from the two kebeles, farmers’ perception were compared with historical climatic data from the closest weather station of the study area. The household survey, focus group discussions and field observation were used as primary data sources in the study area. The data was analyzed by using descriptive statics in Statistical Package for the Social Sciences and multinomial logistic regression model. As data showed, there was the declining and high variability of rainfall in the last three decades In addition, the maximum annual rainfall was observed in 1998, 1755.4 mm and the lowest annual rainfall was recorded in 2015, 537.4 mm in the study area. The focus group discussions and key informant interviews further supported the idea that rainfall in the research area has been falling and very variable over the previous three decades. The finding showed that, temperature increased by 0.1oC over the previous three decade, and socioeconomic factors such sex, age, farming experience, knowledge of the climate, market access, and agro-ecology had an impact on farmers' perceptions of climate change and its impact in agriculture. Therefore awareness creation, increase educational level, sharing experience, scaling up best practice and using new technologies are the best alternatives to minimize the adverse effects of climate change.

The gradual decline of the Aral Sea’s water level over the past five decades poses a huge environmental problem in the heart of Central Asia. Uzbekistan, once blessed with abundant water resources, now struggles with water scarcity in certain regions. While global environmental issues contribute to some degree to this dilemma, irrigation mismanagement plays a central role. This study focuses on the widespread problem of irrigation mismanagement in Uzbekistan and specifically addresses the rural district of Oltinsoy in the southern province of Surkhandarya. The main objective of this research project is to propose effective measures that can alleviate the pressing problem of water scarcity in the region while emphasizing the urgent need for well-executed projects and careful maintenance to ensure long-term sustainability at the local level. It is important to note that this study does not include an examination of the impact of global warming on the decline of water resources in Uzbekistan.

Evapotranspiration (ET) is an essential part of energy flow between the surface of the earth and the atmosphere, simultaneously involving the water, carbon, and energy cycles. It is mainly determined by climate change, land use, and land cover changes. Climate change is expected to intensify the hydrological cycle and alter ET. Land use affects ET within regional ecosystems mainly through vegetation changes and agricultural activities such as farmland reclamation, crop cultivation, and agricultural management. However, there is still a need for quantitative characterization of the impacts of climate change and human activities on ET and regional water resource efficiency in arid and semiarid regions. Based on Landsat-8 remote sensing imagery and land use data, the planting structure in the Liangzhou District of the middle reaches of the Shiyang River Basin was identified using a multiband and multitemporal approach in this study. Subsequently, the ET of major cash crops was inverted using the three-temperature model. This research quantitatively describes the responses of wheat and corn to the climate and human activities over a two-year period. Furthermore, the impact of planting structure and climatic factors on ET was elucidated. The results indicate that a combination of multitemporal green and shortwave infrared 1 bands is the optimal spectral combination to extract the planting structure. Compared to 2019, the wheat area decreased by 23.27% in 2020, while the corn area increased by 5.96%. Both crops exhibited significant spatial heterogeneity in ET during the growing season. The typical daily range of ET for wheat was 0.4–7.2 mm/day, and for corn, it was 1.5–4.0 mm/day. Among the climatic factors, temperature showed the highest correlation with ET (R = 0.80, p ≤ 0.05). Our research findings provide valuable insights for the fine identification of planting structures and a better understanding of the response of ET to climatic factors and human activities.

Climate data are important in building a hydrological risk assessment model. The ClimInonda web application enables interactive and dynamic visualizations of different data collected from different weather stations in the study area on a single platform, allowing users to explore and analyze data in an easy way. This can assist decision-makers and stakeholders in understanding the current state of the environment and in identifying areas of flooding risk. Visualizations can include different types of data, such as satellite imagery, weather data, and terrain data, and can be displayed using various techniques, such as heat maps, contour maps, and 3D models by providing easy-to-understand visualizations. The different stations of the Gafsa and Kasserine governorates in the study area are included and other stations of the Algerian territory (Tebessa governorate) are incorporated. This web application also provides the capability to include each user's stations.

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.

The agricultural sector provides employment and income to the majority of Myanmar's population. The sector, however, is extremely susceptible to severe weather, rising temperatures, and changes in precipitation. This paper aims to analyze how vulnerable Myanmar's agricultural sector is to climate change and highlights the key sectors that are most at risk. This report also examines historical climate information, and the anticipated effects of climate change on Myanmar's agricultural sectors. In-depth literature reviews and summaries of Myanmar's climate change adaptation efforts are included in the report, along with recom-mendations for targeted, locally appropriate actions to strengthen the country's agricultural sector's resilience. Additionally, the study reviews Myanmar's in-stitutional framework for climate action and government priorities for adaptation measures, emphasizes the urgent need for climate action in Myanmar's agricul-ture sectors and calls for more research and development efforts on the effects of climate change on rural livelihoods and agriculture.

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.

Dengue Fever (DF) is an important arthropod-borne viral infection, which has repeatedly oc-curred as outbreaks in eastern and northeastern Ethiopia since 2013. A cross-sectional epidemio-logical outbreak investigation was carried out from September - November 2019 on febrile pa-tients (confirmed malaria negative) who presented with suspected and confirmed DF at both public and private health facilities in Gewane District, Afar Region, northeastern Ethiopia. Ento-mological investigation of containers found in randomly selected houses belonging to DF positive patients was undertaken, to survey for the presence of Aedes larvae or pupae. A total of 1185 DF cases was recorded from six heath facilities during the 3-month study period. The mean age of DF cases was 27.2 years and 42.7% of the cases were female. The most affected age group was 15-49 years (78.98%). However, the attack rate (AR) was highest in the 49+ age group (134.2). A total of 162 artificial containers were inspected from 62 houses, with 49.4% found positive for Aedes larva/pupae. Aedes mosquitoes were mostly found breeding in buckets/bowls, clay jars, plastic tanks, and tires. World Health Organization entomological indices classified the study site as high risk for dengue outbreaks (House Index=45.2%, Container Index=49.4% and Breteau In-dex=129). Study findings highlight the importance of vector control to prevent future dengue out-breaks in the region. The scarcity of drinking water and changing climactic conditions may have also contributed to the occurrence of this outbreak.

Snowpack loss in midlatitude mountains is ubiquitously projected by Earth system models, though the magnitudes, persistence and time horizons of decline vary. Using daily downscaled hydroclimate and snow projections we examine changes in snow seasonality across the U.S. Pacific Southwest region during a simulated severe 20-year dry spell in the 21st century (2051–2070) developed as part of the 4th California Climate Change Assessment to provide a "stress test" for water resources. Across California’s mountains, substantial declines (30–100% loss) in median peak annual snow water equivalent accompany changes in snow seasonality throughout the region compared to the historic period. We find 80% of historic seasonal snowpacks transition to ephemeral conditions. Subsetting empirical-statistical wildfire projections for California by snow seasonality transition regions indicates a two-to-four-fold increase in burned area, consistent with recent observations of high elevation wildfires following extended drought conditions. By analyzing six of the major California snow-fed river systems we demonstrate snowpack reductions and seasonality transitions result in concomitant declines in annual runoff (47-58% of historic values). The negative impacts to statewide water supply reliability by the projected dry spell will likely be magnified by changes in snowpack seasonality and increased wildfire activity.

As its capital, Jakarta plays a critical role in boosting Indonesia’s economic growth and setting the precedent for broader change outside of the city. One crucial avenue of inquiry to better understand, and prepare for, the future of a country so heavily impacted by disastrous weather events is understanding the effects of climate change through data. This study investigates meteorological data collected from 1996 to 2021 and compares the application of the SARIMA and the Holt-Winters methods to predict the future influence of climatic parameters on Jakarta’s weather. The performance of the SARIMA method is proven to provide better results than the Holt-Winter models and both methods showed the best performances when forecasting the humidity data. The results of the forecast are able to demonstrate the characteristic of the climate in Jakarta, with dry season ranging from May to October and wet season ranging from November to April.

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

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

The assessment of aridity conditions is a key factor for water management and the implementation of mitigation and adaptation policies in agroforestry systems. Towards this aim three aridity indices were computed for the Iberian Peninsula (IP): the De Martonne Index (DMI), the Pinna Combinative Index (PCI), and the Erinç Aridity Index (EAI). These three indices were first computed for the baseline period 1961‒1990, using a gridded observational data (E-OBS), and, subsequently, for the periods 2011‒2040 (short-range) and 2041‒2070 (medium-range) using an ensemble of six Regional Climate Models (RCMs) experiments generated by the EURO-CORDEX project. Two Representative Concentration Pathways (RCPs) were analyzed, an intermediate anthropogenic radiative forcing scenario (RCP4.5) and a fossil-intensive emission scenario (RCP8.5). Overall, the three indices disclose a strengthening of aridity and dry conditions in central and southern Iberia until 2070, mainly under RCP8.5. Strong(weak) statistically significant correlations were found between these indices and the total mean precipitation (mean temperature) along with projected significant decreasing(increasing) trends for precipitation(temperature). The prevalence of years with arid conditions (above 70% for 2041‒2070 under both RCPs) are projected to have major impacts in some regions, such as southern Portugal, Extremadura, Castilla-La Mancha, Comunidad de Madrid, Andalucía, Región de Murcia, Comunidad Valenciana, and certain regions within the Aragón province. The projected increase in both the intensity and persistence of aridity conditions in a broader southern half of Iberia will exacerbate the exposure and vulnerability of this region to climate change, while the risk of multi-level desertification should be thoroughly integrated into regional and national water management and planning.

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.

Abstract Depending upon altitudinal gradient in the Himalayas, the rate of climate change varies from lowland to upland. The Chitwan Annapurna Landscape (CHAL) is the central part of the Himalayas and covers all bioclimatic zones. Analysis of time series data (1970-2019) of temperature and precipitation was carried out in seven bioclimatic zones extending from lowland Terai to higher Himalayas. The non-parametric Mann-Kendall test was applied to determine the trend, which was quantified by Sen’s slope. Annual and decade interval average temperature, precipitation trends, and lapse rate were analyzed in each bioclimatic zone. Out of seven bioclimatic zones, four zones showed a decreasing precipitation trend (lower tropical, upper tropical, upper subtropical, and alpine bioclimatic zones)at the rate of 1.8, 1.98, 2.06, and 1.80 mm/year, and in lower sub-tropical, temperate, and lower subalpine bioclimatic zones, increasing at the rate of 0.45, 1.81 and 1.28mm/year, respectively. Precipitation did not show any particular trend at decade intervals. The average annual temperature at different bioclimatic zones clearly indicates that temperature at higher elevations is significantly increasing more than at lower elevations. In lower tropical bioclimatic zone (LTBZ), upper tropical bioclimatic zone(UTBZ), lower subtropical bioclimatic zone (LSBZ), upper subtropical bioclimatic zone(USBZ), and temperate bioclimatic zone(TBZ), the average temperature increased by 0.022, 0.030, 0.036, 0.042 and 0.051oC/year, respectively. The decade level temperature scenario revealed that the hottest decade was from 1999-2009. The average temperature was found as 24.1, 21.8, 19.7, 17.5, and 13.3oC in LTBZ, UTBZ, LSBZ, USBZ, and TBZ, respectively, and the average annual precipitation in LTBZ, UTBZ, LSBZ, USBZ, TBZ, LBZ, and ABZ was 2002.1, 2613.1, 2223.9, 3146.9, 1447.2, 952.1, and 361.7mm/year, respectively, in CHAL. With the impact of climate change site and region-specific, this information highlights the need to mitigate climate change in different bioclimatic zones.

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.

Caribbean SIDS are among the most vulnerable to climate change which will have a disproportionate impact on local environments and economies. Whilst there is a growing literature on how Caribbean SIDS can adapt to become more resilient a question that has received little attention is with regard to migration as an unplanned response. It is recognised that events such as hurricanes and flooding can lead to internal relocation in the short term but societal responses to droughts through migration have not generally been investigated. This paper seeks to address this by considering the case of the island of Carriacou, part of the state of Grenada. Carriacou with its small population, limited land area and local economy, historically based on agriculture has had a high degree of migration. This is in part a response to limited economic opportunities. Environmental stress manifest through limited water availability, inappropriate land management and social conditions is likely to be exacerbated by climate change and variability. Resultant increases in the frequency and intensity of droughts, in the absence of proactive interventions, are likely to result in non-linear migration, both to Grenada itself and beyond.

This paper performs non-parametric Mann Kendall (MK) trend analysis of historical hydroclimatic data (1961-2016), an ensemble climate model validation and a computation of 16 Expert Team on Climate Change Detection and Indices (ETCCDI) temperature and rainfall extremes indices. The climate indices are evaluated using MK test and annual trend analysis for two Representative Concentration Pathways (RCP4.5 & RCP8.5) future scenarios from 2020 to 2045 over Mono River Basin (MRB) in Togo. The annual and seasonal trend analyses are assessed on historical potential evapotranspiration, mean temperature, rainfall and discharge data. Results show positive and negative trends of hydroclimatic data over MRB from1961 to 2016. Mean temperatures increase significantly in most of the stations while a negative non-significant trend is noticed for rainfall. Meanwhile, the discharge presents a significant seasonal and annual trend for three gauge stations (Corrokope, Nangbéto and Athiémé). Validation of the ensemble climate models reveals that the model under-estimates observations at Sokode, Atkakpamé and Tabligbo stations, however linear regression and spatial correlation coefficients are higher than 0.6. Moreover, the percentage of bias between climate model and observations are less than 15% at most of the stations. Finally, the computation of extreme climatic indices under RCP4.5 and RCP8.5 scenarios shows a significant annual trend of some extreme climatic indices of rainfall and temperature at selected stations between 2020 and 2045 in the MRB. Therefore, relevant governmental politics are needed to elaborate strategies and measures to cope with projected climate changes impacts in the country.

Humans may be exposed to microbial pathogens at recreational beaches via environmental sources, such as water, sand, and aerosols. Although infectious disease risk from exposure to waterborne pathogens has been an active area of research for decades, sand is a relatively unexplored reservoir of pathogens and fecal indicator bacteria (FIB). Beach sand and water habitats provide unique advantages and challenges to pathogen introduction, growth, and persistence, as well as continuous exchange between habitats. Models of FIB and pathogen fate and transport in sandy beach habitats can help predict the risk of infectious disease from recreational water use, but filling knowledge gaps such as decay rates and potential for microbial growth in beach habitats is necessary for accurate modeling. Climatic variability, whether natural or anthropogenically-induced, adds complexity to predictive modeling, but may increase human exposure to waterborne pathogens via extreme weather events, warming of water bodies and sea level rise in many regions. The popularity of human recreational beach activities, combined with predicted climate change scenarios, could amplify the risk of human exposure to pathogens and related illnesses. Other global change trends such as increased population growth and urbanization are expected to exacerbate contamination events and the predicted impacts of increasing levels of waterborne pathogens on human health. Such changes will alter microbial population dynamics in beach habitats, and will consequently affect the assumptions and relationships used in population models and quantitative microbial risk assessment (QMRA). Here, we discuss the literature on microbial population and transport dynamics in sand-water continuum habitats at beaches, how these dynamics can be modeled, and how climate change and other anthropogenic influences (e.g., land use, urbanization) should be considered when using and developing more holistic, beachshed-based models.

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.

Fracking in the UK has yet to reach full industrial development but it is still subject to significant opposition. This study uses Beck’s Risk Society theory and anti-politics to examine the views voiced by opponents to fracking in Yorkshire, England. A qualitative approach was used; local newspaper reports were evaluated alongside semi-structured interviews with protesters to provide a thematic analysis. Although there are signs of post-materialist concerns with the environment these issues did not dominate the discussion. Scientists were not held responsible for the risks involved in fracking. Instead economic greediness of politicians and austerity measures were perceived as putting the environment and people’s health at risk. Interviewees thought fossil fuel energy production was economically advantaged over more sustainable energy and jobs in the low carbon economy. Protesters’ trust in politicians had been eroded but faith in democracy remained. It is suggested a citizen-led deliberative approach to all the concerns raised, not simply those relating to scientific risk, might achieve some level of resolution over fracking in the UK.

Ecosystem services (ES) are increasingly recognized as a means to adapt to the ongoing impact of climate change and associated impacts. However, these ES itself are facing adverse impact of climate change especially in developing countries where most of the people are dependent on these services for their livelihood. Very little is known about the relationship between the climate change and ES. Here we assess the impact of climate change on ecosystem services in ES rich landscape of Panchase Mountain Ecological Region of western Nepal. The study area was divided into three ecoregions from lowland through midland to the upland region. Focus group discussion, and key informant interview were used to elicit the required data for the study, which was further supported by transect walk, field observation and secondary source of information. Major impacts of climate change were observed are, reduced availability of water, reduced food production, forest ecosystem, shifting species composition in forest ecosystem, farmland abandonment, and their associated ecosystem services. We recommend to initiate the management actions to help ES adapt to climate change, and which in return could support the ecosystem itself and people dependent on the ES in adaptation to climate change by providing various goods and services.

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

Climate change threatens water, sanitation and hygiene (WaSH) facilities and services, as these are intimately linked to the water cycle and are vulnerable to changes in the quantity and quality of available water resources. Floods and droughts, which pollute and reduce water delivery respectively, have now become a perennial issue to deal with in the northern regions of the country, including the Bolgatanga Municipality. This study aimed to assess the degree to which climate change adaptation measures are mainstreamed into the WaSH development planning process in Ghana. Stakeholders from government and non-government agencies were interviewed to gain perspectives on the threat of climate change, the inclusion of climate change in WaSH planning and the barriers preventing mainstreaming. In general, despite awareness and concern about climate change, adaptation measures have been regarded to be far away from the immediate concerns of WaSH development planning. Most of the current measures are reactive and respond to environmental issues rather than to climate change stressors. In essence, stakeholders expressed the view that the adaptive capacity of the Municipality was low and that mainstreaming has not yet occurred. Despite the lack of progress, there are great opportunities for mainstreaming climate change adaptation into planning through increasing awareness and capacity, legislative and institutional changes and the development of participatory systems to provide early warning systems and disaster risk analyses that will inform future planning.

This study integrated coastal-watershed models and combined a risk assessment method to develop a methodology to investigate the impact resulting from coastal disasters under climate change. The mid-western coast of Taiwan suffering from land subsidence was selected as the demonstrative area for the vulnerability analysis based on prediction of sea level rise (SLR), wave run-up, overtopping, and coastal flooding under the scenarios of 2020 to 2039. Database from tidal gauges and satellite images were used to analyze sea level rise using EEMD (Ensemble Empirical Mode Decomposition). Extreme wave condition and storm surge were estimated by numerical simulation using WWM (Wind Wave Model) and POM (Princeton Ocean Model). Coastal inundation was then simulated via WASH123D watershed model. The risk map of study areas based on the analyses of vulnerability and disaster were established using the AHP (Analytic Hierarchy Process) technique. Predictions of sea level rise, the maximum wave condition and storm surge under the scenarios of 2020 to 2039 are presented. The results indicate that the sea level at the mid-western coast of Taiwan will rise in an average of 5.8 cm, equivalent to a rising velocity of 2.8 mm/year. The analysis indicates that Wuqi, Lukang, Mailiao, and Taixi townships are susceptive, low resistant and low resilient, and reaches the high risk level. The assessment provides that important information for making adaption policy in the mid-western coast of Taiwan.

Long term Precipitation and temperature variations are one of the main determinants of climate variability of one’s area. The aim of this study is to determine trends variation in climatic elements of temperature and precipitation in the southern zone of Tigray regional state, Ethiopia. The station is assumed for the study of climatic records over southern zone of the region in detection for probable trends. The daily, monthly and annual precipitation totals and temperature observed at korem meteorological station were used for the period of 1981-2010 for Precipitation and 1985 – 2010 for minimum and maximum temperature. Summary of descriptive statistics and Mann Kendall test methods were employed for the observed data analysis to demonstrate any existence of possible trends. The main findings of the study indicated that the mean and maximum temperature had a general increasing trend; however, minimum temperature showed decreasing trend. In general annual temperature from 1985 – 2010 of the area showed a warming trend. Moreover analysis of the 30 years (1981-2010) annual precipitation showed a coefficient of variation ranging from 33.77 – 233 %. It indicated that the precipitation dissemination is not normal with large year to year variances.

In Bangladesh, climate change is a major concern because of its geophysical location and climate dependent agriculture. As sessile organisms, crops plants have to face difficulties often in this environmentally vulnerable country. Therefore, this study examines the seasonal trend of two climatic parameters viz. temperature (maximum and minimum) and rainfall over a period of 1983 to 2013. Besides, this study provides insight into the relationship between climatic parameters and crop yield of two major crops viz. rice and wheat during 1997-2013. To assess the relationship of climatic parameters with time and yield using Pearson correlation analysis, time series data used at an aggregate level. SPSS software utilized for this analysis. The cropping seasons such as rice growing seasons Aus (summer rice), Aman (autumn rice) and Boro (winter rice) exhibited a significant increase in maximum and minimum temperature. Rainfall found to have a decreasing trend for all the seasons. This study also revealed that the climatic parameters had significant effects on rice yield, but these results varied among three rice crops. Maximum temperature had positive effects on all rice yields, especially on Aus and Aman. Minimum temperature had a negative effect on Aman rice yield but a positive effect on Aus rice yield. Wheat yield negatively associated with temperature. Rainfall exhibited negative relation with both rice and wheat yield.

Subnational governments play a key role responding to climate change risks in terms of policy strategies and instruments. This article analyzes how Brazilian municipal and state governments have developed and implemented public policies to mitigate and to adapt to climate change risks. We surveyed all cities’ and states’ climate policies within the country. The methodological approach includes five main points of analysis: 1. mitigation targets and intentions; 2. adaptation actions; 3. stakeholders’ participation; 4. policy implementation; 5. participation in networks related to climate change. Our results suggest that even though subnational climate policies in Brazil are isolated initiatives within the national context, they play an important role responding to climate change risks in different scales and levels. The strongest Brazilian policies with both mitigation and adaptation actions counted on previous mobilization for the climate issue involving different stakeholders from several segments of the society. These governments have also participated in transnational cooperation networks related to climate change.

Cities exemplify the evolving world with changing demographics and climates. Urban green spaces play a crucial role in improving the quality of life of people through their potential to mitigate temperatures. Therefore, comprehending their impact is of para-mount interest. Given the challenges in obtaining temperature data from urban locations, this study develops Artificial Neural Networks (ANNs) to predict daily and hourly temperatures in Valladolid, Spain, with a particular focus on urban allotment gardens and a forested urban park. ANNs were built and evaluated from various combinations of inputs (X), hidden neurons (Y) and outputs (Z) under the practical rule of "making net-works simple, to obtain better results". The best performing model was 6-Y-1 ANN archi-tecture with an impressive result of Root Mean Square Error (RMSE) = 0.42°C in the urban garden called Valle de Arán. However, other five ANN architectures were also tested (7-Y-5; 6-Y-5; 7-Y-1; 3-Y-Z and 2-Y-1). ANNs dedicated to urban temperature analysis hold immense potential for urban planning and research, aiding in under-standing the urban climate, forecasting future temperatures, identifying temperature mitigation strategies and even for managing urban crops

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

Climate change-induced events amplify existing social, political, economic, infrastructural and environmental concerns in many Global South cities, and perhaps no city is more vulnerable than Bangladesh’s capital of Dhaka. Climate-induced rural-urban migration is a profound concern, and Dhaka’s political leaders have embraced technology-based innovation as a solution pathway. This article explores the societal impact of Dhaka’s innovation environment strategies for climate change adaptation and mitigation. Employing a case study qualitative methodology, our three findings expand knowledge about innovation-urban climate mitigation as understood by Dhaka-based entrepreneurs: First, the most effective innovations were not the most technologically advanced, but those with the highest degree of participant ownership. Second, gaps between recipient, corporate and governmental understandings of effective mitigation and adaptation harmed projects, and were driven by different definitions of risk and competing understandings of vulnerability. Third, even the most technical climate adaptation measures were inherently political in their application. We discuss how to better position urban climate innovation infrastructures in Bangladesh and beyond, including developing a better recognition of innovation lifecycles for urban climate adaptation and widening our definitions of ‘innovation’ to better incorporate more effective and inclusive climate adaptation solutions.

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

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region's climate has a significant impact on how water is managed and used, mostly in the primary sector (agroforestry systems, livestock, and agriculture), and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the S. Francisco River basin (SFRB) is assessed in three periods (1970−2000, 1981−2022) in the past and 20412060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot-summer (Csa) and warm-summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The Source and the mouth of SFRB are projected to endure the major impacts of climate change that is followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability, and quality for human use will all be impacted. Consequences on ecosystems, agricultural and for the socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating to a larger extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in the São Francisco River basin from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45%, and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$ 6,000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin's dispersed demographic and economic profile. To build routes towards a shared sustainable goal—namely, to adapt and reduce the expected climate change impacts in SFRB—it is imperative that integrated measures be conducted with the cooperation of stakeholders, local population, and decision-makers.

The Canadian Prairies are associated with high natural hydroclimatic variability including the frequent periodic occurrence of droughts and pluvials. These extremes carry various risks in-cluding significant damage to the economy, environment and society. The well-documented level of damage necessitates further risk assessment and planned reductions to vulnerability, particu-larly in light of a warming climate. A logical starting point involves awareness and information about the changing characteristics of such climate extremes. We focus on the compound occurrence of droughts and pluvials as the risks from this type of event are magnified compared to the hy-droclimatic extremes in isolation. Also, research on compound droughts and pluvials is limited. Therefore, the purpose of this paper is to synthesize recent literature concerning the risks of com-pound droughts and pluvials, including examples of past occurrences, with a focus on the Cana-dian Prairies. Since literature from the Prairies is limited, global work is also reviewed. Rela-tionships between drought and pluvials are characterized using the SPEI Global Monitor for the Prairies, emphasizing the recent past, and through synthesis from the Prairie literature. That re-search mostly considers drought and pluvials as separate events, but is integrated here to charac-terize the relationships of these extremes. Examples of periods of compound droughts and exces-sive rainfall provide insights into the regional hydroclimatic variability. Furthermore, most lit-erature on future projections strongly suggests that this variability is likely to increase, mainly driven by anthropogenic climate change. These findings suggest means of decreasing vulnerabil-ity and associated damages. Although the study area is the Canadian Prairies, the work is rele-vant to other regions that are becoming more vulnerable to increasing risks of and vulnerabilities to such compound extremes.

The A.C.Q.U.A. (Advisable Conscious Quality Use from Assisi) project, promoted by the Climate and Energy and Heritage Design courses of the Planet Life Design Master Program, addresses the theme of the recovery and regeneration of ancient wash-houses in the context of energy, environmental sustainability and innovation, a way of understanding cultural heritage in the wider sense of heritage community through the active participation of all the actors involved: universities, institutions, businesses, students and citizens. The proposal, tested in the municipalities of Assisi and Ruviano (ITALY), involves the creation of a "Community Wash House", a new way of carrying out the usual domestic act of washing clothes in the open air, next to the places where this rite was traditionally performed, in technologically innovative constructions that use renewable energy sources and encourage a reduction in household consumption of water and energy. This project is part of the training of professionals in the new inter-university course that combines knowledge of the tools of technical and scientific design with historical and cultural perspectives in a perspective of sustainable redevelopment of existing structures in the area and the use of alternative energy sources with low climate impact, calculated using the statistics of the Copernicus CDS.

How robust is our assessment of impacts to ecosystems and species from a rapidly changing climate during the 21st century? We examine the challenges of uncertainty, complexity and constraints associated with applying climate projections to understanding future biological responses. This includes an evaluation of how to incorporate the uncertainty associated with different greenhouse gas emissions scenarios and climate models, and constraints of spatiotemporal scales and resolution of climate data into impact assessments. We describe the challenges of identifying relevant climate metrics for ecological models and evaluate the usefulness and limitations of different methodologies of applying climate change to both quantitative and qualitative ecological response models. We discuss the importance of incorporating extreme climate events and their stochastic tendencies in assessing ecological impacts and transformation, and provide recommendations for better integration of complex climate-ecological interactions at relevant spatiotemporal scales. We further recognize the compounding nature of uncertainty when accounting for our limited understanding of the interactions between climate and biological processes. Given the inherent complexity in ecological processes and their interactions with climate, we recommend integrating quantitative modeling with expert elicitation from diverse disciplines and experiential understanding of recent climate-driven ecological processes to develop more robust understanding of ecological responses under different scenarios of future climate change. Inherently complex interactions between climate and biological systems also provide an opportunity to develop wide-ranging strategies that resource managers can employ to prepare for the future.

Research Highlights: Data of advanced-age provenance tests were reanalyzed applying a new approach, to directly estimate the growth of populations at their original sites under individually generated future climates. The results reveal surprisingly high resilience potential of fir species. Background and Objectives: The growth and survival of silver fir under future climatic scenarios is insufficiently investigated at the xeric limits. The selective signature of past climate determining the current and projected growth was investigated to analyze the prospects of adaptive silviculture and assisted transfer of silver fir populations, and of the introduction of non-autochthonous species. Materials and Methods: Hargreaves’ climatic moisture deficit was selected to model height responses of adult populations. Climatic transfer distance was used to assess the relative drought stress of populations at the test site, relating these to the past conditions to which the populations had adapted. ClimateEU and ClimateWNA pathway RCP8.5 data served to determine individually past, current, and future moisture deficit conditions. Beside silver fir, other fir species from South Europe and the American Northwest were also tested. Results: Drought tolerance profiles explained the responses of transferred provenances and predicted their future performance and survival. Silver fir displayed significant within-species differentiation regarding drought stress response. Applying the assumed drought tolerance limit of 100mm relative moisture deficit, most of the tested silver fir populations seem to survive their projected climate at their origin until the end of the century. Survival is likely also for transferred Balkan fir species and for grand fir populations, but not for the Mediterranean species. Conclusions: The projections are less dramatic than provided by usual field assessments. Some results contradict generally accepted concepts. The method fills the existing gap between experimentally determined adaptive response and the predictions needed for management decisions. It also underscores the unique potential of provenance tests.

The urgency to address the adverse impacts of climate change on livelihoods and ecosystems has seen an increase in global driven initiatives. However, shifting vulnerabilities associated with land use resource based adaptation and maladaptive feedback loops they create have been given low attention. Policy discourses that frame adaptation as a local responsibility and bias towards reducing industrial Greenhouse gas (GHG) emissions at the expense of Agricultural emissions across scale are thought to account for the undesirable situation. This calls for a reflective policy framework and climate policy innovation. We provide counter arguments using Drivers, Pressure, State, Impact, Response (DPSIR) model and telecoupling principles to suggest use of resilience as an integrative lens in visualising the proposal. Using a case study on resource constrained smallholder dairy production systems, western Kenya, we analyse the critical issues in the context of decision making and environmental externalities. The effect of price risks on dairy cattle feeding strategies and ultimately carbon footprints and ecoefficiencies were examined through methane simulation and gross margin analysis (GM). The lowest ecoefficiency was associated with exclusively local coping strategies i.e. Maize Stover (Ms), while the highest ecoefficiency was observed in feeding strategies that utilise external resources and/or legume fodders. We conclude that management of externalities need to capture institutional, economic processes and incentive systems, as well as organizational and policy coherence to shape the interests and behaviour of individual land user. In particular, policy innovation should focus on price and market risks as critical factors that mediate actor decision making at implementation level as they impact GHG emissions which transcend individual decision boundaries.

To meet the dual-carbon objective, China's economy needs to move from a carbon-intensive to a green economy. Green technology innovation and renewable energy development are key to promoting green economic growth. The study uses 2010–2022 provincial panel data from 30 Chinese provinces. The super-efficient SBM model measures the province's green economic growth index. A panel fixed-effects model is used to experimentally evaluate how green technology innovation and renewable energy development affect green economic growth. Green financing moderates and a panel threshold model tests the threshold effect of renewable energy development on green economic growth. The results demonstrate that (1) China's green economic growth is rising and has a "U" shape. (2) all selected variables significantly impact green economic growth. However, population density, government intervention, and industrial structure are inversely associated with GEG. Green economic growth is significantly boosted by the moderate role of green finance in the development of renewable energy and green technological innovation. (3) Renewable energy development has a single threshold non-linear effect on green economic growth, depending on its development level and green technological innovation. Considering China's current condition and research findings, this study examines the green energy transition to promote green economic growth and high-quality economic development. Meanwhile, puts forward some important policy recommendations.

In India, epilepsy is often viewed with superstition, considered a curse rather than a medical condition. Unfortunately, many affected individuals never receive proper medical attention from neurologists, leading them to seek out alternative remedies, including sorcery. Presently, the number of neurologists in India stands at approximately 3000, a concerning figure given the prevalence of epilepsy, which is reported to affect 5.59 to 10 individuals per 1000. This equates to over one million epilepsy patients across the country, representing more than 1% of the total population. Alarmingly, rural areas experience a higher incidence of epilepsy, around 2%, compared to urban centres, where the incidence is approximately 0.5%. This stark contrast underscores the urgent need for improved access to neurological care, particularly in underserved regions.The term "epilepsy" originates from the Greek verb meaning "to seize" or "to get hold of," forming the basis of its etymology. In certain societies, epilepsy is still interpreted as a "penalty for involvement in a forbidden ritual," although perceptions vary among different cultural groups. Individuals diagnosed with epilepsy (PWE) often exhibit behaviours that have led some to speculate about demonic possession or past-life transgressions as causative factors. Consequently, the term "epilepsy" carries diverse social connotations, leading to variations in treatment approaches based on differing perspectives of the condition. Regrettably, some negative attitudes towards epilepsy have fueled stigma, enduring disability, and significant adverse outcomes for those living with the condition.The majority of unreported cases turn to sorcery, exacerbating the already high mortality rates associated with epilepsy disorder and status epilepticus. Various treatment modalities exist for patients with epilepsy to manage their seizures. Given the debilitating and life-altering nature of epilepsy, India offers a range of options including medications (antiepileptic drugs or AEDs), devices, and surgical interventions. When an individual receives a diagnosis of epilepsy (defined as experiencing at least two unprovoked seizures within a short timeframe), life can be dramatically impacted. Several cases highlight the challenges patients face, leading to an increase in Disability Adjusted Life Years (DALY) overall. For newly born infants, constant vigilance from the mother is essential to monitor for any signs of seizure activity around the clock. When a pediatric patient is enrolled in school, their education is often profoundly disrupted. Should the patient be female, her existence would undergo a profound transformation, marked by societal perceptions deeming her as unfortunate and rendering the prospect of marriage untenable. Seizures in young adults precipitate job loss, thereby exacerbating societal burdens. Conclusion: There is a pressing need to raise awareness about epilepsy among the general populace of India. Dispelling misconceptions surrounding epilepsy is essential to steer individuals away from reliance on superstition, and instead, encourage them to seek guidance from certified specialists in nervous system disorders. Thankfully, by following the treatment regimen prescribed by a qualified neurologist, patients can significantly increase their chances of living a life free from seizures, thereby enhancing their overall quality of life and personal fulfilment.

The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. Based on the core essentials of economic toughness, this paper constructs the tourism economic toughness evaluation index system, uses the entropy weight TOPSIS method to measure the tourism economic toughness of 10 counties and cities in the Yili River Valley in 2010-2019, analyzes its spatio-temporal evolution characteristics through the standard deviation ellipse, the traditional Markov chain, and the spatial Markov chain, and uses the grey correlation analysis method to analyze the driving factors of the tourism economic toughness. The results show that: (1) the economic resilience of tourism in the Yili River Valley shows a "W"-shaped time-series dynamic development trend with an average index of 0.28394, in which it experienced a decline from 0.28 to 0.27 during 2012-2013 and 2015-2016; (2) Spatial Pattern: The Yili River Valley tourism economic resilience is characterized by a clear uneven spatial distribution. The city of Yining, representing the northwestern region, exhibits a high level of resilience, while the southwestern region, endowed with rich tourism resources, demonstrates a medium level of resilience. Conversely, the central to southeastern counties and cities, such as ChabuchaerXibo Autonomous County and other counties and cities, are characterized by a lack of developed tourism facilities, which has resulted in a lower level of resilience and a weak development situation; (3) In terms of spatial and temporal evolution, the standard deviation ellipse is stabilized year by year pointing to "northwest-southeast", the clustering tendency is gradually enhanced, and five tourism economic resilience convergence clubs are identified, whose internal transition probability is significantly affected by spatial location, and which show obvious stability and neighborhood effects; (4) Regarding the driving factors, the impact of each driving factor on the resilience of the tourism economy reaches the statistical significance threshold of 0.77 or above. Among them, the number of employees in the tertiary industry, especially the input of high-quality talents in the tourism industry, plays a key role in improving the quality of tourism services and strengthening the industry's ability to withstand risks and development potential.

Inclusive and sustainable development has become an important part of China's sustainable development agenda, the self-recovery and stability of China's economy cannot be achieved without the macro-governance of the government. Figuring out the internal logic of digital finance and economic resilience is an important part of effective government governance. Based on the panel data of 193 counties in five provinces in northwest China from 2014 to 2021, the paper tested digital finance and county-level economic resilience by using two-way fixed-effect model, intermediary-effect model and threshold-effect model, to test whether financial development promotes government governance in underdeveloped regions. The results prove that digital inclusive finance significantly enhances the resilience of county economies by improving capital allocation efficiency, stimulating entrepreneurship and employment, and reducing pollution emissions. In addition, there are dual threshold effects between capital allocation efficiency and employment vitality, in which capital allocation efficiency has a gradually increasing threshold effect, and entrepreneurship and employment vitality have a fluctuating increasing threshold effect. Therefore, "Digital inclusive finance" in underdeveloped regions is an indispensable part of financial globalization；promoting the healthy development of digital finance is the basis and premise for providing a good financial environment for government management; deepening the reform in the financial field and promoting the green and sustainable development of finance are the future trend and direction of efforts.

This article delves into the enduring relevance of Liberal International Relations (IR) Theory amidst persistent criticisms regarding power dynamics and its applicability in emerging states. Despite its detractors, Liberal IR Theory offers a nuanced understanding of state behavior, blending social contexts with power dynamics. It recognizes the intricacies of economic interdependence and advocates for a balanced approach in advancing democracy and human rights. While nationalism poses challenges to international institutions, their adaptability endures. Leaders, albeit constrained, retain the capacity to foster peace through visionary leadership and global cooperation. By acknowledging its limitations and fostering open dialogue, Liberal IR Theory continues to evolve, poised to contribute to a just and peaceful global order.

BACKGROUND: Patients with diabetic foot ulcers (DFU) and chronic limb-threatening ischemia (CLTI are at higher risk for major amputations and mortality. The aim of this study was to assess the safety and cost-efficacy of intramuscular injection of autologous monocyte-rich PRP platelet-rich plasma Tropocells® PRP (Estar Medical, Holon, Israel) in diabetic patients with chronic limb-threatening ischemia (CLTI) in which revascularization was not feasible. METHODS: a retrospective study was carried out on a series of patients with type 2 diabetes, grade Texas 3C or D DFU, and CLTI. All patients had undergone at least a previous revascularization and were allocated to a surgery waiting list for major amputation. According to the data provided by the manufacturer (https://www.zuccatobiotech.it/index.php/prodotti/tropocells), the monocyte-rich PRP kit obtained a platelet-rich plasma with a high concentration of peripheral blood mononuclear cells (with a proportionately lower amount of lymphocytes), a low concentration of neutrophils and an almost complete depletion of red blood cells. All patients underwent a procedure of local infiltration of autologous mononuclear cells through multiple perilesional and intramuscular injections of 10 mL PBMNC suspensions (0.2–0.3 mL in boluses) performed below the knee along the relevant vascular axis (anterior tibial artery and posterior tibial artery) at intervals of 1–2 cm and to a mean depth of 1.5–2 cm, using a 21 G needle. The procedures were performed according to the instructions of the manufacturer and were repeated at least two times (maximum 3 times) at intervals of 30 days. The principal endpoint was a composite of TcPO2 values at the first toe ≥30 mmHg and/or TcPO2 increase of at least 50% from baseline and/or ulcer healing. Secondary endpoints were individual components of the primary endpoint, quality of life, any adverse events, and direct costs. All the endpoints were evaluated at 26 weeks. RESULTS: Out of 21 enrolled patients, 13 (61.9%) reached the primary endpoint, whereas three patients underwent a major amputation, and two patients died. The median TpCO2 was significantly increased, and pain was significantly reduced. The overall mean and median cost per patient were 9,255±7,328€ and 4,001 [2,991;7,565]€, respectively. CONCLUSIONS: the use of PBMNCs implants in patients with DFU and no-option CLTI seems to be efficacious in reducing the risk of major amputation and improve ulcer healing.

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. Carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China's future carbon quota allocation will gradually transition from free allocation to auction allocation,the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism and constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model and systematically researches the power generation structure under different auction ratios with the time scale of months and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions.The results of the study show that after comprehensively comparing the total economic cost, renewable energy development and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits.

This study employs traditional OLS (ordinary least squares) regression analysis to investigate the influence of various external factors on Bitcoin price fluctuations from January 2014 to March 2023 using a multidimensional approach. We use factors from the traditional financial market, such as economic policy uncertainty (EPU), oil prices, the NASDAQ index, and gold prices, to identify factors contributing to Bitcoin volatility. Considering the unique situation in the Bitcoin market, that is, 24-hour trading and the short duration of its existence, we incorporate the broadest possible data range to achieve alignment between Bitcoin data and other datasets. The findings of the statistical analysis indicate that EPU and the NASDAQ index promote positive fluctuations in Bitcoin volatility, whereas gold prices act as a dampener. However, we find no empirical support for the influence of energy prices on Bitcoin volatility. These results suggest that Bitcoin should not be underestimated; all stakeholders should treat the issue of Bitcoin volatility seriously, including governments, who should actively regulate the Bitcoin market, and investors, who should recognize the dangers of this volatility, making rational decisions based on individual circumstances and employing flexible trading strategies.

The brick manufacturing sector in Bangladesh is experiencing rapid growth, leading to notable environmental and health concerns. The primary objective of this research is to examine the Savar Upazila, a region of significant economic significance owing to its favorable brick manufacturing conditions and proximity to Dhaka city. Brick kilns, among other sources, constitute significant contributors to air pollution. The study utilized primary and secondary data to examine brick kiln emissions' effects on the surrounding area's environment and public health. The collection of primary data was conducted in multiple zones within Savar Upazila, which is home to a significant number of brick kilns. The utilization of secondary data provided valuable insights regarding the toxic pollutants discharged by these kilns and the corresponding health risks they pose. The participants provided accounts of various health ailments, such as dermatological conditions, optical difficulty, and respiratory complications, further aggravated by brick kilns' incidents. The prevalence of crop losses, soil degradation, and reduced agricultural yields was confirmed by 74% of the respondents. The trees and crops in the surrounding area experienced adverse effects due to the deposition of dust particles. During periods of inactivity, the concentrations of sulfur oxide (SOx) were between 6 and 9 times lower compared to periods of operation. Similarly, nitrogen oxide (NOx) levels were observed to be 4 to 6 times lower during non-operational phases. The degradation of water quality in adjacent bodies has been attributed to the deposition of dust and ash originating from brickfields, resulting in substantial repercussions on aquaculture. A significant proportion of participants indicated experiencing diverse health issues, notwithstanding the employment prospects generated by brick kilns, thereby underscoring the adverse consequences on both the environment and the local economy.

Zambia recently experienced extended hours of load shedding due to reduced hydroelectricity generation attributed to poor rainfall patterns. The inability to meet energy demand has influenced the government to consider alternative energy sources. This study aims to assess the economic feasibility of the eight sites using a 25-turbine layout for a 4 MW generic wind turbine at 130m hub height. An economic evaluation mathematical model was developed to analyze the economic feasibility using net present value, simple payback period, internal rate of return, and levelized cost of electricity (LCOE). The study shows that the Lusaka wind farm was the most economical with 386 GWh energy yield analysis (EYA), wind speed of 8 m/s, NPV of 316 million dollars, SPP of 2.9 years, IRR of 82%, and LCOE of $0.182/ kWh. The results also show that the other seven sites are economically feasible, with Petauke being the lowest. The study's economic sensitivity analysis conducted by varying the average electricity tariff shows that Lusaka was the most financially viable site. Therefore, policymakers should develop cost-reflective feed-in tariff (FiT) schemes and power purchase agreements for the country to have cost-reflective electricity tariffs that will motivate independent power producers to invest in Zambia.

Interior designers play a pivotal role in shaping the built environment and catalyzing positive change through the adoption of sustainable design practices. This study centers on the analysis of prevailing attitudes held by interior designers in Jordan towards sustainable interior design practices. Through a comprehensive methodology involving a literature review and a three-part questionnaire, the research explores the benefits, challenges, and integration of sustainability principles. The study highlights substantial awareness (85%) of sustainable interior design's environmental impact and resource preservation. Additionally, 81% acknowledge its enduring significance, and 89% recognize its diverse benefits. While 61% exhibit familiarity, 27% claim professional experience. Among sustainability indicators, energy efficiency scores 4.25, resource efficiency 4.27, and "Design aligns with laws and regulations by the Ministry of Labor" ranks highest at 4.37. This study significantly augments our understanding of sustainable interior design by introducing a comprehensive evaluation framework that encompasses the three sustainability dimensions. It equips decision-makers with a robust tool to identify specific practices that bolster sustainability performance, further advancing the field.