Average Annual Temperature Research Articles

Spatial Differentiation and Influencing Factors of Traditional Villages in Fujian, China: A Watershed Perspective

Watersheds provide a spatial framework for tightly coupling human activities and the natural environment. Investigating the spatial distribution patterns of traditional villages within watersheds is crucial for comprehending their origins and advancing conservation and development efforts. This study employs methods such as the nearest neighbor index, kernel density estimation, spatial auto-correlation analysis, stepwise regression, and geographically weighted regression to explore the watershed characteristics and influential factors governing the spatial differentiation of traditional villages in Fujian Province. The findings indicate that traditional villages in Fujian exhibit an overall clustered distribution within the watershed space, with a tendency to cluster along basin boundaries, primarily concentrated in three hot spot regions. In the remaining small watersheds, the distribution is more balanced. Traditional villages are predominantly located near low-order streams, displaying a distribution pattern along tributaries, while in the Huotongxi river basin, they are more evenly distributed near second-, third-, and fourth-order streams. Relief, annual average temperature, annual average precipitation, arable land, per capita GDP, distance to county-level or higher-grade cities, and the concentration of cultural heritage preservation units are the primary factors affecting the spatial differentiation of traditional villages within watersheds, exhibiting significant spatial heterogeneity. Finally, this study proposes recommendations for the cluster protection and development of traditional villages in watersheds, addressing spatial, cultural, landscape, industrial, and governance aspects.

Comprehensive analysis of the impacts of climate and land use changes on flood damage (Case study: AqQala, Iran)

ABSTRACT Population growth, community development, and waste generation impact climate, land use, water resources, and urban heat island effect. This research assesses the impacts of climate and land use changes on flood damage for different return periods (RPs) in AqQala area, Iran. Climate change anticipation is conducted using the CMCC-ESM2 model under shared socioeconomic pathways (SSPs) 126, 370, and 585 of the Intergovernmental Panel on Climate Change (IPCC) sixth assessment report (Coupled Model Intercomparison Project Phase 6 – CMIP6). The LARS-WG model is used to downscale climatic information, and land use mapping is processed through Landsat satellite images in ENVI 5.3. The Markov chain method is implemented for 2050 and 2080 via TerrSet. Hydrographs and inundation maps are generated by the Autodesk Storm and Sanitary Analysis (SSA) and Hydrologic Engineering Center's River Analysis System (HEC-RAS) models. Results show an increase in average annual precipitation (up to 46%) and temperatures (up to 3.39 °C) under different SSP scenarios until 2080. The result indicates that land use changes are more significant than climate change. Peak flood discharge and damages could escalate by 38 and 29%, respectively, in the worst-case scenario. Eco-friendly design and implementation are crucial for improving the situation.

Predicting potential and quality distribution of Anisodus tanguticus (Maxim.) Pascher under different climatic conditions in the Qinghai-Tibet plateau.

Anisodus tanguticus (Maxim.) Pascher, a distinctive medicinal plant native to the Qinghai-Tibet Plateau, China, has garnered attention due to increasing market demand. This study explores the impact of environmental factors on the distribution and levels of active compounds namely anisodamine, anisodine, and atropine within A. tanguticus. Our goal was to identify suitable cultivation areas for this plant. This study employs the maximum entropy model to simulate the suitable area of A. tanguticus under current conditions and three climate change scenarios during the 2050s and 2070s. The finding revealed that altitude, precipitation in the warmest season (Bio 18), the average annual temperature (Bio 1) exerted significant influences on the distribution of A. tanguticus. Among the environmental factors considered, temperature difference between day and night (Bio 2) had the most substantial impact on the distribution of anisodamine, temperature seasonal variation variance (Bio 4) predominantly influenced anisodine distribution, and Bio 1 had the greatest effected on the distribution of atropine. The suitable areas primarily exist in the eastern Qinghai-Tibet Plateau in China, encompassing a total area of 30.78 × 104 km2. Under the climate scenarios for the future, the suitable areas exhibit increasing trends of approximately 30.2%, 30.3%, and 39.8% by the 2050s, and 25.1%, 48.8%, and 60.1% by the 2070s. This research would provide theoretical suggestions for the protection, and cultivation management of A. tanguticus resources to face the challenge of global climate change.

MODELING THE SPATIAL DISTRIBUTION OF THE EUROPEAN LAND SNAIL COCHLODINA LAMINATA (GASTROPODA, PULMONATA, CLAUSILIIDAE) IN THE EASTERN PART OF THE RANGE

Species distribution modeling (SDM) allows to defi ne the potential range and identify key factors that determine the habitat suitable areas. In this study, we made forecasts for the distribution of the European clausilid Cochlodina laminata (Montagu, 1803) in the eastern part of the range using SDM methods. Various algorithms are used to create models, including machine learning algorithms. We selected climatic factors and Earth remote sensing (ERS) data as predictors (extended vegetation index and land use). An ensemble forecast based on all models showed that the range of C. laminata is a wedge-shaped and largely coincides with the scheme proposed earlier by I.M. Likharev. However, in the eastern and southeastern parts the potential range turned out to be wider. The boundaries of the C. laminata potential distribution have been established in the forest-steppe and steppe zones, as well as in the Black Sea region and the Caucasus. The use of remote sensing data made it possible to identify suitable territories in more detail, which is especially important in the peripheral zones of the range. It is shown that the most signifi cant factors in the distribution of the species in the studied area are the average annual temperature, temperature seasonality and precipitation of the warmest quarter.

Sheep anthrax outbreak in Muddaballi Village, Karnataka, India: a comprehensive study of factors

Anthrax, caused by Bacillus anthracis, remains a persistent threat to global public health and livestock industries. This study investigates a sheep anthrax outbreak in Muddaballi Village, Karnataka, India. Muddaballi has a population of 2,450 people and a livestock population of 2,279 animals, including 756 cows, 82 buffaloes, 1,129 sheep, and 312 goats. The village experienced anthrax outbreaks in 2016, 2021, and 2023, with significant sheep mortalities: 4 out of 200 sheep in 2016, 25 out of 150 sheep in 2021, and multiple incidents in 2023 affecting different farmers with mortality rates ranging from 4 to 20 sheep. The ecological characteristics, including an average annual temperature of 27.0°C and annual rainfall of 587 mm, alongside proximity to the Tungabhadra reservoir, played a crucial role in spore survival and transmission. The study highlights socioeconomic factors and Risk Exposure and Mitigation Behaviour (REMB) as critical determinants of anthrax incidence, with farmers reporting strong agreement on the influence of these factors (Likert scale: 4-5). The integration of AI tools for early detection and rapid response, comprehensive disease surveillance, and ensuring vaccine accessibility are essential measures. Training initiatives for local veterinarians and farmers are also crucial to mitigate future outbreaks. This multifaceted approach is vital for effective anthrax prevention and control in Muddaballi and similar regions.

Correlation between ecological factors and effective component content, flower, and leaf traits of Epimedium pubescens

No systematic research has been reported on the correlation between different ecological factors and the effective component content, flower, and leaf traits of Epimedium pubescens. In this study, 21 kinds of E. pubescens in different regions were investigated, and the content of two effective components of icariin(I) and Epimedin C(C), as well as six leaf traits and 12 flower traits were determined. The correlation between 11 ecological factors and the above traits in different regions for five consecutive years was explored. The results showed that no significant correlation was observed between the ecological factors and the total content of two effective components(I+C) of E. pubescens. Latitude and temperature(including annual average temperature, annual average minimum temperature, and soil temperature of each soil layer) were significantly positively and negatively correlated with the ratio of the content of the two effective components(C/I)(P<0.01), respectively. There was a significant correlation between ecological factors and flower traits, and the annual average soil temperature of each soil layer, annual average temperature, and annual average minimum temperature were significantly correlated with most flower traits in multiple years(P<0.01). However, a weak correlation between ecological factors and leaf traits was detected. A significant positive correlation of the annual average soil temperature of each soil layer and annual average humidity(P<0.01) with the width of nutrient leaf in only a few years was detected. Therefore, it was concluded that the total content of effective components of E. pubescens was determined by genetics, with a slight influence of ecological factors. The annual average temperature, annual average minimum temperature, and soil temperature of each soil layer were the ecological factors that had the most significant impact on flower traits, which showed significant differences in different regions, and similar results were not found in leaf traits. Overall, this study systematically conducted a correlation analysis between ecological factors and the effective components, as well as flower and leaf traits, providing guidance for the quality improvement, introduction, and domestication of E. pubescens.

Intensified warming suppressed the snowmelt in the Tibetan Plateau

Understanding how hydrological factors interrelate is crucial when examining the impact of climate warming on snowmelt. However, these connections are often overlooked, leading to an unclear relationship between temperature and snowmelt. This study investigates the complex interplay between temperature and snowmelt in the Tibetan Plateau from 1961 to 2020, focusing on how extreme high-temperature events affect the frequency of extreme snowmelt. Using a structural equation model, we detected three temperature-related factors that predominantly influenced snowmelt and extreme snowmelt. The annual average temperature was found to have a significant indirect impact on snowmelt, mediated by changes in snowfall, snow depth and snow cover. By contrast, high-temperature days (daily maximum temperatures exceeding the 90th percentile) and heat waves (at least three consecutive high-temperature days) negatively affected extreme snowmelt directly or indirectly. The direct effect of increasing extreme temperature events was associated with an earlier onset of high-temperature periods, which accelerated snowmelt and shortened the duration of extreme snowmelt periods. Additionally, the reduction in snow cover owing to warming emerged as a main factor suppressing snowmelt and extreme snowmelt frequencies. We also revealed spatiotemporal variations in the temperature‒snowmelt relationship that highly depended on changes in snowmelt patterns. The study elucidated why warming suppresses snowmelt and extreme snowmelt events in the Tibetan Plateau, highlighting the mediating roles of snow-related and phenological factors. The findings will provide scientific support for climate simulation and water management policymaking in alpine regions worldwide.

Optimization using central composite design for continuous absorption of CO2 gas with green sodium silicate in a packed bed column

If absolutely nothing is taken to reduce carbon dioxide (CO2) emissions, atmospheric concentrations of carbon dioxide will rise to 550 parts per million by 2050, which will have disastrous effects on the world's climate and food production. An apparatus has been designed and setup to convert CO2 into a useful and vital product which was silica. The effect of different experimental factors on the compositions by weight percent of SiO2 and Na2CO3 were studied including the CO2 gas flow rate (1.037, 1.648 and 2.26 L/min), initial concentration of sodium silicate (Na2SiO3) solution (5, 7.5 and 10 %wt) and the packing size (15.95, 20.175, and 24.4 mm). An optimization process was performed using the Design Expert software program to achieve the optimum experimental conditions at which the maximum weight percent of SiO2 (main product), the minimum weight percent of (Na2CO3) (side product) and the minimum reaction time were determined. From the optimization process, the maximum weight percent of SiO2 (25.63 %), the minimum weight percent of (Na2CO3) (9.62 %) and the minimum reaction time (7.59 min) were achieved at the following optimum experimental conditions of CO2 gas flow rate = 1.648 L/min, packing size = 24.4 mm and initial concentration of sodium silicate solution = 10 %wt.

Potential and Influencing Factors of Urban Spatial Development under Natural Constraints: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area

As urbanization in China progresses, urban spatial development is transitioning from rapid expansion to more intensive and compact growth. This study examined the role of physical geography and environmental factors in shaping the urban spatial development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the current natural conditions, we selected evaluation indices from topography, hydrogeology, climatic conditions, and natural disasters. These indices were used to create a carrying capacity and suitability evaluation system for development land under natural constraints. Finally, the spatial development potential of the city was finalized by taking into account the current state of the built-up area of the city. Meanwhile, we employed the Optimal Parameters-based Geographical Detector and assessed the impact of 14 natural factors on the spatial development of urban built-up areas. In 2020, the GBA had 52,168.77 km2 of land suitable for construction, of which 34,241.13 km2 was highly suitable (61.29%) and 17,927.64 km2 was moderately suitable (32.09%). At the Bay Area level, 90.15% of the development potential remains untapped; at the city level, Zhaoqing City has the highest potential at 99.56%, while Macao has the lowest at 26.83%. Key factors influencing urban development include silty sand content, annual average relative humidity, and cumulative temperature above 0 °C, with varying impacts across different urban scales. At the Bay Area level, the silty sand content, annual average relative humidity, and cumulative temperature above 0 °C are the main influencing factors on the spatial development of urban built-up areas; at the city level, the main factors are annual average relative humidity and cumulative active temperature above 0 °C. This study reveals the important influence of natural environmental factors on urban spatial development, which is conducive to promoting sustainable development of land resources in GBA.

From vulnerability to vitality: Climate change as a catalyst for economic transformation in small island developing states

As climate change intensifies, its associated risks become increasingly important to societal well-being, with small island developing states (SIDS) being particularly susceptible. The challenges faced by these nations transcend the impacts of their greenhouse gas emissions and cannot be mitigated by emission reduction alone. This paper establishes an innovative, interpretable machine learning model for the first time using import and export data from 1970 to 2020 for nine economically advanced Small Island Developing States, to investigate how economic transformation in small islands occurs against specific climatic contexts and to analyse the impact of these climatic challenges in the process of economic transformation. The study finds that when the average annual temperature exceeds 26 °C over the past two years, or when the sea level rises more than 30 mm, certain islands rapidly complete their economic structural transformation. This indicates that climate change is significantly reshaping the developmental trajectories of these small island economies. To confront these challenges, these states are continuously shifting their developmental focus, reconfiguring their economic structures and growth models to address the ongoing challenges posed by climate change.

Spatial patterns and influencing factors of takeaway consumption in 56 cities in China

With the development of the digital economy, the takeaway industry is expanding rapidly. To realize the high-quality development of the takeaway sector, it is necessary to understand the spatial differentiation characteristics of takeaway consumption in Chinese cities and its influencing factors. To this end, we quantitatively studied the spatial distribution of takeaway consumption in 56 cities. We used the number of takeaway orders (copies/person) and the per capita takeaway consumption amount (RMB/person) in major Chinese cities in 2019 to characterize takeaway consumption in China. We investigated the driving mechanisms and factors affecting takeaway consumption amounts per capita and order per capita in China. The results show that takeaway consumption amounts per capita and order per capita is higher in East China than in North and Central China. The tertiary industry population ratio is crucial to takeaway consumption amounts per capita and order per capita in major Chinese cities. Amounts and orders increase as the tertiary industry population ratio rises. Factors affecting takeaway consumption amounts per capita and order per capita in Chinese cities of different population sizes vary. The working-age population ratio heavily influences the takeaway consumption amounts per capita and orders per capita in megacities. Additionally, internet penetration and average annual temperature play a significant role in takeaway consumption amounts per capita and orders per capita in megalopolis. In big cities Ⅰ, the road capacity per capita and GDP per capita are the main factors affecting takeaway consumption amounts per capita and orders per capita. The tertiary industry population ratio is the core factor that determines takeaway consumption amounts per capita and orders per capita in big cities Ⅱ. The interaction between natural and socio-economic factors dramatically increases the impact of takeaway consumption amounts per capita and order per capita in Chinese cities. In conclusion, this study provides a macro-level insight into the spatial characteristics and development factors of takeaway consumption in major Chinese cities. This knowledge is crucial for promoting the takeaway economy's sustainable development and realizing the takeaway industry's green transformation.

Responses of Soil C, N, P and Enzyme Activities to Biological Soil Crusts in China: A Meta-Analysis.

Biological soil crusts (BSCs) are often referred to as the "living skin" of arid regions worldwide. Yet, the combined impact of BSCs on soil carbon (C), nitrogen (N), phosphorus (P), and enzyme activities remains not fully understood. This study identified, screened and reviewed 71 out of 2856 literature sources to assess the responses of soil C, N, P and enzyme activity to BSCs through a meta-analysis. The results indicated that BSC presence significantly increased soil C, N, P and soil enzyme activity, and this increasing effect was significantly influenced by the types of BSCs. Results from the overall effect showed that soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), and available phosphorus (AP) increased by 107.88%, 84.52%, 45.43%, 27.46%, and 54.71%, respectively, and four soil enzyme activities (Alkaline Phosphatase, Cellulase, Sucrase, and Urease) increased by 93.65-229.27%. The highest increases in SOC, TN and AN content occurred in the soil covered with lichen crusts and moss crusts, and significant increases in Alkaline Phosphatase and Cellulase were observed in the soil covered with moss crusts and mixed crusts, suggesting that moss crusts can synergistically enhance soil C and N pool and enzyme activity. Additionally, variations in soil C, N, P content, and enzyme activity were observed under different environmental settings, with more pronounced improvements seen in coarse and medium-textured soils compared to fine-textured soils, particularly at a depth of 5 cm from the soil surface. BSCs in desert ecosystems showed more significant increases in SOC, TN, AN, and Alkaline Phosphatase compared to forest and grassland ecosystems. Specifically, BSCs at low altitude (≤500 m) with an annual average rainfall of 0-400 mm and an annual average temperature ≤ 10 °C were the most conducive to improving soil C, N, and P levels. Our results highlight the role of BSCs and their type in increasing soil C, N, P and enzyme activities, with these effects significantly impacted by soil texture, ecosystem type, and climatic conditions. The implications of these findings are crucial for soil enhancement, ecosystem revitalization, windbreak, and sand stabilization efforts in the drylands of China.

Marine Pollution and Waste Management

Water covers more than 70% of the surface of the globe. The ocean, which is amazing and significantly controls the world's climate, also has a hidden crisis, namely marine pollution. In the modern world, marine pollution is becoming a bigger issue. Article 1 (1) (4) of UNCLOS : says that “Pollution of the marine environment” means the introduction by man, directly or indirectly, of substances or energy into the marine environment, including estuaries, which results or is likely to result in such deleterious effects as harm to living resources and marine life, hazards to human health, a hindrance to marine activities, including fishing and other legitimate uses of the sea, impairment of quality for use of seawater and reduction of amenities”. Chemicals and garbage, most of which originate on land and are blown or carried into the water, are the two main components of marine pollution. Marine pollution, caused by human activities like improper disposal, shipping, and overfishing, harms ecology, health, and global economic institutions. Solutions include international agreements, sustainable fishing, improved waste disposal, and raising awareness. Education-based campaigns have the power to inspire citizens, groups, and governments to action. The legislative reforms and sustainable practices are significantly aided by environmental organizations and advocacy groups. The government has made several notable efforts, such as the plastic ban, marine protected areas, clean-up programs, and environmentally friendly fishing. Several countries have enacted plastic bags, which have significantly reduced the amount of plastic pollution, while the ocean may not be affected. Creating marine protected zones helps safeguard biodiversity and gives damaged ecosystems a place to recover. This article gives a general overview of the complex issue of marine pollution and shows how important it is to have efficient waste management plans. It investigates diverse marine pollution types and causes, emphasizing the dangers it poses, such as biodiversity loss, potential health hazards for humans, and significant financial expenses.

Influence of Nitrogen Application Rate on Wheat Grain Protein Content and Composition in China: A Meta-Analysis

The nitrogen application rate (NAR) has a significant effect on the contents of wheat grain protein and its composition. There is still no consensus regarding the appropriate NAR, given the differences in studied conditions and influence of factors such as geographical location, climate, and soil nutrient contents. In this study, 66 papers related to wheat grain protein and its composition published from 1984 to 2021 were selected for meta-analysis in comprehensively evaluating the response of wheat grain protein content and composition to NAR in China. The results reveal that NAR significantly increased total protein content by 9.49–28.6%, gliadin by 9.13–30.5%, glutenin by 12.9–45.4%, albumin by 5.06–15.8%, and globulin by 8.52–24.0% of wheat grain in China, respectively, compared to no nitrogen application. The optimal NAR is 240–300 kg ha−1 when specific planting conditions are not being considered. Under different growing conditions, the NAR that provided the greatest increase in wheat grain protein and its composition varied as follows: 180–240 kg ha−1 in Northwest China and at >100 m altitudes; >300 kg ha−1 in North China and at <100 m altitudes and lower soil base nutrient levels; 240–300 kg ha−1 in Southeast China, with higher soil nutrients levels and for all average annual temperatures and precipitation ranges. In conclusion, the results of the present study reveal that it is feasible to systematically enhance the contents of wheat grain protein and its related fractions by appropriate NAR under different cropping conditions.

Statistical downscaling of future temperature and precipitation projections in Iraq under climate change scenarios

The research was aimed to; (i) study the observed climate in Iraq from 1971 to 2021 for annually, monthly and seasonally averages of temperature and precipitation for nine meteorological stations; ii) produce RCP4.5 and RCP8.5 scenarios for Iraq region under historical (1900–2005) and future periods (2006–2100) for temperature and precipitation using NCAR-CCSM4 database; and iii) examine the anomaly for near future (2025–2034) and medium future (2050–2059), related to 1986–2005. To evaluate the performance of the monthly averages of temperature and precipitation, three bias correction techniques i.e., Delta, Empirical Quantile Mapping, and Quantile Mapping were applied to nine metrological stations. The results revealed that the Delta is the most efficient method to bias correction for the monthly averages related to temperature and precipitation. The annual average temperature increased from 22.9 C° in 2006, based on both RCP4.5 and RCP8.5, to 24.0 C° and 27.2 C°, respectively, and the anomaly increased from −0.9 C° and −1.9 C° in 2006, to 0.6 C° and 2.4 C°. The precipitation annual and winter month's averages under RCP4.5 and RCP8.5 from 2006 to 2100, 2020–2039 and 2040–2059 showed that southwest region in Iraq (Basra, Missan and Thi-Qar provinces) had more drought and low precipitation than the other regions. From 2029 to 2034 and 2050–2054, rainy years have been predicted, using RCP4.5. Based on RCP.8.5, from 2025 to 2034 and 2050–2055, should witness rainy years, followed by a drought period. The results expected to support decision-makers in incorporating a national initiative to break down social barriers, encourage growth prospects, particularly in southern Iraq.

Study on Driving Factors and Spatiotemporal Differentiation of Eco-Environmental Quality in Jianghuai River Basin of China

For an in-depth analysis of the ecosystems of the Jianghuai Valley, this study utilized municipal data from 2017 to 2021. In addition, this study established an index scale evaluation system for the quality of the ecological environment in the Jianghuai Valley. This system encompasses five critical dimensions: drivers, pressures, states, impacts, and responses, in accordance with the DPSIR model. The entropy-weighted TOPSIS method combined with the gray correlation method was used to assess the ecological status of each region of the Jianghuai Valley at different time periods and the driving factors affecting the ecological quality of the Jianghuai Valley. Our study yields several key conclusions. First, it was observed that the ecological environment within the Jianghuai Valley showed a continuous upward bias in inter-annual variability. Second, there exists variation in ecological environment quality among the eleven urban areas within the Jianghuai Valley, highlighting regional disparities. Third, among the eleven urban areas in the Jianghuai Valley, Anqing has the best ecological quality, and Huainan has the worst ecological performance. Fourth, the ecological environment quality within the Jianghuai Valley demonstrates an aggregated pattern. From west to east, this pattern is delineated by distinct areas: one marked by excellent ecological environment quality, another exhibiting average ecological environment quality, followed by a zone characterized by good ecological environment quality, and finally, an area with poor ecological environment. Fifth, our analysis reveals that Q9 (indicating the percentage of excellent air days) and Q13 (denoting the annual average temperature) have a pronounced correlation with the Jianghuai Valley’s ecological quality. Conversely, Q3, which pertains to the rate of natural population growth, had the lowest relevance to the ecological quality of the Jianghuai Valley.

A research on the relationship between landslide area changes and environmental factors in the southern Tibetan plateau

Introduction: Landslides are known to be one of the most frequent types of geological disasters. However, there is not an established method for large-scale, rapid, and high-precision landslide extraction. The quantitative impact of environmental changes on landslide development is also not well understood, which hinders accurate assessments and decision-making in environmental and disaster response. The polar regions, including the Antarctic, the Arctic, and the Tibetan plateau (TP), sensitive to global environmental changes, are significantly affected by global warming. This leads to extensive landslide development, particularly in the southern TP. This research focuses on new landslides in the southern TP, exploring extraction methods and the relationship between landslides and environmental factors.Methods: Utilizing the Google Earth Engine (GEE) and an improved Otsu threshold segmentation algorithm, we processed remote sensing images with 10 m resolution to identify landslide areas. The proposed Normalized Landslide Bare-soil Separation Index (NDLBSI) achieved an 87% pre-extraction accuracy in extracting landslides from Sentinel-2 images from 2019 to 2023. For the pre-extraction results, manual interpretation and correction were carried out, and a model correlating annual landslide changes with environmental factors was established based on least squares multivariate statistical methods.Results: Results show that a significant increase in landslide areas in the southern TP over the past 5 years, correlating with the watershed-wide increase in annual average temperature and vegetation cover, along with a decrease in snow cover area.Discussion: These changes could affect soil and rock moisture, influencing soil stability and landslide occurrence. The study provides valuable insights for large-scale landslide detection and understanding the environmental factors influencing landslides, which is of some significance for landslide hazards early warning.

Does Pricing Carbon Mitigate Climate Change? Firm-Level Evidence from the European Union Emissions Trading System

Abstract In theory, market-based regulatory instruments correct market failures at least cost. However, evidence on their efficacy remains scarce. Using administrative data, we estimate that, on average, the European Union Emissions Trading System (EU ETS)—the world’s first and largest market-based climate policy—induced regulated manufacturing firms to reduce carbon dioxide emissions by 14–16% with no detectable contractions in economic activity. We find no evidence of outsourcing to unregulated firms or markets; instead, firms made targeted investments, reducing the emissions intensity of production. These results indicate that the EU ETS induced global emissions reductions, a necessary and sufficient condition for mitigating climate change. We show that the absence of any negative economic effects can be rationalized in a model where pricing the externality induces firms to make fixed-cost investments in energy-saving capital that reduce marginal variable costs.

Projections of the start of the airborne pollen season in Barcelona (NE Iberian Peninsula) over the 21st century

The effects of global warming are numerous and recent studies reveal that they can affect the timing of pollination. Temperature is the meteorological variable that presents a clearer relationship with the start of the pollination season of most of the observed airborne pollen taxa. In Catalonia, in the last fifty years, the average annual air temperature has increased by +0.23 °C/decade, and the local warming has been slightly higher than the one on a global scale. Projections point to an increase in temperature in the coming decades, which would be more marked towards the middle of the century.To analyse the effect of the increase in temperature due to global warming on the starting date of pollen season in Barcelona, a forecasting model has been applied to a set of projected future temperatures estimated by the European RESCCUE project. This model, largely used in the literature, is based on determining the thermal needs of the plant for the pollen season to begin. The model calibration to obtain the initial parameters has been made by using 20 years of pollen data (2000–2019), and the model effectiveness has subsequently been tested through an internal evaluation over the period of the calibration and an external evaluation on 4 years not included in the calibration (2020−2023). The mean bias error in the internal calibration ranged between −0.4 and − 0.6 days, and between +0.5 and − 8.3 in the external one, depending on the taxon. The results of the application of the model to the temperature projections over the 21st century point to a progressive advancement in the pollination dates of several pollen types abundant in the city, allergenic most of them. These advances ranged, at the end of the century, between 15 and 27 days, depending on the climate model, for the scenario of the highest concentrations (RCP8.5) and between 7 and 12 days for the emissions stabilization scenario (RCP4.5).

#365 Dialysis centers performance: socioeconomic and environmental determinants

Abstract Background and Aims Healthcare outcomes in hemodialysis centers are intricately shaped by a myriad of factors extending beyond clinical realms. This study explores the interplay of socioeconomic and environmental determinants on the performance of 7638 hemodialysis centers in the United States during 2022. Leveraging data from the Centers for Medicare & Medicaid Services, the United States Census Bureau, and the National Center for Environmental Information, our analysis encompasses outcomes like mortality, hospitalization, readmission rates, and emergency department visit rates. Method A dataset comprising information from 7638 US hemodialysis centers, spanning January to December 2022, was obtained through the Centers for Medicare & Medicaid Services, US Census Bureau and environmental data, and from the National Center for Environmental Information. The study assessed mortality, hospitalization, readmission, and emergency department visits within one-month post-hospitalization. Independent variables included dialysis center characteristics, state-specific socioeconomic and environmental data, analysed through descriptive statistics and a linear regression model. Results Results reveal a significant correlation between racial composition and outcomes, with states having higher Latino populations exhibiting lower ED visit rates, contrasting with elevated mortality rates in states with higher African American populations. Socioeconomic factors, such as education and insurance status, influence ED visit rates. Environmental determinants, specifically average yearly state temperature, impact mortality and hospitalization rates. Operational characteristics matter: for-profit centres and those providing higher number of hemodialysis bed correlate with decreased mortality rates, while centres offering peritoneal dialysis or late-shift services demonstrate lower emergency department visit rates. Conclusion Our study unveils a nuanced interplay of factors influencing outcomes in hemodialysis centers. Disparities rooted in race and socioeconomic status underscore the need for targeted interventions. Environmental considerations further contribute to the complexity, while operational characteristics reveal intriguing trends, challenging conventional expectations. This analysis provides a foundation for tailored strategies to enhance the performance and equity of hemodialysis centers.