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The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
... Carbon dioxide (CO2) emissions significantly contribute to climate change by playing a central role in the greenhouse effect. Combustion of fossil fuels and land use changes drive atmospheric CO2 concentrations, which in turn trap solar heat, leading to global warming and changes in the Earth's climate system [2]. These changes lead to higher average global temperatures, sea-level rise, and an increase in extreme weather events like heatwaves, droughts, and severe flooding [2]. ...
... Combustion of fossil fuels and land use changes drive atmospheric CO2 concentrations, which in turn trap solar heat, leading to global warming and changes in the Earth's climate system [2]. These changes lead to higher average global temperatures, sea-level rise, and an increase in extreme weather events like heatwaves, droughts, and severe flooding [2]. Studies highlight a direct link between the amount of 2 emissions, and the severity of observed and predicted climate changes [3]. ...
... The connection between CO2 emissions and their environmental impact is direct and concerning. The IPCC's [2] Fourth Assessment Report from 2007 states that rising atmospheric CO2 levels are the primary driver of climate change, leading to significant shifts in global climate patterns. Smith et al. [9] in 2014 reinforced this scientific consensus, finding that carbon dioxide emissions heighten the greenhouse effect, resulting in global warming and increasingly frequent and severe extreme weather events. ...
The growing concern over climate change has propelled the urgent need for technological innovation in clean energies, investing in Research and Development (R&D&I), a fundamental pillar for the global energy transition. This study focused on Spain, an active Organization for Economic Cooperation and Development (OECD) member, to examine and discuss the relationships between carbon dioxide () emissions, renewable energy generation, R&D&I investment, and GDP. Through data analysis, economic and environmental trends were highlighted, and the interaction between variables in the context of sustainability policies was explored. The results indicated a negative relationship between the increase in renewable energy generation and emissions, in line with international efforts to mitigate climate change. The robust statistical analysis provides insights into the effectiveness of Spain's energy and environmental policies and suggests a continuous trajectory of emissions reduction. This study modeled and discussed the importance of ongoing investment in R&D&I and implementing policies that reinforce the transition to a cleaner and more sustainable Spanish energy system.
... A atividade industrial é a principal causa dessas mudanças (Watson, 2001). O Painel Intergovernamental sobre Mudanças Climáticas (IPCC) prevê que o aquecimento global pode em breve atingir 1,5 °C, destacando a urgência de ações climáticas para mitigar efeitos como perda de biodiversidade e insegurança alimentar (IPCC, 2023;Wang et. al, 2024). ...
... al, 2024). Ações imediatas podem melhorar a saúde pública e promover a justiça climática (IPCC, 2023). ...
... Contextualização das estimativas das emissões de gases de efeito estufa no Acre Existe 95% de probabilidade de o aquecimento atual do planeta ser oriundo das emissões de gases de efeito estufa (GEE) decorrentes de atividades antrópicas, o que pode ocasionar a elevação da temperatura global entre 2,6 ºC e 4,8 ºC (Stocker et al., 2013). Para haver estratégias de adaptação e mitigação é necessário conhecer melhor e quantificar as emissões de GEE e suas fontes. ...
... A ocorrência natural desse processo mantém constante a temperatura em torno de 15 ºC. Sem a ocorrência natural do efeito estufa, a temperatura média do planeta gira em torno de 18 ºC (Simon;De Fries, 1992;Stocker et al., 2013). Entretanto, ao longo dos últimos séculos, a humanidade vem aumentando as emissões de gases de efeito estufa, presentes na atmosfera naturalmente, além das emissões de outros GEE, decorrentes exclusivamente das ações antrópicas, o que tem sido determinante para o processo de mudanças climáticas (The Core Writing Team et al., 2014). ...
... In recent years, many changes have been observed in the abundance, physiology, and community composition of phytoplankton, caused by climate variability, ocean warming, shifts in ocean stratification, increasing numbers of extreme events, and eutrophication (Ardyna et al., 2014;Cheng et al., 2019;Dai et al., 2023;Deppeler and Davidson, 2017;Ferreira et al., 2022;Lu et al., 2022;Xiao et al., 2018;Sridevi et al., 2019;Trainer et al., 2020;Wang et al., 2021;. Considering the profound impact phytoplankton have on ocean biogeochemical cycles and food webs, and considering current uncertainty in climate projections (IPCC, 2021), tracking the abundance and physiology of marine phytoplankton is of high importance. The chlorophyll-a concentration (Chl-a), a photosynthetic pigment present in one form or another in all marine phytoplankton, can be used to monitor phytoplankton abundance and physiology because it can be measured relatively easily through optical sensors mounted on satellites or in situ autonomous platforms and ship-based profiling rigs. ...
Phytoplankton occupy the oceans' euphotic zone and are responsible for its primary production; thus, our ability to monitor their patterns of abundance and physiology is vital for tracking ocean health. Ocean colour sensors mounted on satellites can monitor the surface patterns of phytoplankton daily at global scales but cannot see into the subsurface. Autonomous robotic platforms, like Biogeochemical-Argo (BGC-Argo) profiling floats, do not have the coverage of satellites but can monitor the subsurface. Combining these methods can help track phytoplankton patterns throughout the euphotic zone. In this study, using a global array of BGC-Argo floats (76,043 profiles, spanning from 2010 to 2023), we revisit empirical relationships between the surface and column-integrated concentrations of chlorophyll-a (a proxy for phytoplankton abundance and physiology), originally developed using ship-based profiling data. We show that these relationships agree well with BGC-Argo float data. We then extend the relationships, removing the binary switch in parameters between mixed and stratified waters and trophic conditions such that the column-integrated chlorophyll-a concentration can be estimated as a continuous function of surface chlorophyll-a and a proxy for stratification (we use the optical mixed-layer depth, the mixed-layer depth multiplied by the diffuse attenuation coefficient, which is proportional to the ratio of the euphotic depth to the mixed layer depth when it approaches 1). The new model is shown to perform well in statistical tests (using separate training and independent validation data, with a correlation coefficient > 0.73) and has fewer parameters than the earlier version. The model can be applied to satellite observations of surface chlorophyll-a and diffuse attenuation, together with fields of mixed-layer depth (e.g., from Argo), to track changes in column-integrated chlorophyll-a. Such fields may be useful for obtaining estimates of primary production, evaluating ecosystem models, and quantifying trophic energy transfer. The model may also be used to evaluate the influence of changing stratification patterns on phytoplankton abundance and physiology.
... One of the paramount reasons to shift away from business as usual is the stark environmental reality. Climate change, driven by anthropogenic greenhouse gas emissions, poses an existential threat (IPCC, 2021). Failing to reduce carbon emissions and transition to a low-carbon economy jeopardizes the habitability of our planet (Rockstr€ om et al., 2009). ...
Substantial sustainability innovation is not a mere aspiration; it's a structured journey that combines hard work, strategy, and collaboration. Substantial sustainability innovation represents a fundamental rethinking of business operations and strategies, challenging organizations to evaluate their impact on the environment, society, and economy. The subjects and concepts suggested in this chapter are deeply rooted in academic research as well as expert insights, and are characterized by a commitment to long-term value creation and competitive advantage. It transcends the boundaries of traditional sustainability practices, emphasizing a holistic view of sustainability that encompasses economic, social, and environmental dimensions.
... Global climate change, particularly the rising CO 2 concentration, has been receiving significant attention due to its profound impacts on the environment (Santos et al. 2023). The atmospheric CO 2 concentration is increasing at a rate of 0.4% per year, and it is projected to be 550 μL/L by 2050 and to 770 μL/L by 2100 (Stocker et al. 2014). The increase not only enhances plant photosynthesis, accelerates plant growth and development, and increases crop yield (Reyes-Fox et al. 2014;Qiao et al. 2019), but also increases the carbon-nitrogen ratio within plants, altering the resource allocation to primary and secondary metabolic products (Becker et al. 2023;Liu et al. 2024). ...
... Three climatic factors are exposing trees to increasing climatic stress, (1) rising summer temperatures that are associated with more frequent and more severe heat extremes, (2) increasing atmospheric vapor pressure deficits (VPD), and (3) an increasing frequency and severity of droughts (Adams et al., 2017;Hammond et al., 2022). Central Europe with its intensive forest management on most of the forested area is particularly vulnerable to climate change-induced destabilization of forests, as (i) warming and the increase in heat exposure are proceeding faster than in other northern temperate regions (IPCC, 2021;Vautard et al., 2023), and (ii) the pool of native tree species and especially the number of valuable timber species is small (Leuschner and Ellenberg, 2017). This has prompted intensive research on the climate vulnerability and drought and heat response of the major tree species of this region in recent time, notably of European beech (Fagus sylvatica L.), Norway spruce (Picea abies Karst.), ...
In recent decades, continued growth decline has been observed in various beech forest regions of Central and Western Europe, especially in the warmer lowlands, which is not necessarily linked to increased mortality. While earlier dendrochronological studies have shown that a deteriorating climatic water balance in the course of climate warming can drive negative growth trends, less is known about the effects of climatic extremes on tree growth, notably heat and rising atmospheric vapor pressure deficits (VPD). Through climate-growth analysis, we analyzed the influence of summer heat duration (frequency of hot days with Tmax > 30°C) and elevated VPD on the basal area increment (BAI) of dominant beech trees in 30 stands across a precipitation gradient in the northern German lowlands. Summer heat (especially in June) and elevated VPD are reducing BAI in a similar manner as does a deteriorated climatic water balance. While growing season length (GSL), derived from thermal thresholds of growth activity, has substantially increased since 1980, BAI has declined in the majority of stands, demonstrating a recent decoupling of tree productivity from GSL. We conclude that heat and elevated VPD most likely are important drivers of the recent beech growth decline in this region, while growing season length has lost its indicative value of beech productivity.
... The Earth's climate system has undergone significant changes characterized by warming over the past century (IPCC, 2021), which has profoundly impacted terrestrial ecosystems on seasonal and inter-annual scales (Nemani et al., 2003). Vegetation phenology, a natural phenomenon occurring under the influence of biological and environmental factors, is the growth and development rhythm formed by the long-term adaptation of vegetation to seasonal changes (Menzel et al., 2006;Richardson et al., 2013). ...
Understanding on relationships between seasonality of vegetation phenology and photosynthesis is lacking for desert ecosystems. We used digital camera (i.e., PhenoCam) to monitor the phenology of forest (i.e., 2 sites with one being closer to a lake) and grassland (i.e., 1 site) ecosystems in the Badain Jaran Desert, China. The vegetation phenology was quantified using vegetation indices calculated from the red, green, and blue digital numbers in images obtained by the PhenoCams. Additionally, various meteorological variables were continuously measured, and gross primary production (GPP) was obtained using the eddy covariance technique at the grassland site. The difference between the phenological periods extracted from the PhenoCam images and the artificial visual method was small (≤6 days), indicating that the digital camera can effectively obtain desert vegetation phenology. The key meteorological factors affecting changes in the vegetation indices were identified, with temperature being the most important factor (i.e., correlation coefficients = 0.4–0.8 and p‐value < 0.001 for all three study sites). Although precipitation showed weak correlation with the vegetation index (correlation coefficient = 0.18–0.14, p‐value < 0.01), rapid increases in the vegetation index were observed in response to precipitation events. Vegetation indices were strongly correlated with GPP variations at the grassland, and the strongest correlation was observed in the green‐up stage (correlation coefficient = 0.67 to 0.85, p‐value < 0.001). The highest GPP lagged about 1 month behind the peak in the vegetation indices in summer (June–August). Our results can markedly improve the knowledge of desert ecosystem processes and aid in assessing the influence of future climate changes in drylands.
... Carbon dioxide (CO 2 ) emissions resulting from fossil fuel combustion represent a critical component of anthropogenic greenhouse gas emissions and are the largest contributor to climate change in the industrial era (IPCC, 2021). These combustion sources, including power plants, cement production facilities, and refineries, make up nearly one-third of anthropogenic emissions (Crippa et al., 2022). ...
Carbon dioxide (CO2 ) emissions from combustion sources are uncertain in many places across the globe. Here, we estimate CO2 emission rates from a small number of collocated observations from the Orbiting Carbon Observatory‐3 (OCO‐3) and the Earth Surface Mineral Dust Source Investigation (EMIT), both onboard the International Space Station (ISS). These near‐simultaneous measurements allow for an unprecedented comparison of two unique space‐based CO2 sensors over both isolated coal‐fired power plants and multi‐source scenes in China. We estimate CO2 emission rates using integrated mass enhancement and a Gaussian plume model. Where validation data is available, 15 of the 19 estimated emission rates have errors less than 37%. For the multi‐source scenes, EMIT can estimate emissions from individual facilities but its aggregate emissions are 42% lower than OCO‐3, likely because it cannot detect small sources or diffuse emissions. OCO‐3, with its excellent precision, may better constrain CO2 emissions over the entire scene.
... The areas of significant reductions in CAW meeting the robustness criterion include most of the U.S. and eastern Canada, the Middle East, and eastern South America . These areas would suffer a greater scarcity of water resources due to global warming (Cramer et al., 2018;IPCC, 2021;Udall & Overpeck, 2017;Waha et al., 2017). All three areas can be attributed to the expansion of descending/dry zones of Hadley cells. ...
Global warming has changed both the amount of global precipitation and the atmospheric capacity to retain water. In this paper, a novel definition of the long‐term Capturability of Atmospheric Water (CAW) based on horizontal atmospheric water transport is proposed, describing the ability of a certain area to intercept and convert the atmospheric water transported by horizontal moisture flux into local precipitation. The significant decrease of the CAW in Amazon and Congo rainforests and Inside Greenland indicates that these areas were having less precipitation with the same water vapor in the past 42 years, while in Asia (especially China), CAW is showing a large‐scale increasing trend, verifying the regional humidifying. Considering the change of both the CAW and the background atmospheric water simultaneously, their mismatch degree is also investigated. The positive mismatch in Qinghai Tibet Plateau, Greenland, and the Andes, suggests higher susceptibility to climate change, and in the areas of negative mismatch (Amazon, Maritime Continent, southeastern China, the Eastern United States, India, and Japan), a more stable precipitation response to climate change is expected. The proposed concept of CAW provides a novel perspective to analyze the precipitation response to climate change on a global scale.
... Climate warming signals are intense on the Tibetan Plateau, which experiences powerful solar radiation due to its low latitude and high altitude [137]. The Tibetan Plateau regulates the climate of the entire eastern hemisphere and plays a significant role in international climate change [138]. ...
Beginning in 2005, Qinghai Lake on the Tibetan Plateau was the scene of the unprecedented appearance of avian influenza among migratory birds. These were significant events in the subsequent global spread of the virus to poultry (and occasionally humans) in many new countries on three continents. Events at Qinghai sparked energetic debates about the role of migratory birds in spreading influenza viruses among domestic and wild birds. In turn, this led to cross-disciplinary research that highlighted the interconnections of environment, wildlife, and human activities. Factors in the Qinghai case study (Qinghai) include the vast permafrost landscape of the Tibetan Plateau, the ecology of wild geese that migrate over the Himalayas, a high-altitude railway (the “permafrost rooster”) that traverses the Tibetan Plateau, and an avian virus (H5N1). This chapter considers multiple factors: the ecology of migratory birds, agricultural practices that mix wild and domestic birds, climate warming, and factory poultry farming. As a place at the crossroads of interconnected global phenomena such as avian influenza and climate change, the Qinghai case study provides a lens to envision the unintended consequences of natural and human forces over the coming decades.
... It is no secret that global warming is affecting regional climates resulting in increased temperatures and more severe weather storms (IPCC 2021). These changes are impacting several sectors including the building industry and require a combination of mitigation and adaptation actions to reduce them (VijayaVenkataRaman, Iniyan, and Goic 2012). ...
... As one of the major abiotic limitations to plant growth, water deficit is responsible for soil degradation and thus has significant effects on global crop yields Bahadur et al. 2019;Tezara et al. 1999). Climate extremes and man-made disruptions have led to changes in precipitation, increasing the severity and duration of droughts (Tang et al. 2024;IPCC. 2021). Currently, the majority of studies have focused on the tolerance and adaptation mechanisms of plants to drought stress (Abdalla et al. 2023;Waqar et al. 2022;Zhao et al. 2015). In the present study, we investigated the effects of the AM fungi C. etunicatum and F. mosseae and their combination in C. migao seedlings under both drought-st ...
... Yet climatological research indicates that the goalposts are moving. Climate change is accelerating both the frequency and severity of extreme weather, posing more (and more extreme) threats than in the past (IPCC 2023). What is more, communities that have historically been protected from extreme weather by topography, geography or climatology are now facing whole new weather threats due to changing weather patterns and intensifying severe weather risks (Wuebbels 2016). ...
This study seeks to understand how historical models of risk perception and protective action antecedents, as predicted by The Protective Action Decision Model (PADM), apply across micro‐regional differences in the context of Florida counties during the 2022 Hurricane Ian, and how these regional differences may lead to differences in reception, perception and response to information and evacuation warnings across the state. Two Florida communities (Southwest vs. Central and Eastern regions) with different typography, historical disaster experience, demographics and existing hazard adjustment programs were surveyed and compared. Results showed that, within the same hurricane event and broader geographic region (Florida), the two community locations differ in their reliance on information sources, social cues and prior hurricane experiences to inform risk perceptions and evacuation decisions. Additionally, different mediation patterns of risk perceptions were found between the antecedents and evacuation behaviours for the different community locations. The findings imply the importance to consider regional variations and to strategize messaging communicating risk and self‐protective behaviours accordingly.
... The Coupled Model Intercomparison Project (CMIP) has been instrumental in advancing climate modelling. With successive iterations, CMIP has introduced additional complexities, enabling a more nuanced understanding of biogeochemical interactions and regional variability (IPCC, 2001(IPCC, , 2007(IPCC, , 2013(IPCC, , 2021. Across CMIP3, CMIP5, and CMIP6, advancements in model sophistication have incorporated biogeochemical variables, improved spatial and temporal resolutions, and introduced Earth System Models (ESMs), (Watanabe et al., 2021). ...
This article investigates the methodological advancements and challenges in climate modeling, focusing on hydrological projections and their application in adaptive water governance frameworks. By exploring the evolution of the Coupled Model Intercomparison Project (CMIP), the paper highlights key advancements, including improved representations of biogeochemical cycles, regional variability, and advanced parameterizations. Specific emphasis is placed on microphysical processes that are critical to precipitation formation but remain major sources of uncertainty in hydrological projections. The article emphasizes the need to address these uncertainties through refined modelling methodologies and the incorporation of robust observational data. Experimental studies and advanced tools, including numerical simulations and machine learning emulators, are essential for linking fine-scale dynamics with global models and enhancing predictions of hydrological feedbacks. The synthesis highlights practical applications, emphasizing how refined models and a precise understanding of uncertainties support adaptive and sustainable water management, particularly in regions under acute stress. This interdisciplinary approach bridges technical precision and governance, providing actionable pathways for addressing global water challenges.
... Figura 8: Malla numérica utilizada para calcular la marea meteorológica a partir de datos de viento y presión atmosférica para cada GCM tanto para el período histórico como para un horizonte de análisis (Esparza, 2023) Nivel medio del mar El NMM corresponde al promedio anual del nivel instantáneo del mar y se calcula a partir de varios procesos físicos (Church et al., 2013;IPCC, 2013). Para efectos prácticos, existen numerosas bases de datos que consideran todos esos procesos en un solo valor de aumento del NMM, lo que simplifica los cálculos asociados a una consultoría. ...
Ante las brechas detectadas en la práctica de la ingeniería nacional, se propone una metodología para integrar los efectos del cambio climático en el diseño de infraestructura costera y portuaria. La metodología considera cuatro etapas: 1) selección de forzantes climáticos a escala global, 2) procesamiento de forzantes climáticos a escala regional, 3) procesamiento de variables de diseño a escala local y 4) aplicación en diferentes ámbitos del diseño de infraestructura. La metodología integra el cálculo de variables oceanográficas (e.g. presión atmosférica, viento, oleaje, marea astronómica, marea meteorológica y aumento del nivel del mar) en un diagrama de flujo que puede interactuar con otras variables de diseño, como los sismos y tsunamis. Se presentan ejemplos sobre cálculos de operatividad portuaria, nivel del mar extremo en playas, sobrepaso de obras marítimas y erosión de playas. Proponemos que el estado desarrolle las etapas 1) y 2), dando acceso libre a los actores que participan en el diseño de infraestructura costera y portuaria.
... Excessive radiative forcing from rising emissions of carbon dioxide and other greenhouse gases (GHGs) is already disrupting the climate in many ways. Damage includes ice cover and glaciers, sea level rise, extreme weather, ocean acidification, greater variability in agricultural and forest production, including risks of crop failure, damage to ecosystems, spread of disease, and other risks to humans and other life forms [12]. ...
Bio-mitigation lowers greenhouse gas technology dioxide levels. Chlorella sorokiniana during a 24-day laboratory study period were evaluated at five distinct CO2 concentrations: 5, 10, 15, 20, and 25 L/min while being cultivated in nitrogen, phosphorus, and potassium (NPK) growth media. The CO2 removal rate employed was 92.94% including proteins, lipids, phenols, flavones, glycosyrosiates, anthocyanins, and carotenoids, whereas the greatest level of gas was 25 L/min or 6000 mg/L. The biomass’s greatest proportion of proteins and lipids for the highest rate of gas (25 L/min) reached 47.08%, respectively, and 34.05% relative to the control 31.32% and 20.35%, respectively, as measured by its 0.102 nm difference from the control, and through the efficiency of the isolate of Chl. sorokiniana. It was tested by reducing the highest CO2 levels of 25 L/min within a 200 L photo bioreactor design. with a period of 24 days in the laboratory’s natural environment. After harvesting the algal reactor cultivation of 200 L, the biomass weight reached 900 g/L. This means that for every 1 g of algae biomass, 1.7 g of CO2 is consumed.
... On top of the existing problems, the hydroclimatic conditions of the region have been altered due to the warming climate, which makes sustainable development highly challenging. Alterations in numbers and periods of dry and wet days, a reduction in water content in rainforests, multidecadal drying trends in streamflow, an increase in temperature by 0.5 • C with a stronger increasing trend in minimum than maximum temperatures, and a decline of rainfall by 9% during the 20th century are a few examples of changes in the past few decades [6][7][8][9][10][11]. The continuation of changes in the climate can cause severe socio-economic vulnerability in the region due to the lack of adequate infrastructure, industrialization, mismanagement, and political issues [10,[12][13][14]. ...
The Congo River Basin is the second-largest watershed globally, flowing through nine countries before reaching the Atlantic Ocean. The Kasai River Basin (KARB), containing about one-fourth of Congo’s freshwater resources, plays a strategic role in sustaining navigation, food production, and hydroelectricity generation in Central Africa. This study applies a multi-model framework suited for data-scarce regions to assess climate change impacts on water availability in the KARB. Using two conceptual hydrological models calibrated with four reanalysis datasets and fed with bias-corrected outputs from 19 climate models under two representative climate pathways (RCPs), we project changes in the mean annual discharge ranging from −18% to +3%, highlighting the sensitivity of impact assessments to model and input data choices. Additionally, streamflow signatures (Q10, Q50, Q90) are projected to decline by approximately 9%, 18%, and 13%, respectively, under RCP 8.5. Annual hydropower potential is estimated to decrease by 14% and 5% under RCPs 4.5 and 8.5, respectively. These findings provide actionable insights for water management practices in the KARB, including guiding the development of adaptive strategies to optimize water allocation, mitigate risks of scarcity, and support sustainable agricultural and industrial activities in the region.
... Adopting a multi-species eco-evolutionary approach is important to understand how multiple species within their community and ecosystem simultaneously evolve to environmental change, and how such multi-species evolutionary changes affect community and ecosystem features in changing environments . One example involves the global increase in mean temperature and increased prevalence of heatwaves (IPCC 2012(IPCC , 2021. Consequently, many species will endure higher temperatures and extreme temperature variability more often (Christidis and Stott 2014). ...
Most eco‐evolutionary research focuses on ecological effects of single‐species evolution. We, therefore, know little of eco‐evolutionary dynamics when multiple species evolve simultaneously. We quantified evolution‐mediated ecological effects in communities equivalent in genetic diversity and starting biomass, but different in selection background (heatwave exposure) of one or all four zooplankton species (three Daphnia and one Scapholeberis species). We observed transient eco‐evolutionary effects that differed depending on which species in the community had evolved. Evolution did not always lead to higher abundances of the evolved species. Indirect effects on species abundances caused by evolution of another species could be as strong as direct effects mediated by its own evolution. The cumulative effect of evolution in multiple species was antagonistic for community composition and grazing pressure but additive for community‐wide biomass. Our results imply that focusing on single species' evolutionary effects on ecology may lead to unreliable predictions when multiple species evolve simultaneously.
Anthropogenic activities such as cattle grazing and forest clearing have led to the establishment of early successional grass layers in some native forests, which may inhibit or entirely prevent native tree regeneration. We hypothesize that increased grass coverage reduces or eliminates the establishment of native tree seedlings by limiting water availability to seeds and seedlings. This study aims to evaluate the impact of grass cover on tree seedling survival under varying levels of soil water stress. We conducted a field experiment using 36 experimental exclosures in two northwest Patagonian valleys, representing a regional gradient in altitude, rainfall, and tree canopy openness. Additionally, a greenhouse experiment was performed with 36 pots, manipulating four levels of grass cover and three levels of water stress. Results from both experiments showed similarities: in the field, the likelihood of finding a live tree seedling was approximately 2.78 times higher in areas without grass compared with grass‐covered sites. In the greenhouse, the presence of grass reduced the final number of established seedlings by an average of 43% across all irrigation levels, indicating significant water competition. These findings suggest that management practices promoting grass invasion could severely hinder tree regeneration in forests not adapted to large herbivore intensive grazing. Such situation may be exacerbated in regions suffering water limitation in the growing season or where the climate change would intensify water stress.
In the face of rapid population growth, urbanisation, and accelerating climate change, the need for rapid and accurate disaster detection has become critical to minimising human and material losses. In this context, geo-social media data has proven to be a sensible data source for tracing disaster-related conversations, especially during flood events. However, current research often neglects the relationship between information from social media posts and their corresponding geographical 15 context. In this paper, we examine the emergence of disaster-related social media topics in relation with hydrological and socio-environmental features on watershed level during the 2021 Western European flood, while focusing on transboundary river basins. Building upon an advanced machine learning-based topic modelling approach, we show the emergence of flood-related geo-social media topics both in river-basin specific and cross-basin contexts. Our analysis reveals distinct spatio-temporal dynamics in the public discourse, showing that timely topics describing heavy rains or flood damages were closely 20 tied to immediate environmental conditions in upstream areas, while post-disaster topics about helping victims or volunteering were more prevalent in less affected areas located in both upstream and downstream areas. These findings highlight how social media responses to disasters differ spatially across watersheds and underscore the importance of integrating geo-social media analysis into disaster coordination efforts, opening new opportunities for transboundary collaborations and the coordination of emergency response along border-crossing rivers.
iAtlantic Deliverable D2.5
Regional Habitat Suitability Modelling
This study addresses the urgent need to move the construction sector toward carbon neutrality and climate resilience, by considering the increasingly intense impacts of climate change. The research aims to evaluate the application of advanced digital prototyping tools and regenerative design principles to identify environmental risks at different scales, with a particular focus on cultural and natural heritage. The hypothesis is that the integration of climate data and predictive models with regenerative design can overcome existing barriers to sustainable practices and significantly enhance the adaptive capacity of the built environment, particularly in safeguarding cultural and natural heritage against the multi-hazard impacts of climate change. To test this hypothesis, an experimental study is conducted using a combination of climate data, advanced modeling and regenerative design tools to assess and manage multi-hazard impacts on cultural and natural heritage. Two case studies were analyzed: Palizzi Marina, a coastal town vulnerable to sea level rise and flooding, and Palazzo Mesiani in Bova, a historic building exposed to increased solar radiation and temperatures. This type of analysis has enabled a comprehensive multi-scenario and multi-hazard assessment that offers a detailed overview of the risks to be considered in the design phase. In conclusion, the research underscores the importance of interdisciplinary approaches and emerging technologies in resilient design frameworks. By integrating climate data and predictive models with regenerative design methodologies, this study can significantly contribute to enhancing the adaptive capacity of the built environment. This approach aids in the transition of the construction sector toward sustainability and climate resilience, particularly in protecting cultural and natural heritage.
The priority during an emergency, regardless of the type, is to rescue as many lives as possible. Field hospitals are usually installed to provide the primary relief to the affected population when hospitals are compromised or absent. There are several sanitary units worldwide ready to be transported to disaster areas. An average field hospital is equipped with an operating room, laboratory, and radiological equipment, but it does not include a unit for the infectious hospital solid waste treatment, which results in improper management with high infection risks and emissions due to incorrect operations (e.g., open incineration). Therefore, the present study identified two market-available solutions (an incinerator and a sterilizer) designed to be transported even under the challenging conditions typical of disasters and are suitable for treating infectious waste. The systems were assessed by a life cycle assessment (LCA), proving an emission savings >90% (considering all impact categories) using the sterilization system. The avoided combustion allows to halve the effect on climate change due to a portable incinerator. This study supplies interesting food for thought for the emergency managers, proving the possibility of integrating the sustainability also in the planning of the response to catastrophic events.
For decades, scientists have tried to explain the evidence for fluvial activity on early Mars, but a consensus has yet to emerge regarding the mechanism for producing it. One hypothesis suggests early Mars was warmed by a thick greenhouse atmosphere. Another suggests that early Mars was generally cold but was warmed occasionally by impacts or by episodes of enhanced volcanism. These latter hypotheses struggle to produce the amounts of rainfall needed to form the martian valleys, but are consistent with inferred low rates of weathering compared to Earth. Here, we provide a geophysical mechanism that could have induced cycles of glaciation and deglaciation on early Mars. Our model produces dramatic climate cycles with extended periods of glaciation punctuated by warm periods lasting up to 10 Myr, much longer than those generated in other episodic warming models. The cycles occur because stellar insolation was low, and because CO2 outgassing is not able to keep pace with CO2 consumption by silicate weathering followed by deposition of carbonates. While CO2 by itself is not able to deglaciate early Mars in our model, we assume that the greenhouse effect is enhanced by substantial amounts of H2 outgassed from Mars' reduced crust and mantle. Our hypothesis can be tested by future Mars exploration that better establishes the time scale for valley formation.
The Brewer‐Dobson circulation (BDC) characterizes the large‐scale meridional overturning mass circulation influencing the composition of the whole middle atmosphere. The BDC consists of two separate parts—a shallow branch in the lower stratosphere and a deep branch higher in the middle atmosphere. Climate models robustly project the advective BDC part to accelerate due to greenhouse gas‐induced climate change and this acceleration strongly influences middle atmospheric chemistry and physics in the projections. A prominent quantity that is being studied as a proxy for advective BDC changes is the net tropical upwelling across pressure levels, particularly in the lower stratosphere. The upper branch of the BDC has received considerably less research attention than its shallow part, although, together with the mean mesospheric pole‐to‐pole circulation, it couples the stratosphere and mesosphere and is responsible for a large portion of the interhemispheric transport in the middle atmosphere. Aiming to fill this gap, we here study climatology and trends in advective mass transport across the stratopause. Results based on the analysis of seven CCMI models include quantification of the climatological cross‐stratopause advective transport, characterization of its interannual variability and long‐term trend as well as detailed analysis of inter‐model differences using a novel decomposition methodology. Our results demonstrate that the changes in circulation speed as well as changes in horizontal and vertical structure in the upper stratosphere and mesosphere jointly shape the projected increasing advective mass flux across the stratopause due to increasing greenhouse‐gas emissions.
Coastal saline cropland ecosystems are becoming increasingly vital for food security in China, driven by the decline in arable land and the growing demand for resource-intensive diets. Although developing and utilizing saline land can boost productivity, it also impacts greenhouse gas (GHG) emissions. This study uses the Yellow River Delta as a case study to analyze the spatial-temporal patterns of carbon footprints in saline croplands from 2001 to 2020 and their correlations with climate factors, cropland management scale, and agricultural mechanization. The results reveal that agricultural production in this region is characterized by high inputs, emissions,
and outputs, with carbon emission efficiency improving significantly due to a
reduction in net carbon emissions. Major sources of carbon emissions include electricity, chemical nitrogen fertilizers, nitrogen input, and straw return, which together account for 65.06% of total emissions. Based on these findings, three key principles have been proposed for policy recommendations to enhance carbon emission efficiency. First, adopt tailored strategies for regions with different salinization levels. Second, strengthen cropland drainage infrastructure to mitigate the adverse effects of heavy rainfall. Third, expand the scale of cropland management through land transfers and promote agricultural mechanization. These insights offer valuable guidance for mitigating GHG emissions in coastal saline cropland ecosystems.
The rising demand for food globally due to unprecedented population growth has led to food insecurity in some populated regions, such as Africa. This leads to global agricultural production to be of increasing concern. The growing requirement for food in an era of a changing climate and scarce resources has inspired substantial crop yield prediction research. Another contributing factor to global food insecurity is climate change and its variability. The impact of increasing climate variability on rice crop yield is now evident. Predicting the potential effects of climate change on rice crops prompts the use of time series, machine learning, and ensemble models. The ensemble model was designed by assigning weights to the individual models based on their performance metrics, such as R-squared values and error rates. Results showed that the ensemble model achieved superior accuracy, with an R-squared value of 0.9523, surpassing the performance of the individual SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous Regressors) and LSTM (Long Short-Term Memory)models. The predicted yields aligned closely with observed values in both training and testing phases, demonstrating the model's ability to capture historical trends and generalise effectively to unseen data. This study shows the importance of integrating time-series forecasting and machine learning techniques to improve rice crop yield predictions.
Animals are predicted to shrink and shape-shift as the climate warms; declining in size, while their appendages lengthen. Determining which types of species are undergoing these morphological changes, and why, is critical to understanding species responses to global change, including potential adaptation to climate warming. We examine body size and bill length changes in 25 shorebird species using extensive field data (>200,000 observations) collected over 46 years (1975-2021) by community scientists. We show widespread body size declines over time, and after short-term exposure to warmer summers. Meanwhile, shorebird bills are lengthening over time but shorten after hot summers. Shrinking and shape-shifting patterns are consistent across ecologically diverse shorebirds from tropical and temperate Australia, are more pronounced in smaller species, and vary according to migration behaviour. These widespread morphological changes could be explained by multiple drivers, including adaptive and maladaptive responses to nutritional stress, or by thermal adaptation to climate warming.
The subalpine grassland ecosystem is sensitive to climatic changes. Previous studies investigated the effects of warming on grassland ecosystems at a single altitude, with little information about the response of subalpine meadows to warming along altitude gradients. This study aimed to evaluate the effects of warming on aboveground grass, belowground soil properties, and fungal community along altitude gradients in the subalpine meadow of Mount Wutai using the high-throughput sequencing method. Warming reduced the restriction of low temperatures on the growth of subalpine grass, resulting in increasing grass biomass, community height, and coverage. More grass biomass led to higher soil organic carbon resources, which primarily affected fungal community composition following warming. Warming might induce more stochastic processes of fungal community assembly, increasing fungal diversity at low altitudes. In contrast, warming triggered more deterministic processes to decrease fungal diversity at medium and high altitudes. Warming might improve the efficiency of soil nutrient cycling and organic matter turnover by increasing the relative abundance of soil saprotrophs and improving fungal network connectivity. The relative abundance of certain grass pathogens significantly increased following warming, thereby posing potential risks to the sustainability and stability of subalpine meadow ecosystems. Overall, this study comprehensively evaluated the response of the subalpine meadow ecosystems to warming along altitude gradients, clarifying that warming changes soil fungal community composition at different altitudes. The long-term monitoring of pathogen-related shifts should be conducted in subalpine meadow ecosystem following warming. This study provided significant scientific insights into the impact of future climatic changes on subalpine ecosystems.
The Mediterranean basin is the main area where the cultivation of the olive tree (Olea europaea L.), one of the oldest fruit trees, took place. Olea, found exclusively in the Mediterranean, stands as the representative of the Olea genus, which encompasses 35–40 species distributed across tropical and southern Africa, south Asia, eastern Australia, New Caledonia, and New Zealand. The proliferation of the olive tree (Olea europaea L.) in the Mediterranean region holds significance in terms of landscape, nutrition, culture, and history. The origin and the domestication of olive tree still remain a hot debatable issue while the cultivation is still expanding. Herein, a comprehensive chapter on the origin and domestication is being presented. Recent advances in molecular techniques like genetic fingerprinting for the discrimination of cultivars, evaluation of ecosystem services, biodiversity issues and ecophysiological parameters are also discussed. These aspects are critical factors in the policy and decision-making process of olive cultivation. The need for systematic monitoring of the olive cultivation is also emphasized. In the face of the ongoing climatic changes, separate sections pertaining to the physiological aspects controlling growth and resilience as well as the existing biodiversity of Olea are also included. Finally, the role of insects in shaping the history and evolution of olive tree, and matters related to sustainability of the crop are other interesting points covered in this chapter.
Ratoon rice can improve rice yield by increasing the multiple cropping index in China. However, the greenhouse gas (CH4 and N2O) emission characteristics from ratoon rice fields and the cultivation methods to reduce CH4 and N2O emissions are rarely reported. This study first conducted the analysis of genotype differences in greenhouse gas emission fluxes using five strong ratoon ability rice varieties in 2020. Second, water management methods, including alternating the wet–dry irrigation (AWD) pattern and conventional flooding irrigation (CF) during the main season, were carried out in 2021. CH4 and N2O emission flux, agronomic traits, and rice yield during both main and ratoon seasons were investigated. The results showed that the CH4 emission flux during the main and ratoon seasons was 157.05–470.73 kg·ha–1 and 31.03–84.38 kg·ha–1, respectively, and the total N2O emission flux was 0.13–0.94 kg·ha–1 in the ratoon rice system over the two seasons (RRSTS). Compared with the main season, the CH4 emission flux during the ratoon season was significantly reduced, thus decreasing the greenhouse gas global warming potential (GWP) and greenhouse gas emission intensity (GHGI) in the ratoon rice system. Cliangyouhuazhan (CLYHZ) showed a high yield, and the lowest GWP and GHGI values among the five rice varieties in RRSTS. Compared with CF, the AWD pattern reduced the CH4 emission flux during the main and ratoon seasons by 67.4–95.3 kg·ha–1 and 1.7–5.1 kg·ha–1, respectively, but increased the N2O emission flux by 0.1–0.6 kg·ha–1 during the RRSTS. Further, compared with CF, the AWD pattern had a declined GWP by 14.3–19.4% and GHGI by 30.3–34.3% during the RRSTS, which was attributed to the significant reduction in GWP and GHGI during the main season. The AWD pattern significantly increased rice yield by 21.9–22.9% during the RRSTS, especially for YX203. Correlation analysis showed that CH4, GWP, and GHGI exhibited significant negative correlations with spikelet number per m2 and the harvest index during the main and ratoon seasons. Collectively, selecting the high-yield, low-emission variety CLYHZ could significantly reduce greenhouse gas emissions from ratoon rice while maintaining a high yield. The AWD pattern could reduce total CH4 emission during the main season, reducing the GWP and GHGI while increasing the ratoon rice system yield. It could be concluded that a variety of CLYHZ and AWD patterns are worthy of promotion and application to decrease greenhouse gas emissions in the ratoon rice area in the upper reaches of Yangtze River, China.
Oxidation of methane by soil microorganisms is an important mechanism controlling the content of this potent greenhouse gas in the atmosphere. Agricultural soils operate under stressful conditions, and ammonium (N-fertilization) and drying (global warming) may have a significant impact on methane oxidation. In order to investigate how soil methanotrophs respond to drying–rewetting (DW), ammonium addition (100 mg/g) (A), and their combined action (MS), agricultural soil microcosms were incubated over the three months and methane oxidation was measured before and after perturbations, while community composition was monitoring using 16S rRNA gene sequencing. A significant decline in the methane-oxidation activity after perturbations was found, with subsequent restoration, and the combined treatment was more effective than the sum of individual treatments, indicating a synergistic effect. After rewetting, the structure of the bacterial community returned to pre-dry-down levels, but the application of ammonia and combined action lead to irreversible changes in the structure of soil methanotrophic communities. Methanotroph Methylomicrobium were significantly reduced under disturbances, while there was a significant increase in the representation of Methylobacter accompanied by the facultative methylotroph Methylovorus. We concluded that methanotrophic communities in agricultural soil demonstrated flexibility, and even when the abundance of dominant populations drops, ecosystem functions can recover.
menguak tabir hubungan
yang tak terpisahkan antara manusia, bahasa, dan lingkungannya. Sebuah
perspektif yang kian relevan di tengah krisis ekologi yang melanda dunia saat
ini. Melalui kolaborasi apik antara Lembaga Swadaya Penelitian dan
Pengembangan Pendidikan Matutu, Badan Riset dan Inovasi Nasional, dan
Universitas Balikpapan, buku ini mencoba menjembatani jurang pemisah antara
teori dan praktik, antara ilmu pengetahuan dan kearifan lokal.
Ekolinguistik, sebagai sebuah bidang ilmu yang relatif baru,
menawarkan sudut pandang segar dalam memahami bagaimana bahasa
berperan penting dalam membentuk persepsi, sikap, dan perilaku manusia
terhadap lingkungan. Lebih dari sekadar alat komunikasi, bahasa adalah
cerminan budaya, nilai-nilai, dan kearifan lokal yang diwariskan turun
temurun. Buku ini kami susun dengan harapan dapat menjadi jendela
pengetahuan bagi para pembaca untuk menyelami lebih dalam dunia
ekolinguistik. Melalui paparan yang komprehensif dan bahasa yang mudah
dipahami, kami mencoba mengurai konsep-konsep dasar ekolinguistik, serta
mengaplikasikannya dalam berbagai konteks, mulai dari isu kerusakan
lingkungan, perubahan iklim, hingga pelestarian keanekaragaman hayati.
In the context of an increasingly pressing environmental crisis, coastal areas in Indonesia face significant challenges related to sustainable natural resource management. Maritime education as a vital element in fostering environmental awareness must be revitalized to integrate green technology and cultivate ecological citizenship. This article aims to present systematic research findings on developing a framework for green maritime education that emphasizes ecological citizenship and sustainable practices in coastal areas. The literature review method is utilized to evaluate and analyze recent studies related to maritime education and the development of ecological citizenship. Findings indicate that a lack of knowledge about sustainability among students contributes to declining environmental quality, including increased pollution and ecosystem degradation. Furthermore, integrating environmentally sustainable practices, such as waste management and marine ecosystem conservation, into the maritime education curriculum can enhance students’ awareness and participation in sustainability initiatives. This research concludes that developing an innovative and inclusive framework for green maritime education is essential for cultivating ecological citizenship and building a more sustainable, environmentally conscious coastal community. The study's results provide a basis for formulating educational policies that respond effectively to environmental issues in coastal areas.
In the summer of 2022, an extreme compound drought and high temperature event (CDHE) occurred in the middle and lower of the Yangtze River Basin (YRB), causing serious impacts on the social economy. To understand the mechanism of this extreme compound event, we have analyzed the characteristics and abnormal circulation of this CDHE based on observation and reanalysis data, and combined with the land-atmosphere coupling index to explore the impact and possible mechanism of land surface feedback related to soil moisture on this compound event. Results show that in August 2022, the days of CDHE over the YRB reached 20 days, which was the highest since 1979. The westward extension of the West Pacific Subtropical High and eastward extension of the South Asian High led to an abnormal enhanced high over the YRB, which manifested strong convergence and descending motion locally, and the adiabatic warming of subsidence is the direct cause of temperature changes in near surface. At the same time, the intensified and northward-shifted westerly jet blocked the southward motion of northern cold air, which is not conducive to the convergence of water vapor over YRB, resulting in abnormally low precipitation in the YRB, and thus forming the extreme CDHE. During the same period, the local soil moisture was abnormally low, and the land-atmosphere coupling index was abnormally high, indicating that soil moisture significantly contributed to the surface sensible heat flux. The temperature anomaly was influenced by evaporation and sensible heating related to soil drought. The composite analysis indicated that dry soil over the YRB resulted in an increase in sensible heat flux, which was conducive to the development of anticyclonic circulation in the upper and middle troposphere. At the same time, local sinking motion is formed, causing a decrease in cloud cover and an increase in incident shortwave radiation. The land-atmosphere coupling and land surface feedback have an undeniable contribution to the increase of temperature and the decrease of precipitation in the middle and lower reaches of the YRB.
This study analyzes the forest flammability hazard in the south of Tyumen Oblast (West-ern Siberia, Russia) and identifies variation patterns in fire areas depending on weather and climate characteristics in 2008-2023. Using correlation analysis, we proved that the area of forest fires is primarily affected by maximum temperature, relative air humidity, and the amount of precipitation, as well as by global climate change associated with an increase in carbon dioxide in the atmosphere and the maximum height of snow cover. As a rule, a year before the period of severe forest fires in the south of Tyumen Oblast, the height of snow cover is insignificant, which leads to insufficient soil moisture in the following spring, less or no time for the vegetation to enter the vegetative phase, and the forest leaf floor remaining dry and easily flammable, which contributes to an increase in the fire area. According to the estimates of the CMIP6 project climate models under the SSP2-4.5 scenario , by the end of the 21st century, a gradual increase in the number of summer temperatures above 35 °C is expected, whereas the extreme SSP5-8.5 scenario forecasts the tripling in the number of such hot days. The forecast shows an increase of fire hazardous conditions in the south of Tyumen Oblast by the late 21st century, which should be taken into account in the territory's economic development .
Extended Abstract
Introduction
The average weather condition in a specific region is defined as climate. The diversity of climatic variables is effective in determining the climate of a region and causes the formation of diverse and different climates. One of the effects of climate change is that causes an increase or decrease in a climate zone and, as a result, a shift in climate zones. Climate classification is an attempt to identify and recognize the differences and similarities of climate in different regions and to discover the relationships between different components of the climate system. Climate classification indicators are used to visualize current climate and quantify future changes in climate types as predicted by climate models. The studies conducted on these methods show that climatic variables affecting experimental methods such as temperature and precipitation should be considered effective variables in determining climatic boundaries in a new way. The De Martonne aridity index is an empirical index for climate classification based on two components, precipitation and temperature. Due to its high accuracy, and the use of variables that are more accessible and can be measured at most meteorological stations, De Martonne’s index has received more attention from researchers and has been used in many studies of climate change. Therefore, the purpose of this research is to evaluate the effects of climate change on the climatic classification of Iran.
Materials and Methods
To investigate the effects of climate change on the climatic classification of Iran, the De Martonne aridity index has been used. To show the effects of climate change in the past and the future on Iran's climate, data from 120 meteorological stations of Iran, which are distributed in different locations with different climates, were collected and analyzed in the statistical period of 1933-2022. The climatic condition of Iran in the base period was determined according to the De Martonne aridity index. In addition, to investigate the effects of climate change in the coming periods on the climatic classification of Iran, the data related to the output of the CanESM2 model, which is one of the CMIP5 models that is hybridized by the Canadian Center for Climate Modeling and Analysis (CCCMA) by combining CanCM4 and CTEM models, were used. To examine the changes in climatic classes of Iran under different scenarios and conditions, the output of two release scenarios, RCP2.6 and RCP8.5, were utilized. Due to the large-scale output of General Circulation Models (GCM), the output of this model was downscaled using the LARS-WG model. The LARS-WG model, which is considered one of the most famous and widely used models for downscaling weather data, was used to generate precipitation values, minimum and maximum temperatures, as well as daily radiation, under base and future climate conditions.
Results and Discussion
According to the results, the majority of Iran (90.49%) has an arid and semi-arid climate. The percentage of arid climate is 68.82%, while that of semi-arid climate is 21.97%. Therefore, Iran should be called an arid and semi-arid country in terms of climate. By analysis of the effects of climate change indicates that in future periods, the precipitation and average temperature will increase. This increase will be greater under the RCP8.5 scenario than the RCP2.6 scenario. The study of the climatic classification of Iran in the coming periods indicates that the majority of the country will continue to experience arid and semi-arid climates. The sum of arid and semi-arid climates will reach its lowest level in the period of 2020-2041. This is following the RCP2.6 scenario, after which these climates are expected to expand once more. According to the RCP8.5 scenario, during the periods of 2021-2040, 2041-2060, and 2061-2080, the total area of arid and semi-arid climates will decrease. However, from 2081 to 2100, this trend will be reversed, increasing in these climates. ccording to the results of this research and according to the forecast, although according to different release scenarios, the difference in the area of different classes can be seen, in the future, arid and semi-arid climatic zones will still form the majority of Iran.
Conclusion
In this research, by using the latest available data, Iran's climate is classified by the De Martonne aridity index, and then the changes in Iran's climate classes under the effects of climate change in the future periods, according to the output of the CanESM2 model from the CMIP5 modes, which is downscaled using the LARS-WG model. It has been investigated according to two emission scenarios, RCP2.6 and RCP8.5. The results indicated that the arid climate with 68.82% and the semi-arid climate with 21.97% constitute the largest area of Iran. The remaining climatic classes collectively comprise less than 10% of Iran's area. Therefore, Iran should be called an arid and semi-arid country in terms of climate. Investigating the effects of climate change on precipitation and temperature showed that both precipitation and average temperature will increase in future periods. However, the increase in both variables will be greater under the RCP8.5 scenario. The study of the climatic classification of Iran in the coming periods indicates that the majority of the country will continue to experience arid and semi-arid climates. The findings of this study indicate the necessity of addressing the issue of climate change and the importance of involving experts and macro planners in the analysis of the effects of climate change. It is suggested to use the output of other GCM models in future research due to the uncertainty of climate scenarios. Also, the use of diverse climate classification methods that incorporate other variables is suggested for more precise identification of climate characteristics.
After stabilizing in the mid-2000s, atmospheric methane (CH4) levels have accelerated over the past decade. In response, satellite-based inversion techniques have been employed to meet the increasing demands of the climate community. In this study, the Integrated Methane Inversion (IMI) model, a novel approach based on the TROPOspheric Monitoring Instrument (TROPOMI), is used to quantify CH4 emissions across Denmark. Over 900,000 TROPOMI observations from spring to early autumn of 2018–2022 were used to inform the inversions. Overall, TROPOMI CH4 concentrations within the inversion domain showed an upward trend of approximately 12.71 ppb per year, reflecting the global trend. Excluding 2022, which included only four months of data, the inversions suggest an underestimation of emissions by 190(160–215) × 103 tonnes, or 66(56–75)% of prior estimates. Northern and southern Jutland, along with the Copenhagen metropolitan area, were identified as key sources of CH4 emissions. Additionally, the inversions indicated a decline in emissions during the COVID-19 pandemic, despite stable activity data. This study demonstrates the feasibility of using the IMI model to monitor CH4 emissions in small countries like Denmark, offering a satellite-based perspective to better identify and mitigate these emissions.
This article is devoted to the analysis of the simulated meteorological and hydrodynamic characteristics of the Sea of Azov using the WRF (Weather Research and Forecasting) model and INMOM (Institute of Numerical Mathematics Ocean Model). The goal is to investigate the sea’s response to atmospheric forcing using two different horizontal resolutions. A comparison of the atmospheric simulation results with available meteorological in situ data from the land-based hydrometeorological stations (HMSs) did not reveal any significant differences between the simulations with different atmospheric forcing resolutions. A spatiotemporal analysis of the WRF model and INMOM results showed the most prominent differences along the entire coastal zone, especially in Taganrog Bay, along the spits in the north part of the sea, and in the Kerch Strait. Here, the wind speed obtained at a high spatial resolution (3.3 km) was ~10–15% higher than that obtained at a coarse resolution (10 km), and the surface and bottom currents were up to ~40% and ~15% higher. In marine coastal zones, the greatest differences were noted in a band of ~5 km, and differences in the rest of the Sea of Azov were negligible. An analysis of the bottom current speed revealed the presence of a counter-current flowing into Taganrog Bay. This shows the necessity of using three-dimensional marine circulation models to study the Sea of Azov’s dynamics.
One percent of the overall value of international trade is made up of coffee, one of the most significant traded commodities. Around the world, 25 million farmers rely on coffee as their main crop. Coffee production and genetic resources are seriously threatened by rising temperatures and increased precipitation that would follow from climate change, despite the fact that coffee is important for the economies of many countries. The examination of the effects of climate change on coffee production and genetic resources, as well as the recommendation of potential measures for their mitigation and adaptation, are the goals of this research. High temperatures and unpredictable rainfall brought on by climate change directly lower coffee yield by impacting plant growth and development. Additionally, it indirectly lowers the yield and quality of coffee and fosters the occurrence of more coffee-related diseases and pests. Furthermore, it was predicted by global circulation models that the distribution of places with the right climate for Arabica coffee could be affected by changes in temperature and precipitation, making many of those regions unsuitable. Additionally, there is a high risk of extinction for wild coffee and coffee germplasm accessions of Arabica coffee, which have been preserved in Ethiopia and many other nations' ex-situ field gene banks. These factors will have a significant impact on the majority of top coffee producers in the future. As a result, countries that cultivate coffee should be aware of how changing climatic factors affect coffee output and genetic resources and implement the necessary mitigation and adaptation measures.
The environmental impacts of livestock agriculture include the production of greenhouse gasses (GHG) such as methane (CH4) through enteric fermentation. Recent advances in our understanding of methanogenesis have led to the development of animal feed additives (AFA) that can reduce enteric CH4 emissions. However, many interacting factors impact hydrogen (H2) and CH4 production and AFA efficacy, including animal factors, basal diet, particle and fluid outflow, microbial populations, rumen fluid pH, and fermentative cofactor dynamics. Characterizing the response of rumen fermentation to AFA is essential for optimizing AFA implementation. Mechanistic models of enteric fermentation are constructed to represent physiological and microbial processes in the rumen and can be updated to characterize the dependency of AFA efficacy on basal diet and the impacts of AFA on fermentation. The objective of this article is to review the current state of rumen mechanistic modeling, contrasting the representation of key pools in extant models with a particular emphasis on representation of CH4 production. Additionally, we discuss the first rumen mechanistic models to include AFA and emphasize future model needs for improved representation of rumen dynamics under CH4-inhibition due to AFA supplementation, including the representation of microbial populations, rumen pH, fractional outflow rates, and thermodynamic control of fermentative pathways.
Terrestrial ecosystem carbon stock (TECS) is critical to socioeconomic development and ecosystem services and is jointly affected by land use and cover and climate change. However, the dynamics of long-term annual TECS levels in urban agglomeration remain largely unknown, and research mostly ignores the spatial heterogeneity of climate factors, compromising sustainable environmental management and land planning strategies. To this end, we integrated field observations of carbon density, land use, and climate factors to map the annual distribution of TECS and analyzed their spatiotemporal variations and policy implications in the urban agglomeration of the middle Yangtze River Basin in China from 1990 to 2020. The results showed that 43,855.47 km2 of the land of the urban agglomeration changed from 1990 to 2020, accounting for 12.54% of the study area. The farmland and forest land area fluctuated and reduced, and the construction land area increased significantly. The increase in construction land was mainly from farmland and forest land. The TECS in urban agglomerations underwent a remarkable change, the overall trend fluctuated downward, and the maximum interannual variation was 1560 Tg. The transfer of construction land, farmland, forest land, shrubs, grassland, and other land mainly caused the change in carbon storage. Due to abnormal climate change, the urban agglomeration in some areas illustrated carbon storage with a spatially aggregated distribution. When considering the impact of climate change on carbon density, the TECS changes of land types other than forest land were found to be consistent with the area change but more significant due to climate change. The research results can provide reference data for regional land management policy formulation and realization of "dual carbon" goals.
Tropical peat swamp forests provide many important ecosystem services, especially their function as global carbon sinks. These carbon‐rich wetlands are widespread in South America, yet few studies have examined carbon stocks or losses due to land use change. In the lower Amazon, they are being converted to pastures largely utilized by domestic water buffalo (Bubalus bubalis). We quantified carbon stocks in intact peat forests and recently converted pastures (<10 years) at the Lago Piratuba Biosphere Reserve (LPBR) in the lower Amazon of Brazil. The soils of intact forests were typified by shallow organic (peat) horizons at the soil surface. The mean total ecosystem carbon stock (TECS) in intact forests was 354 ± 28 Mg C ha⁻¹. In contrast, the TECS of disturbed sites was significantly lower (p = 0.02) with a mean of 248 ± 17 Mg C ha⁻¹. We estimated greenhouse gas (GHG) emissions from water buffalo (due to enteric fermentation and manure deposition) to be 7.5 Mg CO2e ha⁻¹ year⁻¹. Considering GHG emissions from this land use, the social carbon costs (SCCs) arising from the degradation of coastal Amazon peatlands are as high as US100/kg of meat produced, which far exceeds the economic returns from livestock. Based on the estimated numbers of water buffalo for the southern portion of the LPBR and the time since initial disturbance, the annual GHG emissions from this land use are estimated to be 602,846 Mg CO2e year⁻¹ with an SCC as high as US$111,526,524 million year⁻¹. This land use also eliminates opportunity values and services of carbon storage and biodiversity that would be possible from a regenerating biosphere reserve.
Vegetables, being rich in vitamins, carbohydrates, minerals, proteins and antioxidants are essential for overcoming micronutrient deficiencies, offering higher incomes and more employment opportunities per hectare to smallholder farmers compared to staple crops. Major challenges faced by vegetable growers are increased terminal heat stress, rainfall variability leading to flooding, drought, irrigation water availability, salinity, incidence of pests and diseases, extreme weather events. These gets further worsened in the future due to climate change. Vegetables exhibit various physiological adaptations to cope with changing environmental conditions such as enhanced photosynthetic efficiency, improved water-use efficiency, and altered phenological development. Higher temperatures accelerate the life cycle of vegetables cause increased respiration, leading to earlier maturation and potentially lower yields. Increased frequency of heat waves can cause heat stress, affecting growth and development. Moreover elevated temperatures increase the incidence of pests and diseases, leading to higher crop losses. Changes in precipitation patterns alter water availability, impacting growth and productivity. Nevertheless drought conditions cause stomatal closure limiting water loss besides reducing CO2 uptake. Excessive rainfall can lead to waterlogging, disrupting root function and nutrient uptake. Variability in climate conditions lead to inconsistent yields, making it challenging for farmers and necessitating adaptive strategies to ensure crop resilience and productivity. Genetic improvement through breeding for heat and drought tolerance helps to develop resilient vegetables. Additionally, agronomic practices like mulching, organic farming, and resource conservation technologies help mitigate the adverse effects of climate change. Understanding these physiological responses could streamline sustainable vegetable production in the face of a changing climate.
The impact of aviation on climate change due to CO2 emissions is well established and is associated with much less uncertainty than the non CO2 effects. Among the non CO2 effects contrails formation and their evolution into cirrus-type clouds remain a subject of considerable uncertainty. A frequently overlooked source of uncertainty arises from the sensitivity of climate models to adjustable parameters used to represent the effect of subgrid-scale processes. The limited number of state-of-the-art climate models with an explicit contrail representation makes it challenging to evaluate model sensitivity of contrail radiative forcing to parameters and backgroud atmospheric conditions. To better characterize the contrail radiative forcing and its evolution it is therefore necessary to develop their representation within a large range of existing climate models. Here we develop and evaluate a new parameterization of contrail cirrus for the ARPEGE-Climat atmospheric model. The representation of the ice-supersaturated regions, where contrails persist, agrees well with in-situ and satellite observations, as well as the simulated contrail microphysical properties. With this parameterization, and using the ERA5 reanalysis to nudge the ARPEGE-Climat model, we estimate that for the air traffic of the year 2019 the global mean annual contrail coverage is 1.27%. In addition, the global mean annual instantaneous radiative forcing is estimated to be 66.2 mW/m2, although this result is sensitive to the choice of some key parameters of the contrail-cirrus parameterization. These findings are consistent with similar published results obtained using the same flight inventory but based on different methods of representing contrail effects.
Surface water monitoring plays a pivotal role in identify sources of pollution, guiding sustainable practices and preserving aquatic ecosystems. This works aims at research the effectiveness of surface water monitoring in identifying land use and land cover changes and environmental pressures, assessing the impacts of land use and occupation changes, identifying drivers of surface water indicators, and formulating responses to these challenges. The Mondego River Basin located in central Portugal, characterized by diverse geology, land use, and significantly impacted by the 2017 wildfires and the 2021/2022 drought, was selected as the study area. The research hypotheses were examined through extensive monitoring and analysis, leading to practical recommendations.
Systematic surface water monitoring revealed significant water quality indicators associated with environmental pressures. These included increases in water turbidity, and aluminum (Al) and iron (Fe) concentrations associated with land cover changes and increased soil erosion following the wildfires. There were also inputs of ions (e. g. NO3, SO4, Mn) associated with byproducts of combustion during the fires. Land use conversion from fire-affected areas to agricultural areas was also reflected in surface water indicators, such as increased concentrations of NO3 and arsenic (As). These indicators are particularly noticeable during periods of higher precipitation, which demonstrated the role of precipitation in the mobilization of contaminants following land use and cover changes.
Long-term monitoring has proven particularly supportive in identifying the impacts of land use changes on surface water quality. By constructing geochemical baselines using historical data from the same locations, it is possible to establish a comparison threshold for currently monitored data and assess the impacts on surface water.
Using data from surface water monitoring parameters as dependent variables, and precipitation data and geographical data of the catchments as independent variables, it was possible to identify that the extent of the impact from wildfires is more significant when the fires affect developed areas compared to forested areas, highlighting the resilience of ecosystems. Precipitation erosion and transport capacity are higher after land cover changes due to wildfires, even compared to the first flush following a prolonged hydrological drought.
The results of this study indicate that surface water monitoring allows for the attribution of responses to issues regarding the relationship between land use and occupation changes and surface water quality. The responses operations range from measures for soil preservation following wildfires, to maintenance of surface water quality by rehabilitation of the surrounding ecosystems, and recommendations for agricultural restoration following the wildfires. Additionally, community engagement and stakeholder involvement should also contribute to improve surface water quality in these contexts.
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