Future Scenarios Research Articles

Spatiotemporal Dynamics and Scenario Simulation of Regional Green Spaces in a Rapidly Urbanizing Type I Large City: A Case Study of Changzhou, China

The rapid urbanization observed in major Chinese cities has resulted in the degradation of both urban and rural environments. In response to this challenge, the concept of regional green spaces has emerged as an innovative approach to coordinate and manage green space resources across urban and rural areas. This study focuses on conducting a comprehensive analysis of the evolution, driving factors, and future scenarios of regional green spaces in Changzhou, which serves as a representative Type I large city in China. To accomplish this analysis, Landsat satellite images from 1992, 2002, 2012, and 2022 were utilized. Various methodologies, including landscape pattern indices for quantitative evaluation, the CLUE-S model, logistic regression for qualitative evaluation, and the Markov–FLUS model, were employed. The findings indicate a continuous decline in the area of regional green spaces in Changzhou, decreasing from 248.23 km2 in 1992 to 204.46 km2 in 2022. Landscape pattern analysis reveals an increase in fragmentation, complexity, irregularity, and human interference within these green spaces. Logistic regression analysis identifies key driving factors influencing regional green spaces, including elevation, urban population, and proximity to water bodies and transportation. The scenario simulations provide valuable insights into potential future trends of regional green spaces. According to the economic priority scenario, a modest increase in regional green spaces is anticipated, while the ecological priority scenario indicates substantial growth. Conversely, the inertial development scenario predicts a continued decline in regional green spaces. This research emphasizes the significance of achieving a harmonious coexistence between economic progress and environmental preservation. It emphasizes the necessity of optimizing the arrangement of green areas within a region while fostering public engagement in the conservation of these spaces. The findings contribute to the protection and sustainable development of the urban environment in the Yangtze River Delta region.

Water-energy-food-greenhouse gases nexus management in urban environments: A robust multi-agent decision-support system

Conceptual urban water metabolism (CUWM) models provide a holistic view of the efficiency of urban water systems. These models can be linked with multi-agent reinforcement learning (MARL) models to mimic stakeholders' reactions to various strategies. However, the outcomes derived from CUWM-MARL models come with uncertainty. As a result, this paper introduces a decision support system (DSS) that is aware of these uncertainties and uses this information to select robust management strategies based on the output of CUWM-MARL models. First, future scenarios are generated by exploring all combinations of critical values of deeply uncertain variables and values of uncertain variables sampled from an appropriate multivariate copula distribution. Then, a computationally efficient surrogate model is developed to alleviate the computational load of the MARL sub-model. The surrogate model is run through all future scenarios to calculate the system's key performance indicators (KPIs) for each management strategy. Urban water managers can use these KPIs and social choice methods to find consensus management strategies. The proposed methodology has been implemented in the western part of the Tehran metropolitan area, Iran. This study evaluates 26 management strategies consisting of various projects, including reducing water distribution network leakage, implementing urban demand control projects, and utilizing semi-centralized or decentralized wastewater treatment plants. The strategy chosen by the uncertainty-aware DSS enhances the total utility and fairness indices by 125% and 4%, respectively. Moreover, it effectively improves groundwater quality, reduces energy consumption and greenhouse gas emissions, and enhances water supply reliability, ultimately contributing to farmers' job security.

Assessing uncertainty in bioclimatic modelling: a comparison of two high-resolution climate datasets in northern Patagonia

Climate change is reshaping forest ecosystems, presenting urgent and complex challenges that demand attention. In this context, research that quantifies interactions between climate and forests is substantial. However, modelling at a spatial resolution relevant for ecological processes presents a significant challenge, especially given the diverse geographical contexts in which it is applied. In our study, we aimed to assess the effects of applying CHELSA v.2.1 and WorldClim v2.1 data on bioclimatic analysis within the Río Puelo catchment area in northern Patagonia. To achieve this, we inter-compared and evaluated present and future bioclimates, drawing on data from both climate datasets. Our findings underscore substantial consistency between both datasets for temperature variables, confirming the reliability of both for temperature analysis. However, a strong contrast emerges in precipitation predictions, with significant discrepancies highlighted by minimal overlap in bioclimatic classes, particularly in steep and elevated terrains. Thus, while CHELSA and WorldClim provide valuable temperature data for northern Patagonia, their use for precipitation analysis requires careful consideration of their limitations and potential inaccuracies. Nevertheless, our bioclimatic analyses of both datasets under different scenarios reveal a uniform decline in mountain climates currently occupied by N. pumilio, with projections suggesting a sharp decrease in their coverage under future climate scenarios.

Vulnerability, Resilience and Adaptation of Lagos Coastal Communities to Flooding

Lagos has been identified as one of the 50 cities most vulnerable to extreme sea levels. The state also ranked 30th among 136 port cities in terms of population exposure to flooding under a past climate scenario (2005) and 15th under a future climate scenario (2070s). The state faces significant environmental strains as a result of its geo-economic status. Some of the problems are wetland loss, pollution, population pressure, restricted access to drinkable water, and flooding. All these factors have contributed to the instability of Lagos ecosystems, but the impact of flooding is particularly significant because Lagos is surrounded by aquatic ecosystems and its low elevation and topography increase its susceptibility to flooding. The method adopted in this review involved the use of PICO (Population, Intervention, Control, and Outcomes) criteria to synthesize the research questions and objectives. Thereafter, PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines was employed for the study selection criteria, search strategies and data extraction methods. A broad search strategy involving databases (Google scholar, Science Direct), pertinent keywords and search filters was used to identify relevant articles and minimize selection bias. After the search, PICO criteria was again used to select the studies to be considered in the review. The selected text were downloaded and the essential scientific information were extracted and analyzed in the study. The impacts of flooding are numerous. Flooding is a key factors that has prevented Africa’s growing urban population from escaping poverty, and it also impedes the achievement of some SDGs. This is because many African cities lack the resources and infrastructures needed to withstand extreme weather conditions. Surviving in flood-prone cities like Lagos is a daunting task because flood affects livelihood, human health, and can even cause death. Specifically, the 2020 flood incidence in Nigeria affected about 40% of the local government areas, and 97% of the states, displacing over 120,000 persons and killing 68 persons aside from properties and farmlands destroyed. Women and children are the most vulnerable. The adoption of advanced flood risk management strategies could help in flood containment and management in the state.

Modelling Multi-Scenario Ecological Network Patterns and Dynamic Spatial Conservation Priorities in Mining Areas

Mining activities have significantly altered the land use patterns of mining areas, exacerbated the degree of landscape fragmentation, and thereby led to the loss of biodiversity. Ecological networks have been recognized as an essential component for enhancing habitat connectivity and protecting biodiversity. However, existing studies lack dynamic analysis at the landscape scale under multiple future scenarios for mining areas, which is adverse to the identification of ecological conservation regions. This study used the MOP-PLUS (multi-objective optimization problem and patch-level land use simulation) model to simulate the land use patterns in the balance of ecology and economy (EEB) scenario and ecological development priority (EDP) scenario for the Shendong coal base. Then, climate change and land use patterns were integrated into ecosystem models to analyze the dynamic changes in the ecological networks. Finally, the conservation priorities were constructed, and dynamic conservation hotspots were identified using landscape mapping methods. The following results were obtained: (1) From 2000 to 2020, large grassland areas were replaced by mining areas, while cultivated land was replenished. By 2030, the forest and grassland areas (967.00 km2, 8989.70 km2) will reach their peaks and the coal mine area (356.15 km2) will reach its nadir in the EDP scenario. (2) The fragmentation of ecological sources intensified (MPS decreased from 19.81 km2 to 18.68 km2) and ecological connectivity declined (in particular, α decreased by 6.58%) from 2000 to 2020. In 2030, the connectivity in the EDP scenario will increase, while the connectivity in the EEB scenario will be close to that of 2020. (3) The central and southeastern parts of the Shendong coal base have higher conservation priorities, which urgently need to be strengthened. This study offers guidance on addressing the challenges of habitat and biodiversity conservation in mining areas.

Land-Use Feedback under Global Warming—A Transition from Radiative to Hydrological Feedback Regime

Abstract This study examines the effects of land-use (LU) change on regional climate, comparing historical and future scenarios using seven climate models from phase 6 of Coupled Model Intercomparison Project–Land Use Model Intercomparison Project experiments. LU changes are evaluated relative to land-use conditions during the preindustrial climate. Using the Community Earth System Model, version 2–Large Ensemble (CESM2-LE) experiment, we distinguish LU impacts from natural climate variability. We assess LU impact locally by comparing the impacts of climate change in neighboring areas with and without LU changes. Further, we conduct CESM2 experiments with and without LU changes to investigate LU-related climate processes. A multimodel analysis reveals a shift in LU-induced climate impacts, from cooling in the past to warming in the future climate across midlatitude regions. For instance, in North America, LU’s effect on air temperature changes from −0.24° ± 0.18°C historically to 0.62° ± 0.27°C in the future during the boreal summer. The CESM2-LE shows a decrease in LU-driven cooling from −0.92° ± 0.09°C in the past to −0.09° ± 0.09°C in future boreal summers in North America. A hydroclimatic perspective linking LU and climate feedback indicates LU changes causing soil moisture drying in the midlatitude regions. This contrasts with hydrology-only views showing wetter soil conditions due to LU changes. Furthermore, global warming causes widespread drying of soil moisture across various regions. Midlatitude regions shift from a historically wet regime to a water-limited transitional regime in the future climate. This results in reduced evapotranspiration, weakening LU-driven cooling in future climate projections. A strong linear relationship exists between soil moisture and evaporative fraction in midlatitudes. Significance Statement Land–atmosphere feedback involving soil moisture can increase local temperature and affect how land-use (LU) change impacts manifest in a warming climate. Conversely, an increased surface reflectance due to LU change can decrease local temperature in the midlatitude regions. Further, the LU change signal is often mixed with the internal climate variability, making it harder to separate. This study uses a novel technique to separate LU change impact from other climate forcing in the latest generation of climate and Earth system models. In the future climate, soil moisture drying lessens the cooling impact. A large-ensemble climate experiment analysis confirms a significant weakening of the LU-driven cooling impact in the midlatitudes. Both LU and climate changes exacerbate soil moisture drying, leading to a shift toward a water-limited system where hydrological feedback becomes more influential than radiative feedback.

A cradle-to-grave assessment of carbon and energy footprints of ships using synthetic fuel for net-zeros operations

PurposeAchieving net-zero emissions in the maritime sector requires adopting carbon-neutral practices in terms of shipbuilding, operation and recycling. However, research integrating life cycle and energy analysis is missing to inform decision-makers. MethodConsequently, the paper presents models combining a model-based life cycle assessment (MBLCA) and ship energy simulations to examine the footprints of a generic New Panamax Containership (DTC). Analyses were conducted to assess the energy and carbon effects of using synthetic methanol as marine fuel. ResultsThe life-cycle analysis confirms the overwhelming prevalence of operations in the total greenhouse gases emission during the ship's lifetime. The analysis highlights the potential of carbon savings if the vessel consumes methanol produced from neutral energy and renewable carbon sources. However, the magnitude of shipping fuel requirements may profoundly impact energy infrastructures while still requiring large volumes of carbon offset credits. ConclusionThe paper confirms the usefulness of integrating life-cycle analysis and energy modelling to discuss future energy scenarios. The completeness of the models also allows for future research analysing other energy solutions.

Associating reservoir operations with 2D inundation risk and climate uncertainty

ABSTRACT Bridging the research gap between reservoir operations and inundation risks under the future climate, this study integrates a hydrologic reservoir management model with a 2D hydrodynamic model, comparing the conventional regulations and the optimized reservoir operations based on the particle swarm optimization (PSO) algorithm. Results reveal that optimized operations using the PSO algorithm consistently outperform conventional strategies by better-managing peak discharges and controlling downstream inundation. The study further differentiates between PSO-optimized plans: PSO1, which focuses on minimizing inundation areas, and PSO2, which prioritizes peak reduction at the flood control point. Interestingly, PSO2 proves superior for single-point peak reduction, typically the primary objective in current practices, whereas PSO1, despite lesser peak reduction, achieves a smaller inundation area, enhancing basin-scale flood resilience. This discrepancy reveals the need to consider downstream inundation risks as critical evaluation metrics in reservoir optimization, a factor often overlooked in existing studies. The research underscores the importance of updating operational frameworks to incorporate 2D inundation risks and adapt to increased flood risks under changing climate conditions. Despite optimization, future climate scenarios predict increased flood exposure, indicating that the current safety discharge rates and flow regulations at control points are outdated and require revision.

Forecasting ecological water demand of an arid oasis under a drying climate scenario based on deep learning methods

Ecological water diversion projects (EWDP) are an effective management tool for restoring oasis ecosystems in arid regions. Given the potential for drier climatic conditions in arid regions in the future, it is essential to develop water diversion strategies that can adapt to climate change and reduce the risk of oasis ecosystem degradation. Here, this study used a Bayesian optimization-based long- and short-term memory (BO-LSTM) model to determine the optimal amount of water diversion needed to maintain healthy growth of oasis vegetation under future climate change scenarios in the Qingtu Oasis, which is a typical downstream oasis of inland rivers restored by EWDP in China. The results showed that the BO-LSTM model effectively captured the response of oasis vegetation to changes in water inundation areas and drought stress with low computational cost and high accuracy. The study revealed that regional vegetation became more vulnerable than previously thought when extreme drought and a drying trend were taken into account. It was found that if the amount of water entering the oasis ranges from 10 to 15 million m3, there will be a decline in the growth of oasis vegetation as indicated by the normalized difference vegetation index (NDVI). Even if current levels of water diversion (20 million m3) are maintained, oasis vegetation may still face growth decline due to meteorological drought. The optimal amount of water diversion was determined to be 25 million m3, resulting in a 21.7% increase in NDVI regardless of drought events. This study represents an innovative approach as it couples EWDP, climate change, and oasis vegetation dynamics based on deep learning models, which unveils divergent responses of oasis vegetation to climate change and EWDP and verifies a non-linear relationship between water diversion amounts and ecological benefits generated.

RESILIENCE AND LESSONS LEARNED IN COLOMBIAN FAMILY FARMING DURING THE COVID-19 PANDEMIC

<p><strong>Background: </strong>A health crisis exposes people to food vulnerability by restricting the mobilization and commercial exchange of food. During the COVID-19 pandemic, an ample food supply was available to ensure the basic consumption of the population, prompting two questions: What resilient practices did farmers adopt to produce under conditions of high sanitary restriction, and what lessons did they derive to confront future crises? <strong>Objective:</strong> The article presents and collects the experiences of 59 small family farmers in Colombia in implementing good practices for economic and financial resilience and the lessons learned from the Covid-19 pandemic, constituting a new source of knowledge to understand human behaviors and actions in the face of adversity and the experiential learnings gained to act in future crisis scenarios. <strong>Methodology</strong>: To characterize the resilient practices of agricultural producers in the department of Norte de Santander, Colombia, amid the COVID-19 pandemic crisis, researchers conducted interviews with 59 smallholder farmers from 12 municipalities. The study encompassed 11 agricultural products and 6 animal products, ultimately identifying three overarching categories: economic resilience, financial resilience, and lessons learned.<strong> Main Results: </strong>The results indicate strategies for diversification of production, use of local resources, solidarity-based family work, short marketing chains and an economy of scarcity in family spending. <strong>Implications: </strong>These lessons can inform future policies and practices to better prepare for and respond to similar challenges. <strong>Conclusion: </strong>The study's findings provide valuable insights for policymakers and small farmers, emphasizing the importance of local resource utilization, community cooperation, and adaptive strategies to enhance resilience and sustain livelihoods during crises. </p>

Fish and tips: Historical and projected changes in commercial fish species' habitat suitability in the Southern Hemisphere

Global warming has significantly altered fish distribution patterns in the ocean, shifting towards higher latitudes and deeper waters. This is particularly relevant in high-latitude marine ecosystems, where climate-driven environmental changes are occurring at higher rates than the global average. Species Distribution Models (SDMs) are increasingly being used for predicting distributional shifts in habitat suitability for marine species as a response to climate change. Here, we used SDMs to project habitat suitability changes for a range of high-latitude, pelagic and benthopelagic commercial fish species and crustaceans (10 species); from 1850 to two future climate change scenarios (SSP1–2.6: low climate forcing; and SSP5–8.5: high climate forcing). The study includes 11 Large Marine Ecosystems (LME) spanning South America, Southern Africa, Australia, and New Zealand. We identified declining and southward-shifting patterns in suitable habitat areas for most species, particularly under the SSP5–8.5 scenario and for some species such as Argentine hake (Merluccius hubbsi) in South America, or snoek (Thyrsites atun) off Southern Africa. Geographical constraints will likely result in species from Southern Africa, Australia, and New Zealand facing the most pronounced habitat losses due to rising sea surface temperatures (SST). In contrast, South American species might encounter greater opportunities for migrating southward. Additionally, the SSP5–8.5 scenario predicts that South America will be more environmentally stable compared to other regions. Overall, our findings suggest that the Patagonian shelf could serve as a climate refuge, due to higher environmental stability highlighting the importance of proactive management strategies in this area for species conservation. This study significantly contributes to fisheries and conservation management, providing valuable insights for future protection efforts in the Southern Hemisphere.

Quantifying weather-induced unreliable public transportation service in cold regions under future climate model scenarios

Climate change, particularly in cold regions, significantly challenges public transportation systems. This study conducts a comprehensive analysis of weather patterns and public transit reliability in the context of climate change impacts. Leveraging advanced modeling techniques, including a ridge regression model for snow water equivalent data estimation and a long short-term memory (LSTM) based on recurrent neural network, the study aims to assess the reliability trends of the rapid transit system under various climate scenarios. The findings reveal that climate change in general increases weather-related delays in the Toronto transit system. The number of short delays decreased accordingly due to changes in winter temperatures but exacerbated long delays as the number of weather extremes increased. The LSTM model performed effectively in predicting delays, especially for the rapid transit system sensitive to weather variations. This study emphasizes the need for robust planning and interventions to increase the resilience of transit systems against climate change and highlights the importance of the integration of climate and extreme weather considerations into transportation management.

Who needs a tourniquet? And who does not? Lessons learned from a review of tourniquet use in the Russo-Ukrainian war.

Extremity tourniquets have proven to be lifesaving in both civilian and military settings and should continue to be used by first responders for trauma patients with life-threatening extremity bleeding. This is especially true in combat scenarios in which both the casualty and the first responder may be confronted by the imminent threat of death from hostile fire as the extremity hemorrhage is being treated. Not every extremity wound, however, needs a tourniquet. One of the most important aspects of controlling life-threatening extremity bleeding with tourniquets is to recognize what magnitude of bleeding requires this intervention and what magnitude of bleeding does not. Multiple studies, both military and civilian, have shown that tourniquets are often applied when they are not medically indicated. Overuse of extremity tourniquets has not caused excess morbidity in either the recent conflicts in Iraq and Afghanistan or in the US urban civilian setting. In the presence of prolonged evacuation, however, applying a tourniquet when it is not medically indicated changes tourniquet application from being a lifesaving intervention to one that may cause an avoidable amputation and the development of an array of metabolic derangements and acute kidney injury collectively called prolonged tourniquet application syndrome. The recent literature was reviewed for papers that documented the complications of tourniquet use resulting from the prolonged casualty evacuation times being seen in the current Russo-Ukrainian war. The literature was also reviewed for the incidence of tourniquet application that was found to not be medically indicated, in both the US civilian setting and from Ukraine. Finally, an in-person meeting of the US/Ukraine Tourniquet Working Group was held in Warsaw, Poland, in December of 2023. Unnecessary loss of extremities and life-threatening episodes of prolonged tourniquet application syndrome are currently occurring in Ukrainian combat forces because of nonindicated tourniquet use combined with the prolonged evacuation time seen in the Russo-Ukrainian war. Specific numbers of the complications experienced as a result of tourniquet use by Ukrainian forces in the current conflict are treated as classified information and are not available, but multiple sources from the Ukrainian military medical personnel and from the US advisors providing medical assistance to Ukraine have all agreed that the problem is substantial. Unnecessary tourniquet morbidity might also occur in US forces in a variety of potential future combat scenarios in which evacuation to surgical care is delayed. Prehospital trauma training programs, including but not limited to tactical combat casualty care, place insufficient emphasis on the need to avoid leaving tourniquets in place when they are not medically indicated. This aspect of training should receive emphasis in future Tactical Combat Casualty Care (TCCC) and civilian first responder curriculum development. An interim ad hoc training solution on this topic is available at the websites noted in this articles. Additional training modalities may follow in the near future. Therapeutic/Care Management; Level V.

High thermodynamical sensitivity of CO2 emissions from a large oligotrophic-hardwater lake (Nam Co) on the Tibetan Plateau

The Tibetan Plateau (TP) has the world's largest distribution of high-alpine and saline (generally hardwater) lakes, which are expected to affect regional carbon cycling profoundly. However, the variability, and especially underlying factors controlling CO2 dynamics, across widespread hardwater lakes is poorly understood on the TP. Here, we present year-round records of surface water pCO2 from a representative hardwater lake (Nam Co) on the TP, and analyze relationships between ambient variables and pCO2 during open water (i.e., ice-free) and ice-covered months. Surface pCO2 (233.3 μatm on average) was a little oversaturated to atmosphere (219 μatm on average) during the open water season. As a CO2 source, Nam Co emitted 8.73 ± 1.06 Gg C annually, but this flux only accounted for 0.53 ± 0.06 ‰ of its total dissolved inorganic carbon pool (1.64 × 1013 g C). Regression results indicate that, during open water months, both seasonal and diurnal varying patterns of surface pCO2 were influenced predominantly by water temperature, in a quasi-marine mode, by controlling gas solubility and dissolved carbonate equilibria. Therefore, CO2 evasion was elevated during summer months, despite the lake being autotrophic (i.e., CO2 consumption via photosynthesis). By contrast, during ice-covered months the surface pCO2 was strongly related to under-ice thermodynamics, and declined nonlinear with increased inversed stratification. In the hypolimnion, as a result of extremely weak metabolism (as indicated by low dissolved oxygen depletion rates) and a combined high carbonate buffering effect, accumulation of CO2 was negligible, leading to an absence of peak effluxes of CO2 during turnover periods, compared to eutrophic freshwater lakes. We argue that, under future global warming scenarios, consideration of the impact of gradually warming lake water on thermodynamics and dissolved carbonate equilibria are vital in order to understand the future CO2 dynamics of these widespread high-altitude oligotrophic-hardwater lakes situated across the TP.

Strategies for Increasing the Throughput of Genetic Screening: Lessons Learned from the COVID-19 Pandemic within a University Community.

Amidst the COVID-19 pandemic, the Polytechnic University of Setúbal (IPS) used its expertise in molecular genetics to establish a COVID-19 laboratory, addressing the demand for community-wide testing. Following standard protocols, the IPS COVID Lab received national accreditation in October 2020 and was registered in February 2021. With the emergence of new SARS-CoV-2 variants and safety concerns for students and staff, the lab was further challenged to develop rapid and sensitive diagnostic technologies. Methodologies such as sample-pooling extraction and multiplex protocols were developed to enhance testing efficiency without compromising accuracy. Through Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) analysis, the effectiveness of sample pooling was validated, proving to be a clear success in COVID-19 screening. Regarding multiplex analysis, the IPS COVID Lab developed an in-house protocol, achieving a sensitivity comparable to that of standard methods while reducing operational time and reagent consumption. This approach, requiring only two wells of a PCR plate (instead of three for samples), presents a more efficient alternative for future testing scenarios, increasing its throughput and testing capacity while upholding accuracy standards. The lessons learned during the SARS-CoV-2 pandemic provide added value for future pandemic situations.

To explore the effectiveness of various ecological security pattern construction methods in many growth situations in the future: A case study of the West Liaohe River Basin in Inner Mongolia

The Ecological Security Pattern (ESP) has emerged as a prominent area of focus in global ecosystem research, offering valuable scientific insights for reconciling ecological preservation with economic progress. Understanding the differences among different approaches to constructing ESP serves as a fundamental step in ensuring its efficacy. However, there has been a scarcity of studies that quantitatively assess the disparities in the effectiveness of various ESP construction methods. This study focuses on the West Liaohe River Basin as its research subject. Leveraging remote sensing data alongside county-level statistical information, the study employs three distinct ecological source identification methodologies to establish ESP frameworks. Subsequently, it analyzes the discrepancies in ecological protection outcomes across different ESP construction methods under varying future development scenarios. The findings reveal that the ESP centered around ecosystem services emerges as particularly suited for diverse development scenarios, consistently yielding optimal ecological protection outcomes. Our research not only furnishes a theoretical foundation and practical guidance for ESP development in the West Liaohe River Basin but also offers methodological insights transferrable to other regions.

Estimate of Temperature Rise in the 21st Century for Various Scenarios

The International Panel on Climate Change (IPCC) published a lengthy report on climate change in early 2023. This report hypothesizes five potential scenarios of greenhouse gas emissions from 2015 to the end of the century (2100) and estimates the global average temperature gain in the year 2100 from the mid-1800s for each scenario. The method of calculation in the IPCC report is obscure. The results are merely stated. The present paper provides a clear method for estimating the temperature gain each year from 2015 until 2100, along with yearly estimates of ppm of CO2. To facilitate the calculations, a set of scenarios of future emissions was chosen that is analogous to the scenarios used by the IPCC but is more amenable to computation. The basic assumption in this paper is that most of the temperature gain from the mid-1800s to 2015 (1.15 C – as reported by the IPCC) was due to rising CO2 concentration in the atmosphere and a relationship is thereby derived between warming and gigatons of CO2 emitted for the period: 1800s to 2015. If it is assumed that the amount of warming per gigaton CO2 from the past persists into the 21st century, then future warming in the 21st century can be estimated for any assumed future scenario of CO2 emissions. This paper provides a simple and clear estimate of yearly CO2 ppm and temperature rise from 2015 to 2100 since the 1800s for a set of scenarios that cover the likely range of future emissions.

Multi-scale assessment of rainwater harvesting availability across the continental U.S.

Addressing resilience, sustainability, and water resource conservation has become increasingly important in the modern world. Challenges arise due to periodic droughts, climate change, and seasonal variability in areas with limited freshwater availability. Therefore, implementing and promoting water reuse is essential. Rainwater harvesting (RWH) is one such alternative, offering benefits in conserving water resources and mitigating droughts while reducing urban flooding and costs by generating alternative lower-cost water sources. Providing users with knowledge of available volumes for harvesting, including homeowners and governmental entities, is key to encouraging this practice. Hydrological data and geographic information systems are fundamental for managing, designing, and projecting rainwater harvesting practices. However, no tools currently integrate this information at multiple scales with current and future climate scenarios. This research aimed to develop a multi-scale assessment tool named H2O HARVEST, for evaluating the availability and potential of rainwater harvesting. Additional benefits of the H2O HARVEST app include aiding decision-making by national governmental entities and analyzing potential future scenarios for homeowner users. The app also provides regulatory policy information at the state level. We offer an app with the necessary capabilities to bridge the technology gap and promote rainwater harvesting practices. Our research demonstrated that RWH has the potential to be a sustainable water reuse practice. For more than 50% of the states, the RWH could supply at least 50% of the water demand. The regions of the US with the greatest potential are the Central and East.

Long-term changes in tropospheric temperature in India: Insights from radiosonde measurements, reanalysis data and CMIP6 model projections

The continuous rise in greenhouse gases (GHGs) in the atmosphere is one of the major factors responsible for the global warming and enhanced tropospheric temperature. In this context, we examine the long-term spatiotemporal changes in the tropospheric temperature (1000–100 hPa) in India using radiosonde measurements and the reanalysis data from European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), Modern-Era Retrospective analysis for Research and Application Version 2 (MERRA2) and National Center for Environmental Prediction (NCEP) for the period 1980–2020. We also investigate the future projections of tropospheric temperature in the Shared Socio-economic Pathways (SSPs) 2–4.5 and 5–8.5 by using the Coupled Model Intercomparison Project 6 (CMIP6) results for the period 2015–2100 over India. Our analysis shows a significant positive trend (0.01–0.04 °C/yr) in the annual mean temperature in the upper troposphere (500–100 hPa) in India during the period 1980–2020. The warming trends are also noticeable in the middle and lower troposphere of India. Among the regions, the northeast, north central and northwest India exhibit significant warming of about 0.01–0.06 °C/yr in the upper troposphere (500–100 hPa). On the other hand, most regions show a decline in temperature at the tropopause (100 hPa), which is stronger in the interior peninsular, north central and east coast of India, at about −0.05 ± 0.01°C/yr. All reanalysis data show consistent warming and cooling trends in the respective regions as observed from the radiosondes, albeit slight differences in their values. The future high emission scenario of SSP5–8.5 shows a warming trend of about 0.04–0.08 °C/yr at 1000–200 hPa by the end of the century, which is highest at 250 hPa. The increasing trend in tropospheric temperature is a serious concern, which calls for adaptation and mitigation measures to alleviate the impacts of this accelerated warming in India.

Climate change and urban sprawl: Unveiling the escalating flood risks in river deltas with a deep dive into the GBM river delta

River deltas, such as the Ganges-Brahmaputra-Meghna (GBM) delta, are highly vulnerable to flooding, exacerbated by intense human activities and rapid urban growth. This study explores the evolution of urban flood risks in the GBM delta under the combined impacts of climate change and urban expansion. Unlike traditional assessments that focus on a single flood source, we consider multiple sources—coastal, fluvial, and pluvial. Our findings indicate that future urban expansion will significantly increase flood exposure, with a substantial rise in flood risk from all sources by the end of this century. Climate change is the main driver of increased coastal flood risks, while urban growth primarily amplifies fluvial, and pluvial flood risks. This highlights the urgent need for adaptive urban planning strategies to mitigate future flooding and support sustainable urban development. The extreme high emissions future scenario (SSP5–8.5) shows the largest urban growth and consequent flood risk, emphasizing the necessity for preemptive measures to mitigate future urban flooding. Our study provides crucial insights into flood risk dynamics in delta environments, aiding policymakers and planners in developing resilience strategies against escalating flood threats.