Local Climate Change Research Articles

Assessment of Heat Exposure and Health Outcomes in Rural Populations of Western Kenya by Using Wearable Devices: Observational Case Study.

Climate change increasingly impacts health, particularly of rural populations in sub-Saharan Africa due to their limited resources for adaptation. Understanding these impacts remains a challenge, as continuous monitoring of vital signs in such populations is limited. Wearable devices (wearables) present a viable approach to studying these impacts on human health in real time. The aim of this study was to assess the feasibility and effectiveness of consumer-grade wearables in measuring the health impacts of weather exposure on physiological responses (including activity, heart rate, body shell temperature, and sleep) of rural populations in western Kenya and to identify the health impacts associated with the weather exposures. We conducted an observational case study in western Kenya by utilizing wearables over a 3-week period to continuously monitor various health metrics such as step count, sleep patterns, heart rate, and body shell temperature. Additionally, a local weather station provided detailed data on environmental conditions such as rainfall and heat, with measurements taken every 15 minutes. Our cohort comprised 83 participants (42 women and 41 men), with an average age of 33 years. We observed a positive correlation between step count and maximum wet bulb globe temperature (estimate 0.06, SE 0.02; P=.008). Although there was a negative correlation between minimum nighttime temperatures and heat index with sleep duration, these were not statistically significant. No significant correlations were found in other applied models. A cautionary heat index level was recorded on 194 (95.1%) of 204 days. Heavy rainfall (>20 mm/day) occurred on 16 (7.8%) out of 204 days. Despite 10 (21%) out of 47 devices failing, data completeness was high for sleep and step count (mean 82.6%, SD 21.3% and mean 86.1%, SD 18.9%, respectively), but low for heart rate (mean 7%, SD 14%), with adult women showing significantly higher data completeness for heart rate than men (2-sided t test: P=.003; Mann-Whitney U test: P=.001). Body shell temperature data achieved 36.2% (SD 24.5%) completeness. Our study provides a nuanced understanding of the health impacts of weather exposures in rural Kenya. Our study's application of wearables reveals a significant correlation between physical activity levels and high temperature stress, contrasting with other studies suggesting decreased activity in hotter conditions. This discrepancy invites further investigation into the unique socioenvironmental dynamics at play, particularly in sub-Saharan African contexts. Moreover, the nonsignificant trends observed in sleep disruption due to heat expose the need for localized climate change mitigation strategies, considering the vital role of sleep in health. These findings emphasize the need for context-specific research to inform policy and practice in regions susceptible to the adverse health effects of climate change.

Statistical-based spatial analysis on urban water management under changing environments: a case study of Hawassa, Ethiopia

Hawassa characterizes a typical developing city in Ethiopia, owning to rapid urban growth and demographic trends. The combined effect of climate change and urban expansion is increasing the challenge to the environment and the services it provides. Relating changing environments with urban water management (UWM) is required to build resilience in the urban environment. This research analyzed local climate change and urban growth and linked it to UWM. The historical period 1990–2021 of daily rainfall, temperature variables, four satellite imageries, and DEM were analyzed. Changes in rainfall (annual and daily maximum) and temperature (maximum and minimum) trends are detected and projected to 2051 using a statistical-based model. With geospatial techniques sub-watersheds are delineated, and the urban cover change is quantified. The trend detection result implies an upward trend of annual and daily maximum rainfalls however a significance is insufficient (p > 0.05) to associate it with climate change during the study period. Maximum and minimum temperatures change indicate a positive and significant trend. The forecasting result suggests an increment of both temperatures (0.5 °C–1.5 °C) to the projected period compared to historical scenario. The land cover analysis results show the built-up area changed from 11.6 km2 (7.2%) to 42.5 km2 (26.5%) during the historical period, where the rate varies spatially. The surface runoff increased by 30.7% in the urban watersheds. With a growth rate of 8.9% built-up, the urban area will cover 73.6 km2 (45.9%) for the predicted period. The research finding justifies the potential to reorganize the relationship between the spatial effect of climate change and urban growth on UWM. Considering distinct characteristics of urban watershed, exposure to flooding risk, access to water demand and resilient to climate change have spatial variation. Thus, a local-specific planning approach will support effective UWM and climate adaptation for sustainable city development.

Analysis of Local Climate Change Impacts on the Rainfall Patterns and Dry Spells in Banda Aceh and Aceh Besar, Indonesia

Analysis of Local Climate Change Impacts on the Rainfall Patterns and Dry Spells in Banda Aceh and Aceh Besar, Indonesia

Local climate change velocities and evolutionary history explain multidirectional range shifts in a North American butterfly assemblage.

Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonise new suitable climatic niches. However, from 18-years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards regions that are warming the fastest (southeast). Butterflies shifted their centroids at a mean rate of 4.87 km year-1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges. Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity. Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability) were not correlated with the rate at which species shifted their ranges. We observed high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges. This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range.

Assessing climate change impacts on irrigation water requirements in the Lower Mahanadi Basin: A CMIP6-based spatiotemporal analysis and future projections

ABSTRACT Climate change heightens India's agricultural risks, particularly in nations like India heavily reliant on farming. Previous studies focused on Coupled Model Intercomparison Project Phase (CMIP3) and (CMIP5) scenarios for large river basins, but the heightened risk of local climate changes poses a significant threat to smaller basins, notably affecting crops. This study investigates the spatiotemporal dynamics of climate change impacts on paddy crop irrigation in India's Lower Mahanadi Basin, utilizing the latest general circulation models (GCMs) from the CMIP6, focuses on two emission scenarios, SSP585 and SSP370. Thirteen models were analysed, top six were selected based on statistical criteria like PBIAS, NSE, R2, RSR, and RMSE. Models project climate changes for near- (2025–2050), mid- (2051–2075), and far-future (2076–2100) periods against a baseline (1981–2014), investigating spatiotemporal variations in rainfall, temperature, and irrigation water requirements (IWRs) in the region. In both scenarios, future mean seasonal rainfall is expected to increase compared with the baseline. SSP370 projects a 23.7% rise in minimum rainfall, while maximum rainfall varies by 11.5%. SSP585, on the other hand, projects a 9.53% decrease in maximum IWR and a 28.9% increase in maximum rainfall compared with the baseline. Both scenarios anticipate a 3–4 °C temperature increase in the far-future.

Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction

As our planet is entering into the “global boiling” era, understanding regional climate change becomes imperative. Effective downscaling methods that provide localized insights are crucial for this target. Traditional approaches, including computationally-demanding regional dynamical models or statistical downscaling frameworks, are often susceptible to the influence of downscaling uncertainty. Here, we address these limitations by introducing a diffusion probabilistic downscaling model (DPDM) into the meteorological field. This model can efficiently transform data from 1° to 0.1° resolution. Compared with deterministic downscaling schemes, it not only has more accurate local details, but also can generate a large number of ensemble members based on probability distribution sampling to evaluate the uncertainty of downscaling. Additionally, we apply the model to generate a 180-year dataset of monthly surface variables in East Asia, offering a more detailed perspective for understanding local scale climate change over the past centuries.

Spatiotemporal Pattern and Influencing Factors of Thermal Environment Based on SEM Model: A Case Study in Xi'an Metropolitan Area

The urban thermal environment is an important indicator for evaluating the ecological environment of a city. It directly affects the health of residents and the sustainable development of the urban economy. However, there is currently a lack of analysis on the impact pathways of the thermal environment considering both natural and human factors. Based on the MODIS MYD11A2 land surface temperature data, meteorological data, and human activity data of Xi'an metropolitan area in 2020, ArcGIS spatial geostatistical analysis was used to study the temporal and spatial distribution pattern of the thermal environment in different seasons, and redundancy analysis was utilized to select the main factors affecting the thermal environment. Then, structural equation modeling was used to quantify the direct and indirect effects of the dominant factors on the urban thermal environment. The results showed that:① The surface temperature in the Xi'an urban area showed a spatial pattern of higher temperatures in the north and lower temperatures in the south, with a decrease in temperature from the city center to the surrounding areas. The most severe heat environment pollution occurred in the summer. ② The redundancy analysis (RDA) results indicated that the main factors that affected the thermal environment were air temperature, impermeable surfaces, vegetation, and precipitation. ③ The results of the structural equation modeling (SEM) indicated that meteorological, surface, and anthropogenic factors affected the urban thermal environment mainly through direct pathways, which were much more important than all indirect pathways. Factors such as temperature, impervious surfaces, and point of interest density had a significant positive effect on the thermal environment (0.10 and 0.33). On the other hand, factors such as water bodies, precipitation, and vegetation had a significant negative effect on the thermal environment (-0.29 and -0.25). Human activities had a greater direct impact on nocturnal surface temperatures than surface and meteorological factors. Increasing economic efficiency is beneficial for mitigating the urban heat island effect. The results of the study can provide a reference for studying local climate change in urban heat islands and for the construction of green and ecologically livable urban environments.

Youths’ Investigations of Critical Urban Forestry Through Multimodal Sensemaking

AbstractA growing body of research suggests that digital multimodal composing can provide students multiple points of entry for making sense of local climate change issues and sharing their voices through digital activism. Building upon this scholarship, this study examined the processes of 32 small groups (n = 55) of 7th- and 8th-grade students as they co-created a wide range of multimodal projects (e.g., videos, podcasts, infographics, posters, and cartoons) that explored the environmental, ecological, and sociopolitical impacts of inequitable access to urban tree canopy and greenspace in their city. In particular, scholarship on onto-epistemic heterogeneity, critical place-based learning, and multimodality were integrated to gain an interdisciplinary understanding of how digital multimodal composing mediated students’ sensemaking about urban forestry impacts on community health and ecological well-being. Data sources consisted of field notes, audio and video recordings, survey data, student interviews, and students’ final multimodal projects. Through qualitative and multimodal data analysis, five main themes emerged for how multiple modes mediated students’ sensemaking about critical urban forestry: (1) embracing tree equity for compelling stories, (2) engaging authentic audiences through storytelling, (3) perspective-taking through multiple modes, (4) exploring affective dimensions of urban heat islands, and (5) developing solutions for critical urban forestry issues. These findings contribute new insights into how digital multimodal storytelling can provide a productive way for students to make sense of climate justice issues and gain agency by experiencing multiple ways of knowing.

The Groundwater Management in the Mexico Megacity Peri-Urban Interface

Megacities boost peri-urban socioeconomic development but fulfill their high natural resource demands by overexploitation, yielding irreversible environmental damage in surroundings that turn into sacrifice zones. This study reports the effects on the Cuautitlán-Pachuca Valley, the Mexico City main expansion zone at the northeast of the metropolitan area on the Central Mexico plateau, the trend scenarios from 2020 to 2050, and the actions to mitigate the growing water demand that will worsen its aquifer overexploitation. We designed a conceptual archetype to apply the Water Evaluation and Planning System (W.E.A.P.) mathematical model calibrated with 2013–2014 data to calculate groundwater volume demand in future scenarios. The demand output for the international airport and agriculture was less than 5%. The local climate change effect up to 2050 will slightly reduce the infiltration. The most crucial water demand increase (195% in 2050) is due to the population and industrial growth of the Mexico City northern municipalities (89% of the total groundwater extraction volume), and the aquifer will have a notable −2192.3 hm3 accumulated deficit in 2050, while urban sprawl will decrease water infiltration by 2.3%. Mitigation scenarios such as rainwater harvesting may reduce the urban water supply only by 9%, and a leak cutback will do so by 24%, which is still insufficient to achieve sustainable water management in the future. These outcomes emphasize the need to consider other actions, such as importing water from near aquifers and treating wastewater reuse to meet the future water demand.

Tree rings reveal the transient risk of extinction hidden inside climate envelope forecasts

Given the importance of climate in shaping species' geographic distributions, climate change poses an existential threat to biodiversity. Climate envelope modeling, the predominant approach used to quantify this threat, presumes that individuals in populations respond to climate variability and change according to species-level responses inferred from spatial occurrence data-such that individuals at the cool edge of a species' distribution should benefit from warming (the "leading edge"), whereas individuals at the warm edge should suffer (the "trailing edge"). Using 1,558 tree-ring time series of an aridland pine (Pinus edulis) collected at 977 locations across the species' distribution, we found that trees everywhere grow less in warmer-than-average and drier-than-average years. Ubiquitous negative temperature sensitivity indicates that individuals across the entire distribution should suffer with warming-the entire distribution is a trailing edge. Species-level responses to spatial climate variation are opposite in sign to individual-scale responses to time-varying climate for approximately half the species' distribution with respect to temperature and the majority of the species' distribution with respect to precipitation. These findings, added to evidence from the literature for scale-dependent climate responses in hundreds of species, suggest that correlative, equilibrium-based range forecasts may fail to accurately represent how individuals in populations will be impacted by changing climate. A scale-dependent view of the impact of climate change on biodiversity highlights the transient risk of extinction hidden inside climate envelope forecasts and the importance of evolution in rescuing species from extinction whenever local climate variability and change exceeds individual-scale climate tolerances.

Determining anthropogenic pressure on the Southern Black Sea blue flag beaches

Coasts are settlement areas that attract human for many years. Türkiye, geographically located on Mediterranean Basin and Asian Continent passage with unique climate regime, has a great coastal zone. The mid-latitude geographic setting makes possible to experience coastal recreation and tourism activities for almost all year along. Among all activities sun, sea and sand tourism can be placed on the first stage. Recent changes in local climate of the Black Sea such as rising mean atmospheric temperatures and increasing number of sunny days have triggered touristic beach activities in the region. In the literature, there are different techniques for grading and classifying coastal beaches. In this study, as an integral part of coastal landscape formation Land Use/Land Cover (LULC) structure is linked to landscape value and regarded as cover changes that determines landscape pattern of the area under investigation. The research rationale of this study is based on an assumption of Southern Black Sea coastal blue flag beaches are under severe anthropogenic pressure. For this purpose, 15 blue flag beaches which are located on the Black Sea coast of Türkiye were selected based on their morphological dimensions. To determine landscape changes and potential human induced effects on selected beaches for the last 35–40 years period, georeferenced, atmospherically corrected Landsat 5 TM and Landsat 8 OLI-TIRS satellite images were used. Furthermore, carrying capacities for all researched beaches were calculated and documented in order to find the actual human usage frequencies during the high season. According to results of the study, it is clearly observed that all beach areas are under anthropogenic pressure. The most important evidence of this situation is the proportional increases in the IS (Impervious Surface) cover class in the classified images between 1984 and 1985 and 2021 in all 15 beaches. Moreover, these increases have reached up to 5–6 times for some beaches. As inferred, from the field surveys, beach carrying capacities were also exceeded for the most of the beaches under investigation. This means the blue flag beaches of Southern Black Sea are not only affected by construction and urbanization but also under intense pressure of overuse during the high seasons. It is revealed that these areas should be carefully managed with state-of-the-art techniques that prioritize adaptive planning that takes into account all stakeholders participation. Moreover, the activities, authorization and attitudes of municipalities regarding the coastal zones must be limited and inspected by a higher organization.

Hydrometeorological response to afforestation in the UK: findings from a kilometer-scale climate model

Afforestation is of international interest for its positive benefits on carbon storage, ecology, and society, but its impacts on terrestrial and atmospheric processes are still poorly understood. This study presents the first use of a coupled land surface and convection permitting atmospheric model (CPM) to quantify hydrometeorological effects of afforestation across the United Kingdom, focusing on atmospheric processes often missing in hydrological models. Generating a scenario of 93 000 km2 (40%) additional woodland across the UK, the periods of 2042–2052 and 2062–2072 are analysed. Simulated afforestation alters seasonal and regional UK hydrometeorology. Countrywide runoff increases in all seasons (between 5.4–11 mm and 4.3–8.6% per season) due to elevated subsurface flows from greater soil moisture. Evaporation decreases in summer (−20.6 mm, −10%) but increases in winter (8.1 mm, 15%) whereas rainfall increases throughout all seasons (between 2.2–6.86 mm and 0.9%–2.2% per season). Greater winter rainfall is detected along Great Britain’s west coastline as increased surface roughness produces prolonged and heavier rainfall. In the summer, lower albedo increases potential evapotranspiration and reduces near surface specific humidity: water is locked in deeper soil layers as transpiration diminishes and the topsoil dries out. However, the magnitude of hydrometeorological change due to altered land cover is smaller than the uncertainty in local climate change projections. This work sets a precedent in illustrating the impacts of afforestation on hydrology using a high-resolution CPM and highlights the importance of coupled hydrometeorological processes when investigating land cover impacts on hydrological processes.

The giving tree: impacts of deforestation on birth outcomes in Mexico

ABSTRACT Deforestation adversely impacts human health through mechanisms such as increased air pollution, shifts in disease vector distributions, and changes in local climate. Although the influence of deforestation on human health is recognized, its effects on infant health outcomes have been insufficiently studied. This paper examines the effects of deforestation on infant health by analysing birth certificate data from 2011 to 2021 across Mexican municipalities, combined with satellite-derived annual deforestation rates. We show that increased deforestation leads to decreased birth weight, higher rates of low birth weight (LBW), and reduced Apgar scores. Specifically, an increase of one standard deviation in deforestation results in a reduction of average birth weight by 19 grams, an increase in the probability of LBW by 0.43% points, and an increase in the probability of a low Apgar score by 4.7% points. These effects are consistently observed even after controlling for different definitions of forest cover, excluding data during the COVID-19 pandemic, and limiting the analysis to municipalities with at least 2% forest coverage. This study provides critical evidence that deforestation directly impairs newborn health in Mexico, highlighting a significant and underappreciated environmental cost with long-term implications for human capital.

Quantifying and communicating uncertain climate change hazards in participatory climate change adaptation processes

Abstract. Participatory processes for identifying local climate change adaptation measures have to be performed worldwide. As these processes require information about context-specific climate change hazards, we show in this study how to quantify climate change hazards with their uncertainties in regions all around the globe and how to best communicate the potential hazards with their uncertainties in order to identify local climate change adaptation strategies. In a participatory process on water-related adaptation in a biosphere reserve in Germany, we used the freely available output of a multi-model ensemble provided by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) initiative, which provides global coverage, to quantify the wide range of potential future changes in (ground)water resources. Our approach for quantifying the range of potential climate change hazards can be applied worldwide for local to regional study areas and also for adaptations in agriculture, forestry, fisheries, and biodiversity. We evaluated our approach to communicating uncertain local climate change hazards by means of questionnaires that the stakeholders in the participatory process and the audiences from the general public of two project result presentations answered. To support the stakeholders in participatory climate change adaptation processes, we propose the use of percentile boxes rather than boxplots for visualizing the range of potential future changes. This helps the stakeholders identify the future changes they wish to adapt to, depending on the problem (e.g., resource scarcity vs. resource excess) and their risk aversion. The general public is best informed by simple ensemble averages of potential future changes together with the model agreement on the sign of change. Using or adapting our quantification and communication approach, flexible climate change adaptation strategies can and should be developed worldwide in a participatory and transdisciplinary manner, involving stakeholders and scientists.

Soil Hydrothermal Dynamics in the Hengduan Mountains of Southeast Tibet and Associated Influencing Factors

Soil water and soil temperature are important ecological factors and driving forces for ecosystem restoration and sustainable development, possessing great significance for climate modeling and prediction. The Hengduan Mountains in southeastern Tibet, China, are located in a climate-change-sensitive area, and the study of soil hydrothermal dynamics in this area is of great significance for local and global climatic change and water resource utilization. This study, based on the soil hydrothermal and meteorological data of the Hengduan Mountain area in Southeast Tibet, analyzes the dynamic change patterns of soil hydrothermal and meteorological factors and explores their influencing relationships. It was found that the dynamic change in soil water content affected by precipitation was “bimodal” type. Among the meteorological factors, soil water content has the strongest correlation with relative humidity. The intra-annual variation curve of soil temperature is similar to that of the atmospheric temperature, showing a “unimodal” type, and has the highest correlation with atmospheric temperature. Specifically, it takes 70 mm and 170 mm of precipitation to change the soil water content and soil temperature at the 150 cm depth. For every 20 °C change in atmospheric temperature, soil temperature above 150 cm changes by an average of 7.2 °C.

Uncovering sea level patterns in Caspian Sea altimetry data

ABSTRACT This study introduces a technique to uncover concealed patterns in satellite altimetry data, reflecting sea level variations in inland water bodies. We applied the methodology to the Caspian Sea, using altimetry data from four satellite missions over 27 years (1993–2020): TOPEX/Poseidon, Jason1, Jason2, and Jason3. The approach involves two steps: estimating sea level trends and identifying breakpoints that indicate trend shifts; and leveraging time lags between breakpoints at various locations to classify water drainage areas according to their degree of influence on each period. By revealing concealed patterns in the altimetry data, this technique can provide insights to understand the impacts of global warming and local climate changes on sea level fluctuations in the Caspian Sea. We hope that our study can facilitate subsequent interdisciplinary research on the intricate interplay between climate change and hydrological processes in inland water bodies.

A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada

Abstract There is mounting pressure on (re)insurers to quantify the impacts of climate change, notably on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modeling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to climate change risk assessment of pluvial flooding for insurance portfolios over Canada and the United States (US). The underlying flood occurrence model quantifies the financial impacts of short-term (12–48 h) precipitation dynamics over the present (2010–2030) and future climate (2040–2060) by leveraging statistical/machine learning and regional climate models. The flood occurrence model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is applied at the full scale of Canada and the US over 10–25 km grids. Our analyses show that climate change and urbanization will typically increase losses over Canada and the US, while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses.

Comparison of bias correction methods to regional climate model simulations for climate change projection in Muger Subbasin, Upper Blue Nile Basin, Ethiopia

ABSTRACT The objective of this study was to evaluate the best performed bias correction methods to simulate the regional climate models for future climate change projections in Muger Subbasin. Delta change methods perform very well with a coefficient of correlation of 0.99 and a percent of bias –3. When we compare its corrected simulation result with observed data, the delta change method seems to have with no biases for maximum temperature, but increases by 1.67 °C from the mean for minimum temperature of 0.39 and 38.41 mm for monthly and annual precipitation, respectively. Delta change methods underestimate the model result for both temperature and precipitation. Linear scaling and variance scaling methods overestimate the maximum temperature of the simulation by 0.002 and 0.004 °C from the mean of the observed data, but it underestimates 1.59 and 1.56 °C the minimum temperature, respectively. The long-term temperature projection values (2060–2090) are higher than the near-term projections (2030–2060) for both RCP2.6 and RCP8.5 scenarios. Similarly, the change in annual precipitation for the long-term is higher than the near-term projections. As a conclusion, the results draw attention to the fact that bias-adjusted regional climate models data are crucial for the provision of local climate change impact studies in the Muger Subbasin.

A Comprehensive Examination of the Medvezhiy Glacier’s Surges in West Pamir (1968–2023)

The Vanj River Basin contains a dynamic glacier, the Medvezhiy glacier, which occasionally poses a danger to local residents due to its surging, flooding, and frequent blockages of the Abdukahor River, leading to intense glacial lake outburst floods (GLOF). This study offers a new perspective on the quantitative assessment of glacier surface velocities and associated lake changes during six surges from 1968 to 2023 by using time-series imagery (Corona, Hexagon, Landsat), SRTM elevation maps, ITS_LIVE, unmanned aerial vehicles, local climate, and glacier surface elevation changes. Six turbulent periods (1968, 1973, 1977, 1989–1990, 2001, and 2011) were investigated, each lasting three years within a 10–11-year cycle. During inactive phases, a reduction in the thickness of the glacier tongue in the ablation zone occurred. During a surge in 2011, the flow accelerated, creating an ice dam and conditions for GLOF. Using these datasets, we reconstructed the process of the Medvezhiy glacier surge with high detail and identified a clear signal of uplift in the surface above the lower glacier tongue as well as a uniform increase in velocities associated with the onset of the surge. The increased activity of the Medvezhiy glacier and seasonal fluctuations in surface runoff are closely linked to climatic factors throughout the surge phase, and recent UAV observations indicate the absence of GLOFs in the glacier’s channel. Comprehending the processes of glacier movements and related changes at a regional level is crucial for implementing more proactive measures and identifying appropriate strategies for mitigation.

Unlocking carbon finance: Empowering energy communities for mutual benefit

This study investigates the potential of utilizing carbon credits to finance innovative local energy communities in Europe, addressing a significant gap in academic literature. Despite the growing interest in voluntary carbon credits as a mechanism for offsetting carbon emissions, there is limited evidence connecting local energy systems to voluntary carbon markets. The study explores whether carbon credits could serve as a practical tool for funding the development of energy communities, contributing to sustainable energy transitions and climate mitigation strategies. The research employs a comprehensive methodology to assess the quality of carbon credit projects and examines ten innovative energy community projects in Europe. Key findings reveal there is potential for using carbon credits to finance energy community initiatives. However, challenges persist, particularly regarding financing barriers and the volatile nature of carbon markets. The study underscores the importance of policy support in establishing clear standards for voluntary markets and promoting the accessibility of carbon offsets. Furthermore, it suggests potential solutions such as pre-financing agreements and the utilization of carbon market derivatives to enhance project viability. Overall, the study offers insights into the intersection between voluntary carbon markets and local energy initiatives, providing a foundation for further research and policy development in the field of local sustainable development and climate change mitigation.