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BackgroundThe decision of the German federal government to cease lignite mining until 2038 or—if possible—already earlier until 2030, will cause manifold transition processes in the remaining lignite mining districts of Germany. The two largest districts are located in geographically opposite regions: The Rhineland in the western part and Lusatia in the east of Germany. As particularly these two mining districts will experience severe changes in their socioeconomic as well environmental conditions, the federal government has adopted comprehensive economic support measures. However, the environmental changes will also cause altered ecosystem functions and services to be provided by the future post-mining landscapes.ResultsIn this paper, the two main lignite-producing regions of Germany are compared with regard to their natural and cultural settings. The economic situation and its history are reflected and differences are outlined. Part of the disparities in the cultural development can be explained by very different natural conditions, especially edaphic factors and climatic situation. Because of dissimilar geological settings, different mining technologies were developed and are in use in the two regions with distinct effects on the resulting post-mining landscapes.ConclusionThe long-standing and manifold lignite mining activities have radically restructured the landscapes in Lusatia and the Rhineland. With the ongoing decline of the mining industry and its complete cessation, presumably within the next decade, both regions will alter their faces significantly. These changes offer both challenges but also opportunities with respect to the post-mining landscapes and their ecosystem services they are going to provide. The prerequisites for a positive socioeconomic development and for sustainable land-use concepts that also consider ecological aspects are different for both regions. However, or especially because of these differences, the knowledge exchange and experience transfer between both mining regions are pivotal for the success of this extensive transformation process.

To ensure the good chemical status of surface water across Europe, it is necessary to increase research on the comprehensive impact of land use and land cover changes, i.e., deforestation, on the natural environment. For this reason, we used data from 9-year environmental monitoring in the Wüstebach experimental catchment of the TERENO (Terrestrial Environmental Observatories) network to determine the impact of partial deforestation on solute fluxes and stream water ionic composition. In 2013, a partial deforestation experiment was conducted in the study area using a cut-to-length logging method. To this end, two headwater catchments were compared: one partially deforested (22% of the catchment area) and one untreated control catchment. The concentrations of ions in stream water, groundwater, and precipitation were analyzed: Ca2+, Mg2+, Na+, K+, Al3+, Fetot, Mn2+, NO3−, SO4−, and Cl−. Most of the ions (Na+, Ca2+, Mg2+, Cl−, and SO4−) showed decreasing trends in concentrations after deforestation, indicating a dilution effect in stream water due to the reduction of the supply of solutes with precipitation in the open deforested area. The fluxes of these ions decreased by 5–7% in the first year after deforestation, although the stream runoff increased by 5%. In the second year, the decrease in ion fluxes was greater, from 6% to 24%. This finding confirms that only limited soil erosion occurred after the deforestation because the soil was well protected during logging works by covering harvester lanes with branches. Only K+ and NO3− ions showed increasing trends in both concentrations and fluxes in the partially deforested catchment in the first two to three years after deforestation. Spruce die-offs, common in Europe, may decrease the concentration and fluxes of base cations in surface water in a nutrient-limited environment. However, the simultaneous planting of young broad-leaved trees with post-harvesting regrowth could create a nutrient sink that protects the catchment area from nutrient depletion.

Limiting the global temperature rise to 1.5 °C is becoming increasingly difficult. The study analyzed data from 700 locations (1962–2100) to assess climate change impacts on heating‐cooling energy and carbon footprint in under‐researched Central Asia (CA). Under SSP2‐4.5, icing and frost days reduce, while summer days and tropical nights increase. Central Asian countries will see an increase in cooling needs despite the projected decline in heating demands, with Kyrgyzstan experiencing the highest rise in cooling degree days, projected to increase by 132% and 165% in the near‐future under SSP2‐4.5 and SSP5‐8.5, respectively. As a result, cooling energy generation is expected to rise by 39% and 92% under SSP2‐4.5 and SSP5‐8.5, respectively. However, CO2 emissions for cooling are much lower in Kyrgyzstan and Tajikistan due to their reliance on renewable energy. CO2 emissions in these countries are projected to be ≈10 times lower than in other parts of CA. From 2022 to 2100, cooling‐related emissions are estimated to increase by 41% and 80% under SSP2‐4.5 and SSP5‐8.5, respectively across CA. Urgent adaptation is needed for resilient cities and stable power by expanding renewables, modernizing infrastructure, boosting efficiency, adopting policies, and fostering cooperation. This study examines climate change impacts on heating‐cooling demand and carbon footprint in Central Asia (CA). As icing and frost days decrease, cooling needs will rise, especially in Kyrgyzstan. However, Kyrgyzstan and Tajikistan maintain lower CO2 emissions due to renewables. Cooling‐related emissions in CA may rise by 41%–80%, highlighting the need for renewable expansion, infrastructure upgrades, and regional cooperation.

Extreme temperature events, particularly heatwaves, are intensifying due to climate change and urbanization, posing major public health challenges in Central Asia (CA), where research is limited. Despite the rising frequency and severity of heat extremes, long‐term assessments of their health impacts are scarce. This study addresses this gap by analyzing historical and future heatwave trends and associated health risks using multi‐ensemble climate models across 700 locations from 1959 to 2100. Bias correction improved GCMs, reducing bias and RMSE by 24% and 14%, respectively. Under SSP2–4.5, projected heatwave magnitudes (HWM) shift from 26 to 31 °C, consistent with historical moderate to severe events. Under SSP5–8.5, HWM increases to 29–36 °C. Turkmenistan is expected to experience ultra‐extreme heatwaves in the far future, a pattern not seen in other CA countries. Under SSP2–4.5, Kazakhstan and Uzbekistan show the highest rises in heatwave‐related mortality rates, with slopes of 5.432 and 3.021 in the near future, declining to 1.377 and 1.102 in the far future. SSP5–8.5 shows similar but higher estimates, highlighting escalating public health risks. Findings emphasize the urgent need for region‐specific climate policies and public health strategies to mitigate the growing burden of extreme heat in CA. Extreme heatwaves in Central Asia are intensifying due to climate change and urbanization, amplifying public health risks. Using bias‐corrected climate model ensembles across 700 locations (1959–2100), this study projects substantial increases in heatwave magnitude, with Turkmenistan facing ultra‐extreme events under SSP5–8.5. Kazakhstan and Uzbekistan are identified as hotspots for rising heatwave‐related mortality. These findings highlight the escalating health burden of extreme heat in Central Asia and underscore the urgent need for targeted climate policies and public health strategies.

Extreme temperature events such as heatwaves are becoming increasingly severe and frequent because of climate change, posing significant challenges to public health and energy infrastructure. This study explores the impacts of extreme temperature events leading to heat‐/cold waves on public health and energy consumption in Kazakhstan from 1959 to 2021. The most striking trends in heatwave‐related indices emerge in the western and southwestern regions. Conversely, despite heightened coldwave intensity, a decline is noted in their frequency and number. The impact of heatwaves on various health conditions, notably consistent and statistically significant rises in all‐cause and cardiovascular mortalities, is observed. Shifts in energy demand are also unveiled with a noticeable spike in cooling‐degree days and a reduction in heating‐degree days. The mean total energy consumption stood at 552 kWh across the country with an average annual energy generation of ≈8.76 kWh. To gauge the environmental implications, the mean CO2 emissions are estimated at 464 kg per kWh for both heating and cooling purposes. With climate change set to escalate heatwaves, the need for comprehensive health planning is underscored to mitigate their adverse health impacts. Furthermore, transitioning from fossil fuels to green energy sources is crucial to reduce the environmental footprint. This study examines the effects of extreme temperature events, including heatwaves and cold waves, on public health and energy consumption in Kazakhstan from 1959 to 2021. Findings highlight increased heatwave‐related health risks, particularly in western regions, along with shifts in energy demand. The study underscores the need for health planning and a transition to green energy to address these climate‐related challenges.

Background Biogenic volatile organic compounds (BVOC) emitted by plants play an important role for ecological and physiological processes, for example as response to stressors. These emitted compounds are involved in chemical processes within the atmosphere and contribute to the formation of aerosols and ozone. Direct measurement of BVOC emissions requires a specialized sample system in order to obtain repeatable and comparable results. These systems need to be constructed carefully since BVOC measurements may be disturbed by several side effects, e.g., due to wrong material selection and lacking system stability. Results In order to assess BVOC emission rates, a four plant chamber system was constructed, implemented and throughout evaluated by synthetic tests and in two case studies on 3-year-old sweet chestnut seedlings. Synthetic system test showed a stable sampling with good repeatability and low memory effects. The first case study demonstrated the capability of the system to screen multiple trees within a few days and revealed three different emission patterns of sweet chestnut trees. The second case study comprised an application of drought stress on two seedlings compared to two in parallel assessed seedlings of a control. Here, a clear reduction of BVOC emissions during drought stress was observed. Conclusion The developed system allows assessing BVOC as well as CO 2 and water vapor gas exchange of four tree specimens automatically and in parallel with repeatable results. A canopy volume of 30 l can be investigated, which constitutes in case of tree seedlings the whole canopy. Longer lasting experiments of e.g., 1–3 weeks can be performed easily without any significant plant interference.

After publication of this article [1], the authors noted the following error. Due to a calculation error in the temperature term f(TL) of the emission standardization algorithm (Eq. 3 of the original paper), the reported emission rates have to be corrected in the text of the results as well as Fig. 5a.

Water quality and safe water sources are pivotal aspects of consideration for domestic water. Focusing on underserved households in Kenya, this study compared user perceptions and preferences on water-service provision options, particularly investigating the viability of decentralized models, such as the Safe Water Enterprise (SWE), as sustainable safe drinking water sources. Results showed that among a number of water-service provision options available, the majority of households regularly sourced their domestic water from more than one source (86% Ngoliba/Maguguni, 98% Kangemi Gichagi). A majority of households perceived their water sources to be unsafe to drink (84% Ngoliba/Maguguni, 73% Kangemi Gichagi). For this reason, drinking water was mainly chlorinated (48% Ngoliba/Maguguni, 33% Kangemi Gichagi) or boiled (42% Ngoliba/Maguguni, 67% Kangemi Gichagi). However, this study also found that households in Kenya did not apply these household water treatment methods consistently, thus indicating inconsistency in safe water consumption. The SWE concept, a community-scale decentralized safe drinking water source, was a preferred option among households who perceived it to save time and to be less cumbersome as compared to boiling and chlorination. Willingness to pay for SWE water was also a positive indicator for its preference by the underserved households. However, the long-term applicability of such decentralized water provision models needs to be further investigated within the larger water-service provision context.

Within the CO2 time series measured at the Environmental Research Station Schneefernerhaus (UFS), Germany, as part of the Global Atmospheric Watch (GAW) program, pollution episodes are traced back to local and regional emissions, identified by δ13C(CO2) as well as ratios of CO and CH4 to CO2 mixing ratios. Seven episodes of sudden enhancements in the tropospheric CO2 mixing ratio are identified in the measurements of mixing/isotopic ratios during five winter months from October 2012 to February 2013. The short-term CO2 variations are closely correlated with changes in CO and CH4 mixing ratios, achieving mean values of 6.0 ± 0.2 ppb/ppm for CO/CO2 and 6.0 ± 0.1 ppb/ppm for CH4/CO2. The estimated isotopic signature of CO2 sources (δs) ranges between −35‰ and −24‰, with higher values indicating contributions from coal combustion or wood burning, and lower values being the result of natural gas or gasoline. Moving Keeling plots with site-specific data selection criteria are applied to detect these pollution events. Furthermore, the HYSPLIT trajectory model is utilized to identify the trajectories during periods with CO2 peak events. Short trajectories are found covering Western and Central Europe, while clean air masses flow from the Atlantic Ocean and the Arctic Ocean.

Urban energy demand and climate dynamics are inherently interconnected. However, existing modeling approaches often fail to integrate data effectively across multiple spatial scales. Urban Building Energy Models (UBEMs) and Urban Climate Models (UCMs) provide valuable insights into urban energy consumption and microclimate variations, respectively. However, their integration remains a challenge due to differences in spatial resolution, data structures, and computational requirements. While previous studies have explored model coupling, most focus on microclimatic interactions and lack a standardized framework for data integration across different urban scales. This review examines the current state of UBEM tools and UCMs, with a particular emphasis on the correspondence of model data integration at multiple spatial scales. We identify key challenges in harmonizing geospatial data, meteorological inputs, and simulation parameters, particularly the misalignment of Levels of Detail between models operating at different spatial scales. To address this, we propose a multi-scale data framework that enables integration by aligning UBEMs and UCMs data structures through shared urban databases. This approach contributes to more accurate energy predictions, enhances urban climate resilience planning, and improves the applicability of integrated models for policymakers and urban planners. Highlights Explores integration potential of urban climate and building energy models across multiple urban scales, from individual buildings to city-wide districts, enhancing planning accuracy and climate resilience. Emphasizes the need for shared databases and a common language to enable effective integration and knowledge transfer between Urban Building Energy Models (UBEMs) and Urban Climate Models (UCMs). Identifies key challenges in data harmonization and model interoperability across urban scales, proposing solutions to enhance the practical applicability of integrated urban modeling for policymakers and urban planners.