Evaluating the performance of seasonal pumped hydro storage coordinated operation with cascade hydropower station integrating variable renewable energy

Seasonal pumped hydro storage (SPHS) presents a promising solution for China's evolving power systems dominated by variable renewable energy (VRE) sources with pronounced seasonal variations. Unlike conventional pumped storage addressing short-term fluctuations, SPHS integrates new upstream reservoirs with existing cascade hydropower through reversible units and pipelines to mitigate seasonal generation disparities in river-based hydropower systems. This study develops a refined nested long-short term production simulation model to evaluate SPHS's potential in facilitating VRE integration. The model examines three operational modes (non-regulation, short-term regulation, seasonal regulation) across different hydrological conditions and seasonal periods. Case results demonstrate that SPHS implementation enhances system VRE accommodation capacity by 20 % despite having only 8.6 % (1:11.6 ratio) of the downstream reservoir's storage capacity. Annual generation increases by 1.60 %, 1.02 %, and 0.84 % in wet, normal, and dry years respectively, while maintaining stable power supply. The analysis reveals significant sensitivity of system performance to SPHS's water storage redistribution strategies, suggesting seasonal flexibility optimization could yield additional benefits. The findings demonstrate SPHS's capacity to address seasonal hydropower variability while establishing a scalable framework for advancing pumped hydro storage's operational flexibility and evaluation methodologies in long-term renewable energy integration scenarios

Digging in the shadows: A grounded theory study on the drivers of illegal well drilling in southern Iran

The agricultural sector is the largest consumer of water resources in Iran. Due to the country's physical and geographical constraints, groundwater overexploitation has intensified, making illegal well drilling an increasingly critical and uncontrolled national issue. This study investigates the underlying causes of illegal well drilling in Bushehr province using a qualitative grounded theory approach. Data was collected through in-depth, open-ended interviews, document analysis, and observations. The study's statistical population comprised farmers with water wells and experts from relevant organizations. Using snowball sampling, data collection continued until theoretical saturation was reached, resulting in a total of 53 interviews (23 farmers and 30 experts). The grounded theory analysis followed three coding stages: open, axial, and selective coding. Open coding yielded 322 concepts, which were refined into 21 categories during axial coding. Ultimately, a paradigm model of the drivers of illegal well drilling in southern Iran was presented including the main phenomenon, contextual conditions, causal conditions, intervening conditions, strategies, and consequences. Providing a comprehensive conception of the subject, the findings can pave the route for mitigating illegal well drilling and promoting sustainable groundwater management

Persistence of Misinformation and Hate Speech Over the Years: the Manchester Arena Bombing

In the aftermath of the 2017 Manchester Arena bombing, the ensuing debate in the press and on social media underscored terrorism's potential to intensify divisions. This study delves into the social media and press dynamics of rumors following the attack, and into the subsequent discourse on migration policies. We collected a dataset consisting of 3,184 press articles and 89,148 tweets about the Manchester Arena bombing. This research aims to identify prevalent rumors, explore the short- and long-term impacts on user engagement, analyze the sentiment in tweets related to each rumor, and examine perceptions of terrorism threats and migration policies among both the press and X (previously Twitter) users. The study found that X acted as an echo chamber for misinformation, amplifying specific rumors related to the attack, while the press exhibited fact-checking practices and provided nuanced perspectives. Notably, one rumor suggesting the attacker was a refugee gained traction over the years, reflecting an increase in anti-immigrant sentiments. Emotional responses on X ranged from neutral to heightened distress and anger, highlighting the significant impact of social media narratives on public sentiment. The research underscores the polarization of views on social media, influenced by the condensed format of tweets and the rapid production cycle, with X users expressing predominantly very negative attitudes toward immigration. This study emphasizes the critical role of the media in dispelling misinformation and fostering nuanced public understanding in complex sociopolitical contexts

Current and future research in environmental sustainability: Synthesise of the role, responsibilities, and opportunities for the business sector

Environmental sustainability is a timely and important topic to investigate given the increasingly complex challenges requiring businesses to reevaluate their business models in relationships with the natural environment, including their roles and responsibilities, and how opportunities in addressing these challenges may be utilized. This special issue enhances contemporary and future research by soliciting a wide variety of themes from ten papers falling under the scope of an ecological and climate focus of environmental sustainability relevant to the roles, responsibilities, and opportunities for the business sector, while also considering the links between environmental and social aspects. The articles included in the special issue provide an overview of five topics. These are 1) sub-national greenhouse gas accounting approaches, 2) corporate governance, policies, and practices, 3) sustainable finance, 4) consumer viewpoints and expectations, and 5) bioeconomy. Moreover, the crosscutting themes discussed suggest an inter- and transdisciplinary nature of environmental sustainability. In this introductory article to the special issue, the ten articles bring forth national and institutional levels, the sub-national level, and the organizational level. To conclude, future research avenues are vast based on suggestions presented in the ten papers the special issue covers. However, this introductory article also brings up topics suggested in the initial call for papers but were not covered in the papers included in the special issue, thus still relevant for future studies

The hours matter: comparing indicators of US residential cooling from hourly versus daily climate variables

Cooling energy demand in buildings is rapidly increasing as climate warms. Current methods of estimating and predicting residential cooling demand are primarily based on daily temperature, which neglects intraday temperature variations. To determine whether large-scale cooling demand is substantially affected by intraday temperature variations, we conduct a thorough comparison between variable degree days (VDDs) derived from daily temperature data with variable degree hours (VDHs) derived from hourly temperature data during the summer seasons in the United States. The results imply that incorporating intraday variations in temperature will have substantial impacts on cooling estimation and prediction. A comparison of the historical (1990–2014) VDD and VDH calculated from ERA5 temperature data reveals that US summer cooling demand estimated from hourly temperature is 29%–45% higher than those estimated from daily temperature, with differences exceeding 60% when hourly solar radiation is considered. This occurs because the hourly calculations captures the ‘hot hours’ of the mild days. Future scenario analysis, using the NASA Earth Exchange Global Daily Downscaled Projections, indicates that under the medium greenhouse gas emissions pathway (SSP2-45), US summer VDH and VDD are expected to increase by approximately 45% and 100% by the late century (2081–2100). This suggests that, daily-based predictions generally project cooling demand growth at twice the rate of hourly-based predictions, as the daily method accounts for increases in both high and low temperatures regardless of whether they exceed the baseline, while the hourly method, with its finer temporal resolution, includes only temperatures that surpass the baseline. Such effects are seen across most areas of the US. Our analysis underscores the significance of incorporating temperature data at higher temporal resolution in estimating and predicting cooling demand, which is essential for effectively implementing various measures to achieve energy conservation and climate goals

Can short-term memory processes be accurately detected? A reexamination of existing definitions

One major inadequacy in using the sample autocorrelation function (ACF) is the results from sample properties. Hassani’s [Formula: see text] theorem demonstrates that the sum of the sample ACF is always [Formula: see text] for any time series with any length. This result has led to doubts about methodologies that sum sample ACFs for diagnostics and analyses. Thus, the current tools and approaches fall short in detecting short-memory processes with due accuracy. Perhaps the larger question that looms here is about whether, with such definitions and methods, short-memory processes can really be picked up? Resolving this issue stands as a basic precursor to strong predictions and to precluding model mis-specification

Drivers of livestock manure nitrogen recycling on county scale in China

As the world's largest livestock producer, China faces pressing challenges in recycling manure to minimize resource waste and environmental degradation resulting from the vast amounts of manure generated. Understanding the drivering forces behind manure recycling is essential for advancing sustainable agriculture in China. This study estimated the manure recycling ratio (MRR), measured by nitrogen content, across 2853 Chinese counties using data from 390,000 farms representing four major livestock farming types in 2017. Northern Chinese counties demonstrated significantly higher MRRs, with values exceeding 50 %, compared to Southern regions, with values being lower than 30 %. Higher MRRs were linked to larger cropland size, higher urbanization levels, and a greater proportion of chicken farming. In contrast, MRRs declined in regions with higher temperatures, increased precipitation, higher manure production per livestock unit, a greater emphasis on pig farming, and an ageing rural population. Notably, natural factors such as temperature and precipitation predominantly influenced MRRs in both Southern and Northern China, whereas socioeconomic factors like cropland size and urbanization were more impactful in Eastern and Southwestern regions. These findings highlight the need for region-specific strategies that account for natural and socioeconomic conditions to enhance manure recycling practices across China

Thresholds of significant harm at global level: The journey of the Earth Commission

The planetary boundary framework proposes ‘safe’ boundaries, but these boundaries are not necessarily ‘just’. Hence, we ask: How has the Earth Commission defined just boundaries building on the concept of minimizing significant harm and how many people are currently exposed to harm above the safe and just threshold? We document the work of the Earth Commission to address these questions using our Earth System Justice framework. We conclude that: (a) from a justice perspective, nine criteria need to be considered when defining just boundaries; (b) the proportions of populations exposed to harm from exceeding safe and just boundaries today range from 11 to 84 % for the five domains studied (climate, biosphere, water, nutrients, aerosols); and (c) argue that the absolute upper limit for significant harm is possibly harm to 1 % of the population, which although not stringent enough to leave no one behind, would require radical transformations, given the populations currently already above the threshold

The evidence gap index: mapping evidence where it matters for climate change impacts

Climate change impacts are already evident and projected to worsen throughout the 21st century, even with mitigation efforts. Systematic mapping is key to organizing scientific evidence and identifying gaps, but current methods lack geographical context in relation to climate impact risk. In this study, we leverage machine learning to scale up systematic mapping and use automatic geolocation to track place-based research. We then enhance conventional systematic mapping by integrating location-based climate risk components—hazard, exposure, and vulnerability—to create an evidence gap index. This identifies high-risk regions that lack sufficient scientific study. We demonstrate this method using fluvial floods, combining research distribution with a flood-risk indicator (hazard), population density (exposure), and the Human Development Index (vulnerability). Our novel approach refines evidence mapping, supporting data-driven policymaking and directing research resources to the most urgent areas

Social Innovations and Transformations in Flood Risk Management

Flood risk management has changed significantly over the past decades (Kuhlicke et al. 2020). The focus has shifted from flood protection to flood risk management also with the consequence to change the relationship and arrangement between state and nonstate actors (Hartmann and Juepner 2014; Hartmann and Driessen 2017). Flood protection embraces a hazard-based perspective that relies primarily on engineering solutions. It is driven by expert-based and top-down decision-making. Flood risk management include a broader more holistic perspective of dealing with floods, including stronger involvement of nonstate actors (Adger et al. 2013; Hartmann and Driessen 2017; Kuhlicke et al. 2020). A core aim of flood risk management is also to encourage bottom-up innovative solutions for managing flood hazards (Thaler, Attems, and Fuchs 2022; Birkmann et al. 2023; Junger et al. 2023). Nevertheless, the selection process of flood risk management strategies still places a strong emphasis on technical mitigation measures. A significant barrier remains the preference within flood risk management for established and reliable methods over more experimental approaches that could potentially achieve broader objectives. In addition to conventional technical measures, which are often capital-intensive and can lead to environmental degradation, there is a growing need for innovative solutions that can not only effectively reduce flood risks, but also contribute to nature conservation, climate change mitigation, sustainable natural resource management, and the successful implementation of the European Water Framework Directive and the Floods Directive. Moreover, these innovations should aim to deliver societal co-benefits, such as improved quality of life and well-being. However, the success of these innovative concepts depends on social innovations that can drive a societal transformation process. The concept social innovation has been introduced a long time ago with the aim to overcome lock-in situations and to provide “better” responses to ongoing societal problems, such as managing the housing crises, encouraging our society toward decarbonization, selecting and implementing climate adaptation strategies, dealing other national and international crises and so forth (Hamdouch and Nyseth 2023). The core point of social innovation is the encouragement of social change, including a collective decision-making process. Put differently, social innovation can be understood as a way in which people are aiming at establishing new and more effective answers to the challenges that societies face, while at the same time embedding these solutions in a way that address societal needs (and not only steered towards economic profit). In this way, social innovation puts a greater emphasis compared to other types of innovation on values attached to products, including improving relationships, establishing new forms of cooperation, collaboration, and knowledge sharing. In particular, the concept of social innovation acts a counterresponse to the neoliberalism perspective on innovation and its potentially negative consequences for our society, such as privatization. Consequently, social innovation is also seen as a tool to encourage more democratic processes within political decision-making (Metzger, Allmendinger, and Oosterlynck 2014). Therefore, a core focus of social innovation lies in the support of the citizens to participate within political processes, which can eventually also encourage societal transformation process (Meyer and Hartmann 2025)