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)

Co-benefits of efficient and climate friendly cooling in China

The cooling sector plays a pivotal role in the global economy but significantly contributes to global warming. In 2022, cooling-related emissions accounted for 13% of global greenhouse gas (GHG) emissions. China, in particular, played a substantial role in cooling accounting for 10% of its national emissions and consuming 15% of its total electricity. This substantial environmental impact stems largely from the sector's reliance on refrigerants with high Global Warming Potential (GWP) and energy-intensive equipment. The refrigeration and air conditioning sector widely adopted hydrofluorocarbons (HFCs) as replacements for ozone-depleting substances regulated under the Montreal Protocol. However, as potent GHG, HFCs significantly contribute to global warming and are now subject to a global phase-down under the Kigali Amendment to the Montreal Protocol. Improving the energy efficiency of cooling equipment alongside the phasedown of HFCs could potentially double the mitigation benefits of the Kigali Amendment. With the growing demand for cooling in China, it is essential to explore mitigation strategies that simultaneously reduce HFC emissions and enhance energy efficiency. This study evaluates the co-benefits of efficient and climate-friendly cooling solutions in China. This study adopts a bottom-up approach to integrate the Refrigeration and Air Conditioning - Demand, Emission, and Cost (RAC-DEC) model with Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) models. The research focuses on four key cooling subsectors: room air conditioning, mobile air conditioning, commercial air conditioning, and cold chain. The analysis is conducted under three scenarios: Business-as-Usual (BAU), reflecting current policies and practices; Kigali Amendment with enhanced energy efficiency of cooling equipment (KAE); and Accelerated Transformational Energy Efficiency (ATE). This study projects medium- and long-term trends in refrigerant and energy consumption, driven by key demand drivers for each subsector. It then quantifies both direct refrigerant emissions following the IPCC inventory methodology and indirect emissions from energy consumption. Finally, it evaluates the combined emission reduction potential under the alternative KAE and ATE scenarios. The preliminary results indicate that among China's cooling sector, the commercial refrigeration sector offers the highest potential for emission reduction, accounting for approximately 40% of the total cumulative emission reductions from 2023 to 2060. By 2060, China’s cooling sector could achieve cumulative emission reductions of approximately 11.5 Gt CO₂-eq in the KAE scenario and 16.5 Gt CO₂-eq in the ATE scenario. In the KAE scenario, emissions are expected to decline by 48% from 2022 to 2050. In contrast, the ATE scenario predicts a 70% reduction in annual emissions, dropping from 714–721 Mt CO₂-eq in 2022 to 217–218 Mt CO₂-eq by 2050. These significant reductions are primarily driven by the accelerated phase-out of HFC refrigerants, enhanced energy efficiency, and the deep decarbonization of the power system. This study underscores the critical role of the cooling sector in contributing to global climate goals, including the COP28 Global Cooling Pledge and the Kigali Amendment. By providing a methodological framework, our findings offer essential scientific support for policymakers in China and beyond, facilitating coordinated efforts to actively reduce fluorinated GHGs and enhance energy efficiency within the cooling sector

Optimal control models: exploring the limits of predictive power

This paper examines the application of optimal control models across disciplines, highlighting both their strengths and limitations. While these models are valuable tools in biological and socio-economic contexts, their use requires careful consideration of inherent constraints. A key advantage of such models is their ability to facilitate structural analysis. The second part of the study focuses on the continuation algorithm and its role in understanding dynamic optimization. Through two examples, the paper illustrates this approach and emphasizes the need for a critical perspective, especially when modeling human behavior and interactions

Assessing the ammonia mitigation potential from the Indian agriculture sector for improving air quality in India

As an agrarian country, India heavily depends on fertilizers for food production to meet consumption demands, which contributes to a significant portion of global ammonia emissions. Ammonia is an essential precursor gas to form secondary PM2.5 by reacting with SO2 and NO2 and degrades air quality significantly. Thus, it is imperative to implement mitigation strategies to reduce ammonia emissions from the agricultural sector for air quality improvement. In this study, we have updated the sub-sectoral agriculture activity data for each state of India, using 2022 as the base year. Ammonia emissions from each sub-sectoral activity for each state were estimated in the GAINS model for baseline and future scenarios under the current policy framework. We estimated the mitigation potential for ammonia emissions in agriculture by applying different alternate control scenarios. Under the current baseline scenario, the ammonia emissions (in Kilotons) from urea application are the highest among all the states, followed by other livestock such as sheep and horses, other cattle (Beef), dairy cattle, poultry, nitrogenous fertilizer use and production, and agricultural waste burning. The major contributor states to annual ammonia emissions (in Kt/yr) from urea application are Uttar Pradesh (625 ), followed by Andhra Pradesh (290.67) and Madhya Pradesh (271.32). The major contributor states to NH3 emissions from livestock sectoral activities (other cattle, dairy cattle, sheep and horses, poultry, etc.) are Uttar Pradesh (827.73) followed by Andhra Pradesh (478.65) and Rajasthan (491.13). The NH3 emissions (kt/y) from nitrogenous fertilizer production and consumption was highest from Uttar Pradesh (23.28), followed by Gujarat (10.86) and Maharashtra (10.44), while the contribution from agriculture waste burning was estimated largely from Uttar Pradesh (61.10), followed by Andhra Pradesh (32.91) and Tamil Nadu (30.04). We consider several strategies, such as deep manure placement, low nitrogen feed, scrubber for livestock housing, urea substitution, neem-coated urea, and biochar additives to reduce NH3 emissions and estimate their mitigation potentials in this work. To date, there are no specific regulations in India targeting agricultural ammonia emissions at the same level as those of other sector pollutants. Therefore, our results will be useful for policymakers for developing state-specific sub-sectoral mitigation strategies to address this critical issue