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In 2011 the Global Bioenergy Partnership (GBEP) released a set of indicators for sustainable bioenergy. However, two important issues still remain unresolved. One of them is the definition of “sustainability”, and the other is the lack of a holistic assessment tool for drawing conclusions from the indicators. The aim of this paper is to provide clarification on the concept of sustainability in the context of the GBEP indicators, and to develop a holistic assessment tool for assessing the sustainability of bioenergy programmes. The GBEP indicators are diverse in terms of “what to measure”, and some of them are not sufficiently directly related to the concept of sustainability. This makes the indicators ambiguous regarding to sustainability assessment. This study identifies whether the GBEP indicators are concerned with strong or weak sustainability, and develops a tool based on Multi Criteria Analysis (MCA) which can be used for assessing sustainability of bioenergy programmes using the GBEP indicators. The tool is demonstrated in an example for assessing the sustainability of biofuel production in a case study of Kyoto. We found that the biodiesel production in Kyoto performs well on the environmental pillar, but badly on the economic pillar, and based on the weights applied in this study the overall sustainability is better than diesel fuel. The holistic assessment tool provides practical information to policymakers on both ex-ante and ex-post policy evaluations.

Abstract Agriculture in the Black Sea catchment is responsible for a considerable share of the area's total water withdrawal and the majority of its total water consumption. It therefore plays a key role in sustainable water resources management. However, in the future water resources will be exposed to climate change. This assessment aims at identifying the most vulnerable regions and to explain the reasons of this vulnerability. It is based on a combination of the well-known Driver–Pressure–State–Impact–Response framework (DPSIR) and the vulnerability concept as defined by the Intergovernmental Panel on Climate Change (IPCC). Three distinctive climate change scenarios are used to assess their impacts on water resources for agriculture: (1) an increase in temperature; (2) a decrease in precipitation; and (3) a combination of the first and second scenarios. The data for this assessment is derived from a SWAT model (Soil and Water Assessment Tool). The results show that the regions of the Black Sea catchment are impacted by climate change differently. Some countries benefit from climate change (e.g., Turkey, Ukraine, Romania, Moldova, Hungary, Bulgaria) while others will encounter considerably worse agro-climatic conditions in the future (e.g., Montenegro, Austria, Bosnia–Herzegovina). Additionally, natural plant growth conditions mostly improve due to more suitable temperature conditions. In contrast, the deteriorating agricultural conditions mainly result from a diminishing irrigation potential that is caused by reduced precipitation. The conclusion emphasises the important role of the legal framework as well as more sustainable agronomic practices and proposes improvements for future assessment methods in this research field.

Abstract Global supply chains require integrated cost optimisation of sourcing, production and distribution through flexible networks of suppliers, manufacturers and logistics operators. The minimisation of environmental impacts of freight flows must be considered for sustainable development and should turn into a competitive advantage. To these aims, the paper presents a model integrating supply, production networks and sustainable freight transportation for strategic and tactical decision-making. Bill-of-Materials constraints are included in the model. The objective function considers sourcing, production and transportation costs as well as carbon dioxide emissions as environmental impacts of transport over a multimodal network. Computational experiments demonstrate the effectiveness of the model for cost-emissions analysis.

The most extreme environments are the most vulnerable to transformation under a rapidly changing climate. These ecosystems harbor some of the most specialized species, which will likely suffer the highest extinction rates. We document the steepest temperature increase (2010-2021) on record at altitudes of above 4,000 m, triggering a decline of the relictual and highly adapted moss Takakia lepidozioides. Its de-novo-sequenced genome with 27,467 protein-coding genes includes distinct adaptations to abiotic stresses and comprises the largest number of fast-evolving genes under positive selection. The uplift of the study site in the last 65 million years has resulted in life-threatening UV-B radiation and drastically reduced temperatures, and we detected several of the molecular adaptations of Takakia to these environmental changes. Surprisingly, specific morphological features likely occurred earlier than 165 mya in much warmer environments. Following nearly 400 million years of evolution and resilience, this species is now facing extinction.

Earth’s biodiversity and human societies face pollution, overconsumption of natural resources, urbanization, demographic shifts, social and economic inequalities, and habitat loss, many of which are exacerbated by climate change. Here, we review links among climate, biodiversity, and society and develop a roadmap toward sustainability. These include limiting warming to 1.5°C and effectively conserving and restoring functional ecosystems on 30 to 50% of land, freshwater, and ocean “scapes.” We envision a mosaic of interconnected protected and shared spaces, including intensively used spaces, to strengthen self-sustaining biodiversity, the capacity of people and nature to adapt to and mitigate climate change, and nature’s contributions to people. Fostering interlinked human, ecosystem, and planetary health for a livable future urgently requires bold implementation of transformative policy interventions through interconnected institutions, governance, and social systems from local to global levels.

The increasing trend in the consumption of various materials has also led to a huge increase in the final waste streams especially in the form of municipal solid waste (MSW) and the consequent environmental pollutions in particular greenhouse gas (GHG) emissions. These have made MSW management a significant environmental issue for governments and policy-makers. To address these challenges, developed countries have implemented sustainable material management (SMM) strategies which have been comprehensively reviewed herein. Moreover, waste generation statistics reported for most of the developed and developing countries as well as the existing gaps in MSW management among these countries have been fully discussed. The present paper was also aimed at comprehensively assessing electricity generation potentials from MSW using an integrated solid waste management system (including three different technologies of anaerobic digestion (AD), incineration, and pyrolysis-gasification) while the consequent GHG emission reduction potentials as a result of their implementation were also explored. To facilitate the understanding of the potential impacts of these treatment strategies, Iran's data were used as a case study. More specifically, the theoretical and technical potentials of electricity generation were calculated and the GHG emission reduction potentials were estimated using a life cycle assessment (LCA) approach. Overall, it was found that 5005.4–5545.8 GW h of electricity could be generated from MSW in Iran annually which could lead to approximately 3561–4844 thousand tons of avoided CO2eq. Such GHG reductions would be translated into approximately 0.5% of Iran's annual GHG emissions and would be considered a promising achievement given Iran's international GHGs reduction commitment, i.e., 4% reduction of anthropogenic GHGs emissions by 2030 below the business as usual scenario. Such findings could also be modeled for the other developing countries around the world where efficient MSW management is yet to be implemented.

AbstractThe recent rise in atmospheric methane (CH4) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models and top‐down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi‐model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better‐performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU‐ and TD‐based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year−1) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter‐site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site‐specific and ecosystem‐specific variabilities inferred from observations.

Abstract Improving energy supply efficiency and quality is regarded as a key pathway to shifting towards a fully sustainable energy system. To address the low efficiency and high emissions in the downstream oil industry caused by the problem of vertically integrated monopoly, the Chinese government is making an effort to promote a multiproduct pipeline network reform. The fundamental and indispensable step for this goal is the pipeline network interconnectivity. This paper quantifies the energy-environmental impacts of the pipeline network interconnectivity reform on China's downstream oil supply chain to 2030. An integrated framework is developed to obtain the detailed design-scale information required for assessment, introducing demand forecasting and demand reallocation into a pipeline network optimal planning model. The model is formulated as a fuzzy mixed integer linear programming that optimizes the infrastructure development scheme and supply chain operation plan simultaneously while taking into account demand uncertainty. The results show that, compared with the baseline, the pipeline interconnectivity reform could reduce yearly energy consumption and CO2 emissions by 9.7–19.8% and 12.5–17.9%, respectively. It is shown that this reform policy could overcome infrastructure constraints, increase pipeline utilization, and improve both energy and environmental performance. The proposed framework can be a theoretical guideline for policymakers within and beyond China.