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China's urban population will increase by 268 million from 2010 to 2030, with the consumption of a large number of resource‐intensive products. Quantitative analysis of the environmental impacts (water, energy and carbon) of urban agglomerations can make trade‐offs among water conservation, energy use, climate change mitigation, and urban development. In this study, a multi‐layer water‐energy‐carbon production path analysis (MWPPA) model is developed for identifying the key final demands, sectors and supply chain paths of the Pearl River Delta urban agglomeration (PUA). Results show that, water, energy and carbon‐emission intensities respectively reduced by 27.3%, 35.6% and 27.6% in 2015, compared to the levels in 2012. More than half of the water‐energy‐carbon (WEC) footprints are export‐driven, where Guangzhou, Shenzhen and Foshan dominate the WEC footprints of PUA. Results also disclose that Shenzhen is the main recipient of water‐energy, while Jiangmen and Huizhou are the main providers of water and energy, respectively. Policy makers are suggested that each industry actively integrate into global value chains in order to leverage its comparative advantage, and Huizhou should take full advantage of its fossil base to form a complete industry chain from the R&D end to the production end around the energy industry. Plain Language Summary Not only do urban areas consume large amounts of water and energy, they are also the specific implementation units of carbon reduction policies. The United Nations Sustainable Development goals (UN SDGs) make it clear that water conservation, energy access, climate change mitigation, and urbanization development are important parts of its agenda. As one of the most developed urban agglomerations in China, the Pearl River Delta urban agglomeration (PUA) is also the main consumer of water, energy and carbon (WEC). This study reveals that more than half of the WEC footprints are export‐driven, and Guangzhou, Shenzhen and other developed economies dominate the WEC footprints of PUA. Compared to 2012, the consumption intensity of WEC was reduced in 2015. The results also find that light industry and equipment manufacture play key roles in the WEC system. Results suggest that greener production needs to be adopted not only within but also outside of urban agglomerations, while individual cities need to actively promote the integration of each industry into global supply chains. Key Points A multi‐layer water‐energy‐carbon production path analysis model is developed Exports drive more than half of water, energy and carbon footprints in the Pearl River Delta In the Pearl River Delta, cities of Jiangmen and Huizhou supply the most water and energy, and Huizhou and Dongguan provide the most carbon

Water scarcity necessitates desalination technologies, yet their high energy demands and brine disposal challenges hinder sustainability. This research study evaluates the energy footprint and carbon emissions of thermal- and membrane-based desalination technologies, alongside Minimal/Zero Liquid Discharge (MLD/ZLD) frameworks, with a focus on renewable energy source (RES) integration. Data revealed stark contrasts: thermal-based technologies like osmotic evaporation (OE) and brine crystallizers (BCr) exhibit energy intensities of 80–100 kWh/m3 and 52–70 kWh/m3, respectively, with coal-powered carbon footprints reaching 72–100 kg CO2/m3. Membrane-based technologies, such as reverse osmosis (RO) (2–6 kWh/m3) and forward osmosis (FO) (0.8–13 kWh/m3), demonstrate lower emissions (1.8–11.7 kg CO2/m3 under coal). Transitioning to RES reduces emissions by 90–95%, exemplified by renewable energy-powered RO (0.1–0.3 kg CO2/m3). However, scalability barriers persist, including high capital costs, RES intermittency, and technological immaturity in emerging systems like osmotically assisted RO (OARO) and membrane distillation (MD). This research highlights RES-driven MLD/ZLD systems as pivotal for aligning desalination with global climate targets, urging innovations in energy storage, material robustness, and circular economy models to secure water resource resilience.

While quality of life (QOL) is the result of satisfying human needs, our current provision strategies result in global environmental degradation. To ensure sustainable QOL, we need to understand the environmental impact of human needs satisfaction. In this paper we deconstruct QOL, and apply the fundamental human needs framework developed by Max-Neef et al to calculate the carbon and energy footprints of subsistence, protection, creation, freedom, leisure, identity, understanding and participation. We find that half of global carbon emissions are driven by subsistence and protection. A similar amount are due to freedom, identity, creation and leisure together, whereas understanding and participation jointly account for less than 4% of global emissions. We use 35 objective and subjective indicators to evaluate human needs satisfaction and their associated carbon footprints across nations. We find that the relationship between QOL and environmental impact is more complex than previously identified through aggregated or single indicators. Satisfying needs such as protection, identity and leisure is generally not correlated with their corresponding footprints. In contrast, the likelihood of satisfying needs for understanding, creation, participation and freedom, increases steeply when moving from low to moderate emissions, and then stagnates. Most objective indicators show a threshold trend with respect to footprints, but most subjective indicators show no relationship, except for freedom and creation. Our study signals the importance of considering both subjective and objective satisfaction to assess QOL-impact relationships at the needs level. In this way, resources could be strategically invested where they strongly relate to social outcomes, and spared where non-consumption satisfiers could be more effective. Through this approach, decoupling human needs satisfaction from environmental damage becomes more attainable.

Non-technical summaryGlobal income inequality and energy consumption inequality are related. High-income households consume more energy than low-income ones, and for different purposes. Here, we explore the global household energy consumption implications of global income redistribution. We show that global income inequality shapes not only inequalities of energy consumption but the quantity and composition of overall energy demand. Our results call for the inclusion of income distribution into energy system models, as well as into energy and climate policy.Technical summaryDespite a rapidly growing number of studies on the relationship between inequality and energy, there is little research estimating the effect of income redistribution on energy demand. We contribute to this debate by proposing a simple but granular and data-driven model of the global income distribution and of global household energy consumption. We isolate the effect of income distribution on household energy consumption and move beyond the assumption of aggregate income–energy elasticities. First, we model expenditure as a function of income. Second, we determine budget shares of expenditure for a variety of products and services by employing product-granular income elasticities of demand. Subsequently, we apply consumption-based final energy intensities to product and services to obtain energy footprint accounts. Testing variants of the global income distribution, we find that the ‘energy costs’ of equity are small. Equitable and inequitable distributions of income, however, entail distinct structural change in energy system terms. In an equitable world, fewer people live in energy poverty and more energy is consumed for subsistence and necessities, instead of luxury and transport.Social media summaryEquality in global income shifts household energy footprints towards subsistence, while inequality shifts them towards transport and luxury.

In this study, the biomethane potential of five agricultural crop residues (ACRs) (rice straw, vegetable waste, maize straw, coffee husk and oil palm empty fruit bunches (OPEFB)) and five Fruit-Based Agro-Industrial Wastes (FBAIWs) (jackfruit straw, banana, orange, apple and pineapple peel waste) were evaluated. The carbon and energy balance for each waste was also theoretically modelled for two biogas conversion scenarios (anaerobic digestion (AD) with CHP or biogas upgrading). A standard biomethane potential test (BMP) was operated over 30 days at 37 °C. Specific methane potential (SMP) of FBAIWs was generally higher than that of the ACRs, except for vegetable waste. Vegetable waste was identified as having the highest SMP (0.420 m3 kg−1 volatile solids (VS)added). With respect to ACRs, OPEFB and coffee husk had the lowest SMP values of 0.185 and 0.181 m3 kg−1 VSadded, respectively. This was attributed to the higher lignin content of these wastes which can impact on biodegradation and subsequent biogas production. Theoretical estimations showed a positive energy balance for all wastes tested. In terms of exportable energy, apple peel waste was shown to have the highest exportable energy potential. The FBAIWs also exhibited greater emissions savings than ACRs (with the exception of vegetable waste). This study concluded that there is good potential to valorise these wastes using AD and that this could address the challenges of waste management and clean energy provision in Indonesia.

The link between energy use, social and environmental well-being is at the root of critical synergies between clean and affordable energy (SDG7) and other Sustainable Development Goals (SDGs). Household-level quantitative energy analyses enable better understanding regarding interconnections between the level and composition of energy use, and SDG achievement. This study examines the household-level energy footprints in Nepal, Vietnam, and Zambia. We calculate the footprints using multi-regional input-output with energy extensions based on International Energy Agency data. We propose an original perspective on the links between household final energy use and well-being, measured through access to safe water, health, education, sustenance, and modern fuels. In all three countries, households with high well-being show much lower housing energy use, due to a transition from inefficient biomass-based traditional fuels to efficient modern fuels, such as gas and electricity. We find that households achieving well-being have 60%-80% lower energy footprint of residential fuel use compared to average across the countries. We observe that collective provisioning systems in form of access to health centers, public transport, markets, and garbage disposal and characteristics linked to having solid shelter, access to sanitation, and minimum floor area are more important for the attainment of well-being than changes in income or total energy consumption. This is an important finding, contradicting the narrative that basic well-being outcomes require increased income and individual consumption of energy. Substantial synergies exist between the achievement of well-being at a low level of energy use and other SDGs linked to poverty reduction (encompassed in SDG1), health (SDG3), sanitation (SDG6), gender equality (SDG5), climate action and reduced deforestation (SDG 13 and SDG15) and inequalities (SDG10).

Current climate crisis makes the need for reducing carbon emissions more than evident. For this reason, renewable energy sources are expected to play a fundamental role. However, these sources are not controllable, but depend on the weather conditions. Therefore, green hydrogen (hydrogen produced from water electrolysis using renewable energies) is emerging as the key energy carrier to solve this problem. Although different properties of hydrogen have been widely studied, some key aspects such as the water and energy footprint, as well as the technological development and the regulatory framework of green hydrogen in different parts of the world have not been analysed in depth. This work performs a data-driven analysis of these three pillars: water and energy footprint, technological maturity, and regulatory framework of green hydrogen technology. Results will allow the evaluation of green hydrogen deployment, both the current situation and expectations. Regarding the water footprint, this is lower than that of other fossil fuels and competitive with other types of hydrogen, while the energy footprint is higher than that of other fuels. Additionally, results show that technological and regulatory framework for hydrogen is not fully developed and there is a great inequality in green hydrogen legislation in different regions of the world.

As a significant protein source for humans and animals, soybean (Glycine max) has experienced a fast growth with the rapid development of population and economy. Despite broad interest in energy consumption and CO2 emissions generated by soybean production, there are few impact-oriented water footprint assessments of soybean production. This study evaluates the fossil energy, carbon, and water footprints of China’s soybean production so that key environmental impacts can be identified. To provide reliable results for decision-making, uncertainty analysis is conducted based on the Monte Carlo model. Results show that the impact on climate change, ecosystem quality, human health, and resources is 3.33 × 103 kg CO2 eq (GSD2 = 1.87), 6.18 × 10−5 Species·yr (GSD2 = 1.81), 3.26 × 10−3 Disability-adjusted Life Years (GSD2 = 1.81), and 81.51 $ (GSD2 = 2.28), respectively. Freshwater ecotoxicity is the dominant contributor (77.69%) to the ecosystem quality category, while climate change (85.22%) is the dominant contributor to the human health category. Key factors analysis results show that diammonium phosphate and diesel, and on-site emissions, are the major contributors to the overall environmental burden of soybean production. Several policy recommendations are proposed, focusing on trade structure optimization, efficient resource use, and technological improvements. Such policy recommendations provide valuable insights to those decision-makers so that they can prepare appropriate mitigation policies.

With the urgent global need to limit warming to 2 °C as well as a localized need in our case study to address rising energy demand amid electrical and thermal network limitations, a critical examination of demand-side energy reductions and the concept of energy sufficiency is needed. This paper contributes to the sparse literature on bottom-up analysis by utilizing Iceland—a leader in renewable energy generation—as a case study to explore the socio-economic factors influencing energy footprints. Our findings reveal significant energy footprints across various consumption domains, particularly housing and mobility, influenced by income levels, urbanization, and lifestyle choices. The study highlights the paradox of a high renewable energy supply leading to potential misconceptions regarding abundant and low-cost energy, resulting in substantial energy consumption-related environmental impacts. Using detailed household consumption survey data, this research provides insights crucial for developing sustainable energy policies that not only target technological advancements but also address the need for a reduction in energy demand and a shift towards energy sufficiency. This work marks a contribution to the literature through the provision of a case study of low income inequality and high energy footprints in a highly renewable energy system context. Further, this work is useful for Icelandic and international policymakers to understand in such high-demand contexts which consumption domains would be most relevant for sufficiency policies. This comprehensive analysis opens pathways for future research to further explore the intersections of energy consumption, socio-economic factors, and well-being, offering a nuanced understanding necessary for crafting sufficiency and demand-side policies aimed at a sustainable energy future.

In this research, U.S. manufacturing activities' life cycle-based carbon and energy footprint impacts have been quantified, taking international trade linkages with the rest of the world into account. The U.S economy has been integrated into a multi-region input-output (MRIO) life cycle assessment framework where total of 40 major economies, including the USA, China, Russia, and others, plus the rest of the world (ROW) were modelled to assess global energy and carbon footprint impacts. Each country's economy is assumed to compromise 35 major industries based on the WIOD database classification. A total of 1435 (41 × 35 = 1435) industries has therefore been taken to represent the global structure of the world economy. The novelty of the approach is that the MRIO model has been developed in a stochastic fashion, plus global trade-linked uncertainties have also been taken into consideration. Top carbon emitting and energy consumer industries and countries have been analysed using data analytics and statistical modelling methods. The results show that the USA is the largest contributor to the total carbon footprint (CFP) and the total energy footprint (EFP) with 81.73% and 84%, respectively. Moreover, the agriculture/hunting forestry/fishing sector and the electricity/gas/water supply sectors dominate the overall U.S. carbon footprint, contributing 22% and 21.28%, respectively. The coke/refined petroleum/nuclear fuel sector has the largest share of the total energy footprint, with 47.9% of the total impacts.