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Biomethane production from processed industrial food waste (IFW) in admixture with sewage sludge (primary and waste activated sludge: PS and WAS) was evaluated at a range of C:N ratios using a standard biochemical methane potential (BMP) test. IFW alone had a C:N of 30 whereas for WAS it was 5.4 and thus the C:N ratio of the blends fell in that range. Increasing the IFW content in mix improves the methane potential by increasing both the cumulative biogas production and the rate of methane production. Optimum methane yield 239 mL/g VSremoved occurred at a C:N ratio of 15 which was achieved with a blend containing 11 percent (w/w) IFW. As the fraction of IFW in the blend increased, volatile solids (VS) destruction was increased and this led to a reduction in methane yield and amount of production. The highest destruction of volatile solids of 93 percent was achieved at C:N of 20 followed by C:N 30 and 15. A shortened BMP test is adequate for evaluating optimum admixtures.

SummaryEnvironmentally extended multiregional input‐output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental‐Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3—a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply‐use tables (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.

Results-based financing (RBF) programmes in the clean cooking sector have gained increasing donor interest over the last decade. Although the risks and advantages of RBF have been discussed quite extensively for other sectors, especially health services, there is limited research-documented experience of its application to clean cooking. Due to the sheer scale of the important transition from ‘dirty’ to clean cooking for the 4 billion people who lack access, especially in the Global South, efficient and performance-proven solutions are urgently required. This paper, undertaken as part of the work of the UKAid-funded Modern Energy Cooking Services (MECS) programme, aims to close an important research gap by reviewing evidence-based support mechanisms and documenting essential experiences from previous and ongoing RBF programmes in the clean cooking and other sectors. On this basis, the paper derives key strategic implications and learning lessons for the global scaling of RBF programmes and finds that qualitative key performance indicators such as consumer acceptance as well as longer-term monitoring are critical long-term success factors for RBF to ensure the continued uptake and use of clean cooking solutions (CCS), however securing the inclusion of these indicators within programmes remains challenging. Finally, by discussing the opportunities for the evolution of RBF into broader impact funding programmes and the integration of energy access and clean cooking strategies through multi-sector approaches, the paper illustrates potential steps to enhance the impact of RBF in this sector in the future.

Green ammonia is gaining momentum as a globally significant technology for deep decarbonisation. In this thesis, several models are developed across chemical, techno-economic, and energy system modelling disciplines to explore the future role of green ammonia. First, standalone models of production (i.e., power-to-ammonia) and re-electrification (i.e., ammonia-to-power) are developed and compared to competing technologies. Second, these models are integrated into a planning and dispatch energy system model (ESM) of India to 2050. The ESM has several novel additions including the sector coupling of hydrogen and ammonia, multiple years of granular weather data, and learning-curve-based technology cost forecasts. India is chosen as an ideal case study given its globally unmatched demand growth in all three relevant sectors: electricity, green hydrogen, and green ammonia. The projected electricity demands for green hydrogen and ammonia production account for 25% of the total Indian electricity demand in 2050, underscoring the transformational potential that green hydrogen and ammonia sector coupling can have on the Indian energy system. The results of the state-of-the-art ESM highlight synergistic effects of hydrogen and ammonia sector coupling with the power system. The least-cost system employs seasonal green ammonia production paired with up to 40 million tonnes (i.e., 200 TWh) of ammonia storage, as well as some re-electrification via gas turbines. Sector coupling reduces system curtailment, addresses challenges of long-duration storage, and improves system resilience to interannual weather variations. While India is a crucial case study from a global decarbonisation perspective, the methodology and findings are generally applicable, and it is the aim of this work to motivate and accelerate the wider research community into considering the potential impacts of green ammonia sector coupling on electricity grid design. Finally, this work highlights strategic technology development direction for ammonia producers and gas turbine manufacturers, as well as implications for policymakers.

Abstract Decentralised energy in the UK is rare. Cities in the north of England however lead the UK in terms of sustainable, low-carbon, local/district heating, through the implementation of combined-heat-and-power (CHP) facilities; substantial schemes are installed in several cities, including Barnsley and Sheffield. This paper presents the results from extensive experimental and theoretical feasibility studies, in which the merits of these were explored. Barnsley has a number of biomass-fuelled community energy generators, where pollutant monitoring and mathematical modelling were conducted to assess combustion characteristics and overall system performance. Measured pollutant levels were within the relative emission limits, though emission concentrations (CO, CO2, NO and particles) in the flue gas from the coal boiler were higher than the wood pellet boiler. Sheffield already has a citywide district energy network, centred around a sustainably-sourced waste-to-energy facility; an expansion of this scheme was investigated here. This focuses mainly on the link to a 30 MW wood-fired CHP plant, which could be a significant provider of additional thermal capacity (low-grade heat) to an expanded network. Through identifying heat sources and sinks – potential suppliers and end-users – key areas were identified where a connection to the heat network would be feasible.

AbstractMany developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government’s five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China’s long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced.

District heating is a network of pipes through which heat is delivered from a centralised source. It is expected to play an important role in the decarbonisation of the energy sector in the coming years. In district heating, heat is traditionally generated through fossil fuels, often with combined heat and power (CHP) units. However, increasingly, waste heat is being used as a low carbon alternative, either directly or, for low temperature sources, via a heat pump. The design of district heating often has competing objectives: the need for inexpensive energy and meeting low carbon targets. In addition, the planning of district heating schemes is subject to multiple sources of uncertainty such as variability in heat demand and energy prices. This paper proposes a decision support tool to analyse and compare system designs for district heating under uncertainty using stochastic ordering (dominance). Contrary to traditional uncertainty metrics that provide statistical summaries and impose total ordering, stochastic ordering is a partial ordering and operates with full probability distributions. In our analysis, we apply the orderings in the mean and dispersion to the waste heat recovery problem in Brunswick, Germany.