• Energy Research

This spreadsheet contains the results for the article, "Meeting the costs of decarbonising industry – the potential effects on prices and competitiveness (a case study of the UK)". These include projected impacts for industrial process decarbonisation (costs, fuel use, residual emissions), for key years (2030, 2040, 2050), distributed in the following ways: - Directly allocated to industrial sector in which they occur - Shared between sectors in proportion to the share of GVA of each supply chain - Embodied in final products - Embodied in final products, aggregated to consumption patterns The source of the projections and the method to perform the distribution are described in detail in the associated article. Further relevant documentation may be found in the following resources. Cooper, S. J.G., Allen, S. R., Gailani, A., Norman, J. B., Owen, A., Barrett, J., and Taylor, P., 2024. Meeting the costs of decarbonising industry – The potential effects on prices and competitiveness (a case study of the UK). Energy Policy, 184, 113904. Available from: https://doi.org/10.1016/j.enpol.2023.113904. For details of the methods used, please see the associated journal article.

This work considers the potential reduction in the carbon dioxide emissions associated with the operation of Air Source Heat Pump which could be achieved by using demand side management. In order to achieve significant reductions in carbon dioxide emissions, it is widely envisioned that electrification of the heating sector will need to be combined with decarbonisation of the electrical supply. By influencing the times at when electric heat pumps operate such that they coincide more with electricity generation which has a low marginal carbon emissions factor, it has been suggested that these emissions could be reduced further. In order to investigate this possibility, models of the UK electrical grid based on scenarios for 2020 to 2050 have been combined with a dynamic model of an air source heat pump unit and thermal models of a population of dwellings. The performance and carbon dioxide emissions associated with the heat pumps are compared both with and without demand side management interventions intended to give preference to operation when the marginal emissions factor of the electricity being generated is low. It is found that these interventions are unlikely to be effective at achieving further reductions in emissions. A reduction of around 3% was observed in scenarios based around 2035 but in other scenarios the reduction was insignificant. In the scenarios with high wind generation (2050), the DSM scheme considered here tends to improve thermal comfort (with minimal increases in emissions) rather than achieving a decrease in emissions. The reasons for this are discussed and further recommendations are made.

Abstract Plant operators and policy makers frequently use energy benchmarking to assess the potential for reducing energy consumption from industrial plants. As benchmarking studies require considerable resources and the cooperation of plant operators it is tempting to try to merge or compare data from different studies. This paper reviews published benchmarks and energy-saving estimates from the paper and pulp industries to explore how comparable data from independent studies are. A literature review was conducted which identified that benchmarks were either produced through a top-down process using annual production and fuel consumption data or through a bottom-up process from process-level data. It was concluded that top-down benchmarks are useful in measuring national trends but are of little value to individual plants. For common process such as Kraft pulp production it is possible to compare values from different studies but only if sufficient information is given in the original studies to confirm that their scope is identical. However, it is unlikely that improvement rates in energy use can be inferred from the difference between studies that use different sources, as the degree of disagreement between contemporary studies is of the same order as the identified potential energy savings. Benchmarking studies were found to provide good summaries of potential technological improvements although there is some inconsistency in estimations of potential impacts.

This dataset contains data, analysis and results generated in research reported in "Energy saving potential of high temperature heat pumps in the UK Food and Drink sector" in Energy Procedia and presented at the International Conference on Sustainable Energy & Resource Use in Food Chains (17-19 October 2018, Paphos, Cyprus). This includes performance data for heat pumps, parameters and calculations for selected dairy processes, energy use data for the UK Food and Drink sector and calculation steps used in the analysis. The heat pump performance data consists of the nominal Coefficient of Performance (COP) that can be achieved at specified temperature conditions by several high-temperature heat pumps (HTHPs) that are considered representative for the study. The dairy processes selected are pasteurisation of liquid milk, cheese production, yogurt production, milk drying and cleaning in place. For each process, a representative diagram is provided and temperature bounds for each sub-process are used to calculate the COP that the HTHPs would achieve. UK air temperature data is provided and binned into seven 5K bands to enable these calculations. Data on the relative energy uses within the dairy processes (from the Useable Energy Database and other referenced sources) are used with these COP results, to estimate the overall energy savings that are possible. This is repeated at a more aggregated level for the UK Food and Drink sector. The GHG and fuel cost implications of these energy savings are presented in table and graphical format. The dairy process data was collected through literature review. The heat pump data was based on expert review of published test data. The results were based on calculations described in spreadsheet. Please see the references in the spreadsheet for the sources of the background data used. Spreadsheet is in Microsoft Excel 2007+ format.

Abstract The greenhouse gas emissions associated with bioenergy are often temporally dispersed and can be a mixture of long-term forcers (such as carbon dioxide) and short-term forcers (such as methane). These factors affect the timing and magnitude of climate-change impacts associated with bioenergy in ways that cannot be clearly communicated with a single metric. This is critical as key comparisons that determine incentives and policy for bioenergy are based upon climate-change impacts expressed as carbon dioxide equivalent calculated with GWP100. This paper explores these issues further and presents a spreadsheet tool to facilitate quick assessment of these temporal effects. The potential effect of (i) a mix of GHGs and (ii) emissions that change with time are illustrated through two case studies. In case study 1, variations in the mix of greenhouse gases mean that apparently similar impacts after 100-years, mask radically different impacts before then. In case study 2, variations in the timing of emissions cause their climate-change impacts (integrated radiative-forcing and temperature change) to differ from the impacts that an emissions-balance would suggest. The effect of taking alternative approaches to considering “CO2-equivalence” are also assessed. In both cases, a single metric for climate-change effects was found to be wanting. A simple tool has been produced to help practitioners evaluate whether this is the case for any given system. If complex dynamics are apparent, it is recommended that additional metrics, more detailed inventory, or full time-series impact results are used in order to accurately communicate these climate-change effects.

La bioénergie est largement incluse dans les stratégies énergétiques pour son potentiel d'atténuation des GES. Les technologies de la bioénergie devront probablement être déployées à grande échelle pour atteindre les objectifs de décarbonation et, par conséquent, la biomasse devra être de plus en plus cultivée/mobilisée. Les risques de durabilité associés à la bioénergie peuvent s'intensifier avec l'augmentation du déploiement et lorsque les matières premières proviennent du commerce international. Cette recherche applique le modèle d'indicateur de durabilité de la bioéconomie (BSIM) pour cartographier et analyser la performance de la bioénergie sur 126 questions de durabilité, en évaluant 16 études de cas de bioénergie qui reflètent l'étendue des ressources de biomasse, des technologies, des vecteurs énergétiques et des bioproduits. La recherche trouve des tendances communes en matière de performance de durabilité dans tous les projets qui peuvent éclairer la politique et la prise de décision en matière de bioénergie. Les avantages potentiels en matière de durabilité sont identifiés pour les personnes (emplois, compétences, revenus, accès à l'énergie) ; pour le développement (économie, énergie, utilisation des terres) ; pour les systèmes naturels (sol, métaux lourds) ; et pour le changement climatique (émissions, carburants). En outre, des tendances cohérentes des risques de durabilité où une attention particulière est nécessaire pour assurer la viabilité des projets de bioénergie, y compris pour les infrastructures, la mobilisation des matières premières, la techno-économie et les stocks de carbone. L'atténuation des émissions peut être un objectif principal pour la bioénergie, cette recherche révèle que les projets de bioénergie peuvent offrir des avantages potentiels bien au-delà des émissions - il existe un argument en faveur du soutien de projets basés sur les services écosystémiques et/ou la stimulation économique qu'ils peuvent fournir. Compte tenu également de la vaste dynamique et des caractéristiques des projets de bioénergie, une approche rigide de l'évaluation de la durabilité peut être incompatible. L'octroi de « crédits » sur un plus large éventail d'indicateurs de durabilité, en plus d'exiger des performances minimales dans des domaines clés, peut être plus efficace pour assurer la durabilité de la bioénergie. La bioenergía está ampliamente incluida en las estrategias energéticas por su potencial de mitigación de GEI. Es probable que las tecnologías de bioenergía tengan que implementarse a escala para cumplir con los objetivos de descarbonización y, en consecuencia, la biomasa tendrá que crecer/movilizarse cada vez más. Los riesgos de sostenibilidad asociados con la bioenergía pueden intensificarse con el aumento del despliegue y donde las materias primas se obtienen a través del comercio internacional. Esta investigación aplica el Modelo de Indicadores de Sostenibilidad de la Bioeconomía (BSIM) para mapear y analizar el rendimiento de la bioenergía en 126 temas de sostenibilidad, evaluando 16 estudios de casos de bioenergía que reflejan la amplitud de los recursos de biomasa, las tecnologías, los vectores energéticos y los bioproductos. La investigación encuentra tendencias comunes en el desempeño de la sostenibilidad en todos los proyectos que pueden informar la política de bioenergía y la toma de decisiones. Se identifican posibles beneficios de sostenibilidad para las personas (empleos, habilidades, ingresos, acceso a la energía); para el desarrollo (economía, energía, utilización de la tierra); para los sistemas naturales (suelo, metales pesados) y para el cambio climático (emisiones, combustibles). Además, las tendencias consistentes de los riesgos de sostenibilidad donde se requiere un enfoque para garantizar la viabilidad de los proyectos de bioenergía, incluida la infraestructura, la movilización de materias primas, la tecnoeconomía y las reservas de carbono. La mitigación de emisiones puede ser un objetivo principal para la bioenergía, esta investigación encuentra que los proyectos de bioenergía pueden proporcionar beneficios potenciales mucho más allá de las emisiones: existe un argumento para apoyar proyectos basados en los servicios ecosistémicos y/o la estimulación económica que pueden brindar. También dada la amplia dinámica y características de los proyectos de bioenergía, un enfoque rígido de evaluación de la sostenibilidad puede ser incompatible. La concesión de "créditos" a través de una gama más amplia de indicadores de sostenibilidad, además de requerir rendimientos mínimos en áreas clave, puede ser más eficaz para garantizar la sostenibilidad de la bioenergía. Bioenergy is widely included in energy strategies for its GHG mitigation potential. Bioenergy technologies will likely have to be deployed at scale to meet decarbonisation targets, and consequently biomass will have to be increasingly grown/mobilised. Sustainability risks associated with bioenergy may intensify with increasing deployment and where feedstocks are sourced through international trade. This research applies the Bioeconomy Sustainability Indicator Model (BSIM) to map and analyse the performance of bioenergy across 126 sustainability issues, evaluating 16 bioenergy case studies that reflect the breadth of biomass resources, technologies, energy vectors and bio-products. The research finds common trends in sustainability performance across projects that can inform bioenergy policy and decision making. Potential sustainability benefits are identified for People (jobs, skills, income, energy access); for Development (economy, energy, land utilisation); for Natural Systems (soil, heavy metals), and; for Climate Change (emissions, fuels). Also, consistent trends of sustainability risks where focus is required to ensure the viability of bioenergy projects, including for infrastructure, feedstock mobilisation, techno-economics and carbon stocks. Emission mitigation may be a primary objective for bioenergy, this research finds bioenergy projects can provide potential benefits far beyond emissions - there is an argument for supporting projects based on the ecosystem services and/or economic stimulation they may deliver. Also given the broad dynamics and characteristics of bioenergy projects, a rigid approach of assessing sustainability may be incompatible. Awarding 'credit' across a broader range of sustainability indicators in addition to requiring minimum performances in key areas, may be more effective at ensuring bioenergy sustainability. يتم تضمين الطاقة الحيوية على نطاق واسع في استراتيجيات الطاقة لإمكانات التخفيف من غازات الدفيئة. من المرجح أن يتم نشر تقنيات الطاقة الحيوية على نطاق واسع لتحقيق أهداف إزالة الكربون، وبالتالي سيتعين زيادة نمو/تعبئة الكتلة الحيوية. قد تزداد مخاطر الاستدامة المرتبطة بالطاقة الحيوية مع زيادة الانتشار وحيث يتم الحصول على المواد الأولية من خلال التجارة الدولية. يطبق هذا البحث نموذج مؤشر استدامة الاقتصاد الحيوي (BSIM) لرسم وتحليل أداء الطاقة الحيوية عبر 126 قضية استدامة، وتقييم 16 دراسة حالة للطاقة الحيوية تعكس اتساع موارد الكتلة الحيوية والتقنيات وناقلات الطاقة والمنتجات الحيوية. وجد البحث اتجاهات مشتركة في أداء الاستدامة عبر المشاريع التي يمكن أن تسترشد بها سياسة الطاقة الحيوية وصنع القرار. يتم تحديد فوائد الاستدامة المحتملة للناس (الوظائف والمهارات والدخل والوصول إلى الطاقة) ؛ للتنمية (الاقتصاد والطاقة واستخدام الأراضي) ؛ للنظم الطبيعية (التربة والمعادن الثقيلة)، و ؛ لتغير المناخ (الانبعاثات والوقود). أيضًا، الاتجاهات المتسقة لمخاطر الاستدامة حيث يكون التركيز مطلوبًا لضمان استمرارية مشاريع الطاقة الحيوية، بما في ذلك البنية التحتية وتعبئة المواد الوسيطة والاقتصاد التقني ومخزونات الكربون. قد يكون تخفيف الانبعاثات هدفًا أساسيًا للطاقة الحيوية، ويجد هذا البحث أن مشاريع الطاقة الحيوية يمكن أن توفر فوائد محتملة تتجاوز الانبعاثات - هناك حجة لدعم المشاريع القائمة على خدمات النظام الإيكولوجي و/أو التحفيز الاقتصادي الذي قد تقدمه. أيضًا نظرًا للديناميكيات والخصائص الواسعة لمشاريع الطاقة الحيوية، قد يكون النهج الصارم لتقييم الاستدامة غير متوافق. قد يكون منح "الائتمان" عبر مجموعة أوسع من مؤشرات الاستدامة بالإضافة إلى طلب الحد الأدنى من الأداء في المجالات الرئيسية أكثر فعالية في ضمان استدامة الطاقة الحيوية.