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The authors are all devoted energy system and sustainability transformation scholars, who collaborate regularly and actively at global and local levels to advance the knowledge space of demand-side solutions and policies. They are members of a growing bottom-up initiative, the Energy Demand Changes Induced by Technological and Social Innovations (EDITS) network (https://iiasa.ac.at/projects/edits), which builds on various research disciplines to facilitate advances in modeling, data compilation, and analysis of the scope and breadth of the potential contributions of demand-side solutions for climate change mitigation, improved wellbeing for all, and sustainability, complementing supply-side solutions for decarbonizing the energy and material systems.

The authors are all devoted energy system and sustainability transformation scholars, who collaborate regularly and actively at global and local levels to advance the knowledge space of demand-side solutions and policies. They are members of a growing bottom-up initiative, the Energy Demand Changes Induced by Technological and Social Innovations (EDITS) network (https://iiasa.ac.at/projects/edits), which builds on various research disciplines to facilitate advances in modeling, data compilation, and analysis of the scope and breadth of the potential contributions of demand-side solutions for climate change mitigation, improved wellbeing for all, and sustainability, complementing supply-side solutions for decarbonizing the energy and material systems.

The authors are all devoted energy system and sustainability transformation scholars, who collaborate regularly and actively at global and local levels to advance the knowledge space of demand-side solutions and policies. They are members of a growing bottom-up initiative, the Energy Demand Changes Induced by Technological and Social Innovations (EDITS) network (https://iiasa.ac.at/projects/edits), which builds on various research disciplines to facilitate advances in modeling, data compilation, and analysis of the scope and breadth of the potential contributions of demand-side solutions for climate change mitigation, improved wellbeing for all, and sustainability, complementing supply-side solutions for decarbonizing the energy and material systems.

Developing transformative pathways for industry’s compliance with international climate targets requires model-based insights on how supply- and demand-side measures affect industry, material cycles, global supply chains, socio-economic activities and service provisioning supporting societal wellbeing. Herein, we review the recent literature modelling the industrial system for Low Energy and Materials Demand (LEMD) futures, resulting in lowered environmental pressures without relying on negative emissions. We identify 77 innovative studies drawing on nine distinct industry modelling traditions and critically assess system definitions and scopes, biophysical and thermodynamic consistency, granularity and heterogeneity, and operationalization of demand and service provision. We find large potentials of combined supply- and demand-side measures to reduce current economy-wide material use by -56%, energy use by -40 to -60%, and GHG emissions by -70% to net-zero. We call for strengthening interdisciplinary collaborations between industry modelling traditions and demand-side research, to produce more insightful scenarios and discuss research challenges and recommendations.

Developing transformative pathways for industry’s compliance with international climate targets requires model-based insights on how supply- and demand-side measures affect industry, material cycles, global supply chains, socio-economic activities and service provisioning supporting societal wellbeing. Herein, we review the recent literature modelling the industrial system for Low Energy and Materials Demand (LEMD) futures, resulting in lowered environmental pressures without relying on negative emissions. We identify 77 innovative studies drawing on nine distinct industry modelling traditions and critically assess system definitions and scopes, biophysical and thermodynamic consistency, granularity and heterogeneity, and operationalization of demand and service provision. We find large potentials of combined supply- and demand-side measures to reduce current economy-wide material use by -56%, energy use by -40 to -60%, and GHG emissions by -70% to net-zero. We call for strengthening interdisciplinary collaborations between industry modelling traditions and demand-side research, to produce more insightful scenarios and discuss research challenges and recommendations.

Developing transformative pathways for industry’s compliance with international climate targets requires model-based insights on how supply- and demand-side measures affect industry, material cycles, global supply chains, socio-economic activities and service provisioning supporting societal wellbeing. Herein, we review the recent literature modelling the industrial system for Low Energy and Materials Demand (LEMD) futures, resulting in lowered environmental pressures without relying on negative emissions. We identify 77 innovative studies drawing on nine distinct industry modelling traditions and critically assess system definitions and scopes, biophysical and thermodynamic consistency, granularity and heterogeneity, and operationalization of demand and service provision. We find large potentials of combined supply- and demand-side measures to reduce current economy-wide material use by -56%, energy use by -40 to -60%, and GHG emissions by -70% to net-zero. We call for strengthening interdisciplinary collaborations between industry modelling traditions and demand-side research, to produce more insightful scenarios and discuss research challenges and recommendations.

Mitigation solutions are often evaluated in terms of costs and greenhouse gas reduction potentials, missing out on the consideration of direct effects on human well-being. Here, we systematically assess the mitigation potential of demand-side options categorized into avoid, shift and improve, and their human well-being links. We show that these options, bridging socio-behavioural, infrastructural and technological domains, can reduce counterfactual sectoral emissions by 40–80% in end-use sectors. Based on expert judgement and an extensive literature database, we evaluate 306 combinations of well-being outcomes and demand-side options, finding largely beneficial effects in improvement in well-being (79% positive, 18% neutral and 3% negative), even though we find low confidence on the social dimensions of well-being. Implementing such nuanced solutions is based axiomatically on an understanding of malleable rather than fixed preferences, and procedurally on changing infrastructures and choice architectures. Results demonstrate the high mitigation potential of demand-side mitigation options that are synergistic with well-being.

Mitigation solutions are often evaluated in terms of costs and greenhouse gas reduction potentials, missing out on the consideration of direct effects on human well-being. Here, we systematically assess the mitigation potential of demand-side options categorized into avoid, shift and improve, and their human well-being links. We show that these options, bridging socio-behavioural, infrastructural and technological domains, can reduce counterfactual sectoral emissions by 40–80% in end-use sectors. Based on expert judgement and an extensive literature database, we evaluate 306 combinations of well-being outcomes and demand-side options, finding largely beneficial effects in improvement in well-being (79% positive, 18% neutral and 3% negative), even though we find low confidence on the social dimensions of well-being. Implementing such nuanced solutions is based axiomatically on an understanding of malleable rather than fixed preferences, and procedurally on changing infrastructures and choice architectures. Results demonstrate the high mitigation potential of demand-side mitigation options that are synergistic with well-being.

Mitigation solutions are often evaluated in terms of costs and greenhouse gas reduction potentials, missing out on the consideration of direct effects on human well-being. Here, we systematically assess the mitigation potential of demand-side options categorized into avoid, shift and improve, and their human well-being links. We show that these options, bridging socio-behavioural, infrastructural and technological domains, can reduce counterfactual sectoral emissions by 40–80% in end-use sectors. Based on expert judgement and an extensive literature database, we evaluate 306 combinations of well-being outcomes and demand-side options, finding largely beneficial effects in improvement in well-being (79% positive, 18% neutral and 3% negative), even though we find low confidence on the social dimensions of well-being. Implementing such nuanced solutions is based axiomatically on an understanding of malleable rather than fixed preferences, and procedurally on changing infrastructures and choice architectures. Results demonstrate the high mitigation potential of demand-side mitigation options that are synergistic with well-being.

Fully decarbonizing global industry is essential to achieving climate stabilization, and reaching net zero greenhouse gas emissions by 2050–2070 is necessary to limit global warming to 2 °C. This paper assembles and evaluates technical and policy interventions, both on the supply side and on the demand side. It identifies measures that, employed together, can achieve net zero industrial emissions in the required timeframe. Key supply-side technologies include energy efficiency (especially at the system level), carbon capture, electrification, and zero-carbon hydrogen as a heat source and chemical feedstock. There are also promising technologies specific to each of the three top-emitting industries: cement, iron & steel, and chemicals & plastics. These include cement admixtures and alternative chemistries, several technological routes for zero-carbon steelmaking, and novel chemical catalysts and separation technologies. Crucial demand-side approaches include material-efficient design, reductions in material waste, substituting low-carbon for high-carbon materials, and circular economy interventions (such as improving product longevity, reusability, ease of refurbishment, and recyclability). Strategic, well-designed policy can accelerate innovation and provide incentives for technology deployment. High-value policies include carbon pricing with border adjustments or other price signals; robust government support for research, development, and deployment; and energy efficiency or emissions standards. These core policies should be supported by labeling and government procurement of low-carbon products, data collection and disclosure requirements, and recycling incentives. In implementing these policies, care must be taken to ensure a just transition for displaced workers and affected communities. Similarly, decarbonization must complement the human and economic development of low- and middle-income countries.

Fully decarbonizing global industry is essential to achieving climate stabilization, and reaching net zero greenhouse gas emissions by 2050–2070 is necessary to limit global warming to 2 °C. This paper assembles and evaluates technical and policy interventions, both on the supply side and on the demand side. It identifies measures that, employed together, can achieve net zero industrial emissions in the required timeframe. Key supply-side technologies include energy efficiency (especially at the system level), carbon capture, electrification, and zero-carbon hydrogen as a heat source and chemical feedstock. There are also promising technologies specific to each of the three top-emitting industries: cement, iron & steel, and chemicals & plastics. These include cement admixtures and alternative chemistries, several technological routes for zero-carbon steelmaking, and novel chemical catalysts and separation technologies. Crucial demand-side approaches include material-efficient design, reductions in material waste, substituting low-carbon for high-carbon materials, and circular economy interventions (such as improving product longevity, reusability, ease of refurbishment, and recyclability). Strategic, well-designed policy can accelerate innovation and provide incentives for technology deployment. High-value policies include carbon pricing with border adjustments or other price signals; robust government support for research, development, and deployment; and energy efficiency or emissions standards. These core policies should be supported by labeling and government procurement of low-carbon products, data collection and disclosure requirements, and recycling incentives. In implementing these policies, care must be taken to ensure a just transition for displaced workers and affected communities. Similarly, decarbonization must complement the human and economic development of low- and middle-income countries.

Contains fulltext : 207817.pdf (preprint version ) (Open Access)

Contains fulltext : 207817.pdf (preprint version ) (Open Access)

Contains fulltext : 207817.pdf (preprint version ) (Open Access)

Data centers are energy intensive buildings that have grown in size and number to meet the increasing demands of a digital economy. This paper presents a bottom-up model to estimate data center electricity demand in the United States over a 20 year period and examines observed and projected electricity use trends in the context of changing data center operations. Results indicate a rapidly increasing electricity demand at the turn of the century that has significantly subsided to a nearly steady annual electricity use of about 70 billion kWh in recent years. While data center workloads continue to grow exponentially, comparable increases in electricity demand have been avoided through the adoption of key energy efficiency measures and a shift towards large cloud-based service providers. Alternative projections from the model illustrate the wide range in potential electricity that could be consumed to support data centers, with the US data center workload demand estimated for 2020 requiring a total electricity use that varies by about 135 billion kWh, depending on the adoption rate of efficiency measures during this decade. While recent improvements in data center energy efficiency have been a success, the growth of data center electricity use beyond 2020 is uncertain, as modeled trends indicate that the efficiency measures of the past may not be enough for the data center workloads of the future. The results show that successful stabilization of data center electricity will require new innovations in data center efficiency to further decouple electricity demand from the ever-growing demand for data center services.

Carbon capture (CC) technology is receiving increasing attention as a critical technology for climate change mitigation. Most previous studies focus on the application of CC technology in the power generation sector, while fewer studies have analyzed applications in the refining industry, which is one of the largest greenhouse gas (GHG) emissions sources in the U.S. industrial sector. Unlike the power generation sector, the refining industry has highly distributed CO2 emission sources. In this paper, bottom-up modeling and techno-economic analysis approaches are integrated to quantify the national CO2 emission reduction potential and costs of three types of CC technologies applied to U.S. refineries: (1) pre-combustion, (2) post-combustion, and (3) oxyfuel-combustion. Two scenarios are developed to compare different design strategies for CC systems; one is a distributed design scenario for post-combustion technology, the other is a centralized design scenario for pre-combustion and oxyfuel-combustion technology. The results of the two scenarios are compared, and the trade-offs between different design strategies are highlighted. The results shown in this study provide an intuitive and quantitative understanding of the potential of CC technology to reduce CO2 emissions from the U.S. refining industry. Such information is helpful to policymakers, oil companies, and energy/environmental analysts for strategic planning and systems design to manage future CO2 emissions of refineries.

Carbon capture (CC) technology is receiving increasing attention as a critical technology for climate change mitigation. Most previous studies focus on the application of CC technology in the power generation sector, while fewer studies have analyzed applications in the refining industry, which is one of the largest greenhouse gas (GHG) emissions sources in the U.S. industrial sector. Unlike the power generation sector, the refining industry has highly distributed CO2 emission sources. In this paper, bottom-up modeling and techno-economic analysis approaches are integrated to quantify the national CO2 emission reduction potential and costs of three types of CC technologies applied to U.S. refineries: (1) pre-combustion, (2) post-combustion, and (3) oxyfuel-combustion. Two scenarios are developed to compare different design strategies for CC systems; one is a distributed design scenario for post-combustion technology, the other is a centralized design scenario for pre-combustion and oxyfuel-combustion technology. The results of the two scenarios are compared, and the trade-offs between different design strategies are highlighted. The results shown in this study provide an intuitive and quantitative understanding of the potential of CC technology to reduce CO2 emissions from the U.S. refining industry. Such information is helpful to policymakers, oil companies, and energy/environmental analysts for strategic planning and systems design to manage future CO2 emissions of refineries.

Data centers are energy intensive buildings that have grown in size and number to meet the increasing demands of a digital economy. This paper presents a bottom-up model to estimate data center electricity demand in the United States over a 20 year period and examines observed and projected electricity use trends in the context of changing data center operations. Results indicate a rapidly increasing electricity demand at the turn of the century that has significantly subsided to a nearly steady annual electricity use of about 70 billion kWh in recent years. While data center workloads continue to grow exponentially, comparable increases in electricity demand have been avoided through the adoption of key energy efficiency measures and a shift towards large cloud-based service providers. Alternative projections from the model illustrate the wide range in potential electricity that could be consumed to support data centers, with the US data center workload demand estimated for 2020 requiring a total electricity use that varies by about 135 billion kWh, depending on the adoption rate of efficiency measures during this decade. While recent improvements in data center energy efficiency have been a success, the growth of data center electricity use beyond 2020 is uncertain, as modeled trends indicate that the efficiency measures of the past may not be enough for the data center workloads of the future. The results show that successful stabilization of data center electricity will require new innovations in data center efficiency to further decouple electricity demand from the ever-growing demand for data center services.

Implementation of carbon capture and sequestration (CCS) will increase water demand due to the cooling water requirements of CO2 capture equipment. If the captured CO2 is injected into saline aquifers for sequestration, brine may be extracted to manage the aquifer pressure, and can be desalinated to provide additional freshwater supply. We conduct a geospatial analysis to determine how CCS may affect local water supply and demand across the contiguous United States. We calculate baseline indices for each county in the year 2005, and project future water supply and demand with and without CCS through 2030. We conduct sensitivity analyses to identify the system parameters that most significantly affect water balance. Water supply changes due to inter-annual variability and projected climate change are overwhelmingly the most significant sources of variation. CCS can have strong local effects on water supply and demand, but overall it has a modest effect on water balances.

Implementation of carbon capture and sequestration (CCS) will increase water demand due to the cooling water requirements of CO2 capture equipment. If the captured CO2 is injected into saline aquifers for sequestration, brine may be extracted to manage the aquifer pressure, and can be desalinated to provide additional freshwater supply. We conduct a geospatial analysis to determine how CCS may affect local water supply and demand across the contiguous United States. We calculate baseline indices for each county in the year 2005, and project future water supply and demand with and without CCS through 2030. We conduct sensitivity analyses to identify the system parameters that most significantly affect water balance. Water supply changes due to inter-annual variability and projected climate change are overwhelmingly the most significant sources of variation. CCS can have strong local effects on water supply and demand, but overall it has a modest effect on water balances.

The U.S. EPA is in the final stages of promulgating regulations to reduce CO2 emissions from the electricity generating industry. A major component of EPA's regulatory strategy targets improvements to power plant operating efficiencies. As the EPA expands regulatory requirements to other industries, including petroleum refining, it is likely that plant efficiency improvements will be critical to achieving CO2 emission reductions. This paper identifies efficiency improvement measures applicable to refining, and quantifies potential cost of conserved energy for these measures. Analysis is at the U.S. petroleum refining sector national-level employing an aggregated notional refinery model (NRM), with the aim of estimating the efficacy of efficiency improvements for reducing emissions. Using this method, roughly 1500 petajoules per year (PJ/yr) of plant fuel savings and 650 gigawatt-hour per year (GWh/yr) of electricity savings (representing 54% and 2% of U.S. refining industry consumption, respectively) are potentially cost-effective. This equates to a potential 85 Mt-CO2/yr reduction. An additional 458 PJ/yr fuel reduction and close to 2750 GWh/yr of electricity reduction (27 Mt-CO2/yr) are not cost-effective at prevailing natural gas market prices. Results are presented as a supply-curve ordering measures from low to high cost of fuel savings versus cumulative energy reduction.

The U.S. EPA is in the final stages of promulgating regulations to reduce CO2 emissions from the electricity generating industry. A major component of EPA's regulatory strategy targets improvements to power plant operating efficiencies. As the EPA expands regulatory requirements to other industries, including petroleum refining, it is likely that plant efficiency improvements will be critical to achieving CO2 emission reductions. This paper identifies efficiency improvement measures applicable to refining, and quantifies potential cost of conserved energy for these measures. Analysis is at the U.S. petroleum refining sector national-level employing an aggregated notional refinery model (NRM), with the aim of estimating the efficacy of efficiency improvements for reducing emissions. Using this method, roughly 1500 petajoules per year (PJ/yr) of plant fuel savings and 650 gigawatt-hour per year (GWh/yr) of electricity savings (representing 54% and 2% of U.S. refining industry consumption, respectively) are potentially cost-effective. This equates to a potential 85 Mt-CO2/yr reduction. An additional 458 PJ/yr fuel reduction and close to 2750 GWh/yr of electricity reduction (27 Mt-CO2/yr) are not cost-effective at prevailing natural gas market prices. Results are presented as a supply-curve ordering measures from low to high cost of fuel savings versus cumulative energy reduction.