Editing IPCC:AR6/WGIII/Chapter-11 (section)

=== 11.3.4 Energy Efficiency ===

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Energy efficiency in industry is an important mitigation option and central in keeping 1.5°C within reach (IPCC SR1.5). It has long been recognised as the first mitigation option in industry (Yeen [[#Chan--2016|Chan and Kantamaneni 2016]] ; [[#Nadel--2019|Nadel and Ungar 2019]] ; [[#IEA--2021a|IEA 2021a]] ). It allows reduction of the necessary scale of deployment for low-carbon energy supplies and associated mitigation costs ( [[#Energy%20Transitions%20Commission--2018|Energy Transitions Commission 2018]] ). The efficiency potentials are greatest in the non-energy-intensive industries and are often relatively limited in energy-intensive ones, such as steel ( [[#Pardo--2013|Pardo and Moya 2013]] ; [[#Kuramochi--2016|Kuramochi 2016]] ; [[#Arens--2017|Arens et al. 2017]] ). Deep decarbonisation in these subsectors requires fundamental process changes but energy efficiency remains important to reduce costs and the need for low-carbon energy supplies.

Below, we focus mainly on the technical progress and on new options that are reflected in the literature since AR5 and refer the reader there for a broader and deeper treatment of energy efficiency. Digitalisation and the development of industrial high-temperature heat pumps are two notable technology developments that can facilitate energy efficiency improvements.

Industrial energy efficiency can be improved through multiple technologies and practices ( [[#Tanaka--2011|Tanaka 2011]] ; [[#Fawkes--2016|Fawkes et al. 2016]] ; [[#Lovins--2018|Lovins 2018]] ; [[#Crijns-Graus--2020|Crijns-Graus et al. 2020]] ; [[#IEA--2020a|IEA 2020a]] ). There are two parallel processes in improvement of specific energy consumption (SEC): progress in energy-efficient BAT and moving the SEC of industrial plants towards BAT. Both slow down as theoretical thermodynamic minimums are approached ( [[#Gutowski--2013|Gutowski et al. 2013]] ). For the last several decades the focus has been on effective spreading of BAT technologies through application of policies for worldwide diffusion of energy-saving technologies ( [[#11.6|Section 11.6]] ). As a result the SEC for many basic primary materials is approaching BAT and there are signs that energy efficiency improvements have been slowing down over recent decades ( [[#IEA--2019d|IEA 2019d]] , 2020a, 2021a) (Figure 11.8).

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==== 11.3.4.1 Heat-use Energy Efficiency Improvement ====

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While about 10% of global GHG emissions originate from combustion to produce high-temperature heat for basic material production processes ( [[#Sandalow--2019|Sandalow et al. 2019]] ), limited efforts have been made to decarbonise heat production. There is still a large potential for using various grades of waste heat and the development of high-temperature heat pumps facilitates its use. [[#NEDO--2019|NEDO (2019)]] applies a ‘Reduce, Reuse, and Recycle’ concept for improved energy efficiency, and we use this frame our discussion of heat efficiency.

''Reduce'' refers to reducing heat needs via improved thermal insulation, for example, where porous type insulators have been developed with thermal conductivity half of what is traditionally achieved by heat-resistant bricks under conditions of high compressive strength (Fukushima and Yoshizawa 2016). ''Reuse'' refers to waste heat recovery. A study for the EU identified a waste heat potential of about 300 TWh yr –1 , corresponding to about 10% of total energy use in industry. About 50% of this was below 200°C, about 25% at temperatures 200°C–500°C, and 25% at temperatures of 500°C and above ( [[#Papapetrou--2018|Papapetrou et al. 2018]] ). A survey conducted in Japan showed that 9% of the input energy is lost as waste heat, of which heat below 199°C accounts for 68% and that below 149°C was 29% ( [[#NEDO--2019|NEDO 2019]] ). [[#McBrien--2016|McBrien et al. (2016)]] identified that in the steel sector process heat recovery presently saves 1.8 GJ per tonne of hot rolled steel, while integrated across all production processes heat recovery with conventional heat exchange could save 2.5 GJ t –1 , and it scales up to 3.0 GJ t –1 using an alternative heat exchange that recovers energy from hot steel. High-temperature industrial heat pumps represent a new and important development for upgrading waste heat and at the same time they facilitate electrification. One recent example is a high-temperature heat pump that can raise temperatures up to 165°C at a coefficient of performance (COP) of 3.5 by recovering heat from unused hot water (35°C–65°C) ( [[#Arpagaus--2018|Arpagaus et al. 2018]] ). Commercially available heat pumps can deliver 100°C–150°C but at least up to 280°C is feasible ( [[#Zühlsdorf--2019|Zühlsdorf et al. 2019]] ). Mechanical vapour recompression avoids the loss of latent heat by condensation, then it acts as a highly efficient heat pump with a 5–10 COP ( [[#Philibert--2017a|Philibert 2017a]] ).

Waste heat to power (WHP), or ''Recycle'' in NEDO’s terms, is also an under-utilised option. For example, a study for the cement, glass and iron industries in China showed that current technology enables only 7–13% of waste heat to be used for power generation. With improved technologies, potentially 40–57% of waste heat with temperatures above 150°C could be used for power generation via heat recovery. Thermal power fluctuations can be a challenge and negatively affect the operation and economic feasibility of heat recovery power systems such as steam and/or organic Rankine cycle. In such cases, latent heat storage technology and intermediate storage units may be applied ( [[#Jiménez-Arreola--2018|Jiménez-Arreola et al. 2018]] ). The development of thermoelectric conversion materials that produce power from unused heat and energy harvested from a higher temperature environment is also progressing, with several possible applications in industrial processes (Gayner and Kar 2016; [[#Jood--2018|Jood et al. 2018]] ; [[#Lv--2018|Lv et al. 2018]] ; [[#Ohta--2018|Ohta et al. 2018]] ). A potential early application in industry is to power wireless sensors, a niche that uses microwatts or milliwatts, and avoid power cables ( [[#Champier--2017|Champier 2017]] ).

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==== 11.3.4.2 Smart Energy Management ====

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Energy management systems to reduce energy costs in an integrated and systematic manner were first developed in the 1970s, mainly in low-energy-resource countries, for example, by establishing energy managers and institutionalising management targets ( [[#Tanaka--2011|Tanaka 2011]] ). Strategic energy management has since then evolved and been promoted through the establishment of dedicated organisational infrastructures for energy-use optimisation, such as ISO-50001 which specifies the requirements for establishing, implementing, maintaining, and improving an energy management system ( [[#Biel--2016|Biel and Glock 2016]] ; [[#Tunnessen--2017|Tunnessen and Macri 2017]] ). Digitalisation, sometimes referred to as Industry 4.0, facilitates further improvements in process control and optimisation through technology development involving sensors, communications, analytics, digital twins, machine learning, virtual reality, and other simulation and computing technologies ( [[#Rogers--2018|Rogers 2018]] ), all of which can improve energy efficiency. One example is combustion control systems, where big data analysis of factors affecting boiler efficiency, operation optimisation and load forecasting have shown that it can lead to energy savings of 9% ( [[#Wang--2017|Wang et al. 2017]] ).

Smart energy systems with real-time monitoring allow for optimisation of innovative technologies, energy demand response, balancing of energy supply and demand including that on real-time pricing, and product quality management, and prediction and reduction of idle time for workers and robots ( [[#ERIA--2016|ERIA 2016]] ; [[#Pusnik--2016|Pusnik et al. 2016]] ; [[#ISO--2018|ISO 2018]] ; [[#Legorburu--2018|Legorburu and Smith 2018]] ; [[#Ferrero--2020|Ferrero et al. 2020]] ; [[#Nimbalkar--2020|Nimbalkar et al. 2020]] ). The IEA estimated that smart manufacturing could deliver 15 EJ in energy savings between 2014 and 2030 ( [[#IEA--2019d|IEA 2019d]] ). Smart manufacturing systems that integrate manufacturing intelligence in real time through the entire production operation have not been yet widely spread in the industry. Examples have been demonstrated and integrated in real operation in the electrical appliance assembly industry ( [[#Yoshimoto--2016|Yoshimoto 2016]] ). Combining process controls and automation allows cost optimisation and improved productivity ( [[#Edgar--2018|Edgar and Pistikopoulos 2018]] ).

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