Editing IPCC:AR6/SR15/Chapter-4 (section)

==== Examples of technological innovations relevant to 1.5°C enabled by general purpose technologies (GPT) ====

Note: lists of enabling GPT or adaptation/mitigation options are not exhaustive, and the GPTs by themselves do not reduce emissions or increase climate change resilience.

{| class="wikitable"
|-
! Sector
! Examples of Mitigation/Adaptation Technological Innovation
! Enabling GPT
|-
! rowspan="2"| Buildings
| Energy and CO <sub>2</sub> efficiency of logistics, warehouse and shops (GeSI, 2015; IEA, 2017a)
| IoT, AI
|-
| Smart lighting and air conditioning (IEA, 2016b, 2017a)
| IoT, AI
|-
! rowspan="3"| Industry
| Energy efficiency improvement by industrial process optimization (IEA, 2017a)
| Robots, IoT
|-
| Bio-based plastic production by biorefinery (OECD, 2017c)
| Biotechnology
|-
| New materials from biorefineries (Fornell et al., 2013; McKay et al., 2016)
| ICT, biotechnology
|-
! rowspan="6"| Transport
| Electric vehicles, car sharing, automation (Greenblatt and Saxena, 2015; Fulton et al., 2017)
| Biotechnology
|-
| Bio-based diesel fuel by biorefinery (OECD, 2017c)
| ICT, biotechnology
|-
| Second generation bioethanol potentially coupled to carbon capture systems (De Souza et al., 2014; Rochedo et al., 2016)
| Biotechnology
|-
| Logistical optimization, and electrification of trucks by overhead line (IEA, 2017e)
| ICT, biotechnology
|-
| Reduction of transport needs by remote education, health and other services (GeSI, 2015; IEA, 2017a)
| Biotechnology
|-
| Energy saving by lightweight aircraft components (Beyer, 2014; Faludi et al., 2015; Verhoef et al., 2018)
| Additive manufacturing (3D printing)
|-
! rowspan="3"| Electricity
| Solar PV manufacturing (Nemet, 2014)
| Nanotechnology
|-
| Smart grids and grid flexibility to accommodate intermittent renewables (Heard et al., 2017)
| IoT, AI
|-
| Plasma confinement for nuclear fusion (Baltz et al., 2017)
| AI
|-
! rowspan="4"| Agriculture
| Precision agriculture (improvement of energy and resource efficiency including reduction of fertilizer use and N2O emissions)<br />
(Pierpaoli et al., 2013; Brown et al., 2016; Schimmelpfennig and Ebel, 2016)
| Biotechnology ICT, AI
|-
| Methane inhibitors (and methane-suppressing vaccines) that reduce livestock emissions from enteric fermentation (Wedlock et al., 2013; Hristov et al., 2015; Wollenberg et al., 2016)
| Biotechnology
|-
| Engineering C3 into C4 photosynthesis to improve agricultural production and productivity (Schuler et al., 2016)
| Biotechnology
|-
| Genome editing using CRISPR to improve/adapt crops to a changing climate (Gao, 2018)
| Biotechnology
|-
! rowspan="3"| Disaster Reduction and Adaptation
| Weather forecasting and early warning systems, in combination with user knowledge (Hewitt et al., 2012; Lourenço et al., 2016)
| ICT
|-
| Climate risk reduction (Upadhyay and Bijalwan, 2015)
| ICT
|-
| Rapid assessment of disaster damage (Kryvasheyeu et al., 2016)
| ICT
|}

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Government policy usually plays a role in promoting or limiting GPTs, or science and technology in general. It has impacts on climate action, because the performance of further climate technologies will partly depend on the progress of GPTs. Governments have established institutions for achieving many social, and sometimes conflicting goals, including economic growth and addressing climate change (OECD, 2017c) <sup>[[#fn:r1273|1273]]</sup> , which include investment in basic research and development (R&amp;D) that can help develop game-changing technologies (Shayegh et al., 2017) <sup>[[#fn:r1274|1274]]</sup> . Governments are also needed to create an enabling environment for the growth of scientific and technological ecosystems necessary for GPT development (Tassey, 2014) <sup>[[#fn:r1275|1275]]</sup> .

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