Editing IPCC:AR6/WGIII/Chapter-1 (section)

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-----

<div id="footnote-008" class="_idFootnote"></div>

[[#footnote-008-backlink|1]] These are the Special Report on Global Warming of 1.5°C (SR1.5) ( [[#IPCC--2018b|IPCC 2018b]] ); the Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) ( [[#IPCC--2019b|IPCC 2019b]] ); and the Special Report on Climate Change and Land (SRCCL) ( [[#IPCC--2019c|IPCC 2019c]] ).

<div id="footnote-007" class="_idFootnote"></div>

[[#footnote-007-backlink|2]] Indeed, cooling effects of anthropogenic aerosols (organic carbon, black carbon, sulphates, nitrates), which are also important components of local air pollution ( [[#Myhre--2013|Myhre et al. 2013]] ) (AR6 WGI SPM D1.7) may in global average be of similar magnitude to warming from methane at present. Mitigation which reduces such aerosol masking could thereby increase global temperatures, and reducing methane emissions would offset this much more rapidly than reducing CO 2 because of its relatively short lifetime, with the combined effects which could counterbalance each other (AR6 WGI SPM D1.7). Methane is thus particularly important in determining whether or when 1.5˚C is reached for example.

<div id="footnote-006" class="_idFootnote"></div>

[[#footnote-006-backlink|3]] With some exclusions for countries which were very small or undergoing economic collapse: fossil-fuel-and industry (CO 2 -FFI) emissions in 2018 were below 2008 levels in 32 developed countries, but only in 24 when including other GHGs. Reductions were by less than 10% in half these countries. Data from Chapter 2: see [[IPCC:Wg3:Chapter:Chapter-2#2.2.3|Section 2.2.3]] , as analysed in [[#Lamb--2021|Lamb et al. (2021)]] . An earlier study found 18 developed countries that had reduced CO 2 -FFI emissions over 2005–2015 ( [[#Le%20Quéré--2019|Le Quéré et al. 2019]] ). Decomposition analysis of national trends in [[#Xia--2021|Xia et al. (2021)]] , identified 23 industrialised countries (UNFCCC Annex I) with CO 2 -FFI emissions in 2017 lower than in 2000 (Figure 1.3), of which 22 had increased GDP over the period. The previously rising trend of ‘outsourced/embodied emissions’ associated with goods imported into developed countries peaked in 2006, but detailed data on this are only available for CO 2 -FFI up to 2018 ( [[IPCC:Wg3:Chapter:Chapter-2#2.3|Section 2.3]] ). See [[IPCC:Wg3:Chapter:Chapter-3|Chapter 3]] for reduction rates associated with 1.5°C and 2°C.

<div id="footnote-005" class="_idFootnote"></div>

[[#footnote-005-backlink|4]] Continually updated information on net zero commitments is available at [https://www.zerotracker.net https://www.z erotracker.net] .

<div id="footnote-004" class="_idFootnote"></div>

[[#footnote-004-backlink|5]] AFOLU accounted for about 13% of CO 2 , 44% of CH 4 and 82% of N 2 O global anthropogenic GHG emissions in 2007–2016.

<div id="footnote-003" class="_idFootnote"></div>

[[#footnote-003-backlink|6]] Linking estimated policy impacts to trends is complex, and as yet very tentative. An important factor is that many mitigation policies involve investments in low-carbon or energy-efficient technology, the savings from which persist. As a purely illustrative example: the annual increase in global emissions during 2000–2010 averaged around 1 GtCO 2 -eq yr –1 , but with large fluctuations. If policies by 2010 reduced the annual increase in that year by 100 MtCO 2 -eq (0.1 GtC0 2 -eq) below what it would otherwise have been, this is hard to discern. But if these savings sustain, and in each subsequent year, policies cut another 100 MtCO 2 -eq off the annual increase compared to the previous year, global emissions after a decade would be around 5 GtCO 2 -eq yr –1 below what they would have been without any such policies, and on average close to stabilising. However each step would be difficult to discern in the noise of annual fluctuations.

<div id="footnote-002" class="_idFootnote"></div>

[[#footnote-002-backlink|7]] The Historical Index of Human Development (HIHD) emulates the widely used Human Development Index (HDI) as they both summarise in indexes the key human development dimensions consisting of a healthy life, knowledge and a decent standard of living. HDI is based on: life expectancy, expected years of schooling of children, the mean years of schooling of the adult population, and gross national income (GNI) per capita adjusted for purchasing power; the HIHD is based on: life expectancy at birth, adult literacy rates, educational enrolment rates, and GDP per capita, and is used in Figure 1.6 because it is available for a longer time series ( [[#Prados%20de%20la%20Escosura--2015|Prados de la Escosura 2015]] ).

<div id="footnote-001" class="_idFootnote"></div>

[[#footnote-001-backlink|8]] Based on global population projections of between 8 and 8.5 billion people in 2030, and GHG emissions levels from the C1, C2 and C3 categories of scenarios in Table 3.2 and Box 3.7.

<div id="footnote-000" class="_idFootnote"></div>

[[#footnote-000-backlink|9]] Beyond GHG externalities, [[#Stern--2015|Stern (2015)]] lists such market failures as: inadequate R&amp;D; failures in risk/capital markets; network effects creating coordination failures; wider information failures; and co-benefits.