Framing and Context

The AR5 suggested that equity, sustainable development, and poverty eradication are best understood as mutually supportive and co-achievable within the context of climate action and are underpinned by various other international hard and soft law instruments (Denton et al., 2014; Fleurbaey et al., 2014; Klein et al., 2014; Olsson et al., 2014; Porter et al., 2014; Stavins et al., 2014)²². The aim of the Paris Agreement under the UNFCCC to ‘pursue efforts to limit’ the rise in global temperatures to 1.5°C above pre-industrial levels raises ethical concerns that have long been central to climate debates (Fleurbaey et al., 2014; Kolstad et al., 2014)²³. The Paris Agreement makes particular reference to the principle of equity, within the context of broader international goals of sustainable development and poverty eradication. Equity is a long-standing principle within international law and climate change law in particular (Shelton, 2008; Bodansky et al., 2017)²⁴.

The AR5 describes equity as having three dimensions: intergenerational (fairness between generations), international (fairness between states), and national (fairness between individuals) (Fleurbaey et al., 2014)²⁵. The principle is generally agreed to involve both procedural justice (i.e., participation in decision making) and distributive justice (i.e., how the costs and benefits of climate actions are distributed) (Kolstad et al., 2014; Savaresi, 2016; Reckien et al., 2017)²⁶. Concerns regarding equity have frequently been central to debates around mitigation, adaptation and climate governance (Caney, 2005; Schroeder et al., 2012; Ajibade, 2016; Reckien et al., 2017; Shue, 2018)²⁷. Hence, equity provides a framework for understanding the asymmetries between the distributions of benefits and costs relevant to climate action (Schleussner et al., 2016; Aaheim et al., 2017)²⁸.

Four key framing asymmetries associated with the conditions of a 1.5°C warmer world have been noted (Okereke, 2010; Harlan et al., 2015; Ajibade, 2016; Savaresi, 2016; Reckien et al., 2017)²⁹ and are reflected in the report’s assessment. The first concerns differential contributions to the problem: the observation that the benefits from industrialization have been unevenly distributed and those who benefited most historically also have contributed most to the current climate problem and so bear greater responsibility (Shue, 2013; McKinnon, 2015; Otto et al., 2017; Skeie et al., 2017)³⁰. The second asymmetry concerns differential impact: the worst impacts tend to fall on those least responsible for the problem, within states, between states, and between generations (Fleurbaey et al., 2014; Shue, 2014; Ionesco et al., 2016)³¹. The third is the asymmetry in capacity to shape solutions and response strategies, such that the worst-affected states, groups, and individuals are not always well represented (Robinson and Shine, 2018)³². Fourth, there is an asymmetry in future response capacity: some states, groups, and places are at risk of being left behind as the world progresses to a low-carbon economy (Fleurbaey et al., 2014; Shue, 2014; Humphreys, 2017)³³.

A sizeable and growing literature exists on how best to operationalize climate equity considerations, drawing on other concepts mentioned in the Paris Agreement, notably its explicit reference to human rights (OHCHR, 2009; Caney, 2010; Adger et al., 2014; Fleurbaey et al., 2014; IBA, 2014; Knox, 2015; Duyck et al., 2018; Robinson and Shine, 2018)³⁴. Human rights comprise internationally agreed norms that align with the Paris ambitions of poverty eradication, sustainable development, and the reduction of vulnerability (Caney, 2010; Fleurbaey et al., 2014; OHCHR, 2015)³⁵. In addition to defining substantive rights (such as to life, health, and shelter) and procedural rights (such as to information and participation), human rights instruments prioritise the rights of marginalized groups, children, vulnerable and indigenous persons, and those discriminated against on grounds such as gender, race, age or disability (OHCHR, 2017)³⁶. Several international human rights obligations are relevant to the implementation of climate actions and consonant with UNFCCC undertakings in the areas of mitigation, adaptation, finance, and technology transfer (Knox, 2015; OHCHR, 2015; Humphreys, 2017)³⁷.

Much of this literature is still new and evolving (Holz et al., 2017; Dooley et al., 2018; Klinsky and Winkler, 2018)³⁸, permitting the present report to examine some broader equity concerns raised both by possible failure to limit warming to 1.5°C and by the range of ambitious mitigation efforts that may be undertaken to achieve that limit. Any comparison between 1.5°C and higher levels of warming implies risk assessments and value judgements and cannot straightforwardly be reduced to a cost-benefit analysis (Kolstad et al., 2014)³⁹. However, different levels of warming can nevertheless be understood in terms of their different implications for equity – that is, in the comparative distribution of benefits and burdens for specific states, persons, or generations, and in terms of their likely impacts on sustainable development and poverty (see especially Sections 2.3.4.2, 2.5, 3.4.5–3.4.13, 3.6, 5.4.1, 5.4.2, 5.6 and Cross-Chapter boxes 6 in Chapter 3 and 12 in Chapter 5).

This report assesses the role of poverty and its eradication in the context of strengthening the global response to the threat of climate change and sustainable development. A wide range of definitions for poverty exist. The AR5 discussed ‘poverty’ in terms of its multidimensionality, referring to ‘material circumstances’ (e.g., needs, patterns of deprivation, or limited resources), as well as to economic conditions (e.g., standard of living, inequality, or economic position), and/or social relationships (e.g., social class, dependency, lack of basic security, exclusion, or lack of entitlement; Olsson et al., 2014)⁴⁰. The UNDP now uses a Multidimensional Poverty Index and estimates that about 1.5 billion people globally live in multidimensional poverty, especially in rural areas of South Asia and Sub-Saharan Africa, with an additional billion at risk of falling into poverty (UNDP, 2016)⁴¹.

A large and rapidly growing body of knowledge explores the connections between climate change and poverty. Climatic variability and climate change are widely recognized as factors that may exacerbate poverty, particularly in countries and regions where poverty levels are high (Leichenko and Silva, 2014)⁴². The AR5 noted that climate change-driven impacts often act as a threat multiplier in that the impacts of climate change compound other drivers of poverty (Olsson et al., 2014)⁴³. Many vulnerable and poor people are dependent on activities such as agriculture that are highly susceptible to temperature increases and variability in precipitation patterns (Shiferaw et al., 2014; Miyan, 2015)⁴⁴. Even modest changes in rainfall and temperature patterns can push marginalized people into poverty as they lack the means to recover from associated impacts. Extreme events, such as floods, droughts, and heat waves, especially when they occur in series, can significantly erode poor people’s assets and further undermine their livelihoods in terms of labour productivity, housing, infrastructure and social networks (Olsson et al., 2014)⁴⁵.

AR5 (IPCC, 2014c)⁴⁶ noted with high confidence that ‘equity is an integral dimension of sustainable development’ and that ‘mitigation and adaptation measures can strongly affect broader sustainable development and equity objectives’ (Fleurbaey et al., 2014)⁴⁷. Limiting global warming to 1.5°C would require substantial societal and technological transformations, dependent in turn on global and regional sustainable development pathways. A range of pathways, both sustainable and not, are explored in this report, including implementation strategies to understand the enabling conditions and challenges required for such a transformation. These pathways and connected strategies are framed within the context of sustainable development, and in particular the United Nations 2030 Agenda for Sustainable Development (UN, 2015b)⁴⁸ and Cross-Chapter Box 4 on SDGs (in this chapter). The feasibility of staying within 1.5°C depends upon a range of enabling conditions with geophysical, environmental–ecological, technological, economic, socio-cultural, and institutional dimensions. Limiting warming to 1.5°C also involves identifying technology and policy levers to accelerate the pace of transformation (see Chapter 4). Some pathways are more consistent than others with the requirements for sustainable development (see Chapter 5). Overall, the three-pronged emphasis on sustainable development, resilience, and transformation provides Chapter 5 an opportunity to assess the conditions of simultaneously reducing societal vulnerabilities, addressing entrenched inequalities, and breaking the circle of poverty.

The feasibility of any global commitment to a 1.5°C pathway depends, in part, on the cumulative influence of the nationally determined contributions (NDCs), committing nation states to specific GHG emission reductions. The current NDCs, extending only to 2030, do not limit warming to 1.5°C. Depending on mitigation decisions after 2030, they cumulatively track toward a warming of 3°-4°C above pre-industrial temperatures by 2100, with the potential for further warming thereafter (Rogelj et al., 2016a; UNFCCC, 2016)⁴⁹. The analysis of pathways in this report reveals opportunities for greater decoupling of economic growth from GHG emissions. Progress towards limiting warming to 1.5°C requires a significant acceleration of this trend. AR5 concluded that climate change constrains possible development paths, that synergies and trade-offs exist between climate responses and socio-economic contexts, and that opportunities for effective climate responses overlap with opportunities for sustainable development, noting that many existing societal patterns of consumption are intrinsically unsustainable (Fleurbaey et al., 2014)⁵⁰.

What is meant by ‘the increase in global average temperature… above pre-industrial levels’ referred to in the Paris Agreement depends on the choice of pre-industrial reference period, whether 1.5°C refers to total warming or the human-induced component of that warming, and which variables and geographical coverage are used to define global average temperature change. The cumulative impact of these definitional ambiguities (e.g., Hawkins et al., 2017; Pfleiderer et al., 2018)⁵¹ is comparable to natural multi-decadal temperature variability on continental scales (Deser et al., 2012)⁵² and primarily affects the historical period, particularly that prior to the early 20th century when data is sparse and of less certain quality. Most practical mitigation and adaptation decisions do not depend on quantifying historical warming to this level of precision, but a consistent working definition is necessary to ensure consistency across chapters and figures. We adopt definitions that are as consistent as possible with key findings of AR5 with respect to historical warming.

This report defines ‘warming’, unless otherwise qualified, as an increase in multi-decade global mean surface temperature (GMST) above pre-industrial levels. Specifically, warming at a given point in time is defined as the global average of combined land surface air and sea surface temperatures for a 30-year period centred on that time, expressed relative to the reference period 1850–1900 (adopted for consistency with Box SPM.1 Figure 1 of IPCC (2014a)⁵³ ‘as an approximation of pre-industrial levels’, excluding the impact of natural climate fluctuations within that 30-year period and assuming any secular trend continues throughout that period, extrapolating into the future if necessary. There are multiple ways of accounting for natural fluctuations and trends (e.g., Foster and Rahmstorf, 2011; Haustein et al., 2017; Medhaug et al., 2017; Folland et al., 2018; Visser et al., 2018)⁵⁴, but all give similar results. A major volcanic eruption might temporarily reduce observed global temperatures, but would not reduce warming as defined here (Bethke et al., 2017)⁵⁵. Likewise, given that the level of warming is currently increasing at 0.3°C–0.7°C per 30 years (likely range quoted in Kirtman et al., 2013⁵⁶ and supported by Folland et al., 2018)⁵⁷, the level of warming in 2017 was 0.15°C–0.35°C higher than average warming over the 30-year period 1988–2017.

In summary, this report adopts a working definition of ‘1.5°C relative to pre-industrial levels’ that corresponds to global average combined land surface air and sea surface temperatures either 1.5°C warmer than the average of the 51-year period 1850–1900, 0.87°C warmer than the 20-year period 1986–2005, or 0.63°C warmer than the decade 2006–2015. These offsets are based on all available published global datasets, combined and updated, which show that 1986–2005 was 0.63°C warmer than 1850–1900 (with a 5–95% range of 0.57°C–0.69°C based on observational uncertainties alone), and 2006–2015 was 0.87°C warmer than 1850–1900 (with a likely range of 0.75°C–0.99°C, also accounting for the possible impact of natural fluctuations). Where possible, estimates of impacts and mitigation pathways are evaluated relative to these more recent periods. Note that the 5–95% intervals often quoted in square brackets in AR5 correspond to very likely ranges, while likely ranges correspond to 17–83%, or the central two-thirds, of the distribution of uncertainty.

Warming is not observed or expected to be spatially or seasonally uniform (Collins et al., 2013)¹⁰³. A 1.5°C increase in GMST will be associated with warming substantially greater than 1.5°C in many land regions, and less than 1.5°C in most ocean regions. This is illustrated by Figure 1.3, which shows an estimate of the observed change in annual and seasonal average temperatures between the 1850–1900 pre-industrial reference period and the decade 2006–2015 in the Cowtan-Way dataset. These regional changes are associated with an observed GMST increase of 0.91°C in the dataset shown here, or 0.87°C in the four-dataset average (Table 1.1). This observed pattern reflects an on-going transient warming: features such as enhanced warming over land may be less pronounced, but still present, in equilibrium (Collins et al., 2013)¹⁰⁴. This figure illustrates the magnitude of spatial and seasonal differences, with many locations, particularly in Northern Hemisphere mid-latitude winter (December–February), already experiencing regional warming more than double the global average. Individual seasons may be substantially warmer, or cooler, than these expected changes in the long-term average.

Pathways considered in this report, consistent with available literature on 1.5°C, primarily focus on the time scale up to 2100, recognising that the evolution of GMST after 2100 is also important. Two broad categories of 1.5°C pathways can be used to characterise mitigation options and impacts: pathways in which warming (defined as 30-year averaged GMST relative to pre-industrial levels, see Section 1.2.1) remains below 1.5°C throughout the 21st century, and pathways in which warming temporarily exceeds (‘overshoots’) 1.5°C and returns to 1.5°C either before or soon after 2100. Pathways in which warming exceeds 1.5°C before 2100, but might return to that level in some future century, are not considered 1.5°C pathways.

Because of uncertainty in the climate response, a ‘prospective’ mitigation pathway (see Cross-Chapter Box 1 in this chapter), in which emissions are prescribed, can only provide a level of probability of warming remaining below a temperature threshold. This probability cannot be quantified precisely since estimates depend on the method used (Rogelj et al., 2016b; Millar et al., 2017b; Goodwin et al., 2018; Tokarska and Gillett, 2018)¹⁰⁷. This report defines a ‘1.5°C pathway’ as a pathway of emissions and associated possible temperature responses in which the majority of approaches using presently available information assign a probability of approximately one-in-two to two-in-three to warming remaining below 1.5°C or, in the case of an overshoot pathway, to warming returning to 1.5°C by around 2100 or earlier. Recognizing the very different potential impacts and risks associated with high-overshoot pathways, this report singles out 1.5°C pathways with no or limited (<0.1°C) overshoot in many instances and pursues efforts to ensure that when the term ‘1.5°C pathway’ is used, the associated overshoot is made explicit where relevant. In Chapter 2, the classification of pathways is based on one modelling approach to avoid ambiguity, but probabilities of exceeding 1.5°C are checked against other approaches to verify that they lie within this approximate range. All these absolute probabilities are imprecise, depend on the information used to constrain them, and hence are expected to evolve in the future. Imprecise probabilities can nevertheless be useful for decision-making, provided the imprecision is acknowledged (Hall et al., 2007; Kriegler et al., 2009; Simpson et al., 2016)¹⁰⁸. Relative and rank probabilities can be assessed much more consistently: approaches may differ on the absolute probability assigned to individual outcomes, but typically agree on which outcomes are more probable.

Importantly, 1.5°C pathways allow a substantial (up to one-in-two) chance of warming still exceeding 1.5°C. An ‘adaptive’ mitigation pathway in which emissions are continuously adjusted to achieve a specific temperature outcome (e.g., Millar et al., 2017b)¹⁰⁹ reduces uncertainty in the temperature outcome while increasing uncertainty in the emissions required to achieve it. It has been argued (Otto et al., 2015; Xu and Ramanathan, 2017)¹¹⁰ that achieving very ambitious temperature goals will require such an adaptive approach to mitigation, but very few studies have been performed taking this approach (e.g., Jarvis et al., 2012)¹¹¹.

Figure 1.4 illustrates categories of (a) 1.5°C pathways and associated (b) annual and (c) cumulative emissions of CO₂. It also shows (d) an example of a ‘time-integrated impact’ that continues to increase even after GMST has stabilised, such as sea level rise. This schematic assumes for the purposes of illustration that the fractional contribution of non-CO₂ climate forcers to total anthropogenic forcing (which is currently increasing, Myhre et al., 2017)¹¹² is approximately constant from now on. Consequently, total human-induced warming is proportional to cumulative CO₂ emissions (solid line in c), and GMST stabilises when emissions reach zero. This is only the case in the most ambitious scenarios for non-CO₂ mitigation (Leach et al., 2018)¹¹³. A simple way of accounting for varying non-CO₂ forcing in Figure 1.4 would be to note that every 1 W m⁻² increase in non-CO₂ forcing between now and the decade or two immediately prior to the time of peak warming reduces cumulative CO₂ emissions consistent with the same peak warming by approximately 1100 GtCO₂, with a range of 900-1500 GtCO₂  (using values from AR5: Myhre et al., 2013; Allen et al., 2018; Jenkins et al., 2018¹¹⁴; Cross-Chapter Box 2 in this chapter).

It is frequently asked whether limiting warming to 1.5°C is ‘feasible’ (Cross-Chapter Box 3 in this chapter). There are many dimensions to this question, including the warming ‘commitment’ from past emissions of greenhouse gases and aerosol precursors. Quantifying commitment from past emissions is complicated by the very different behaviour of different climate forcers affected by human activity: emissions of long-lived greenhouse gases such as CO₂ and nitrous oxide (N₂O) have a very persistent impact on radiative forcing (Myhre et al., 2013)¹⁵³, lasting from over a century (in the case of N₂O) to hundreds of thousands of years (for CO₂). The radiative forcing impact of short-lived climate forcers (SLCFs) such as methane (CH₄) and aerosols, in contrast, persists for at most about a decade (in the case of methane) down to only a few days. These different behaviours must be taken into account in assessing the implications of any approach to calculating aggregate emissions (Cross-Chapter Box 2 in this chapter).

Geophysical warming commitment is defined as the unavoidable future warming resulting from physical Earth system inertia. Different variants are discussed in the literature, including (i) the ‘constant composition commitment’ (CCC), defined by Meehl et al. (2007)¹⁵⁴ as the further warming that would result if atmospheric concentrations of GHGs and other climate forcers were stabilised at the current level; and (ii) and the ‘zero emissions commitment’ (ZEC), defined as the further warming that would still occur if all future anthropogenic emissions of greenhouse gases and aerosol precursors were eliminated instantaneously (Meehl et al., 2007; Collins et al., 2013)¹⁵⁵.

The CCC is primarily associated with thermal inertia of the ocean (Hansen et al., 2005)¹⁵⁶, and has led to the misconception that substantial future warming is inevitable (Matthews and Solomon, 2013)¹⁵⁷. The CCC takes into account the warming from past emissions, but also includes warming from future emissions (declining but still non-zero) that are required to maintain a constant atmospheric composition. It is therefore not relevant to the warming commitment from past emissions alone.

The ZEC, although based on equally idealised assumptions, allows for a clear separation of the response to past emissions from the effects of future emissions. The magnitude and sign of the ZEC depend on the mix of GHGs and aerosols considered. For CO₂, which takes hundreds of thousands of years to be fully removed from the atmosphere by natural processes following its emission (Eby et al., 2009; Ciais et al., 2013)¹⁵⁸, the multi-century warming commitment from emissions to date in addition to warming already observed is estimated to range from slightly negative (i.e., a slight cooling relative to present-day) to slightly positive (Matthews and Caldeira, 2008; Lowe et al., 2009; Gillett et al., 2011; Collins et al., 2013)¹⁵⁹. Some studies estimate a larger ZEC from CO₂, but for cumulative emissions much higher than those up to present day (Frölicher et al., 2014; Ehlert and Zickfeld, 2017)¹⁶⁰. The ZEC from past CO₂ emissions is small because the continued warming effect from ocean thermal inertia is approximately balanced by declining radiative forcing due to CO₂ uptake by the ocean (Solomon et al., 2009; Goodwin et al., 2015; Williams et al., 2017)¹⁶¹. Thus, although present-day CO₂-induced warming is irreversible on millennial time scales (without human intervention such as active carbon dioxide removal or solar radiation modification; Section 1.4.1), past CO₂ emissions do not commit to substantial further warming (Matthews and Solomon, 2013)¹⁶².

Sustained net zero anthropogenic emissions of CO₂ and declining net anthropogenic non-CO₂ radiative forcing over a multi-decade period would halt anthropogenic global warming over that period, although it would not halt sea level rise or many other aspects of climate system adjustment. The rate of decline of non-CO₂ radiative forcing must be sufficient to compensate for the ongoing adjustment of the climate system to this forcing (assuming it remains positive) due to ocean thermal inertia. It therefore depends on deep ocean response time scales, which are uncertain but of order centuries, corresponding to decline rates of non-CO₂ radiative forcing of less than 1% per year. In the longer term, Earth system feedbacks such as the release of carbon from melting permafrost may require net negative CO₂ emissions to maintain stable temperatures (Lowe and Bernie, 2018)¹⁶³.

For warming SLCFs, meaning those associated with positive radiative forcing such as methane, the ZEC is negative. Eliminating emissions of these substances results in an immediate cooling relative to the present (Figure 1.5, magenta lines) (Frölicher and Joos, 2010; Matthews and Zickfeld, 2012; Mauritsen and Pincus, 2017)¹⁶⁴. Cooling SLCFs (those associated with negative radiative forcing) such as sulphate aerosols create a positive ZEC, as elimination of these forcers results in rapid increase in radiative forcing and warming (Figure 1.5, green lines) (Matthews and Zickfeld, 2012; Mauritsen and Pincus, 2017; Samset et al., 2018)¹⁶⁵. Estimates of the warming commitment from eliminating aerosol emissions are affected by large uncertainties in net aerosol radiative forcing (Myhre et al., 2013, 2017)¹⁶⁶ and the impact of other measures affecting aerosol loading (e.g., Fernández et al., 2017)¹⁶⁷. If present-day emissions of all GHGs (short- and long-lived) and aerosols (including sulphate, nitrate and carbonaceous aerosols) are eliminated (Figure 1.5, yellow lines) GMST rises over the following decade, driven by the removal of negative aerosol radiative forcing. This initial warming is followed by a gradual cooling driven by the decline in radiative forcing of short-lived greenhouse gases (Matthews and Zickfeld, 2012; Collins et al., 2013)¹⁶⁸. Peak warming following elimination of all emissions was assessed at a few tenths of a degree in AR5, and century-scale warming was assessed to change only slightly relative to the time emissions are reduced to zero (Collins et al., 2013)¹⁶⁹. New evidence since AR5 suggests a larger methane forcing (Etminan et al., 2016)¹⁷⁰ but no revision in the range of aerosol forcing (although this remains an active field of research, e.g., Myhre et al., 2017)¹⁷¹. This revised methane forcing estimate results in a smaller peak warming and a faster temperature decline than assessed in AR5 (Figure 1.5, yellow line).

Expert judgement based on the available evidence (including model simulations, radiative forcing and climate sensitivity) suggests that if all anthropogenic emissions were reduced to zero immediately, any further warming beyond the 1°C already experienced would likely be less than 0.5°C over the next two to three decades, and also likely less than 0.5°C on a century time scale.

Since most sources of emissions cannot, in reality, be brought to zero instantaneously due to techno-economic inertia, the current rate of emissions also constitutes a conditional commitment to future emissions and consequent warming depending on achievable rates of emission reductions. The current level and rate of human-induced warming determines both the time left before a temperature threshold is exceeded if warming continues (dashed blue line in Figure 1.5) and the time over which the warming rate must be reduced to avoid exceeding that threshold (approximately indicated by the dotted blue line in Figure 1.5). Leach et al. (2018)¹⁷⁵ use a central estimate of human-induced warming of 1.02°C in 2017, increasing at 0.215°C per decade (Haustein et al., 2017)¹⁷⁶, to argue that it will take 13–32 years (one-standard-error range) to reach 1.5°C if the current warming rate continues, allowing 25–64 years to stabilise temperatures at 1.5°C if the warming rate is reduced at a constant rate of deceleration starting immediately. Applying a similar approach to the multi-dataset average GMST used in this report gives an assessed likely range for the date at which warming reaches 1.5°C of 2030 to 2052. The lower bound on this range, 2030, is supported by multiple lines of evidence, including the AR5 assessment for the likely range of warming (0.3°C–0.7°C) for the period 2016–2035 relative to 1986–2005. The upper bound, 2052, is supported by fewer lines of evidence, so we have used the upper bound of the 5–95% confidence interval given by the Leach et al. (2018)¹⁷⁷ method applied to the multi-dataset average GMST, expressed as the upper limit of the likely range, to reflect the reliance on a single approach. Results are sensitive both to the confidence level chosen and the number of years used to estimate the current rate of anthropogenic warming (5 years used here, to capture the recent acceleration due to rising non-CO₂ forcing). Since the rate of human-induced warming is proportional to the rate of CO₂ emissions (Matthews et al., 2009; Zickfeld et al., 2009)¹⁷⁸ plus a term approximately proportional to the rate of increase in non-CO₂ radiative forcing (Gregory and Forster, 2008; Allen et al., 2018¹⁷⁹; Cross-Chapter Box 2 in this chapter), these time scales also provide an indication of minimum emission reduction rates required if a warming greater than 1.5°C is to be avoided (see Figure 1.5, Supplementary Material 1.SM.6 and FAQ 1.2).

Consistent with the AR5 (IPCC, 2014a)²⁰⁵, ‘impact’ in this report refers to the effects of climate change on human and natural systems. Impacts may include the effects of changing hazards, such as the frequency and intensity of heat waves. ‘Risk’ refers to potential negative impacts of climate change where something of value is at stake, recognizing the diversity of values. Risks depend on hazards, exposure, vulnerability (including sensitivity and capacity to respond) and likelihood. Climate change risks can be managed through efforts to mitigate climate change forcers, adaptation of impacted systems, and remedial measures (Section 1.4.1).

In the context of this report, regional impacts of global warming at 1.5°C and 2°C are assessed in Chapter 3. The ‘warming experience at 1.5°C’ is that of regional climate change (temperature, rainfall, and other changes) at the time when global average temperatures, as defined in Section 1.2.1, reach 1.5°C above pre-industrial (the same principle applies to impacts at any other global mean temperature). Over the decade 2006–2015, many regions have experienced higher than average levels of warming and some are already now 1.5°C or more warmer with respect to the pre-industrial period (Figure 1.3). At a global warming of 1.5°C, some seasons will be substantially warmer than 1.5°C above pre-industrial (Seneviratne et al., 2016)²⁰⁶. Therefore, most regional impacts of a global mean warming of 1.5°C will be different from those of a regional warming by 1.5°C.

The impacts of 1.5°C global warming will vary in both space and time (Ebi et al., 2016)²⁰⁷. For many regions, an increase in global mean temperature by 1.5°C or 2°C implies substantial increases in the occurrence and/or intensity of some extreme events (Fischer and Knutti, 2015; Karmalkar and Bradley, 2017; King et al., 2017; Chevuturi et al., 2018)²⁰⁸, resulting in different impacts (see Chapter 3). By comparing impacts at 1.5°C versus those at 2°C, this report discusses the ‘avoided impacts’ by maintaining global temperature increase at or below 1.5°C as compared to 2°C, noting that these also depend on the pathway taken to 1.5°C (see Section 1.2.3 and Cross-Chapter Box 8 in Chapter 3 on 1.5°C warmer worlds). Many impacts take time to observe, and because of the warming trend, impacts over the past 20 years were associated with a level of human-induced warming that was, on average, 0.1°C–0.23°C colder than its present level, based on the AR5 estimate of the warming trend over this period (Section 1.2.1 and Kirtman et al., 2013)²⁰⁹. Attribution studies (e.g., van Oldenborgh et al., 2017)²¹⁰ can address this bias, but informal estimates of ‘recent impact experience’ in a rapidly warming world necessarily understate the temperature-related impacts of the current level of warming.

Impacts of climate change are due to multiple environmental drivers besides rising temperatures, such as rising atmospheric CO₂, shifting rainfall patterns (Lee et al., 2018)²¹¹, rising sea levels, increasing ocean acidification, and extreme events, such as floods, droughts, and heat waves (IPCC, 2014a)²¹². Changes in rainfall affect the hydrological cycle and water availability (Schewe et al., 2014; Döll et al., 2018; Saeed et al., 2018)²¹³. Several impacts depend on atmospheric composition, increasing atmospheric carbon dioxide levels leading to changes in plant productivity (Forkel et al., 2016)²¹⁴, but also to ocean acidification (Hoegh-Guldberg et al., 2007)²¹⁵. Other impacts are driven by changes in ocean heat content such as the destabilization of coastal ice sheets and sea level rise (Bindoff et al., 2007; Chen et al., 2017)²¹⁶, whereas impacts due to heat waves depend directly on ambient air or ocean temperature (Matthews et al., 2017)²¹⁷. Impacts can be direct, such as coral bleaching due to ocean warming, and indirect, such as reduced tourism due to coral bleaching. Indirect impacts can also arise from mitigation efforts such as changed agricultural management (Section 3.6.2) or remedial measures such as solar radiation modification (Section 4.3.8, Cross-Chapter Box 10 in Chapter 4).

Impacts may also be triggered by combinations of factors, including ‘impact cascades’ (Cramer et al., 2014)²¹⁸ through secondary consequences of changed systems. Changes in agricultural water availability caused by upstream changes in glacier volume are a typical example. Recent studies also identify compound events (e.g., droughts and heat waves), that is, when impacts are induced by the combination of several climate events (AghaKouchak et al., 2014; Leonard et al., 2014; Martius et al., 2016; Zscheischler and Seneviratne, 2017)²¹⁹.

There are now techniques to attribute impacts formally to anthropogenic global warming and associated rainfall changes (Rosenzweig et al., 2008; Cramer et al., 2014; Hansen et al., 2016)²²⁰, taking into account other drivers such as land-use change (Oliver and Morecroft, 2014)²²¹ and pollution (e.g., tropospheric ozone; Sitch et al., 2007)²²². There are multiple lines of evidence that climate change has observable and often severely negative effects on people, especially where climate-sensitive biophysical conditions and socio-economic and political constraints on adaptive capacities combine to create high vulnerabilities (IPCC, 2012a; 2014a; World Bank, 2013)²²³. The character and severity of impacts depend not only on the hazards (e.g., changed climate averages and extremes) but also on the vulnerability (including sensitivities and adaptive capacities) of different communities and their exposure to climate threats. These impacts also affect a range of natural and human systems, such as terrestrial, coastal and marine ecosystems and their services; agricultural production; infrastructure; the built environment; human health; and other socio-economic systems (Rosenzweig et al., 2017)²²⁴.

Sensitivity to changing drivers varies markedly across systems and regions. Impacts of climate change on natural and managed ecosystems can imply loss or increase in growth, biomass or diversity at the level of species populations, interspecific relationships such as pollination, landscapes or entire biomes. Impacts occur in addition to the natural variation in growth, ecosystem dynamics, disturbance, succession and other processes, rendering attribution of impacts at lower levels of warming difficult in certain situations. The same magnitude of warming can be lethal during one phase of the life of an organism and irrelevant during another. Many ecosystems (notably forests, coral reefs and others) undergo long-term successional processes characterised by varying levels of resilience to environmental change over time. Organisms and ecosystems may adapt to environmental change to a certain degree, through changes in physiology, ecosystem structure, species composition or evolution. Large-scale shifts in ecosystems may cause important feedbacks, in terms of changing water and carbon fluxes through impacted ecosystems – these can amplify or dampen atmospheric change at regional to continental scale. Of particular concern is the response of most of the world’s forests and seagrass ecosystems, which play key roles as carbon sinks (Settele et al., 2014; Marbà et al., 2015)²²⁵.

Some ambitious efforts to constrain atmospheric greenhouse gas concentrations may themselves impact ecosystems. In particular, changes in land use, potentially required for massively enhanced production of biofuels (either as simple replacement of fossil fuels, or as part of bioenergy with carbon capture and storage, BECCS) impact all other land ecosystems through competition for land (e.g., Creutzig, 2016)²²⁶ (see Cross-Chapter Box 7 in Chapter 3, Section 3.6.2.1).

Human adaptive capacity to a 1.5°C warmer world varies markedly for individual sectors and across sectors such as water supply, public health, infrastructure, ecosystems and food supply. For example, density and risk exposure, infrastructure vulnerability and resilience, governance, and institutional capacity all drive different impacts across a range of human settlement types (Dasgupta et al., 2014; Revi et al., 2014; Rosenzweig et al., 2018)²²⁷. Additionally, the adaptive capacity of communities and human settlements in both rural and urban areas, especially in highly populated regions, raises equity, social justice and sustainable development issues. Vulnerabilities due to gender, age, level of education and culture act as compounding factors (Arora-Jonsson, 2011; Cardona et al., 2012; Resurrección, 2013; Olsson et al., 2014; Vincent et al., 2014)²²⁸.

Uncertainties in projections of future climate change and impacts come from a variety of different sources, including the assumptions made regarding future emission pathways (Moss et al., 2010)²²⁹, the inherent limitations and assumptions of the climate models used for the projections, including limitations in simulating regional climate variability (James et al., 2017)²³⁰, downscaling and bias-correction methods (Ekström et al., 2015)²³¹, the assumption of a linear scaling of impacts with GMST used in many studies (Lewis et al., 2017; King et al., 2018b)²³², and in impact models (e.g., Asseng et al., 2013)²³³. The evolution of climate change also affects uncertainty with respect to impacts. For example, the impacts of overshooting 1.5°C and stabilization at a later stage compared to stabilization at 1.5°C without overshoot may differ in magnitude (Schleussner et al., 2016)²³⁴.

AR5 (IPCC, 2013b)²³⁵ and World Bank (2013)²³⁶ underscored the non-linearity of risks and impacts as temperature rises from 2°C to 4°C of warming, particularly in relation to water availability, heat extremes, bleaching of coral reefs, and more. Recent studies (Schleussner et al., 2016; James et al., 2017; Barcikowska et al., 2018; King et al., 2018a)²³⁷ assess the impacts of 1.5°C versus 2°C warming, with the same message of non-linearity. The resilience of ecosystems, meaning their ability either to resist change or to recover after a disturbance, may change, and often decline, in a non-linear way. An example are reef ecosystems, with some studies suggesting that reefs will change, rather than disappear entirely, and with particular species showing greater tolerance to coral bleaching than others (Pörtner et al., 2014)²³⁸. A key issue is therefore whether ecosystems such as coral reefs survive an overshoot scenario, and to what extent they would be able to recover after stabilization at 1.5°C or higher levels of warming (see Box 3.4).

Key broad categories of responses to the climate change problem are framed here. Mitigation refers to efforts to reduce or prevent the emission of greenhouse gases, or to enhance the absorption of gases already emitted, thus limiting the magnitude of future warming (IPCC, 2014b)²⁴². Mitigation requires the use of new technologies, clean energy sources, reduced deforestation, improved sustainable agricultural methods, and changes in individual and collective behaviour. Many of these may provide substantial co-benefits for air quality, biodiversity and sustainable development. Mal-mitigation includes changes that could reduce emissions in the short-term but could lock in technology choices or practices that include significant trade-offs for effectiveness of future adaptation and other forms of mitigation (Chapters 2 and 4).

Carbon dioxide removal (CDR) or ‘negative emissions’ activities are considered in this report as distinct from the above mitigation activities. While most mitigation activities focus on reducing the amount of carbon dioxide or other greenhouse gases emitted, CDR aims to reduce concentrations already in the atmosphere. Technologies for CDR are mostly in their infancy despite their importance to ambitious climate change mitigation pathways (Minx et al., 2017)²⁴³. Although some CDR activities such as reforestation and ecosystem restoration are well understood, the feasibility of massive-scale deployment of many CDR technologies remains an open question (IPCC, 2014d; Leung et al., 2014)²⁴⁴ (Chapters 2 and 4). Technologies for the active removal of other greenhouse gases, such as methane, are even less developed, and are briefly discussed in Chapter 4.

Climate change adaptation refers to the actions taken to manage the impacts of climate change (IPCC, 2014a)²⁴⁵. The aim is to reduce vulnerability and exposure to the harmful effects of climate change (e.g., sea level rise, more intense extreme weather events or food insecurity). It also includes exploring the potential beneficial opportunities associated with climate change (for example, longer growing seasons or increased yields in some regions). Different adaptation pathways can be undertaken. Adaptation can be incremental, or transformational, meaning fundamental attributes of the system are changed (Chapter 3 and 4). There can be limits to ecosystem-based adaptation or the ability of humans to adapt (Chapter 4). If there is no possibility for adaptive actions that can be applied to avoid an intolerable risk, these are referred to as hard adaptation limits, while soft adaptation limits are identified when there are currently no options to avoid intolerable risks, but they are theoretically possible (Chapter 3 and 4). While climate change is a global issue, impacts are experienced locally. Cities and municipalities are at the frontline of adaptation (Rosenzweig et al., 2018)²⁴⁶, focusing on reducing and managing disaster risks due to extreme and slow-onset weather and climate events, installing flood and drought early warning systems, and improving water storage and use (Chapters 3 and 4 and Cross-Chapter Box 12 in Chapter 5). Agricultural and rural areas, including often highly vulnerable remote and indigenous communities, also need to address climate-related risks by strengthening and making more resilient agricultural and other natural resource extraction systems.

Remedial measures are distinct from mitigation or adaptation, as the aim is to temporarily reduce or offset warming (IPCC, 2012b)²⁴⁷. One such measure is solar radiation modification (SRM), also referred to as solar radiation management in the literature, which involves deliberate changes to the albedo of the Earth system, with the net effect of increasing the amount of solar radiation reflected from the Earth to reduce the peak temperature from climate change (The Royal Society, 2009; Smith and Rasch, 2013; Schäfer et al., 2015)²⁴⁸. It should be noted that while some radiation modification measures, such as cirrus cloud thinning (Kristjánsson et al., 2016)²⁴⁹, aim at enhancing outgoing long-wave radiation, SRM is used in this report to refer to all direct interventions on the planetary radiation budget. This report does not use the term ‘geo-engineering’ because of inconsistencies in the literature, which uses this term to cover SRM, CDR or both, whereas this report explicitly differentiates between CDR and SRM. Large-scale SRM could potentially be used to supplement mitigation in overshoot scenarios to keep the global mean temperature below 1.5°C and temporarily reduce the severity of near-term impacts (e.g., MacMartin et al., 2018)²⁵⁰. The impacts of SRM (both biophysical and societal), costs, technical feasibility, governance and ethical issues associated need to be carefully considered (Schäfer et al., 2015²⁵¹; Section 4.3.8 and Cross-Chapter Box 10 in Chapter 4).

A challenge in creating the enabling conditions of a 1.5°C warmer world is the governance capacity of institutions to develop, implement and evaluate the changes needed within diverse and highly interlinked global social-ecological systems (Busby, 2016)²⁵² (Chapter 4). Policy arenas, governance structures and robust institutions are key enabling conditions for transformative climate action (Chapter 4). It is through governance that justice, ethics and equity within the adaptation–mitigation–sustainable development nexus can be addressed (Von Stechow et al., 2016)²⁵³ (Chapter 5).

Governance capacity includes a wide range of activities and efforts needed by different actors to develop coordinated climate mitigation and adaptation strategies in the context of sustainable development, taking into account equity, justice and poverty eradication. Significant governance challenges include the ability to incorporate multiple stakeholder perspectives in the decision-making process to reach meaningful and equitable decisions, interactions and coordination between different levels of government, and the capacity to raise financing and support for both technological and human resource development. For example, Lövbrand et al. (2017)²⁵⁴, argue that the voluntary pledges submitted by states and non-state actors to meet the conditions of the Paris Agreement will need to be more firmly coordinated, evaluated and upscaled.

Barriers for transitioning from climate change mitigation and adaptation planning to practical policy implementation include finance, information, technology, public attitudes, social values and practices (Whitmarsh et al., 2011; Corner and Clarke, 2017)²⁵⁵, and human resource constraints. Institutional capacity to deploy available knowledge and resources is also needed (Mimura et al., 2014)²⁵⁶. Incorporating strong linkages across sectors, devolution of power and resources to sub-national and local governments with the support of national government, and facilitating partnerships among public, civic, private sectors and higher education institutions (Leal Filho et al., 2018)²⁵⁷ can help in the implementation of identified response options (Chapter 4). Implementation challenges of 1.5°C pathways are larger than for those that are consistent with limiting warming to well below 2°C, particularly concerning scale and speed of the transition and the distributional impacts on ecosystems and socio-economic actors. Uncertainties in climate change at different scales and capacities to respond combined with the complexities of coupled social and ecological systems point to a need for diverse and adaptive implementation options within and among different regions involving different actors. The large regional diversity between highly carbon-invested economies and emerging economies are important considerations for sustainable development and equity in pursuing efforts to limit warming to 1.5°C. Key sectors, including energy, food systems, health, and water supply, also are critical to understanding these connections.

Embedded in the goal of limiting warming to 1.5°C is the opportunity for intentional societal transformation (see Box 1.1 on the Anthropocene). The form and process of transformation are varied and multifaceted (Pelling, 2011; O’Brien et al., 2012; O’Brien and Selboe, 2015; Pelling et al., 2015)²⁶¹. Fundamental elements of 1.5°C-related transformation include a decoupling of economic growth from energy demand and CO₂ emissions; leap-frogging development to new and emerging low-carbon, zero-carbon and carbon-negative technologies; and synergistically linking climate mitigation and adaptation to global scale trends (e.g., global trade and urbanization) that will enhance the prospects for effective climate action, as well as enhanced poverty reduction and greater equity (Tschakert et al., 2013; Rogelj et al., 2015; Patterson et al., 2017)²⁶² (Chapters 4 and 5). The connection between transformative climate action and sustainable development illustrates a complex coupling of systems that have important spatial and time scale lag effects and implications for process and procedural equity, including intergenerational equity and for non-human species (Cross-Chapter Box 4 in this chapter, Chapter 5). Adaptation and mitigation transition pathways highlight the importance of cultural norms and values, sector-specific context, and proximate (i.e., occurrence of an extreme event) drivers that when acting together enhance the conditions for societal transformation (Solecki et al., 2017; Rosenzweig et al., 2018)²⁶³ (Chapters 4 and 5).

Diversity and flexibility in implementation choices exist for adaptation, mitigation (including carbon dioxide removal, CDR) and remedial measures (such as solar radiation modification, SRM), and a potential for trade-offs and synergies between these choices and sustainable development (IPCC, 2014d; Olsson et al., 2014)²⁶⁴. The responses chosen could act to synergistically enhance mitigation, adaptation and sustainable development, or they may result in trade-offs which positively impact some aspects and negatively impact others. Climate change is expected to decrease the likelihood of achieving the Sustainable Development Goals (SDGs). While some strategies limiting warming towards 1.5°C are expected to significantly increase the likelihood of meeting those goals while also providing synergies for climate adaptation and mitigation (Chapter 5).

Dramatic transformations required to achieve the enabling conditions for a 1.5°C warmer world could impose trade-offs on dimensions of development (IPCC, 2014c; Olsson et al., 2014)²⁶⁵. Some choices of adaptation methods also could adversely impact development (Olsson et al., 2014)²⁶⁶. This report recognizes the potential for adverse impacts and focuses on finding the synergies between limiting warming, sustainable development, and eradicating poverty, thus highlighting pathways that do not constrain other goals, such as sustainable development and eradicating poverty.

The report is framed to address these multiple goals simultaneously and assesses the conditions to achieve a cost-effective and socially acceptable solution, rather than addressing these goals piecemeal (von Stechow et al., 2016)²⁶⁷ (Section 4.5.4 and Chapter 5), although there may be different synergies and trade-offs between a 2°C (von Stechow et al., 2016)²⁶⁸ and 1.5°C warmer world (Kainuma et al., 2017)²⁶⁹. Climate-resilient development pathways (see Cross-Chapter Box 12 in Chapter 5 and Glossary) are trajectories that strengthen sustainable development, including mitigating and adapting to climate change and efforts to eradicate poverty while promoting fair and cross-scalar resilience in a changing climate. They take into account dynamic livelihoods; the multiple dimensions of poverty, structural inequalities; and equity between and among poor and non-poor people (Olsson et al., 2014)²⁷⁰. Climate-resilient development pathways can be considered at different scales, including cities, rural areas, regions or at global level (Denton et al., 2014²⁷¹; Chapter 5).

This report is based on a comprehensive assessment of documented evidence of the enabling conditions to pursuing efforts to limit the global average temperature rise to 1.5°C and adapting to this level of warming in the overarching context of the Anthropocene (Delanty and Mota, 2017)²⁸⁰. Two sources of evidence are used: peer-reviewed scientific literature and ‘grey’ literature in accordance with procedure on the use of literature in IPCC reports (IPCC, 2013a²⁸¹, Annex 2 to Appendix A), with the former being the dominant source. Grey literature is largely used on key issues not covered in peer-reviewed literature.

The peer-reviewed literature includes the following sources: 1) knowledge regarding the physical climate system and human-induced changes, associated impacts, vulnerabilities, and adaptation options, established from work based on empirical evidence, simulations, modelling, and scenarios, with emphasis on new information since the publication of the IPCC AR5 to the cut-off date for this report (15th of May 2018); 2) humanities and social science theory and knowledge from actual human experiences of climate change risks and vulnerability in the context of social-ecological systems, development, equity, justice, and governance, and from indigenous knowledge systems; and 3) mitigation pathways based on climate projections into the future.

The grey literature category extends to empirical observations, interviews, and reports from government, industry, research institutes, conference proceedings and international or other organisations. Incorporating knowledge from different sources, settings and information channels while building awareness at various levels will advance decision-making and motivate implementation of context-specific responses to 1.5°C warming (Somanathan et al., 2014)²⁸². The assessment does not assess non-written evidence and does not use oral evidence, media reports or newspaper publications. With important exceptions, such as China, published knowledge from the most vulnerable parts of the world to climate change is limited (Czerniewicz et al., 2017)²⁸³.

Climate models and associated simulations

The multiple sources of climate model information used in this assessment are provided in Chapter 2 (Section 2.2) and Chapter 3 (Section 3.2). Results from global simulations, which have also been assessed in previous IPCC reports and that are conducted as part of the World Climate Research Programme (WCRP) Coupled Models Intercomparison Project (CMIP) are used. The IPCC AR4 and Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) reports were mostly based on simulations from the CMIP3 experiment, while the AR5 was mostly based on simulations from the CMIP5 experiment. The simulations of the CMIP3 and CMIP5 experiments were found to be very similar (e.g., Knutti and Sedláček, 2012; Mueller and Seneviratne, 2014)²⁸⁴. In addition to the CMIP3 and CMIP5 experiments, results from coordinated regional climate model experiments (e.g., the Coordinated Regional Climate Downscaling Experiment, CORDEX) have been assessed and are available for different regions (Giorgi and Gutowski, 2015)²⁸⁵. For instance, assessments based on publications from an extension of the IMPACT2C project (Vautard et al., 2014; Jacob and Solman, 2017)²⁸⁶ are newly available for 1.5°C projections. Recently, simulations from the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) multimodel experiment have been performed to specifically assess climate changes at 1.5°C vs 2°C global warming (Mitchell et al., 2016)²⁸⁷. The HAPPI protocol consists of coupled land–atmosphere initial condition ensemble simulations with prescribed sea surface temperatures (SSTs); sea ice, GHG and aerosol concentrations; and solar and volcanic activity that coincide with three forced climate states: present-day (2006–2015) (see Section 1.2.1) and future (2091–2100) either with 1.5°C or 2°C global warming (prescribed by modified SSTs).

Detection and attribution of change in climate and impacted systems

Formalized scientific methods are available to detect and attribute impacts of greenhouse gas forcing on observed changes in climate (e.g., Hegerl et al., 2007; Seneviratne et al., 2012; Bindoff et al., 2013)²⁸⁸ and impacts of climate change on natural and human systems (e.g., Stone et al., 2013; Hansen and Cramer, 2015; Hansen et al., 2016)²⁸⁹. The reader is referred to these sources, as well as to the AR5 for more background on these methods.

Global climate warming has already reached approximately 1°C (see Section 1.2.1) relative to pre-industrial conditions, and thus ‘climate at 1.5°C global warming’ corresponds to approximately the addition of only half a degree of warming compared to the present day, comparable to the warming that has occurred since the 1970s (Bindoff et al., 2013)²⁹⁰. Methods used in the attribution of observed changes associate with this recent warming are therefore also applicable to assessments of future changes in climate at 1.5°C warming, especially in cases where no climate model simulations or analyses are available.

Impacts of 1.5°C global warming can be assessed in part from regional and global climate changes that have already been detected and attributed to human influence (e.g., Schleussner et al., 2017)²⁹¹ and are components of the climate system that are most responsive to current and projected future forcing. For this reason, when specific projections are missing for 1.5°C global warming, some of the assessments of climate change provided in Chapter 3 (Section 3.3) build upon joint assessments of (i) changes that were observed and attributed to human influence up to the present, that is, for 1°C global warming and (ii) projections for higher levels of warming (e.g., 2°C, 3°C or 4°C) to assess the changes at 1.5°C. Such assessments are for transient changes only (see Chapter 3, Section 3.3).

Besides quantitative detection and attribution methods, assessments can also be based on indigenous and local knowledge (see Chapter 4, Box 4.3). While climate observations may not be available to assess impacts from a scientific perspective, local community knowledge can also indicate actual impacts (Brinkman et al., 2016; Kabir et al., 2016)²⁹². The challenge is that a community’s perception of loss due to the impacts of climate change is an area that requires further research (Tschakert et al., 2017)²⁹³.

Costs and benefits analysis

Cost–benefit analyses are common tools used for decision-making, whereby the costs of impacts are compared to the benefits from different response actions (IPCC, 2014a, b)²⁹⁴. However, for the case of climate change, recognising the complex inter-linkages of the Anthropocene, cost–benefit analysis tools can be difficult to use because of disparate impacts versus costs and complex interconnectivity within the global social-ecological system (see Box 1.1 and Cross-Chapter Box 5 in Chapter 2). Some costs are relatively easily quantifiable in monetary terms but not all. Climate change impacts human lives and livelihoods, culture and values, and whole ecosystems. It has unpredictable feedback loops and impacts on other regions (IPCC, 2014a)²⁹⁵, giving rise to indirect, secondary, tertiary and opportunity costs that are typically extremely difficult to quantify. Monetary quantification is further complicated by the fact that costs and benefits can occur in different regions at very different times, possibly spanning centuries, while it is extremely difficult if not impossible to meaningfully estimate discount rates for future costs and benefits. Thus standard cost–benefit analyses become difficult to justify (IPCC, 2014a; Dietz et al., 2016)²⁹⁶ and are not used as an assessment tool in this report.