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

== Cross-Chapter Box 9: Risks, Adaptation Interventions, and Implications for Sustainable Development and Equity Across Four Social-Ecological Systems: Arctic, Caribbean, Amazon, and Urban ==

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====== Lead Authors ======

* Debora Ley (Guatemala, Mexico)
* Malcolm E Araos (Canada)
* Amir Bazaz (India)
* Marcos Buckeridge (Brazil)
* Ines Camilloni (Argentina)
* James Ford (United Kingdom, Canada)
* Bronwyn Hayward (New Zealand)
* Shagun Mehrotra (United States, India)
* Antony Payne (United Kingdom)
* Patricia Fernanda Pinho (Brazil)
* Aromar Revi (India)
* Kevon Rhiney (Jamaica)
* Chandni Singh (India)
* William Solecki (United States)
* Avelino G. Suarez Rodriguez (Cuba)
* Michael Taylor (Jamaica)
* Adelle Thomas (The Bahamas)

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This box presents four case studies from different social-ecological systems as examples of risks of 1.5°C warming and higher (Chapter 3); adaptation options that respond to these risks (Chapter 4); and their implications for poverty, livelihoods and sustainability (Chapter 5). It is not yet possible to generalize adaptation effectiveness across regions due to a lack of empirical studies and monitoring and evaluation of current efforts.

'''Arctic'''

The Arctic is undergoing the most rapid climate change globally (Larsen et al., 2014) <sup>[[#fn:r494|494]]</sup> , warming by 1.9 '''°''' C  over the last 30 years (Walsh, 2014; Grosse et al., 2016) <sup>[[#fn:r495|495]]</sup> . For 2°C of global warming relative to pre-industrial levels, chances of an ice-free Arctic during summer are substantially higher than at 1.5°C (see Chapter 3, Sections 3.3.5 and 3.3.8), with permafrost melt, increased instances of storm surge, and extreme weather events anticipated along with later ice freeze up, earlier break up, and a longer ice-free open water season (Bring et al., 2016; DeBeer et al., 2016; Jiang et al., 2016; Chadburn et al., 2017; Melvin et al., 2017) <sup>[[#fn:r496|496]]</sup> . Negative impacts on health, infrastructure, and economic sectors (AMAP, 2017a, b, 2018) <sup>[[#fn:r497|497]]</sup> are projected, although the extension of the summer ocean-shipping season has potential economic opportunities (Ford et al., 2015b; Dawson et al., 2016; K.Y et al. 2018) <sup>[[#fn:r498|498]]</sup> .

Communities, many with indigenous roots, have adapted to environmental change, developing or shifting harvesting activities and patterns of travel and transitioning economic systems (Forbes et al., 2009; Wenzel, 2009; Ford et al., 2015b; Pearce et al., 2015) <sup>[[#fn:r499|499]]</sup> , although emotional and psychological effects have been documented (Cunsolo Willox et al., 2012; Cunsolo and Ellis, 2018) <sup>[[#fn:r500|500]]</sup> . Besides climate change (Keskitalo et al., 2011; Loring et al., 2016) <sup>[[#fn:r501|501]]</sup> , economic and social conditions can constrain the capacity to adapt unless resources and cooperation are available from public and private sector actors (AMAP, 2017a, 2018) <sup>[[#fn:r502|502]]</sup> (see Chapter 5, Box 5.3). In Alaska, the cumulative economic impacts of climate change on public infrastructure are projected at 4.2 billion USD to 5.5 billion USD from 2015 to 2099, with adaptation efforts halving these estimates (Melvin et al., 2017) <sup>[[#fn:r503|503]]</sup> . Marginalization, colonization, and land dispossession provide broader underlying challenges facing many communities across the circumpolar north in adapting to change (Ford et al., 2015a; Sejersen, 2015) <sup>[[#fn:r504|504]]</sup> (see Section 4.3.5).

Adaptation opportunities include alterations to building codes and infrastructure design, disaster risk management, and surveillance (Ford et al., 2014a; AMAP, 2017a, b; Labbé et al., 2017) <sup>[[#fn:r505|505]]</sup> . Most adaptation initiatives are currently occurring at local levels in response to both observed and projected environmental changes as well as social and economic stresses (Ford et al., 2015a) <sup>[[#fn:r506|506]]</sup> . In a recent study of Canada, most adaptations were found to be in the planning stages (Labbé et al., 2017) <sup>[[#fn:r507|507]]</sup> . Studies have suggested that a number of the adaptation actions are not sustainable, lack evaluation frameworks, and hold potential for maladaptation (Loboda, 2014; Ford et al., 2015a; Larsson et al., 2016) <sup>[[#fn:r508|508]]</sup> . Utilizing indigenous and local knowledge and stakeholder engagement can aid the development of adaptation policies and broader sustainable development, along with more proactive and regionally coherent adaptation plans and actions, and regional cooperation (e.g., through the Arctic Council) (Larsson et al., 2016; AMAP, 2017a; Melvin et al., 2017; Forbis Jr and Hayhoe, 2018) <sup>[[#fn:r509|509]]</sup> (see Section 4.3.5).

'''Caribbean Small Island Developing States (SIDS) and Territories'''

Extreme weather, linked to tropical storms and hurricanes, represent one of the largest risks facing Caribbean island nations (Chapter 3, Section 3.4.5.3). Non-economic damages include detrimental health impacts, forced displacement and destruction of cultural heritages. Projections of increased frequency of the most intense storms at 1.5°C and higher warming levels (Wehner et al., 2018; Chapter 3, Section 3.3.6; Box 3.5) <sup>[[#fn:r510|510]]</sup> are a significant cause for concern, making adaptation a matter of survival (Mycoo and Donovan, 2017) <sup>[[#fn:r511|511]]</sup> .

Despite a shared vulnerability arising from commonalities in location, circumstance and size (Bishop and Payne, 2012; Nurse et al., 2014) <sup>[[#fn:r512|512]]</sup> , adaptation approaches are nuanced by differences in climate governance, affecting vulnerability and adaptive capacity (see Section 4.4.1). Three cases exemplify differences in disaster risk management.

'''Cuba:''' Together with a robust physical infrastructure and human-resource base (Kirk, 2017) <sup>[[#fn:r513|513]]</sup> , Cuba has implemented an effective civil defence system for emergency preparedness and disaster response, centred around community mobilization and preparedness (Kirk, 2017) <sup>[[#fn:r514|514]]</sup> . Legislation to manage disasters, an efficient and robust early warning system, emergency stockpiles, adequate shelter system and continuous training and education of the population help create a ‘culture of risk’ (Isayama and Ono, 2015; Lizarralde et al., 2015) <sup>[[#fn:r515|515]]</sup> which reduces vulnerability to extreme events (Pichler and Striessnig, 2013) <sup>[[#fn:r516|516]]</sup> . Cuba’s infrastructure is still susceptible to devastation, as seen in the aftermath of the 2017 hurricane season.

'''United Kingdom Overseas Territories (UKOT):''' All UKOT have developed National Disaster Preparedness Plans (PAHO/WHO, 2016) <sup>[[#fn:r517|517]]</sup> and are part of the Caribbean Disaster Risk Management Program which aims to improve disaster risk management within the health sector. Different vulnerability levels across the UKOT (Lam et al., 2015) <sup>[[#fn:r518|518]]</sup> indicate the benefits of greater regional cooperation and capacity-building, not only within UKOT, but throughout the Caribbean (Forster et al., 2011) <sup>[[#fn:r519|519]]</sup> . While sovereign states in the region can directly access climate funds and international support, Dependent Territories are reliant on their controlling states (Bishop and Payne, 2012) <sup>[[#fn:r520|520]]</sup> . There tends to be low-scale management for environmental issues in UKOT, which increases UKOT’s vulnerability. Institutional limitations, lack of human and financial resources, and limited long-term planning are identified as barriers to adaptation (Forster et al., 2011) <sup>[[#fn:r521|521]]</sup> .

'''Jamaica:''' Disaster management is coordinated through a hierarchy of national, parish and community disaster committees under the leadership of the Office of Disaster Preparedness and Emergency Management (ODPEM). ODPEM coordinates disaster preparedness and risk-reduction efforts among key state and non-state agencies (Grove, 2013) <sup>[[#fn:r522|522]]</sup> . A National Disaster Committee provides technical and policy oversight to the ODPEM and is composed of representatives from multiple stakeholders (Osei, 2007) <sup>[[#fn:r523|523]]</sup> . Most initiatives are primarily funded through a mix of multilateral and bilateral loan and grant funding focusing on strengthening technical and institutional capacities of state- and research-based institutions and supporting integration of climate change considerations into national and sectoral development plans (Robinson, 2017) <sup>[[#fn:r524|524]]</sup> .

To improve climate change governance in the region, Pittman et al. (2015) <sup>[[#fn:r525|525]]</sup> suggest incorporating holistic and integrated management systems, improving flexibility in collaborative processes, implementing monitoring programs, and increasing the capacity of local authorities. Implementation of the 2030 Sustainable Development Agenda and the Sustainable Development Goals (SDGs) can contribute to addressing the risks related with extreme events (Chapter 5, Box 5.3).

'''The Amazon'''

Terrestrial forests, such as the Amazon, are sensitive to changes in the climate, particularly drought (Laurance and Williamson, 2001) <sup>[[#fn:r526|526]]</sup> which might intensify through the 21st century (Marengo and Espinoza, 2016) <sup>[[#fn:r527|527]]</sup> (Chapter 3, Section 3.5.5.6).

The poorest communities in the region face substantial risks with climate change, and barriers and limits to adaptive capacity (Maru et al., 2014; Pinho et al., 2014, 2015; Brondízio et al., 2016) <sup>[[#fn:r528|528]]</sup> . The Amazon is considered a hotspot, with interconnections between increasing temperature, decreased precipitation and hydrological flow (Betts et al., 2018) <sup>[[#fn:r529|529]]</sup> (Sections 3.3.2.2, 3.3.3.2 and 3.3.5); low levels of socio-economic development (Pinho et al., 2014) <sup>[[#fn:r530|530]]</sup> ; and high levels of climate vulnerability (Darela et al., 2016) <sup>[[#fn:r531|531]]</sup> . Limiting global warming to 1.5°C could increase food and water security in the region compared to 2°C (Betts et al., 2018) <sup>[[#fn:r532|532]]</sup> , reduce the impact on poor people and sustainable development, and make adaptation easier (O’Neill et al., 2017) <sup>[[#fn:r533|533]]</sup> , particularly in the Amazon (Bathiany et al., 2018) <sup>[[#fn:r534|534]]</sup> (Chapter 5, Section 5.2.2).

Climate policy in many Amazonian nations has focused on forests as carbon sinks (Soares-Filho et al., 2010) <sup>[[#fn:r535|535]]</sup> . In 2009, the Brazilian National Policy on Climate Change acknowledged adaptation as a concern, and the government sought to mainstream adaptation into public administration. Brazil’s National Adaptation Plan sets guidelines for sectoral adaptation measures, primarily by developing capacity building, plans, assessments and tools to support adaptive decision-making. Adaptation is increasingly being presented as having mitigation co-benefits in the Brazilian Amazon (Gregorio et al., 2016) <sup>[[#fn:r536|536]]</sup> , especially within ecosystem-based adaptation (Locatelli et al., 2011) <sup>[[#fn:r537|537]]</sup> . In Peru’s Framework Law for Climate Change, every governmental sector will consider climatic conditions as potential risks and/or opportunities to promote economic development and to plan adaptation.

Drought and flood policies have had limited effectiveness in reducing vulnerability (Marengo et al., 2013) <sup>[[#fn:r538|538]]</sup> . In the absence of effective adaptation, achieving the SDGs will be challenging, mainly in poverty, health, water and sanitation, inequality and gender equality (Chapter 5, Section 5.2.3).

'''Urban systems'''

Around 360 million people reside in urban coastal areas where precipitation variability is exposing inadequacies of urban infrastructure and governance, with the poor being especially vulnerable (Reckien et al., 2017) <sup>[[#fn:r539|539]]</sup> (Cross-Chapter Box 13 in Chapter 5). Urban systems have seen growing adaptation action (Revi et al., 2014b; Araos et al., 2016b; Amundsen et al., 2018) <sup>[[#fn:r540|540]]</sup> . Developing cities spend more on health and agriculture-related adaptation options while developed cities spend more on energy and water (Georgeson et al., 2016) <sup>[[#fn:r541|541]]</sup> . Current adaptation activities are lagging in emerging economies, which are major centres of population growth facing complex interrelated pressures on investment in health, housing and education (Georgeson et al., 2016; Reckien et al., 2017) <sup>[[#fn:r542|542]]</sup> .

'''New York, United States:''' Adaptation plans are undertaken across government levels, sectors and departments (NYC Parks, 2010; Vision 2020 Project Team, 2011; PlaNYC, 2013) <sup>[[#fn:r543|543]]</sup> , and have been advanced by an expert science panel that is obligated by local city law to provide regular updates on policy-relevant climate science (NPCC, 2015) <sup>[[#fn:r544|544]]</sup> . Federal initiatives include 2013’s Rebuild By Design competition to promote resilience through infrastructural projects (HSRTF, 2013) <sup>[[#fn:r545|545]]</sup> . In 2013 the Mayor’s office, in response to Hurricane Sandy, published the city’s adaptation strategy (PlaNYC, 2013) <sup>[[#fn:r546|546]]</sup> . In 2015, the OneNYC Plan for a Strong and Just City (OneNYC Team, 2015) <sup>[[#fn:r547|547]]</sup> laid out a strategy for urban planning through a justice and equity lens. In 2017, new climate resiliency guidelines proposed that new construction must include sea level rise projections into planning and development (ORR, 2018) <sup>[[#fn:r548|548]]</sup> . Although this attention to climate-resilient development may help reduce income inequality, its full effect could be constrained if a policy focus on resilience obscures analysis of income redistribution for the poor (Fainstein, 2018) <sup>[[#fn:r549|549]]</sup> .

'''Kampala, Uganda:''' Kampala Capital City Authority (KCCA) has the statutory responsibility for managing the city.  The Kampala Climate Change Action Strategy (KCCAS) is responding to climatic impacts of elevated temperature and more intense, erratic rain. KCCAS has considered multi-scale and temporal aspects of response (Chelleri et al., 2015; Douglas, 2017; Fraser et al., 2017) <sup>[[#fn:r550|550]]</sup> , strengthened community adaptation  (Lwasa, 2010; Dobson, 2017) <sup>[[#fn:r551|551]]</sup> , responded to differential adaptive capacities (Waters and Adger, 2017) <sup>[[#fn:r552|552]]</sup> and believes in participatory processes and bridging of citywide linkages (KCCA, 2016) <sup>[[#fn:r553|553]]</sup> . Analysis of the implications of uniquely adapted local solutions (e.g., motorcycle taxis) suggests sustainability can be enhanced when planning recognizes the need to adapt to uniquely local solutions (Evans et al., 2018) <sup>[[#fn:r554|554]]</sup> .

'''Rotterdam, The Netherlands:''' The Rotterdam Climate Initiative (RCI) was launched to reduce greenhouse gas emissions and climate-proof Rotterdam (RCI, 2017) <sup>[[#fn:r555|555]]</sup> . Rotterdam has an integrated adaptation strategy, built on flood management, accessibility, adaptive building, urban water systems and urban climate, defined through the Rotterdam Climate Proof programme and the Rotterdam Climate Change Adaptation Strategy (RCI, 2008, 2013) <sup>[[#fn:r556|556]]</sup> . Governance mechanisms that enabled integration of flood risk management plans with other policies, citizen participation, institutional eco-innovation, and focusing on green infrastructure (Albers et al., 2015; Dircke and Molenaar, 2015; de Boer et al., 2016a; Huang-Lachmann and Lovett, 2016) <sup>[[#fn:r557|557]]</sup> have contributed to effective adaptation (Ward et al., 2013) <sup>[[#fn:r558|558]]</sup> . Entrenched institutional characteristics constrain the response framework (Francesch-Huidobro et al., 2017) <sup>[[#fn:r559|559]]</sup> , but emerging evidence suggests that new governance arrangements and structures can potentially overcome these barriers in Rotterdam (Hölscher et al., 2018) <sup>[[#fn:r560|560]]</sup> .

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=== 4.3.6 Short-Lived Climate Forcers ===

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The main short-lived climate forcer (SLCF) emissions that cause warming are methane (CH <sub>4</sub> ), other precursors of tropospheric ozone (i.e., carbon monoxide (CO), non-methane volatile organic compounds (NMVOC), black carbon (BC) and hydrofluorocarbons (HFCs); Myhre et al., 2013) <sup>[[#fn:r561|561]]</sup> . SLCFs also include emissions that lead to cooling, such as sulphur dioxide (SO <sub>2</sub> ) and organic carbon (OC). Nitrogen oxides (NOx) can have both warming and cooling effects, by affecting ozone (O <sub>3</sub> ) and CH <sub>4</sub> , depending on time scale and location (Myhre et al., 2013) <sup>[[#fn:r562|562]]</sup> .

Cross-Chapter Box 2 in Chapter 1 provides a discussion of role of SLCFs in comparison to long-lived GHGs. Chapter 2 shows that 1.5°C-consistent pathways require stringent reductions in CO <sub>2</sub> and CH <sub>4</sub> , and that non-CO <sub>2</sub> climate forcers reduce carbon budgets by about 2200 GtCO <sub>2</sub> per degree of warming attributed to them (see the Supplementary Material to Chapter 2).

Reducing non-CO <sub>2</sub> emissions is part of most mitigation pathways (IPCC, 2014c) <sup>[[#fn:r563|563]]</sup> . All current GHG emissions and other forcing agents affect the rate and magnitude of climate change over the next few decades, while long-term warming is mainly driven by CO <sub>2</sub> emissions. CO <sub>2</sub> emissions result in a virtually permanent warming, while temperature change from SLCFs disappears within decades after emissions of SLCFs are ceased. Any scenario that fails to reduce CO <sub>2</sub> emissions to net zero would not limit global warming, even if SLCFs are reduced, due to accumulating CO <sub>2</sub> -induced warming that overwhelms SLCFs’ mitigation benefits in a couple of decades (Shindell et al., 2012; Schmale et al., 2014) <sup>[[#fn:r564|564]]</sup> (and see Chapter 2, Section 2.3.3.2).

Mitigation options for warming SLCFs often overlap with other mitigation options, especially since many warming SLCFs are co-emitted with CO <sub>2</sub> . SLCFs are generally mitigated in 1.5°C- or 2°C-consistent pathways as an integral part of an overall mitigation strategy (Chapter 2). For example Section 2.3 indicates that most very-low-emissions pathways include a transition away from the use of coal and natural gas in the energy sector and oil in transportation, which coincides with emission-reduction strategies related to methane from the fossil fuel sector and BC from the transportation sector. Much SLCF emission reduction aims at BC-rich sectors and considers the impacts of several co-emitted SLCFs (Bond et al., 2013; Sand et al., 2015; Stohl et al., 2015) <sup>[[#fn:r565|565]]</sup> . The benefits of such strategies depend greatly upon the assumed level of progression of access to modern energy for the poorest populations who still rely on biomass fuels, as this affects the reference level of BC emissions (Rogelj et al., 2014) <sup>[[#fn:r566|566]]</sup> .

Some studies have evaluated the focus on SLCFs in mitigation strategies and point towards trade-offs between short-term SLCF benefits and lock-in of long-term CO <sub>2</sub> warming (Smith and Mizrahi, 2013; Pierrehumbert, 2014) <sup>[[#fn:r567|567]]</sup> . Reducing fossil fuel combustion will reduce aerosols levels, and thereby cause warming from removal of aerosol cooling effects (Myhre et al., 2013; Xu and Ramanathan, 2017; Samset et al., 2018) <sup>[[#fn:r568|568]]</sup> . While some studies have found a lower temperature effect from BC mitigation, thus questioning the effectiveness of targeted BC mitigation for climate change mitigation (Myhre et al., 2013; Baker et al., 2015; Stjern et al., 2017; Samset et al., 2018) <sup>[[#fn:r569|569]]</sup> , other models and observationally constrained estimates suggest that these widely-used models do not fully capture observed effects of BC and co-emissions on climate (e.g., Bond et al., 2013; Cui et al., 2016; Peng et al., 2016) <sup>[[#fn:r570|570]]</sup> .

Table 4.5 provides an overview of three warming SLCFs and their emission sources, with examples of options for emission reductions and associated co-benefits.

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'''Table 4.5'''

Overview of main characteristics of three warming short-lived climate forcers (SLCFs) (core information based on Pierrehumbert, 2014 <sup>[[#fn:r571|571]]</sup> and Schmale et al., 2014 <sup>[[#fn:r572|572]]</sup> ; rest of the details as referenced)

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{| class="wikitable"
|-
! SLCF Compound
! Atmospheric Lifetime
! Annual Global Emission
! Main Anthropogenic Emission Sources
! Examples of Options to Reduce Emissions Consistent with 1.5°C
! Examples of Co-Benefits Based on Haines et al. (2017) <sup>[[#fn:r1537|1537]]</sup> Unless Specified Otherwise
|-
| Methane
| On the order of 10 years
| 0.3 GtCH <sub>4</sub> (2010)<br />
(Pierrehumbert, 2014)  <sup>[[#fn:r574|574]]</sup>
| Fossil fuel extraction and transportation;<br />
Land-use change;<br />
Livestock and rice cultivation; Waste and wastewater
| Managing manure from livestock; Intermittent irrigation of rice;<br />
Capture and usage of fugitive methane;<br />
Dietary change;<br />
For more: see Section 4.3.2
| Reduction of tropospheric ozone (Shindell et al., 2017a);  <sup>[[#fn:r575|575]]</sup><br />
Health benefits of dietary changes; Increased crop yields;<br />
Improved access to drinking water
|-
| HFCs
| Months to decades, depending on the gas
| 0.35 GtCO <sub>2</sub> -eq (2010)(Velders et al., 2015)  <sup>[[#fn:r576|576]]</sup>
| Air conditioning; Refrigeration; Construction material
| Alternatives to HFCs in air-conditioning and refrigeration applications
| Greater energy efficiency (Mota-Babiloni et al., 2017)  <sup>[[#fn:r577|577]]</sup>
|-
| Black Carbon
| Days
| ~7 Mt (2010) (Klimont et al., 2017)  <sup>[[#fn:r578|578]]</sup>
| Incomplete combustion of fossil fuels or biomass in vehicles (esp. diesel), cook stoves or kerosene lamps;<br />
Field and biomass burning
| Fewer and cleaner vehicles; Reducing agricultural biomass burning;<br />
Cleaner cook stoves, gas-based<br />
or electric cooking;<br />
Replacing brick and coke ovens;<br />
Solar lamps;<br />
For more see Section 4.3.3
| Health benefits of better air quality;<br />
Increased education opportunities;<br />
Reduced coal consumption for modern brick kilns;<br />
Reduced deforestation
|}
<!-- END TABLE -->

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A wide range of options to reduce SLCF emissions was extensively discussed in AR5 (IPCC, 2014b) <sup>[[#fn:r579|579]]</sup> . Fossil fuel and waste sector methane mitigation options have high cost-effectiveness, producing a net profit over a few years, considering market costs only. Moreover, reducing roughly one-third to one-half of all human-caused emissions has societal benefits greater than mitigation costs when considering environmental impacts only (UNEP, 2011; Höglund-Isaksson, 2012; IEA, 2017b; Shindell et al., 2017a) <sup>[[#fn:r580|580]]</sup> . Since AR5, new options for methane, such as those related to shale gas, have been included in mitigation portfolios (e.g., Shindell et al., 2017a) <sup>[[#fn:r581|581]]</sup> .

Reducing BC emissions and co-emissions has sustainable development co-benefits, especially around human health (Stohl et al., 2015; Haines et al., 2017; Aakre et al., 2018) <sup>[[#fn:r582|582]]</sup> , avoiding premature deaths and increasing crop yields (Scovronick et al., 2015; Peng et al., 2016) <sup>[[#fn:r583|583]]</sup> . Additional benefits include lower likelihood of non-linear climate changes and feedbacks (Shindell et al., 2017b) <sup>[[#fn:r584|584]]</sup> and temporarily slowing down the rate of sea level rise (Hu et al., 2013) <sup>[[#fn:r585|585]]</sup> . Interventions to reduce BC offer tangible local air quality benefits, increasing the likelihood of local public support (Eliasson, 2014; Venkataraman et al., 2016) <sup>[[#fn:r586|586]]</sup> (see Chapter 5, Section 5.4.2.1). Limited interagency co-ordination, poor science-policy interactions (Zusman et al., 2015) <sup>[[#fn:r587|587]]</sup> , and weak policy and absence of inspections and enforcement (Kholod and Evans, 2016) <sup>[[#fn:r588|588]]</sup> are among barriers that reduce the institutional feasibility of options to reduce vehicle-induced BC emissions. A case study for India shows that switching from biomass cook stoves to cleaner gas stoves (based on liquefied petroleum gas or natural gas) or to electric cooking stoves is technically and economically feasible in most areas, but faces barriers in user preferences, costs and the organization of supply chains (Jeuland et al., 2015) <sup>[[#fn:r589|589]]</sup> . Similar feasibility considerations emerge in switching from kerosene wick lamps for lighting to solar lanterns, from current low-efficiency brick kilns and coke ovens to cleaner production technologies; and from field burning of crop residues to agricultural practices using deep-sowing and mulching technologies (Williams et al., 2011; Wong, 2012) <sup>[[#fn:r590|590]]</sup> .

The radiative forcing from HFCs are currently small but have been growing rapidly (Myhre et al., 2013) <sup>[[#fn:r591|591]]</sup> . <sub> </sub> The Kigali Amendment (from 2016) to the Montreal Protocol set out a global accord for phasing out these compounds (Höglund-Isaksson et al., 2017) <sup>[[#fn:r592|592]]</sup> . HFC mitigation options include alternatives with reduced warming effects, ideally combined with improved energy efficiency so as to simultaneously reduce CO <sub>2</sub> and co-emissions (Shah et al., 2015) <sup>[[#fn:r593|593]]</sup> . Costs for most of HFC’s mitigation potential are estimated to be below USD <sub>2010</sub> 60 tCO <sub>2</sub> -eq <sup>−1</sup> , and the remainder below roughly double that number (Höglund-Isaksson et al., 2017) <sup>[[#fn:r594|594]]</sup> .

Reductions in SLCFs can provide large benefits towards sustainable development, beneficial for social, institutional and economic feasibility. Strategies that reduce SLCFs can provide benefits that include improved air quality (e.g., Anenberg et al., 2012) <sup>[[#fn:r595|595]]</sup> and crop yields (e.g., Shindell et al., 2012) <sup>[[#fn:r596|596]]</sup> , energy access, gender equality and poverty eradication (e.g.,Shindell et al., 2012; Haines et al., 2017) <sup>[[#fn:r597|597]]</sup> . Institutional feasibility can be negatively affected by an information deficit, with the absence of international frameworks for integrating SLCFs into emissions accounting and reporting mechanisms being a barrier to developing policies for addressing SLCF emissions (Venkataraman et al., 2016) <sup>[[#fn:r598|598]]</sup> . The incentives for reducing SLCFs are particularly strong for small groups of countries, and such collaborations could increase the feasibility and effectiveness of SLCF mitigation options (Aakre et al., 2018) <sup>[[#fn:r599|599]]</sup> .

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=== 4.3.7 Carbon Dioxide Removal (CDR) ===

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CDR methods refer to a set of techniques for removing CO <sub>2</sub> from the atmosphere. In the context of 1.5°C-consistent pathways (Chapter 2), they serve to offset residual emissions and, in most cases, achieve net negative emissions to return to 1.5°C from an overshoot. See Cross-Chapter Box 7 in Chapter 3 for a synthesis of land-based CDR options. Cross-cutting issues and uncertainties are summarized in Table 4.6.

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==== 4.3.7.1 Bioenergy with carbon capture and storage (BECCS) ====

<div id="section-4-3-3-7-1-block-1"></div>

BECCS has been assessed in previous IPCC reports (IPCC, 2005b, 2014b; P. Smith et al., 2014; Minx et al., 2017) <sup>[[#fn:r600|600]]</sup> and has been incorporated into integrated assessment models (Clarke et al., 2014) <sup>[[#fn:r601|601]]</sup> but also, 1.5°C-consistent pathways without BECCS have emerged (Bauer et al., 2018; Grubler et al., 2018; Mousavi and Blesl, 2018; van Vuuren et al., 2018) <sup>[[#fn:r602|602]]</sup> . Still, the overall set of  pathways limiting global warming to 1.5°C with limited or no overshoot indicates that 0–1, 0–8, and 0–16 GtCO <sub>2</sub> yr <sup>−1</sup> would be removed by BECCS by 2030, 2050 and 2100, respectively (Chapter 2, Section 2.3.4). BECCS is constrained by sustainable bioenergy potentials (Section 4.3.1.2, Chapter 5, Section 5.4.1.3 and Cross-Chapter Box 6 in Chapter 3), and availability of safe storage for CO <sub>2</sub> (Section 4.3.1.6). Literature estimates for BECCS mitigation potentials in 2050 range from 1–85 GtCO <sup>[[#fn:4|4]]</sup> . Fuss et al. (2018) <sup>[[#fn:r603|603]]</sup> narrow this range to 0.5–5 GtCO <sub>2</sub> yr <sup>−1</sup> ( ''medium agreement, high evidence'' ) (Figure 4.3), meaning that BECCS mitigation potentials are not necessarily sufficient for 1.5°C-consistent pathways. This is, among other things, related to sustainability concerns (Boysen et al., 2017; Heck et al., 2018; Henry et al., 2018) <sup>[[#fn:r604|604]]</sup> .

Assessing BECCS deployment in 2°C pathways (of about 12 GtCO <sub>2</sub> -eq yr <sup>−1</sup> by 2100, considered as a conservative deployment estimate for BECCS-accepting pathways consistent with 1.5°C), Smith et al. (2016b) <sup>[[#fn:r605|605]]</sup> estimate a land-use intensity of 0.3–0.5 ha tCO <sub>2</sub> -eq <sup>−1</sup> yr <sup>−1</sup> using forest residues, 0.16 ha CO <sub>2</sub> -eq <sup>−1</sup> yr <sup>−1</sup> for agricultural residues, and 0.03–0.1 ha tCO <sub>2</sub> -eq <sup>−1</sup> yr <sup>−1</sup> for purpose-grown energy crops. The average amount of BECCS in these pathways requires 25–46% of arable and permanent crop area in 2100. Land area estimates differ in scale and are not necessarily a good indicator of competition with, for example, food production, because requiring a smaller land area for the same potential could indicate that high-productivity agricultural land is used. In general, the literature shows ''low agreement'' on the availability of land (Fritz et al., 2011 <sup>[[#fn:r606|606]]</sup> ; see Erb et al., 2016b <sup>[[#fn:r607|607]]</sup> for recent advances). Productivity, food production and competition with other ecosystem services and land use by local communities are important factors for designing regulation. These potentials and trade-offs are not homogenously distributed across regions. However, Robledo-Abad et al. (2017) <sup>[[#fn:r608|608]]</sup> find that regions with higher potentials are understudied, given their potential contribution. Researchers have expressed the need to complement global assessments with regional, geographically explicit bottom-up studies of biomass potentials and socio-economic impacts (e.g., de Wit and Faaij, 2010; Kraxner et al., 2014; Baik et al., 2018) <sup>[[#fn:r609|609]]</sup> .

Energy production and land and water footprints show wide ranges in bottom-up assessments due to differences in technology, feedstock and other parameters (−1–150 EJ yr <sup>−1</sup> of energy, 109–990 Mha, 6–79 MtN, 218–4758 km <sup>3</sup> yr <sup>−1</sup> of water per GtCO <sub>2</sub> yr <sup>−1</sup> ; Smith and Torn, 2013; Smith et al., 2016b; Fajardy and Mac Dowell, 2017) <sup>[[#fn:r610|610]]</sup> and are not comparable to IAM pathways which consider system effects (Bauer et al., 2018) <sup>[[#fn:r611|611]]</sup> . Global impacts on nutrients and albedo are difficult to quantify (Smith et al., 2016b) <sup>[[#fn:r612|612]]</sup> . BECCS competes with other land-based CDR and mitigation measures for resources (Chapter 2).

There is uncertainty about the feasibility of timely upscaling (Nemet et al., 2018) <sup>[[#fn:r613|613]]</sup> . CCS (see Section 4.3.1) is largely absent from the Nationally Determined Contributions (Spencer et al., 2015) <sup>[[#fn:r614|614]]</sup> and lowly ranked in investment priorities (Fridahl, 2017) <sup>[[#fn:r615|615]]</sup> . Although there are dozens of small-scale BECCS demonstrations (Kemper, 2015) <sup>[[#fn:r616|616]]</sup> and a full-scale project capturing 1 MtCO <sub>2</sub> exists (Finley, 2014) <sup>[[#fn:r617|617]]</sup> ''',''' this is well below the numbers associated with 1.5°C or 2°C-compatible pathways (IEA, 2016a; Peters et al., 2017) <sup>[[#fn:r618|618]]</sup> . Although the majority of BECCS cost estimates are below 200 USD tCO  <sup>−1</sup> (Figure 4.2), estimates vary widely. Economic incentives for ramping up large CCS or BECCS infrastructure are weak (Bhave et al., 2017) <sup>[[#fn:r619|619]]</sup> . The 2050 average investment costs for such a BECCS infrastructure for bio-electricity and biofuels are estimated at 138 and 123 billion USD yr <sup>−1</sup> , respectively (Smith et al., 2016b) <sup>[[#fn:r620|620]]</sup> .

BECCS deployment is further constrained by bioenergy’s carbon accounting, land, water and nutrient requirements (Section 4.3.1), its compatibility with other policy goals and limited public acceptance of both bioenergy and CCS (Section 4.3.1). Current pathways are believed to have inadequate assumptions on the development of societal support and governance structures (Vaughan and Gough, 2016) <sup>[[#fn:r621|621]]</sup> . However, removing BECCS and CCS from the portfolio of available options significantly raises modelled mitigation costs (Kriegler et al., 2013; Bauer et al., 2018) <sup>[[#fn:r622|622]]</sup> .

<div id="section-4-3-3-7-1-block-2"></div>

<span id="figure-4.2"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 4.2'''

<span id="evidence-on-carbon-dioxide-removal-cdr-abatement-costs-2050-deployment-potentials-and-key-side-effects."></span>
<!-- IMG CAPTION -->
'''Evidence on carbon dioxide removal (CDR) abatement costs, 2050 deployment potentials, and key side effects.'''
<!-- IMG FILE -->
[[File:d868fe4092f4229ebcec7975ddc2c6f4 fig-4.2-768x1024.jpg]]

Panel A presents estimates based on a systematic review of the bottom up literature (Fuss et al., 2018) <sup>[[#fn:r623|623]]</sup> , corresponding to dashed blue boxes in Panel B. Dashed lines represent saturation limits for the corresponding technology. Panel B shows the percentage of papers at a given cost or potential estimate. Reference year for all potential estimates is 2050, while all cost estimates preceding 2050 have been included (as early as 2030, older estimates are excluded if they lack a base year and thus cannot be made comparable). Ranges have been trimmed to show detail (see Fuss et al., 2018 <sup>[[#fn:r624|624]]</sup> for the full range). Costs refer only to abatement costs. Icons for side-effects are allocated only if a critical mass of papers corroborates their occurrence

Notes: For references please see Supplementary Material Table 4.SM.3. Direct air carbon dioxide capture and storage (DACCS) is theoretically only constrained by geological storage capacity, estimates presented are considering upscaling and cost challenges (Nemet et al., 2018) <sup>[[#fn:r625|625]]</sup> . BECCS potential estimates are based on bioenergy estimates in the literature (EJ yr <sup>−1</sup> ), converted to GtCO <sub>2</sub> following footnote 4. Potentials cannot be added up, as CDR options would compete for resources (e.g., land). SCS – soil carbon sequestration; OA – ocean alkalinization; EW- enhanced weathering; DACCS – direct air carbon dioxide capture and storage; BECCS – bioenergy with carbon capture and storage; AR – afforestation

<!-- END IMG -->
<div id="section-4-3-7-2"></div>

<span id="afforestation-and-reforestation-ar"></span>
==== 4.3.7.2 Afforestation and reforestation (AR) ====

<div id="section-4-3-7-2-block-1"></div>

Afforestation implies planting trees on land not forested for a long time (e.g., over the last 50 years in the context of the Kyoto Protocol), while reforestation implies re-establishment of forest formations after a temporary condition with less than 10% canopy cover due to human-induced or natural perturbations. Houghton et al. (2015) <sup>[[#fn:r626|626]]</sup> estimate about 500 Mha could be available for the re-establishment of forests on lands previously forested, but not currently used productively. This could sequester at least 3.7 GtCO <sub>2</sub> yr <sup>−1</sup> for decades. The full literature range gives 2050 potentials of 1–7 GtCO <sub>2</sub> yr <sup>−1</sup> ( ''low evidence, medium agreement'' ), narrowed down to 0.5–3.6 GtCO <sub>2</sub> yr <sup>−1</sup> based on a number of constraints (Fuss et al., 2018) <sup>[[#fn:r627|627]]</sup> . Abatement costs are estimated to be low compared to other CDR options, 5–50 USD tCO <sub>2</sub> -eq <sup>−1</sup> ( ''robust evidence, high agreement'' ). Yet, realizing such large potentials comes at higher land and water footprints than BECCS, although there would be a positive impact on nutrients and the energy requirement would be negligible (Smith et al., 2016b <sup>[[#fn:r628|628]]</sup> ; Cross-Chapter Box 7 in Chapter 3). The 2030 estimate by Griscom et al. (2017) <sup>[[#fn:r629|629]]</sup> is up to 17.9 GtCO <sub>2</sub> yr <sup>−1</sup> for reforestation with significant co-benefits (Cross-Chapter Box 7 in Chapter 3).

Biogenic storage is not as permanent as emission reductions by geological storage. In addition, forest sinks saturate, a process which typically occurs in decades to centuries compared to the thousands of years of residence time of CO <sub>2</sub> stored geologically (Smith et al., 2016a) <sup>[[#fn:r630|630]]</sup> and is subject to disturbances that can be exacerbated by climate change (e.g., drought, forest fires and pests) (Seidl et al., 2017) <sup>[[#fn:r631|631]]</sup> . Handling these challenges requires careful forest management. There is much practical experience with AR, facilitating upscaling but with two caveats: AR potentials are heterogeneously distributed (Bala et al., 2007) <sup>[[#fn:r632|632]]</sup> , partly because the planting of less reflective forests results in higher net absorbed radiation and localised surface warming in higher latitudes (Bright et al., 2015; Jones et al., 2015) <sup>[[#fn:r633|633]]</sup> , and forest governance structures and monitoring capacities can be bottlenecks and are usually not considered in models (Wang et al., 2016; Wehkamp et al., 2018b) <sup>[[#fn:r634|634]]</sup> . There is ''medium agreement'' on the positive impacts of AR on ecosystems and biodiversity due to different forms of afforestation discussed in the literature: afforestation of grassland ecosystems or diversified agricultural landscapes with monocultures or invasive alien species can have significant negative impacts on biodiversity, water resources, etc. (P. Smith et al., 2014) <sup>[[#fn:r635|635]]</sup> , while forest ecosystem restoration (forestry and agroforestry) with native species can have positive social and environmental impacts (Cunningham et al., 2015; Locatelli et al., 2015; Paul et al., 2016 <sup>[[#fn:r636|636]]</sup> ; See Section 4.3.2).

Synergies with other policy goals are possible (see also Section 4.5.4); for example, land spared by diet shifts could be afforested (Röös et al., 2017) <sup>[[#fn:r637|637]]</sup> or used for energy crops (Grubler et al., 2018) <sup>[[#fn:r638|638]]</sup> . Such land-sparing strategies could also benefit other land-based CDR options.

<div id="section-4-3-7-3"></div>

<span id="soil-carbon-sequestration-and-biochar"></span>
==== 4.3.7.3 Soil carbon sequestration and biochar ====

<div id="section-4-3-7-3-block-1"></div>

At local scales there is ''robust evidence'' that soil carbon sequestration (SCS, e.g., agroforestry, De Stefano and Jacobson, 2018) <sup>[[#fn:r639|639]]</sup> , restoration of degraded land (Griscom et al., 2017) <sup>[[#fn:r640|640]]</sup> , or conservation agriculture management practices (Aguilera et al., 2013; Poeplau and Don, 2015; Vicente-Vicente et al., 2016) <sup>[[#fn:r641|641]]</sup> have co-benefits in agriculture and that many measures are cost-effective even without supportive climate policy. Evidence at global scale for potentials and especially costs is much lower. The literature spans cost ranges of −45–100 USD tCO <sub>2</sub> <sup>−1</sup> (negative costs relating to the multiple co-benefits of SCS, such as increased productivity and resilience of soils; P. Smith et al., 2014) <sup>[[#fn:r642|642]]</sup> , and 2050 potentials are estimated at between 0.5 and 11 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> , narrowed down to 2.3–5.3 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> considering that studies above 5 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> often do not apply constraints, while estimates lower than 2 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> mostly focus on single practices (Fuss et al., 2018) <sup>[[#fn:r643|643]]</sup> .

SCS has negligible water and energy requirements (Smith, 2016) <sup>[[#fn:r644|644]]</sup> , affects nutrients and food security favourably ( ''high agreement, robust evidence'' ) and can be applied without changing current land use, thus making it socially more acceptable than CDR options with a high land footprint. However, soil sinks saturate after 10–100 years, depending on the SCS option, soil type and climate zone (Smith, 2016) <sup>[[#fn:r645|645]]</sup> .

Biochar is formed by recalcitrant (i.e., very stable) organic carbon obtained from pyrolysis, which, applied to soil, can increase soil carbon sequestration leading to improved soil fertility properties. <sup>[[#fn:5|5]]</sup> Looking at the full literature range, the global potential in 2050 lies between 1 and 35 Gt CO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> ( ''low agreement, low evidence'' ), but considering limitations in biomass availability and uncertainties due to a lack of large-scale trials of biochar application to agricultural soils under field conditions, Fuss et al. (2018) <sup>[[#fn:r646|646]]</sup> lower the 2050 range to 0.3–2 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> . This potential is below previous estimates (e.g., Woolf et al., 2010) <sup>[[#fn:r647|647]]</sup> , which additionally consider the displacement of fossil fuels through biochar. Permanence depends on soil type and biochar production temperatures, varying between a few decades and several centuries (Fang et al., 2014) <sup>[[#fn:r648|648]]</sup> . Costs are 30– 120 USD tCO <sub>2</sub> <sup>−1</sup> ( ''medium agreement, medium evidence'' ) (McCarl et al., 2009; McGlashan et al., 2012; McLaren, 2012; Smith, 2016) <sup>[[#fn:r649|649]]</sup> .

Water requirements are low and at full theoretical deployment, up to 65 EJ yr <sup>−1</sup> of energy could be generated as a side product (Smith, 2016) <sup>[[#fn:r650|650]]</sup> . Positive side effects include a favourable effect on nutrients and reduced N <sub>2</sub> O emissions (Cayuela et al., 2014; Kammann et al., 2017) <sup>[[#fn:r651|651]]</sup> . However, 40–260 Mha are needed to grow the biomass for biochar for implementation at 0.3 GtCO <sub>2</sub> -eq yr <sup>−1</sup> (Smith, 2016) <sup>[[#fn:r652|652]]</sup> , even though it is also possible to use residues (e.g., Windeatt et al., 2014) <sup>[[#fn:r653|653]]</sup> . Biochar is further constrained by the maximum safe holding capacity of soils (Lenton, 2010) <sup>[[#fn:r654|654]]</sup> and the labile nature of carbon sequestrated in plants and soil at higher temperatures (Wang et al., 2013) <sup>[[#fn:r655|655]]</sup> .

<div id="section-4-3-7-4"></div>

<span id="enhanced-weathering-ew-and-ocean-alkalinization"></span>
==== 4.3.7.4 Enhanced weathering (EW) and ocean alkalinization ====

<div id="section-4-3-7-4-block-1"></div>

Weathering is the natural process of rock decomposition via chemical and physical processes in which CO <sub>2</sub> is spontaneously consumed and converted to solid or dissolved alkaline bicarbonates and/or carbonates (IPCC, 2005a) <sup>[[#fn:r656|656]]</sup> . The process is controlled by temperature, reactive surface area, interactions with biota and, in particular, water solution composition. CDR can be achieved by accelerating mineral weathering through the distribution of ground-up rock material over land (Hartmann and Kempe, 2008; Wilson et al., 2009; Köhler et al., 2010; Renforth, 2012; ten Berge et al., 2012; Manning and Renforth, 2013; Taylor et al., 2016) <sup>[[#fn:r657|657]]</sup> , shorelines (Hangx and Spiers, 2009; Montserrat et al., 2017) <sup>[[#fn:r658|658]]</sup> or the open ocean (House et al., 2007; Harvey, 2008; Köhler et al., 2013; Hauck et al., 2016) <sup>[[#fn:r659|659]]</sup> . Ocean alkalinization adds alkalinity to marine areas to locally increase the CO <sub>2</sub> buffering capacity of the ocean (González and Ilyina, 2016; Renforth and Henderson, 2017) <sup>[[#fn:r660|660]]</sup> .

In the case of land application of ground minerals, the estimated CDR potential range is 0.72–95 GtCO <sub>2</sub> yr <sup>−1</sup> ( ''low evidence, low agreement'' ) (Hartmann and Kempe, 2008; Köhler et al., 2010; Hartmann et al., 2013; Taylor et al., 2016; Strefler et al., 2018a) <sup>[[#fn:r661|661]]</sup> . Marine application of ground minerals is limited by feasible rates of mineral extraction, grinding and delivery, with estimates of  1–6 GtCO <sub>2</sub> yr <sup>−1</sup> ( ''low evidence, low agreement'' ) (Köhler et al., 2013; Hauck et al., 2016; Renforth and Henderson, 2017) <sup>[[#fn:r662|662]]</sup> . Agreement is low due to a variety of assumptions and unknown parameter ranges in the applied modelling procedures that would need to be verified by field experiments (Fuss et al., 2018) <sup>[[#fn:r663|663]]</sup> . As with other CDR options, scaling and maturity are challenges, with deployment at scale potentially requiring decades (NRC, 2015a) <sup>[[#fn:r664|664]]</sup> , considerable costs in transport and disposal (Hangx and Spiers, 2009; Strefler et al., 2018a) <sup>[[#fn:r665|665]]</sup> and mining (NRC, 2015a; Strefler et al., 2018a) <sup>[[#fn:r666|666]]</sup> <sup>[[#fn:6|6]]</sup> .

Site-specific cost estimates vary depending on the chosen technology for rock grinding (an energy-intensive process; Köhler et al., 2013; Hauck et al., 2016) <sup>[[#fn:r667|667]]</sup> , material transport, and rock source (Renforth, 2012; Hartmann et al., 2013) <sup>[[#fn:r668|668]]</sup> , and range from 15–40 USD tCO <sub>2</sub> <sup>−1</sup> to 3,460 USD tCO <sub>2</sub> <sup>−1</sup> ( ''limited evidence, low agreement'' ; Figure 4.2) (Schuiling and Krijgsman, 2006; Köhler et al., 2010; Taylor et al., 2016) <sup>[[#fn:r669|669]]</sup> . The evidence base for costs of ocean alkalinization and marine enhanced weathering is sparser than the land applications. The ocean alkalinization potential is assessed to be 0.1–10 GtCO <sub>2</sub> yr <sup>−1</sup> with costs of 14– &gt;500 USD tCO <sub>2</sub> <sup>−1</sup> (Renforth and Henderson, 2017) <sup>[[#fn:r670|670]]</sup> .

The main side effects of terrestrial EW are an increase in water pH (Taylor et al., 2016) <sup>[[#fn:r671|671]]</sup> , the release of heavy metals like Ni and Cr and plant nutrients like K, Ca, Mg, P and Si (Hartmann et al., 2013) <sup>[[#fn:r672|672]]</sup> , and changes in hydrological soil properties. Respirable particle sizes, though resulting in higher potentials, can have impacts on health (Schuiling and Krijgsman, 2006; Taylor et al., 2016) <sup>[[#fn:r673|673]]</sup> ; utilization of wave-assisted decomposition through deployment on coasts could avert the need for fine grinding (Hangx and Spiers, 2009; Schuiling and de Boer, 2010) <sup>[[#fn:r674|674]]</sup> . Side effects of marine EW and ocean alkalinization are the potential release of heavy metals like Ni and Cr (Montserrat et al., 2017) <sup>[[#fn:r675|675]]</sup> . Increasing ocean alkalinity helps counter ocean acidification (Albright et al., 2016; Feng et al., 2016) <sup>[[#fn:r676|676]]</sup> . Ocean alkalinization could affect ocean biogeochemical functioning (González and Ilyina, 2016) <sup>[[#fn:r677|677]]</sup> . A further caveat of relates to saturation state and the potential to trigger spontaneous carbonate precipitation. <sup>[[#fn:7|7]]</sup> While the geochemical potential to remove and store CO <sub>2</sub> is quite large, ''limited evidence'' on the preceding topics makes it difficult to assess the true capacity, net benefits and desirability of EW and ocean alkalinity addition in the context of CDR.

<div id="section-4-3-7-5"></div>

<span id="direct-air-carbon-dioxide-capture-and-storage-daccs"></span>
==== 4.3.7.5 Direct air carbon dioxide capture and storage (DACCS) ====

<div id="section-4-3-7-5-block-1"></div>

Capturing CO <sub>2</sub> from ambient air through chemical processes with subsequent storage of the CO <sub>2</sub> in geological formations is independent of source and timing of emissions and can avoid competition for land. Yet, this is also the main challenge: while the theoretical potential for DACCS is mainly limited by the availability of safe and accessible geological storage, the CO <sub>2</sub> concentration in ambient air is 100–300 times lower than at gas- or coal-fired power plants (Sanz-Pérez et al., 2016) <sup>[[#fn:r678|678]]</sup> thus requiring more energy than flue gas CO <sub>2</sub> capture (Pritchard et al., 2015) <sup>[[#fn:r679|679]]</sup> . This appears to be the main challenge to DACCS (Sanz-Pérez et al., 2016; Barkakaty et al., 2017) <sup>[[#fn:r680|680]]</sup> .

Studies explore alternative techniques to reduce the energy penalty of DACCS (van der Giesen et al., 2017) <sup>[[#fn:r681|681]]</sup> . Energy consumption could be up to 12.9 GJ tCO <sub>2</sub> -eq <sup>−1</sup> ; translating into an average of 156 EJ yr <sup>−1</sup> by 2100 (current annual global primary energy supply is 600 EJ); water requirements are estimated to average 0.8–24.8 km <sup>3</sup> GtCO <sub>2</sub> -eq <sup>−1</sup> yr <sup>−1</sup>  (Smith et al., 2016b, based on Socolow et al., 2011) <sup>[[#fn:r682|682]]</sup> .

However, the literature shows ''low agreement'' and is fragmented (Broehm et al., 2015) <sup>[[#fn:r683|683]]</sup> . This fragmentation is reflected in a large range of cost estimates: from 20–1,000 USD tCO <sub>2</sub> <sup>−1</sup> (Keith et al., 2006; Pielke, 2009; House et al., 2011; Ranjan and Herzog, 2011; Simon et al., 2011; Goeppert et al., 2012; Holmes and Keith, 2012; Zeman, 2014; Sanz-Pérez et al., 2016; Sinha et al., 2017) <sup>[[#fn:r684|684]]</sup> . There is lower agreement and a smaller evidence base at the lower end of the cost range. Fuss et al. (2018) <sup>[[#fn:r685|685]]</sup> narrow this range to 100–300 USD tCO <sub>2</sub> <sup>-1</sup> .

Research and efforts by small-scale commercialization projects focus on utilization of captured CO <sub>2</sub> (Wilcox et al., 2017) <sup>[[#fn:r686|686]]</sup> . Given that only a few IAM scenarios incorporate DACCS (e.g., Chen and Tavoni, 2013; <sup>[[#fn:r687|687]]</sup> Strefler et al., 2018b) <sup>[[#fn:r688|688]]</sup> its possible role in cost-optimized 1.5°C scenarios is not yet fully explored. Given the technology’s early stage of development (McLaren, 2012; NRC, 2015a; Nemet et al., 2018) <sup>[[#fn:r689|689]]</sup> and few demonstrations (Holmes et al., 2013; Rau et al., 2013; Agee et al., 2016) <sup>[[#fn:r690|690]]</sup> , deploying the technology at scale is still a considerable challenge, though both optimistic (Lackner et al., 2012) <sup>[[#fn:r691|691]]</sup> and pessimistic outlooks exist (Pritchard et al., 2015) <sup>[[#fn:r692|692]]</sup> .

<div id="section-4-3-7-6"></div>

<span id="ocean-fertilization"></span>
==== 4.3.7.6 Ocean fertilization ====

<div id="section-4-3-7-6-block-1"></div>

Nutrients can be added to the ocean resulting in increased biologic production, leading to carbon fixation in the sunlit ocean and subsequent sequestration in the deep ocean or sea floor sediments. The added nutrients can be either micronutrients (such as iron) or macronutrients (such as nitrogen and/or phosphorous) (Harrison, 2017) <sup>[[#fn:r693|693]]</sup> . There is ''limited evidence'' and ''low agreement'' on the readiness of this technology to contribute to rapid decarbonization (Williamson et al., 2012) <sup>[[#fn:r694|694]]</sup> . Only small-scale field experiments and theoretical modelling have been conducted (e.g., McLaren, 2012) <sup>[[#fn:r695|695]]</sup> . The full range of CDR potential estimates is from 15.2 ktCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> (Bakker et al., 2001) <sup>[[#fn:r696|696]]</sup> for a spatially constrained field experiment up to 44 GtCO <sub>2</sub> yr <sup>−</sup> <sup>1</sup> (Sarmiento and Orr, 1991) <sup>[[#fn:r697|697]]</sup> following a modelling approach, but Fuss et al. (2018) <sup>[[#fn:r698|698]]</sup> consider the potential to be extremely limited given the evidence and existing barriers. Due to scavenging of iron, the iron addition only leads to inefficient use of the nitrogen in exporting carbon (Zeebe, 2005; Aumont and Bopp, 2006; Zahariev et al., 2008) <sup>[[#fn:r699|699]]</sup> .

Cost estimates range from 2 USD tCO <sub>2</sub> <sup>−</sup> <sup>1</sup> (for iron fertilization) (Boyd and Denman, 2008) <sup>[[#fn:r700|700]]</sup> to 457 USD tCO <sub>2</sub> <sup>−</sup> <sup>1</sup> (Harrison, 2013) <sup>[[#fn:r701|701]]</sup> . Jones (2014) <sup>[[#fn:r702|702]]</sup> proposed values greater than 20 USD tCO <sub>2</sub> <sup>−</sup> <sup>1</sup> for nitrogen fertilization. Fertilization is expected to impact food webs by stimulating its base organisms (Matear, 2004) <sup>[[#fn:r703|703]]</sup> , and extensive algal blooms may cause anoxia (Sarmiento and Orr, 1991; Matear, 2004; Russell et al., 2012) <sup>[[#fn:r704|704]]</sup> and deep water oxygen decline (Matear, 2004) <sup>[[#fn:r705|705]]</sup> , with negative impacts on biodiversity. Nutrient inputs can shift ecosystem production from an iron-limited system to a P, N-, or Si-limited system depending on the location (Matear, 2004; Bertram, 2010) <sup>[[#fn:r706|706]]</sup> and non-CO <sub>2</sub> GHGs may increase (Sarmiento and Orr, 1991; Matear, 2004; Bertram, 2010) <sup>[[#fn:r707|707]]</sup> . The greatest theoretical potential for this practice is the Southern Ocean, posing challenges for monitoring and governance (Robinson et al., 2014) <sup>[[#fn:r708|708]]</sup> . The London Protocol of the International Maritime Organization has asserted authority for regulation of ocean fertilization (Strong et al., 2009) <sup>[[#fn:r709|709]]</sup> , which is widely viewed as a de facto moratorium on commercial ocean fertilization activities.

There is ''low agreement'' in the technical literature on the permanence of CO <sub>2</sub> in the ocean, with estimated residence times of 1,600 years to millennia, especially if injected or buried in or below the sea floor (Williams and Druffel, 1987; Jones, 2014) <sup>[[#fn:r710|710]]</sup> . Storage at the surface would mean that the carbon would be rapidly released after cessation (Zeebe, 2005; Aumont and Bopp, 2006) <sup>[[#fn:r711|711]]</sup> .

<div id="section-4-3-7-6-block-2"></div>

<span id="table-4.6"></span>
<!-- START TABLE -->
'''Table 4.6'''

<span id="cross-cutting-issues-and-uncertainties-across-carbon-dioxide-removal-cdr-options-aspects-and-uncertainties"></span>
'''Cross-cutting issues and uncertainties across carbon dioxide removal (CDR) options, aspects and uncertainties'''

<!-- TABLE -->
{| class="wikitable"
|-
! Area of Uncertainty
! Cross-Cutting Issues and Uncertainties
|-
| Technology upscaling
| * CDR options are at different stages of technological readiness (McLaren, 2012) <sup>[[#fn:r712|712]]</sup> and differ with respect to scalability.
* Nemet et al. (2018)  <sup>[[#fn:r713|713]]</sup> find &gt;50% of the CDR innovation literature concerned with the earliest stages of the innovation process (R&amp;D), identifying a dissonance between the large CO <sub>2</sub> removals needed in 1.5°C pathways and the long -time periods involved in scaling up novel technologies.
* Lack of post-R&amp;D literature, including incentives for early deployment, niche markets, scale up, demand, and public acceptance.

|-
| Emerging and niche technologies
| * For BECCS, there are niche opportunities with high efficiencies and fewer trade-offs, for example, sugar and paper processing facilities (Möllersten et al., 2003) <sup>[[#fn:r714|714]]</sup> , district heating (Kärki et al., 2013; Ericsson and Werner, 2016) <sup>[[#fn:r715|715]]</sup> ,  and industrial and municipal waste (Sanna et al., 2012) <sup>[[#fn:r716|716]]</sup> . Turner et al. (2018)  <sup>[[#fn:r717|717]]</sup> constrain potential using sustainability considerations and overlap with storage basins to avoid the CO <sub>2</sub> transportation challenge, providing a possible, though limited entry point for BECCS.
* The impacts on land use, water, nutrients and albedo of BECCS could be alleviated using marine sources of biomass that could include aquacultured micro and macro flora (Hughes et al., 2012; Lenton, 2014) <sup>[[#fn:r718|718]]</sup> .
* Regarding captured CO <sub>2</sub> as a resource is discussed as an entry point for CDR. However, this does not necessarily lead to carbon removals, particularly if the CO <sub>2</sub> is sourced from fossil fuels and/or if the products do not store the CO <sub>2</sub> for climate-relevant horizons (von der Assen et al., 2013)  <sup>[[#fn:r719|719]]</sup> (see also Section 4.3.4.5).
* Methane <sup>[[#fn:8|8]]</sup> is a much more potent GHG than CO <sub>2</sub> (Montzka et al., 2011) <sup>[[#fn:r720|720]]</sup> , associated with difficult-to-abate emissions in industry and agriculture and with outgassing from lakes, wetlands, and oceans (Lockley, 2012; Stolaroff et al., 2012) <sup>[[#fn:r721|721]]</sup> . Enhancing processes that naturally remove methane, either by chemical or biological decomposition (Sundqvist et al., 2012) <sup>[[#fn:r722|722]]</sup> , has been proposed to remove CH <sub>4</sub> . There is ''low confidence'' that existing technologies for CH <sub>4</sub>  removal are economically or energetically suitable for large-scale air capture (Boucher and Folberth, 2010) <sup>[[#fn:r723|723]]</sup> . Methane removal potentials are limited due to its low atmospheric concentration and its low chemical reactivity at ambient conditions.

|-
| Ethical aspects
| * Preston (2013)  <sup>[[#fn:r724|724]]</sup> identifies distributive and procedural justice, permissibility, moral hazard (Shue, 2018) <sup>[[#fn:r725|725]]</sup> , and hubris as ethical aspects that could apply to large-scale CDR deployment.
* There is a lack of reflection on the climate futures produced by recent modelling and implying very different ethical costs/risks and benefits (Minx et al., 2018) <sup>[[#fn:r726|726]]</sup> .

|-
| Governance
| * Existing governance mechanisms are scarce and either targeted at particular CDR options (e.g., ocean-based) or aspects (e.g., concerning indirect land-use change (iLUC)) associated with bioenergy upscaling, and often the mechanisms are at national or regional scale (e.g., EU). Regulation accounting for iLUC by formulating sustainability criteria (e.g., the EU Renewable Energy Directive) has been assessed as insufficient in avoiding leakage (e.g., Frank et al., 2013) <sup>[[#fn:r727|727]]</sup> .
* An international governance mechanism is only in place for R&amp;D of ocean fertilization within the Convention on Biological Diversity (IMO, 1972, 1996; CBD, 2008, 2010) <sup>[[#fn:r728|728]]</sup> .
* Burns and Nicholson (2017)  <sup>[[#fn:r729|729]]</sup> propose a human rights-based approach to protect those potentially adversely impacted by CDR options.

|-
| Policy
| * The CDR potentials that can be realized are constrained by the lack of policy portfolios incentivising large-scale CDR (Peters and Geden, 2017) <sup>[[#fn:r730|730]]</sup> .
* Near-term opportunities could be supported through modifying existing policy mechanisms (Lomax et al., 2015) <sup>[[#fn:r731|731]]</sup> .
* Scott and Geden (2018)  <sup>[[#fn:r732|732]]</sup> sketch three possible routes for limited progress, (i) at EU-level, (ii) at EU Member State level, and (iii) at private sector level, noting the implied paradigm shift this would entail.
* EU may struggle to adopt policies for CDR deployment on the scale or time-frame envisioned by IAMs (Geden et al., 2018) <sup>[[#fn:r733|733]]</sup> .
* Social impacts of large-scale CDR deployment (Buck, 2016) <sup>[[#fn:r734|734]]</sup> require policies taking these into account.

|-
| Carbon cycle
| * On long time scales, natural sinks could reverse (C.D. Jones et al., 2016)  <sup>[[#fn:r735|735]]</sup>
* No robust assessments yet of the effectiveness of CDR in reverting climate change (Tokarska and Zickfeld, 2015; Wu et al., 2015; Keller et al., 2018) <sup>[[#fn:r736|736]]</sup> , see also Chapter 2, Section 2.2.2.2.

|}
<!-- END TABLE -->

<span id="solar-radiation-modification-srm"></span>
=== 4.3.8 Solar Radiation Modification (SRM) ===

<div id="section-4-3-8-block-1"></div>

This report refrains from using the term ‘geoengineering’ and separates SRM from CDR and other mitigation options (see Chapter 1, Section 1.4.1 and Glossary).

Table 4.7 gives an overview of SRM methods and characteristics. For a more comprehensive discussion of currently proposed SRM methods, and their implications for geophysical quantities and sustainable development, also see Cross-Chapter Box 10 in this Chapter. This section assesses the feasibility, from an institutional, technological, economic and social-cultural viewpoint, focusing on stratospheric aerosol injection (SAI) unless otherwise indicated, as most available literature is about SAI.

Some of the literature on SRM appears in the forms of commentaries, policy briefs, viewpoints and opinions (e.g., (Horton et al., 2016; Keith et al., 2017; Parson, 2017) <sup>[[#fn:r737|737]]</sup> . This assessment covers original research rather than viewpoints, even if the latter appear in peer-reviewed journals.

<div id="section-4-3-8-block-2"></div>

<span id="table-4.7"></span>
<!-- START TABLE -->
'''Table 4.7'''

<span id="overview-of-the-main-characteristics-of-the-most-studied-srm-methods"></span>
'''Overview of the main characteristics of the most-studied SRM methods'''

<!-- TABLE -->
{| class="wikitable"
|-
! SRM indicator
! Stratospheric Aerosol injection (SAI)
! Marine Cloud Brightening (MCB)
! Cirrus Cloud<br />
Thinning (CCT)
! Ground-Based Albedo Modification (GBAM)
|-
| Description of SRM method
| Injection of a gas in the stratosphere, which then converts to aerosols. Injection of other particles also considered.
| Spraying sea salt or other particles into marine clouds, making them more reflective.
| Seeding to promote nucleation, reducing optical thickness and cloud lifetime, to allow more outgoing longwave radiation to escape into space.
| Whitening roofs, changes in land use management (e.g., no-till farming), change of albedo at a larger scale (covering glaciers or deserts with reflective sheeting and changes in ocean albedo).
|-
| Radiative forcing efficiencies
| 1–4 TgS W <sup>−1</sup> m <sup>2</sup> yr <sup>−1</sup>
| 100–295 Tg dry sea salt W <sup>−1</sup> m <sup>2</sup> yr <sup>−1</sup>
| Not known
| Small on global scale, up to 1°C–3°C on regional scale
|-
| Amount needed for 1°C overshoot
| 2–8 TgS yr <sup>−1</sup>
| 70 Tg dry sea salt yr <sup>−1</sup>
| Not known
| 0.04–0.1 albedo change in agricultural and urban areas
|-
| SRM specific impacts on climate variables
| Changes in precipitation patterns and circulation regimes; in case of SO <sub>2</sub> injection, disruption to stratospheric chemistry (for instance NOx depletion and changes in methane lifetime); increase in stratospheric water vapour and tropospheric-stratospheric ice formation affecting cloud microphysics
| Regional rainfall responses; reduction in hurricane intensity
| Low-level cloud changes; tropospheric drying; intensification of the hydrological cycle
| Impacts on precipitation in monsoon areas; could target hot extremes
|-
| SRM specific impacts on human/natural systems
| In case of SO <sub>2</sub> injection, stratospheric ozone loss (which could also have a positive effect – a net reduction in global mortality due to competing health impact pathways) and significant increase of surface UV
| Reduction in the number of mild crop failures
| Not known
|-
| Maturity of science
| Volcanic analogues; ''high agreement'' amongst simulations;<br />
''robust evidence'' on ethical, governance and sustainable development limitations
| Observed in ships tracks;<br />
several simulations confirm mechanism;<br />
regionally limited
| No clear physical mechanism;<br />
''limited evidence'' and ''low agreement'' ;<br />
several simulations
| Natural and land-use analogues;<br />
several simulations confirm mechanism;<br />
''high agreement'' to influence on regional temperature; land use costly
|-
| Key references
| Robock et al., 2008;<br />
Heckendorn et al., 2009;<br />
Tilmes et al., 2012, 2016;<br />
Pitari et al., 2014;<br />
Crook et al., 2015;<br />
C.J. Smith et al., 2017;<br />
Visioni et al., 2017a, b;<br />
Eastham et al., 2018; Plazzotta et al., 2018 <sup>[[#fn:r738|738]]</sup>
| Salter et al., 2008;<br />
Alterskjær et al., 2012;<br />
Jones and Haywood, 2012; Latham et al., 2012, 2013;<br />
Kravitz et al., 2013;<br />
Crook et al., 2015;<br />
Parkes et al., 2015; Ahlm et al., 2017 <sup>[[#fn:r739|739]]</sup>
| Storelvmo et al., 2014;<br />
Kristjánsson et al., 2015;<br />
Jackson et al., 2016;<br />
Kärcher, 2017;<br />
Lohmann and Gasparini, 2017 <sup>[[#fn:r740|740]]</sup>
| Irvine et al., 2011;<br />
Akbari et al., 2012;<br />
Jacobson and Ten Hoeve, 2012;<br />
Davin et al., 2014;<br />
Crook et al., 2015, 2016;<br />
Seneviratne et al., 2018 <sup>[[#fn:r741|741]]</sup>
|}
<!-- END TABLE -->

<div id="section-4-3-8-block-3"></div>

SRM could reduce some of the global risks of climate change related to temperature rise (Izrael et al., 2014; MacMartin et al., 2014) <sup>[[#fn:r742|742]]</sup> , rate of sea level rise (Moore et al., 2010) <sup>[[#fn:r743|743]]</sup> , sea-ice loss (Berdahl et al., 2014) <sup>[[#fn:r744|744]]</sup> and frequency of extreme storms in the North Atlantic and heatwaves in Europe (Jones et al., 2018) <sup>[[#fn:r745|745]]</sup> . SRM also holds risks of changing precipitation and ozone concentrations and potentially reductions in biodiversity (Pitari et al., 2014; Visioni et al., 2017a; Trisos et al., 2018) <sup>[[#fn:r746|746]]</sup> . Literature only supports SRM as a supplement to deep mitigation, for example in overshoot scenarios (Smith and Rasch, 2013; MacMartin et al., 2018) <sup>[[#fn:r747|747]]</sup> .

<div id="section-4-3-8-1"></div>

<span id="governance-and-institutional-feasibility"></span>
==== 4.3.8.1 Governance and institutional feasibility ====

<div id="section-4-3-8-1-block-1"></div>

There is ''robust evidence'' but ''medium agreement'' for unilateral action potentially becoming a serious SRM governance issue (Weitzman, 2015; Rabitz, 2016) <sup>[[#fn:r748|748]]</sup> , as some argue that enhanced collaboration might emerge around SRM (Horton, 2011) <sup>[[#fn:r749|749]]</sup> . An equitable institutional or governance arrangement around SRM would have to reflect views of different countries (Heyen et al., 2015) <sup>[[#fn:r750|750]]</sup> and be multilateral because of the risk of termination, and risks that implementation or unilateral action by one country or organization will produce negative precipitation or extreme weather effects across borders (Lempert and Prosnitz, 2011; Dilling and Hauser, 2013; NRC, 2015b) <sup>[[#fn:r751|751]]</sup> . Some have suggested that the governance of research and field experimentation can help clarify uncertainties surrounding deployment of SRM (Long and Shepherd, 2014; Parker, 2014; NRC, 2015c; Caldeira and Bala, 2017; Lawrence and Crutzen, 2017) <sup>[[#fn:r752|752]]</sup> , and that SRM is compatible with democratic processes (Horton et al., 2018) <sup>[[#fn:r753|753]]</sup> or not (Szerszynski et al., 2013; Owen, 2014) <sup>[[#fn:r754|754]]</sup> .

Several possible institutional arrangements have been considered for SRM governance: under the UNFCCC (in particular under the Subsidiary Body on Scientific and Technological Advice (SBSTA)) or the United Nations Convention on Biological Diversity (UNCBD) (Honegger et al., 2013; Nicholson et al., 2018) <sup>[[#fn:r755|755]]</sup> , or through a consortium of states (Bodansky, 2013; Sandler, 2017) <sup>[[#fn:r756|756]]</sup> . Reasons for states to join an international governance framework for SRM include having a voice in SRM diplomacy, prevention of unilateral action by others and benefits from research collaboration (Lloyd and Oppenheimer, 2014) <sup>[[#fn:r757|757]]</sup> .

Alongside SBSTA, the WMO, UNESCO and UN Environment could play a role in governance of SRM (Nicholson et al., 2018) <sup>[[#fn:r758|758]]</sup> . Each of these organizations has relevance with respect to the regulatory framework (Bodle et al., 2012; Williamson and Bodle, 2016) <sup>[[#fn:r759|759]]</sup> . The UNCBD gives guidance that ‘that no climate-related geo-engineering activities that may affect biodiversity take place’ (CBD, 2010) <sup>[[#fn:r760|760]]</sup> .

<div id="section-4-3-8-2"></div>

<span id="economic-and-technological-feasibility"></span>
==== 4.3.8.2 Economic and technological feasibility ====

<div id="section-4-3-8-2-block-1"></div>

The literature on the engineering costs of SRM is limited and may be unreliable in the absence of testing or deployment. There is ''high agreement'' that costs of SAI (not taking into account indirect and social costs, research and development costs and monitoring expenses) may be in the range of 1–10 billion USD yr <sup>−1</sup> for injection of 1–5 MtS to achieve cooling of 1–2 W m <sup>−</sup> <sup>2</sup> (Robock et al., 2009; McClellan et al., 2012; Ryaboshapko and Revokatova, 2015; Moriyama et al., 2016) <sup>[[#fn:r761|761]]</sup> , suggesting that cost-effectiveness may be high if side-effects are low or neglected (McClellan et al., 2012) <sup>[[#fn:r762|762]]</sup> . The overall economic feasibility of SRM also depends on externalities and social costs (Moreno-Cruz and Keith, 2013; Mackerron, 2014) <sup>[[#fn:r763|763]]</sup> , climate sensitivity (Kosugi, 2013) <sup>[[#fn:r764|764]]</sup> , option value (Arino et al., 2016) <sup>[[#fn:r765|765]]</sup> , presence of climate tipping points (Eric Bickel, 2013) <sup>[[#fn:r766|766]]</sup>   and damage costs as a function of the level of SRM (Bahn et al., 2015; Heutel et al., 2018) <sup>[[#fn:r767|767]]</sup> . Modelling of game-theoretic, strategic interactions of states under heterogeneous climatic impacts shows ''low agreement'' on the outcome and viability of a cost-benefit analysis for SRM (Ricke et al., 2015; Weitzman, 2015) <sup>[[#fn:r768|768]]</sup> .

For SAI, there is ''high agreement'' that aircrafts could, after some modifications, inject millions of tons of SO <sub>2</sub> in the lower stratosphere (at approximately 20 km; (Davidson et al., 2012; McClellan et al., 2012; Irvine et al., 2016) <sup>[[#fn:r769|769]]</sup> .

<div id="section-4-3-8-3"></div>

<span id="social-acceptability-and-ethics"></span>
==== 4.3.8.3 Social acceptability and ethics ====

<div id="section-4-3-8-3-block-1"></div>

Ethical questions around SRM include those of international responsibilities for implementation, financing, compensation for negative effects, the procedural justice questions of who is involved in decisions, privatization and patenting, welfare, informed consent by affected publics, intergenerational ethics (because SRM requires sustained action in order to avoid termination hazards), and the so-called ‘moral hazard’ (Burns, 2011; Whyte, 2012; Gardiner, 2013; Lin, 2013; Buck et al., 2014; Klepper and Rickels, 2014; Morrow, 2014; Wong, 2014; Reynolds, 2015; Lockley and Coffman, 2016; McLaren, 2016; Suarez and van Aalst, 2017; Reynolds et al., 2018) <sup>[[#fn:r770|770]]</sup> . The literature shows ''low agreement'' on whether SRM research and deployment may lead policy-makers to reduce mitigation efforts and thus imply a moral hazard (Linnér and Wibeck, 2015) <sup>[[#fn:r771|771]]</sup> . SRM might motivate individuals (as opposed to policymakers) to reduce their GHG emissions, but even a subtle difference in the articulation of information about SRM can influence subsequent judgements of favourability (Merk et al., 2016) <sup>[[#fn:r772|772]]</sup> . The argument that SRM research increases the likelihood of deployment (the ‘slippery slope’ argument), is also made (Quaas et al., 2017) <sup>[[#fn:r773|773]]</sup> , but some also found an opposite effect (Bellamy and Healey, 2018) <sup>[[#fn:r774|774]]</sup> .

Unequal representation and deliberate exclusion are plausible in decision-making on SRM, given diverging regional interests and the anticipated low resource requirements to deploy SRM (Ricke et al., 2013) <sup>[[#fn:r775|775]]</sup> . Whyte (2012) <sup>[[#fn:r776|776]]</sup> argues that the concerns, sovereignties, and experiences of indigenous peoples may particularly be at risk.

The general public can be characterized as oblivious to and worried about SRM (Carr et al., 2013; Parkhill et al., 2013; Wibeck et al., 2017) <sup>[[#fn:r777|777]]</sup> . An emerging literature discusses public perception of SRM, showing a lack of knowledge and unstable  opinions (Scheer and Renn, 2014) <sup>[[#fn:r778|778]]</sup> . The perception of controllability affects legitimacy and public acceptability of SRM experiments (Bellamy et al., 2017) <sup>[[#fn:r779|779]]</sup> . In Germany, laboratory work on SRM is generally approved of, field research much less so, and immediate deployment is largely rejected (Merk et al., 2015; Braun et al., 2017) <sup>[[#fn:r780|780]]</sup> . Various factors could explain variations in the degree of rejection of SRM between Canada, China, Germany, Switzerland, the United Kingdom, and the United States (Visschers et al., 2017) <sup>[[#fn:r781|781]]</sup> .

<div id="section-4-3-8-3-block-2" class="box"></div>

<span id="cross-chapter-box-10-solar-radiation-modification-in-the-context-of-1.5c-mitigation-pathways"></span>