Editing IPCC:AR6/WGII/Chapter-8 (section)

==== 8.2.1.3. Observed Differential Vulnerability to Climate Change, and Loss and Damage ====

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The negative impacts of climate change on groups of vulnerable or marginalised communities generate so-called ‘residual impacts’ and residual risks that can remain a challenge in their lives ( [[#Warner--2013|Warner and Van der Geest, 2013]] ; [[#James--2014|James et al., 2014]] ; [[#Klein--2014|Klein et al., 2014]] ; [[#Boyd--2017|Boyd et al., 2017]] ). Such ‘unacceptable’ L&amp;Ds include the loss of income sources, food insecurity, malnutrition, permanent impacts to health and labour productivity, loss of life and loss of homelands, among others ( [[#McNamara--2019|McNamara and Jackson, 2019]] ; [[#Schwerdtle--2020|Schwerdtle et al., 2020]] ). The literature on L&amp;D provides ''robust evidence'' not only on economic dimensions of global L&amp;Ds, but also experiences of non-economic losses from the impacts of climate change (see detail in [[#8.3|Section 8.3]] ; [[#Barnett--2016|Barnett et al., 2016]] ; [[#Roy--2018|Roy et al., 2018]] ; [[#McNamara--2019|McNamara and Jackson, 2019]] ). The extreme events that have occurred in recent years highlight the potential for L&amp;D, including 2019’s Cyclone Kenneth, the strongest in the recorded history of the African continent, which made landfall in northern Mozambique causing 45 deaths and destroying approximately 40,000 houses, leaving hundreds of thousands at risk of acquiring waterborne diseases such as cholera during a prolonged recovery period ( [[#Cambaza--2019|Cambaza et al., 2019]] ).

In parallel to evidence on L&amp;D, the science of climate event attribution has evolved from a theoretical possibility into a subfield of climate science. As attribution science strengthens, with it the evidence base linking greenhouse gas (GHG) emissions to extreme heat events, heavy rainfall and wind storms grows and becomes more robust ( [[#Otto--2016|Otto et al., 2016]] ; [[#Stott--2016|Stott et al., 2016]] ; [[#Otto--2018|Otto et al., 2018]] ; [[#Otto--2020|Otto, 2020]] ; [[#Clarke--2021|Clarke et al., 2021]] ; [[#van%20Oldenborgh--2021a|van Oldenborgh et al., 2021a]] ; [[#van%20Oldenborgh--2021b|van Oldenborgh et al., 2021b]] ; [[#Verschuur--2021|Verschuur et al., 2021]] ).

Climate justice questions arise about the observed differential L&amp;Ds due to climatic hazards to affected populations in close connection with their vulnerability ( [[#Wrathall--2015|Wrathall et al., 2015]] ). Individual extreme weather events attributable to climate change result in L&amp;Ds in communities and societies, which allow a quantification of the differential impacts of such events on different groups ( [[#Hoegh-Guldberg--2019a|Hoegh-Guldberg et al., 2019a]] ). Considering the disproportionately adverse impacts of climatic hazard on most vulnerable groups and regions and their relatively minor contribution to anthropogenic climate change ( [[#Mora--2018|Mora et al., 2018]] ; [[#Robinson--2018|Robinson and Shine, 2018]] ), it is evident that vulnerability reduction and adaptation to climate change have also to be seen as an issue of climate justice and climate just development ( [[#Byers--2018|Byers et al., 2018]] ).

Probabilistic attribution allows an assessment of people’s future climate risks and estimates about the costs of successfully adapting to them ( [[#James--2014|James et al., 2014]] ; [[#James--2019|James et al., 2019]] ). To answer questions about impacts on people, the vulnerable and poor in particular, requires attribution, vulnerability and adaptation science need to move far beyond understanding physical events and incorporate information (including Indigenous knowledge and local knowledge (IKLK)) on people’s vulnerability and capacities, and exposure and losses resulting from discrete events ( [[#Bellprat--2019|Bellprat et al., 2019]] ). Attribution science is therefore highly compatible with risk management tools (i.e., risk reduction, risk transfer, insurance, risk pooling, recovery, rehabilitation and compensation) suggested in policy ( [[#James--2019|James et al., 2019]] ).

New observations provide greater evidence on the role of extreme poverty and global inequality, most of the detrimental direct impacts of climate change (e.g., rising food insecurity) disproportionately affecting the Global South ( [[#Hasegawa--2018|Hasegawa et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ; [[#Khan--2021|Khan and Zhang, 2021]] ) compared with the Global North. Poor populations in many countries are also disproportionately facing extreme L&amp;D from heatwaves, flooding and tropical weather extremes ( [[#Gamble--2016|Gamble et al., 2016]] ). New case studies, such as the European heatwave of 2018, illustrate significant negative impacts across crop production in the Global North ( [[#Beillouin--2020|Beillouin et al., 2020]] ), livestock value chain ( [[#FAO--2018|FAO, 2018]] ; [[#Godde--2021|Godde et al., 2021]] ) and fishing ( [[#Plagányi--2019|Plagányi, 2019]] ). Heatwave-induced intense fires can cause property damage, physical injury and death, as well as health and psychological harm of the victims. Heatwaves also create ideal conditions for the prevalence of certain pathogens, increase the risk of temperature-related health problems and exacerbate many pre-existing diseases ( [[#Rossiello--2019|Rossiello and Szema, 2019]] ).

A focus in the chapter is on the intersections between climate hazards and differential vulnerability resulting in actual and potential economic and non-economic losses ( [[#8.3|Section 8.3]] , 8.4; [[#Thomas--2019|Thomas et al., 2019]] ). Increasingly, intersections of age, gender, socioeconomic class, ethnicity and race are recognised as important to the climate risks and differential impacts and losses experienced by vulnerable, marginal and poor in societies ( ''high confidence'' ).( [[#8.2|Section 8.2]] ,2.3; CCB GENDER in Chapter 18; [[#Nyantakyi-Frimpong--2015|Nyantakyi-Frimpong and Bezner-Kerr, 2015]] ). For example, linkages between wildfires and gendered norms and values are real-world examples ( [[#Walker--2021|Walker et al., 2021]] ). A broader climate agenda which considers social structures and power relations intersecting with climate change extremes is important ( [[#Versey--2021|Versey, 2021]] ), in order to understand disproportionate impacts of climate hazards, observed and future losses and vulnerability (see Figure 8.3).

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[[File:162801f252ced747635a3d71c966a628 IPCC_AR6_WGII_Figure_8_003.png]]

'''Figure 8.3 |''' '''Illustration of the relationship between climate hazards, their impacts (including economic and non-economic losses and damages) and human systems leading to systemic vulnerability.''' We need to understand who is vulnerable, where, at what scale and why. We cannot just look at the climate hazard (e.g., wild fires, floods, droughts, sea level rise, etc.) but must also look at who is being affected by these hazards and factors that make people and groups vulnerable (e.g., poverty, uneven power structures, disadvantage and discrimination due to, for example, social location and the intersectionality or the overlapping and compounding risks from ethnicity or racial discrimination, gender, age, or disability, etc.) (see also Cross-Chapter Box GENDER in Chapter 18; [[IPCC:Wg2:Chapter:Chapter-5#5.12|Section 5.12]] ).

Extreme events (e.g., heatwaves, cold periods, icy conditions) occurring in the Global North illustrate that such events cause disproportionate impacts among ageing populations, due to their immobility, isolation, infrastructure deficiencies and poor health assistance ( [[#Carter--2016|Carter et al., 2016]] ; [[#Reckien--2018|Reckien et al., 2018]] ). A well-known example is the heatwave in 2003 that killed thousands of elderly citizens across Europe ( [[#Poumadere--2005|Poumadere et al., 2005]] ; [[#García-Herrera--2010|García-Herrera et al., 2010]] ; [[#Laaidi--2011|Laaidi et al., 2011]] ). More recently, in the Nordic region, elderly populations have been experiencing distress associated with heatwaves and extreme cold events, with significant increases in morbidity and mortality due to cardiovascular and respiratory failure, showing that both age and underlying health issues intersect with climate change impacts ( [[#Carter--2016|Carter et al., 2016]] ; [[#Li--2016|Li et al., 2016]] ). The elderly also experience severe impacts from extreme winter seasons, such as in Finland, where of the from 3000 deaths associated with extreme winter weather and 50,000 injuries associated with slippery pavement conditions, the majority were people over 65 years old ( [[#Carter--2016|Carter et al., 2016]] ). Adaptation to extreme events including heatwaves, cold periods and icy conditions in the Global South and North will increase energy demand and the individuals’ carbon footprint across all income levels ( [[#van%20Ruijven--2019|van Ruijven et al., 2019]] ).

The 2018 US National Climate Assessment has identified that southeastern USA is already experiencing more frequent and longer summer heatwaves and, by 2050, rising global temperatures are expected to mean that cities in southeastern USA may experience extreme heat ( [[#USGCRP--2018|USGCRP, 2018]] ). This includes disadvantaged African American communities, who are more exposed and hence disproportionately experience the impacts of climate change ( [[#Shepherd--2015|Shepherd and KC, 2015]] ; [[#Marsha--2018|Marsha et al., 2018]] ). The historically discriminated Sami in northern Sweden and Maasai in Africa are examples of Indigenous People who also face climate risks and have limited resources, capacity or power to respond ( [[#Leal%20Filho--2017|Leal Filho et al., 2017]] ; [[#Persson--2017|Persson et al., 2017]] ).

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