Europe Europe Europe

Insurance and Business: European scale

Vulnerabilities - Insurance affordability and coverage

Rising climate-related risks such as from floods and windstorms threaten affordability and coverage availability for society at large (34). The solvency of the insurance industry as
 a whole doesn't seem to be threatened by climate change. However, extreme hydro-meteorological events might compromise the ability of insurance companies to deal with climate impacts and increase the costs of doing business 
in the insurance sector. This could result in companies exiting the market or certain segments becoming uninsurable (33).

After extreme hydro-meteorological events, insurers tend to critically reassess their risks if payouts were higher than estimated. This reassessment could result in decreased affordability and availability of insurance. For example, after the 2002 German floods, which cost
 €9 billion in public funds, some observers noticed that the risk reassessment by insurance companies led to an increase in premiums of up to 50%, and a reduction in areas where flood insurance was offered of 10–20% (35). In the USA, insured losses of over US$100 billion caused by Hurricane Katrina and others during 
2004 and 2005 resulted in a decrease in 
the availability of insurance (36). In the UK, the end of ‘universally available’ flood insurance coverage was mostly motivated by damages over £1 billion during the 2000 autumn floods (37), while in Ireland a series of recent floods have left businesses and homeowners in certain areas struggling to secure flood insurance (38). 

Entrepreneurial robustness

In our globalized world an extreme event in one part of the world can have a major impact on business continuity on the other side of the planet. This happened in 2011 when a flooding in Thailand hit suppliers of the electronics and automotive industries, and thus car manufacturers in Europe and the US.

The Thailand event illustrates the importance of supply chain networks being sufficiently robust with respect to the risks that result from climate change. Large-scale impacts of climate change on industrial supply chain networks have been assessed for manufacturing industries in Austria, in the alpine state of Tyrol (10). A survey on climate change risk perceptions and a number of interviews was carried out among 102 manufacturing firms. This was done for the sectors metal and engineering, timber products, and construction. Remarkably, the response rate to the questionnaire was extremely low: only 102 out of 1871 firms replied. Apparently, many firms considered the topic as strategically irrelevant or found it difficult to conceive of climate change impacts as a relevant business factor.

Supply chain networks are vulnerable with respect to climate change in a number of ways (10).

  1. Disruption supply raw materials, water and electricity. Raw material supply may be disrupted. Price fluctuations or a long-term increase in prices for timber may result from more insect outbreaks and fires in forestst, for instance. The production of mineral raw materials may be hindered by flooding of mines, by gravel roads or railroads being damaged due to heavy precipitation or forest fires, and by water needed for mining operations becoming increasingly scarce (11). Deliveries from suppliers may be interrupted due to extreme weather events in locations of supplying companies, like the Thailand event in 2011 (12). Roads and railroads may be closed due to inundations or storms, and operations of seaports and inland shipping may be disrupted. Electricity supply may fail when there is not enough cooling water for thermal power plants during heat waves, or water for hydropower during droughts. In addition, inundations and storms may damage power lines or transformer stations (13), and blackouts may result from increased energy demand for cooling systems and air conditioning during heat waves (14). Water supply infrastructure may fail during heavy precipitation and floods, and less precipitation may increase risks of water conflicts between water intensive industrial processes and other forms of water demand (15).
  2. Disruption working processes. More intense heat waves can pose health risks particularly for manual labourers due to potential loss of concentration at machines or even heat stroke (16). Besides, labour productivity may decline. IT networks may fail, when server rooms get flooded or when cables underground or aboveground get damaged during floods or storms (17). Extreme events like inundations or storms can lead to physical damages at plants as well as at office and storage buildings (18).
  3. Disruption of delivery to consumers. The climate change discussion may increase environmental consciousness of citizens and thus change customer preferences (19). Extreme weather events can lead to a decline in sales due to decreasing purchasing power of consumers. Moreover, product delivery to customers may be affected by disruption of infrastructure (20).
  4. Political and capital market risks. Climate change may motivate changes in regulations, incentives and reporting requirements which affect manufacturing firms, including for example changes in product policy (21), rising environmental taxation (21), or increasing reporting requirements from capital market institutions. Furthermore, access to finance may become a risk if banks start to refuse credits to companies that are not managing climate risks properly (22). 

Vulnerabilities - Loss of work time and labour productivity globally

Study 1:

The exposure of workers to hot environments is expected to increase as a result of climate change, especially in sub-Saharan Africa, south Asia, and southeast Asia (46). Physical activities in hot environments can elevate the risk of heat-related illness, such as heat exhaustion and heat stroke, some of which may be fatal. In particular, outdoor workers are vulnerable to hot environments, and thus effective preventive measures are necessary in the workplace. In order to prevent heat-related illness, it is recommended that workers take breaks during working hours. However, this would lead to reductions in work time and labour productivity. The global future economic cost of heat-related illness prevention through worker breaks has been estimated under a wide range of climatic conditions (the so-called RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios) and socioeconomic conditions (the so-called SSP1, SSP2 and SSP3 socioeconomic scenarios) (31).

Under a high-end scenario of climate change (RCP8.5), the loss of work time and labour productivity may result in a loss of 2.6 to 4.0% of Gross Domestic Product (GDP) in 2100 compared to current climate conditions (the year 2005 as a reference). The estimated cost in the low-end scenario (RCP2.6) is substantially lower: 0.46% - 0.49% in 2100. Estimated GDP losses will be less than 0.5% if the 2.0 °C goal of the Paris Agreement is achieved (31).

According to the authors of this study, these numbers may be a strong incentive for achieving the mitigation target of the Paris Agreement, in particular for regions such as India and South-East Asia where the risk of heat-related illness seems to increase strongly. The cost of mitigation corresponding to the low-end scenario of climate change (RCP2.6) measured by GDP loss rate (median value) is estimated to be approximately 5% in 2100 (32). The estimated extra economic cost of work time and labour productivity loss under a high-end scenario of climate change compared with this low-end scenario is about 2.1 to 3.5% of GDP. Thus, according to these estimates, approximately 40% - 70% of the mitigation cost may be recovered by only the cost benefit derived from avoiding the high loss of work time and labour productivity under a high-end scenario of climate change (31). 

Of course, these results should be interpreted with care. There are several limitations to this study, due to assumptions with respect to air-conditioning device availability, for instance, or technological or social innovations in the future. After all, who knows what the future of outdoor workers in 2100 looks like? The results are a worst-case-scenario analysis. Still, this study illustrates that on a global scale, and in particular for certain regions such as India and South-East Asia, heat-related illness and the economic cost of avoiding it is a serious issue that should be kept in mind when discussing the benefits and economic cost of climate change mitigation.

Study 2

In another study the impacts of climate change on daylight working hours was quantified globally for mid-century (2041-2070) and for the end of this century (2071-2099) under a low-end (RCP 2.6) and moderate (RCP 6.0) scenario of climate change (39). Projections of several (GCM) climate models were used for this; these projections were combined with data on population in different age groups to estimate the impact on the working part of the population. Focus was on in-shade, moderately heavy physical work (industry).

Today, tropical and sub-tropical areas already experience serious heat stress, and this will increase. Even relatively little global warming of 1.5 °C will increase the loss of daylight working hours due to heat stress in many tropical areas from less than 2% on an annual basis now (reference period: 1981-2010) up to more than 6% at the end of the century. A (more realistic) global warming of 2.7 °C will double the heat impact on work in such areas (39).

Not only the tropics and subtropics, but also the southern parts of Europe and the USA will be affected. In the USA, 2.7 °C global warming will increase the loss of working hours from 0.17% on an annual basis now to more than 1.3% at the end of the century for all activities that may be considered ‘moderately heavy physical work’. India is much more affected already now (2% loss), and this may increase to 8% at the end of the century for 2.7 °C global warming. China has values between these two countries. Cambodia is one of the most affected countries with losses up to 11%. Overall, the impact for Europe is relatively small (39). 

Study 3

Recently, results have been published on labour productivity loss in Europe at different times in this century. The results are based on a high-end scenario of climate change and, therefore, represent a worst-case scenario (47).

Heat stress is represented by the combination of temperature, humidity, wind speed and solar exposure. Heat stress was calculated for a high-end scenario of climate change (RCP 8.5) from the results of 11 regional climate models. The impact of heat stress on labour productivity loss was calculated for four work categories that vary in the exposure to heat stress from the lowest exposure for workers undertaking light work indoors to the highest exposure for workers in agriculture and construction working outdoors in the sun. The average impact was calculated for 30-year time slices representing the 2020s, 2050s and 2080s. A 30-year time slice representing the 1990s was selected as a reference. The economic impacts are presented as changes in annual GDP in 2013 Euros (47).

Without adaptation to the increasing heat stress, the average productivity loss in Europe, compared to the reference of the 1990s, is projected to be 0.1%, 0.3% and 0.7% of Europe’s GDP for the time horizons of the 2020s, 2050s and 2080s, respectively. The worst-case scenario losses could be around three times larger and reach, respectively, 0.3%, 0.8% and 1.6% (47).

These averages mask underlying diversity of regional impacts. Future production losses are largest in southern European regions: south of Spain, then along the Mediterranean coast through France and Italy, Croatia and Greece. In this part of Europe, productivity losses can reach 3% of a country’s GDP by the 2080s on average, and up to 8% in the worst-case scenario. This is not only due to a relatively high heat stress. In this part of Europe, a large part of the population works in agriculture, forestry and fishing, with a high exposure to heat stress. Quite high productivity losses are also estimated for Romania, where a large part of the population works in the category of high exposure to heat stress. The estimated productivity losses are lowest for northern European countries and would not exceed 0.23% of the GDP even in the worst case (47).

Adaptation could alleviate the negative impacts of heat stress. The authors of this study looked at the effects of two different types of measures: more space cooling and an increasing use of robotic exoskeletons. The use of wearable robotics, the authors assume, will allow reducing the physical workload of humans from heavy to moderate. The authors conclude that adaptation can reduce the productivity losses by around 40%. In the short term – the 2020s – air conditioning would be most effective. In the longer term – the 2050s and 2080s – robotic solutions would have become an effective adaptation method (47).

Study 4

It’s not just the heat but the combination with high humidity that causes heat stress conditions where you can no longer work outside. Exposure to high humid heat, by workers in agriculture, fisheries, forestry, and construction, already leads to over 650 billion hours of lost labor per year, globally, according to data over the period 2001-2020 (48). This number equals a loss of almost 150 million jobs globally per year, comparable to temporary work loss during the global COVID-19 lockdowns (49).

This estimate is much higher than previous estimates of approximately 200 billion hours of lost labor per year for workers engaged in heavy labor in agriculture and construction (50). According to the scientists that have calculated this higher number, 72% of the global working-age population is living in regions where climate conditions sometimes lead to heavy labor losses, compared with 40% in previous estimates. Climate conditions in much of the tropics and subtropics are already exceeding thresholds for human safety (51).

Labor losses are highest in South, East, and Southeast Asia, where a large part of the working-age population is working in agriculture. Labor losses are most pronounced in India. Almost half of the global total losses are attributable to India, being over four times the labor losses of the second worst-hit country, China (48).

These labor losses translate to significant economic costs. The annual, humid heat-related global labor loss amounts to a global productivity loss of approximately 2.1 trillion USD (price level 2017), equivalent to 1.7% of global gross domestic product (GDP). China and India again experience the largest losses. For India the annual productivity losses from high humid heat amount to almost 7% of its 2017 GDP. This loss estimate substantially exceeds a previous estimate of 311 billion USD (price level 2010), which was about 0.5% of global GDP in 2010, and approaches a previous loss estimate for 2030 of 2.4–2.5 trillion USD (price level 2010) (52).

Labor productivity losses are already increasing in time. The estimated losses over the 2001–2020 period are at least 9% higher than the losses over the period 1981–2000. This agrees with an increase of economic costs of at least 100 billion USD (2017 prices). This illustrates that relatively small changes in climate (about 0.4°C) can cause large-scale increases in lost global labor productivity. These increases in losses are felt most strongly in the tropics and subtropics (48).

High humid heat is expected to increase labor loss and decrease global GDP by up to 4.0% by 2100 (31).

Vulnerabilities - Loss of work time and labour productivity in Europe

Future projections on the combination of changes in high temperatures and humidity can be used to estimate how climate change may affect working conditions and economic productivity. This has been done for shaded and sunny conditions, and for an unacclimatized and acclimatized worker for future scenarios until 2099. The calculations are based on a large number of model simulations, performed by 11 regional climate models driven by 10 different global climate models, and a low-end, moderate and high-end scenario of climate change (the so-called RCP2.6, RCP4.5 and RCP8.5 scenarios). The reference period is 1981-2010 (43).

Current high heat risk

Currently, the number of summer days with high heat risk reaches up to 20 days on average in a few locations in Spain, Italy, Greece and Cyprus in the shade. In the sun, the area with such conditions spans over Southern Europe and reaches 30-50 days in some Mediterranean locations. In Central and Northern Europe, the thresholds for moderate and high heat risk are currently reached only occasionally (43).

More frequent high heat exposure in the future

Compared to today’s climate, high heat risk frequency for both shaded and sunny conditions is projected to increase by 5-15 days per year in the Mediterranean region by the end of the century under the low-end scenario of climate change. Under the moderate and high-end scenario these numbers are 15-30 and 30-50 days per year, respectively. In some Southern European locations, workers might suffer high heat risk at the end of this century for almost the entire summer in sunny conditions and more than half of the summer days under shade conditions.

This century, high heat risk in shaded conditions will be confined to the Mediterranean area. In sunny conditions, however, high heat risk is projected to affect the entire continent except Scandinavia and the British Isles by 2100. High heat risk in the sun is projected to occur during up to 10% of summer days in many locations in Central Europe for the low-end and moderate scenarios of climate change, and even on 20-30% of summer days for the high-end scenario (43).

Productivity losses

At the end of this century, many European workers will very likely be affected by heat stress, not only due to the increase of heat exposure but also because such situations will become more frequent in large areas of the continent. Currently, only at a few locations in the Mediterranean area up to 20% of summer working hours are lost under sunny conditions. By the end of this century, under the high-end scenario of climate change, Southern Europe will experience a widespread loss of working hours by at least 15%, reaching more than 50% in some locations in Spain, Italy, Greece and Cyprus. In northern Europe, on the other hand, future warming might increase outside labour productivity during the winter months, thus compensating the loss in summer due to high temperatures (43).

Urban heat island effect

In this study, the urban heat island effect is not fully accounted for. Future heat exposure in urban areas may be quite different. The urban heat island effect is, for instance, associated with warmer nights in urban compared to rural areas. The number of high-heat-stress nights is projected to increase in particular in urban areas. As a result, urban citizens might not recover from the daytime heat and might subsequently not be able to handle any extreme heat the following day (44). The results presented in this study should be regarded as a lower bound of future heat risk in urban areas (43).

Vulnerabilities -Southern European islands 

The islands of southern Europe are particularly vulnerable to the consequences of climate change. This mainly results from two facts: they are geographically remote, and their economic diversification is low. Climate change impacts have been assessed for nine islands and archipelagos: Azores, Baleares, Canaries, Crete, Cyprus, Malta, Madeira, Sardinia, and Sicily. Both a low-end (RCP2.6) and a high-end (RCP8.5) scenario of climate change was used for this. Focus was on three sectors: tourism, maritime transport, and electricity. The assessment describes the economic costs that the southern European islands could face if anticipatory and adaptation measures are not undertaken (53).

With respect to tourism, the possible consequences of seagrass loss, forest fires, beach reduction, and thermal comfort were included. The impacts on energy included increased electricity consumption for cooling purposes and water desalination. For maritime transport, the impacts of climate damages on port infrastructure were assessed (53).

The results of the assessment indicate that climate change impacts have a negative effect on the island’s economic activities. For 2050, the projected economic impacts are GDP losses up to 3.8% under the low-end scenario of climate change and up to 7.3% under the high-end scenario, compared with present-day conditions. By the end of the century, the economic impacts may be twice as large (53).

Projected GDP losses are largest for the Canary Islands, followed by Crete and the Balearic Islands. The economy of these islands strongly depends on tourism; the effects of climate change on the tourism sector are detrimental to the islandic economies. Besides, the Canary Islands are geographically remote, which makes their energy supply more vulnerable to the consequences of climate change. Climate change will increase the demand for cooling and water desalination, both of which are energy-intensive processes. Being geographically remote hinders the electrical interconnection of islands with the mainland and increases the costs associated with higher electricity demand. Islands with proximity to the mainland, like Malta and Sicily, have less intense economic impacts. Compared with the impacts on tourism and energy, the impact on maritime transport is negligible (53).

Vulnerabilities - Global base metal resources

Mine sites utilise water in a range of processes, such as mineral processing and dust suppression. The overall water requirements depend on factors such as local climate, ore mineralogy and grade, the scale of infrastructure and ore processing, and the extent of tailings dewatering and water recycling (24). A first global assessment of water risks facing the mining industry under climate change was presented for copper, lead-zinc and nickel resources (23). These metals are vital for modern infrastructure. This was done for a number of climate change scenarios (the so-called A1FI, A2, B1 and B2 emission scenarios) spanning a range of low to high global warming, and 5 general circulation models.

Copper resources most exposed to climate change

Currently, copper resources are, on average, located in regions with more water stress, scarcity and risk than regions containing lead-zinc or nickel resources. In addition, regions containing copper and lead-zinc resources are potentially more exposed to the consequences of climate change over the coming century than those containing nickel resources. Significant changes in climate are projected for regions that contain 27-32% of global copper resources, 7-29% of global lead-zinc resources, and 6-13% of global nickel resources. In addition, smaller changes are projected for a further 15-23% of copper, 23-32% of lead-zinc, and 29-32% of nickel resources. Undeveloped copper resources, however, are located in less water scarce or stressed regions than resources that have been recently mined (23).

Climate changes are likely to alter the water balance, water quality and infrastructure risks at mining and mineral processing operations:

  1. Too little water. Sourcing sufficient water to meet the requirements of mining operations may be challenging in regions where water resources are also fully allocated for other purposes, such as agriculture, forestry or environmental flows. Water requirements may still be met, however, by improving water efficiency along with investments in water storage infrastructure, seawater desalination and pipeline capacity (25).
  2. Too much water. Compared with the risk of too little water the risks associated with too much water may be a bigger concern for many mining operations. Heavy rainfall (or snowfall) can result in sections of mines becoming inaccessible or unsafe to operate, which can lead to supply disruptions. Unplanned or uncontrolled water discharges may be detrimental to surrounding environments. The financial implications of flood events in mining regions can be significant. During the 2010/2011 Queensland floods (Australia), the associated financial costs of inoperable coalmines and operating restrictions were AU$ 5-9 billion (26).
  3. Infrastructure risks. Climate change may lead to a thawing of permafrost over time in some regions, and thus affect the stability of existing slopes and dams that were designed under the assumption of being continually frozen (27). Receding glaciers may significantly change runoff volumes to mine-sites. Transport infrastructure may be impacted in a variety of ways. Mine wall collapses caused by high rainfall may damage or block access roads. Drought conditions can lower river levels and prevent barges accessing remote mine sites. Ice roads providing access to mines may experience decreases in the operating season. Breaking up of ice sheets may create hazards for shipping of mineral concentrates (28). Alternatively there may be some benefits to the industry’s transport system, such as the opening and development of the Northwest Passage that may shorten shipping routes.
  4. Water quality risks. A major source of water quality issues associated with the mining industry is acid mine drainage (AMD), the release of which depends on surface weathering and chemical or bacterial oxidation processes of sulphide minerals, and (groundwater) flow rates (29). These processes, in turn, depend on a number of conditions such as temperature, precipitation, and dry spell length that vary with climate change (30). The overall effect in a certain area varies with geochemistry, waste containment and management practices of individual mine sites. 

Vulnerabilities - Global economic response to river floods

Global network: All countries are connected in a global network of supply chains and trade relations. A flood in one country, leading to production losses, affects economic sectors elsewhere via supply shortages, changes in demand, and price effects (41). At the same time, economic sectors elsewhere may benefit from the flood because demands will shift to non-affected suppliers, and these market adjustments may dampen economic losses (42). The flexibility of the global economic system dampens the shocks caused by flood events.

Direct production losses and their indirect repercussions in the global economic network have been assessed for projections of near-future fluvial floods until the year 2035. This was done for a large number of climate simulations based on a low-end scenario of climate change (RCP 2.6). In this study, the current level of adaptation to floods was kept constant until 2035 (40).

Strong losses in China have little impact on EU: The study shows that, in the absence of large-scale structural adaptation, the total economic losses due to fluvial floods will increase in the next 20 years globally by 17% despite partial compensation through market adjustment within the global trade network.Large direct losses are observed in China, the United States, Canada, India, Pakistan and various countries of the European Union. China will suffer the strongest direct losses, with an increase of 82%.

For the vulnerabilities of the United States and the European Union, their trade relations with China are particularly relevant. Although the United States and the European Union are affected by Chinese supply-chain losses to a similar extent, the European Union has a competitive advantage when it comes to exports to China; since there are stronger trade relations between the European Union and China than between the United States and China, the European Union is in a better position to increase exports and temporally replace affected Chinese producers. Thus, the balanced trade relations between the European Union and China are more advantageous for loss mitigation than the unbalanced situation between the United States and China. These balanced trade relations with the EU are also advantageous for China: they help sectors in the Chinese economy that are not affected by floods to keep up production in the disaster aftermath and to mitigate indirect losses.

Balanced trade relations to climate-proof economies: The European Union is well adjusted for the future increase in flood events in China, the scientists conclude. Over the past two decades, European exports to China were able to catch up with the growth of Chinese exports to the European Union, thereby balancing trade relations. By contrast, the US trade deficit with China has significantly increased.

The scientists stress the importance of building balanced trade relations between world regions: this might be a viable strategy to climate-proof regional economies and help to protect a national economy against a global intensification of weather extremes.

Adaptation -  Flood risk management

No ‘one-size-fits-all’ solution

Flood insurance differs widely in scope and form across Europe. There seems to be little appetite for harmonization of flood insurance arrangements across the EU, and little intention at the EU to embrace a top-down regulatory effort to harmonize insurance. The design and implementation of insurance schemes remains a national concern. The wide variety of existing insurance schemes, as well as different supply and demand patterns, show that there is no ‘one-size-fits-all’ solution (4).

Two contrasting cases of flood insurance are the UK and the Netherlands. In the UK, flood insurance provision is widely available. In the Netherlands, several efforts over the last years to introduce broader flood insurance coverage have failed (4). The latter is partly due to the extreme low-probability/high-impact nature of flood risks in the Netherlands which results in relatively high premiums for limited commercial flood insurance coverage (5).

Incentives due to insurance

Insurance can reduce financial burdens and uncertainty (6) and assists economies in dealing with the negative long-run impacts of natural hazards such as flooding (7). Risk pricing may encourage the reduction of exposure and lead to lower damage costs (8). Flood insurance could send signals leading to more preventative actions by those insured or the government (9).

In the case of genuine private insurance markets, the role of the state can be limited to preserving fair competition and financial viability of the insurer. When the preconditions for private markets are not fulfilled, or the potential positive externalities of insurance are not internalized, state interventions may boost insurance markets. This can either be by financially backing up the private insurers, e.g. government lead reinsurance, by investing in preventative measures, or by imposing regulatory measures (such as mandatory flood insurance) (4).

Adaptation – Risk management policies in agriculture

Risk management instruments in agriculture, such as crop insurance and disaster assistance programme, and especially how they are designed, will affect incentives to adapt (2). Three types of crop production insurance are: individual yield, area-yield and weather index insurance. In addition to these insurance schemes governments may decide to assist farmers financially after climate extremes that caused a lot of damage to their yields (ex post assistance) (1):

  • Traditional individual-yield crop insurance makes an indemnity payment when the farm incurs a yield loss. This can help to manage production risk but it is known to be expensive and will diminish incentives to adapt to climate change (1).
  • Area-yield crop insurance is a crop insurance scheme in which both indemnities and premiums are based on the aggregate yield of a geographical area. The indemnity equals the difference in value, if positive, between the area yield and some predetermined critical yield level. Participating producers in a given area would receive the same indemnity per insured unit of land, regardless of their own crop yield, and all would pay the same premium rate (3). Under changing climate conditions, area yield insurance would have the advantage of maintaining incentives to adapt (1).
  • Weather index insurance is an insurance scheme where a threshold in the proxy variable marks the point at which payments begin. Once the threshold is reached, the payment increases incrementally as the value of the index worsens. The payment rate is independent of the actual loss incurred by a policyholder (1).
  • Ex post payments are highly variable and can be extremely high in some years (1).

Weather index insurance or area yield insurance, which do not require on-farm verification, can help keep administrative costs down as compared to individual yield insurance, and they do not discourage adaptation since indemnities are paid independently of actual loss incurred by a policyholder. However, they are not a means for structural adaptation. Farmers will incorporate any insurance subsidies or ex post disaster payments to their production decisions, which may favour insurance over crop diversification or other risk management and adaptation strategies (1).

Adaptation – Working conditions in relation to heat stress

Many workers in Europe need to adapt to a future with more frequent heat situations. Some protective strategies to alleviate heat exposure might be heat wave monitoring and warning, a reduction of sources of heat in workplaces, a reduction of physical work intensity, personal protection through movable personal microclimate cooling and sophisticated technical developments in clothing (45). 

Adaptation – Risk management mining industry

Any climate change adaptation requirements in the mining industry are likely to be highly site specific, and so are the potential financial implications of these measures throughout the industry (23).


The references below are cited in full in a separate map 'References'. Please click here if you are looking for the full references for Europe.

  1. Antón et al. (2013)
  2. Collier et al. (2009), in: Antón et al. (2013)
  3. Miranda (1991); Barnett et al. (2005), both in: Antón et al. (2013)
  4. Surminski et al. (2015)
  5. Paudel et al. (2013), in: Surminski et al. (2015)
  6. Ghesquiere and Mahul (2007); Melecky and Raddatz (2011), both in: Surminski et al. (2015)
  7. von Peter et al. (2012), in: Surminski et al. (2015)
  8. Bozzola (2014), in: Surminski et al. (2015)
  9. Kunreuther (1996); Botzen et al. (2009); Shilling et al. (1989); Treby et al. (2006), all in: Surminski et al. (2015)
  10. Meinel and Abegg (2017)
  11. Ford et al. (2010); IPCC (2014a); Loechel et al. (2013), all in: Meinel and Abegg (2017)
  12. Allianz Global Corporate and Specialty (2012), in: Meinel and Abegg (2017)
  13. Busch (2011), in: Meinel and Abegg (2017)
  14. Maller and Strengers (2011), in: Meinel and Abegg (2017)
  15. Neunteufel et al. (2015), in: Meinel and Abegg (2017)
  16. Kjellström and Crowe (2011); UKCIP (2010), both in: Meinel and Abegg (2017)
  17. Horrocks et al. (2010), in: Meinel and Abegg (2017)
  18. Grossman et al. (2012), in: Meinel and Abegg (2017)
  19. BSR (2011); UKCIP (2010), both in: Meinel and Abegg (2017)
  20. Agrawala et al. (2011); Loechel et al. (2013), both in: Meinel and Abegg (2017)
  21. European Commission (2011), in: Meinel and Abegg (2017)
  22. UKCIP (2010), in: Meinel and Abegg (2017)
  23. Northey et al. (2017)
  24. Gunson et al. (2012); Mudd (2008); Northey et al. (2013, 2014a, 2016), all in: Northey et al. (2017)
  25. COCHILCO (2015a, 2015b); Mudd et al. (2013); USGS (2016), all in: Northey et al. (2017)
  26. Sharma and Franks (2013); QRC (2011), both in: Northey et al. (2017)
  27. Pearce et al. (2011), in: Northey et al. (2017)
  28. Haley et al. (2011), in: Northey et al. (2017)
  29. Dold (2014); Lottermoser (2010); Nordstrom et al. (2015); Amos et al. (2015), all in: Northey et al. (2017)
  30. Anawar (2013); Lin (2012); MEND (2011); Nordstrom (2009); Phillips (2016), all in: Northey et al. (2017)
  31. Takakura et al. (2017)
  32. IPCC (2014)
  33. Cremades et al. (2018)
  34. Dixon et al. (2013); Lamond and Penning-Rowsell (2014), both in: Cremades et al. (2018)
  35. Schwarze and Wagner (2004), in: Cremades et al. (2018)
  36. Herweijer et al. (2009), in: Cremades et al. (2018)
  37. Penning-Rowsell et al. (2014), in: Cremades et al. (2018)
  38. Surminski (2017), in: Cremades et al. (2018)
  39. Kjellstrom et al. (2018)
  40. Willner et al. (2018)
  41. Hallegatte (2014); Maluck and Donner (2015), both in: Willner et al. (2018)
  42. Henriet et al. (2012), in: Willner et al. (2018)
  43. Casanueva et al. (2020)
  44. Perkins (2015), in: Casanueva et al. (2020)
  45. Gao et al. (2018), in: Casanueva et al. (2020)
  46. Dasgupta et al. (2021)
  47. Szewczyk et al. (2021)
  48. Parsons et al. (2022)
  49. ILO (2020a), in: Parsons et al. (2022)
  50. DARA and Climate Vulnerable Forum (2012); Kjellstrom et al. (2019), both in: Parsons et al. (2022)
  51. Li et al. (2020); Raymond et al. (2020), both in: Parsons et al. (2022)
  52. Kjellstrom et al. (2019); Borg et al. (2021), both in: Parsons et al. (2022)
  53. Vrontisi et al. (2022)