Economic Evaluation of Climate Change Impacts

Climate change has the potential to lead to major impacts and economic costs in Europe. This chapter reports on a recent regional assessment—the ClimateCost project—which has combined sectoral assessments and wider economic analysis to derive such estimates.

The results reveal potentially high economic costs from climate change in Europe, though these vary with the emission scenario and time period. While many of these impacts are projected to be adverse and lead to economic costs, there are also economic benefits. The results also show large differences in the patterns of impacts across Europe, with more negative impacts in South-Eastern Europe and the Mediterranean, due to a combination of the enhanced climate signal and the higher vulnerability in these regions. The analysis of different scenarios shows that mitigation (towards a 2 °C stabilisation scenario) would reduce these costs significantly, but only in the medium-long term (after 2040). There will therefore be a need for adaptation as well as mitigation, but given the high future uncertainty, this is likely to be best advanced through a framework of adaptive management.

While this European-wide view is important, the chapter also shows there is a need for country level analysis—as presented in this book—to capture national context and insights, to allow analysis of country specific risks, and to provide national-level information to start planning for adaptation.

This paper provides an overview on how climate change impact assessment is conducted in some EU countries, strengths and weaknesses of the current approaches, and the added values of the Austrian study (COIN). It focuses on bottom-up approaches for the assessment of climate risks and opportunities (CRA) as well as costs and benefits (CBA) of climate change. Main findings are: Despite different decision making contexts all methodologies acknowledge the inevitability of “unquantifiable impacts”. Uncertainties are pervasive but confidence rankings are not universally applied. Risk scorings and CBA coexist in almost all countries but are differently established in adaptation planning. An important gap in many methodologies of bottom-up is the assessment of cross-sectoral, indirect and macroeconomic effects. The COIN project advances CBA methods in several respects: It carefully defines concepts and impact chains, applies consistent socio-economic scenarios and shared policy assumptions across sectors. It covers cross-sectoral, indirect and macroeconomic effects. And it combines observations and projections, which can be more easily communicated in national dialogues than top down models. A logical next step is parallel national CRA effort—much in similarity to other European countries.

Impact assessment at the national level requires sectoral detail, economy-wide integration, and a consistent framework and toolbox to do so. This chapter discusses the issues and derives the requirements for climate scenarios and local indicators, shared socioeconomic pathways, and economic evaluation to allow for and ensure consistent integration. Finally, a methodological check-list for national level quantitative climate impact assessment is provided.

The aim of this task within the COIN framework is the preparation of the climatological information for all involved sectors for the past and the possible range of future developments. As a basis for the historical observations, products of the Austrian weather service (ZAMG) are used. The climate change scenarios are derived from 31 regional and global climate models forced with four different emission scenarios.

Impact relevant climate depending indicators have been developed and calculated from observational data and climate change scenario on a NUTS3 level. In total, 63 impact relevant indicators have been defined. The majority of the indicators are a kind of “peak over threshold” analyses like the temperature threshold heat day (Tmax ≥ 30 °C).

All climate scenarios indicate a warming within the twenty-first century. The whole ensemble indicates a warming of 0.5 up to 4 °C till 2050 and at the end of the century the warming reaches from ~2 °C up to 6 °C in winter and up to 9 °C in summer. The low border stems from models forced with the RCP 4.5 emission scenario and the high border from models forced with RCP 8.5.

The climate change signal for precipitation is not that clear. The annual sum shows no clear trend. For summer precipitation, the majority of the model indicates a decrease till −20 % and in winter an increase of the same magnitude.

The derived indicators reflect the same trends. In general, it can be said that temperature depending indicators at the middle of the century derived from the hottest realisations have a similar climate change signal as the “mid-range” scenarios at the end of the century.

Socio-economic pathways determine future climate impacts and costs thereof. Pragmatically, we have referred to a global reference socio-economic pathway (represented by SSP2 in the IPCC process) and derived figures for the core economic, demographic, land-use and (qualitatively) technological development in Austria, which again frame the sectoral development assumptions necessary to follow a scenario-based cost assessment approach.

In principal, trend projections and existing studies have been used to describe a single country, here applied for Austria, in 2030/2050 that is growing slowly in terms of population (0.27 % p.a.) and medium in terms of GDP (1.65 % p.a.) and in which forests, meadows and settlements expand in the north-east-south crescent—at the cost of arable land, within which further intensification will take place. Policy assumptions as well as technological change have been set to a medium path, at which risk zoning put forward, the EU integration ‘muddles through’ and no technological wonders are taken into account. A reference scenario might be regarded as least uncertain—which is not true—but we might expect more volatile developments to equilibrate over some decades.

The Austria we expose to climate change by 2050 is significantly different from nowadays: Its population is older and its public and private infrastructure density is higher—at least two factors that might influence future climate costs of inaction.

The first step in an economic assessment of climate change impacts at the country level is the identification of so-called “impact fields”. These fields can be either single economic sectors, parts of sectors or aggregates of sectors. For the case of Austria that is explored in this book, 12 impact fields are identified and investigated regarding climate change impacts and the resulting economic costs and benefits. As impact fields are often of very different character, the mechanisms of climate change impacts are different and, therefore, also the costing methods to obtain costs and benefits of climate change are diverse. Hence, depending on the impact field, one or several of the following costing methods are applied: Changes in production technology and subsequent production cost structure, changes in productivity, changes in final demand, changes in investment, changes in public expenditures, and, finally, level of replacement cost. By applying these methods we obtain the direct costs by impact field.

As a modern economy is characterised by a strong specialisation across activities and sectors, there are strong interdependencies between different economic sectors (e.g. the food sector relies heavily on agriculture). For that reason, indirect effects on other sectors may contribute to total costs (or benefits) for the economy as well. A framework is needed which is able to capture these interactions between economic sectors. For that reason we here employ a computable general equilibrium (CGE) model as it depicts linkages between economic sectors as well as agents and is therefore able to cover interaction between different climate impacts occurring in different sectors. Relevant model outputs are changes in welfare, changes in sectoral activity (output), changes in value added and GDP, as well as in public budgets.

Agriculture is highly exposed to climate change. The severity of impacts on agricultural systems usually varies by geographic, natural, and socioeconomic factors. We match results from a bio-physical process model with the climate change scenario of the COIN (Cost of Inaction) project to derive climate induced yield impacts on major crops and permanent grassland in Austria. An economic calculation is applied to estimate average annual changes of production values and costs for the periods 2016–2045 and 2036–2065. Results feed into a computable general equilibrium (CGE) model to assess economy-wide effects. Uncertainties are addressed in the study and are mainly due to high spatial and sectoral aggregation as well as the unknown autonomous adaptation behaviour of farmers. Our analysis indicates moderately higher outputs and value added at the sector level. This results in a positive impact on the rest of the Austrian economy. The aggregated results conceal adverse regional and farm type specific impacts.

A warmer climate with reduced summer precipitation will affect the biomass productivity in Austrian forests. In mountain forests with sufficient precipitation, an extended growing season will lead to productivity increases. In eastern and north-eastern lowlands and in inner-Alpine basins, extended and more frequent drought periods will result in reduced production. The two most relevant disturbance factors in Austrian forests are bark beetles and storms. Disturbance regimes from temperature driven agents such as bark beetles will intensify under all available climate change scenarios. Abiotic disturbance factors such as storms, snow and late frost events have the potential to cause damage, however information about future development of these drivers is highly uncertain. Forest fires will likely occur more often in Austrian forests, however, the scale of fires is comparably small and of local importance only. Disturbances will impact on contribution margins of timber production and increase regeneration costs. Other ecosystem services like recreation and CO₂ sequestration might be negatively affected as well by an intensified disturbance regime. A particularly important service in Austria is protection against gravitational hazards (snow avalanches, rockfall, mudflow). We have used data of the National Forest Inventory and available results from earlier climate change related studies to quantify the effect of climate change on timber production and on the bark beetle disturbance regime in Norway spruce forests. At the end of the century (2070–2100) conservative estimates indicate mean annual losses of 2.43 million euros p.a. due to impacts on productivity. Bark beetle damages in production forests may cause damages as high as 141 million euros p.a. (period 2074–2100). To substitute for losses in protective capacity, mean annual investment costs between 85 million euros (period 2014–2035) and 189 million euros (period 2074–2100) have been estimated. The macroeconomic effects triggered by these three impact chains are found to be negative, both for welfare and GDP. Welfare is found to decline by up to −0.10 % by mid-century, compared to a baseline scenario without climate change. The lion’s share of macroeconomic impacts is due to the investment requirements to maintain or restore protective forests after disturbances, followed by the damages due to bark beetle disturbances in timber production. Future storm damages as one potential implication of climate change were beyond the scope of this study and were not considered.

Among the several ecosystem services delivered by biodiversity, natural pest control and pollination are comparatively well understood and highly relevant for ensuring food provision. We describe the potential impacts of climate change, in particular the effects of increasing temperatures, on pest antagonists and pollinators, and evaluate the relevance for Austria’s agricultural ecosystems. Temperature changes lead to species range shifts, causing a reshuffling of assemblages and a decoupling of community interactions, followed by an impairment of pest control and pollination services. The effects are strongly modulated by socio-economic factors, particularly the development of semi-natural elements in agricultural landscapes. An enlargement of semi-natural area might mitigate the effects of climate change; a reduction in semi-natural area might exacerbate the climatic effects by impeding migration to track temperature changes even further. We calculated the value of pest control in Austria to be approximately 255 million euros or 8.5 % of the total agricultural plant product value in 2008. Pollination in Austria is worth 298 million euros, corresponding to 9.9 % of the total agricultural plant product value. We distinguish and discuss four possible climate impact scenarios; a scenario describing a moderate reduction of these values emerged as the most likely one.

There are manifold pathways by which climate change affects human health. Most directly, temperature increases will bring fewer deaths from cold on a global scale. However, despite temperature increases, single cold events might occur at the same time, mainly threatening humans in regions like Southern Europe, which are not well adapted to cold conditions. For Austria, cold-related deaths play a minor role. In contrast, the risk of dying due to increasing temperatures and heat waves in summer is growing significantly in the future. Estimates for Austria for three climate and three socioeconomic scenarios excluding adaptation forecast roughly 600–3,000 deaths or 7,000–32,000 “years of life lost due to premature mortality” for the 2050s. Impacts are three times more sensitive to varying climatic than to varying socioeconomic scenarios. Amongst indirect health effects, Salmonellosis cases have been declining steadily due to EU-wide programs. It is highly uncertain if and to what extent climate change will slow down the effectiveness of these programs in future. Allergy as another indirect health effect will be enhanced by climate change due to the increasing spread of Ragweed, which is a potent source of allergens. A study shows that the increase in treatment costs is about ten times higher than the implementation costs of appropriate management plans in the case of Austria up to 2050.

The Water Supply and Sanitation (WSS) sector is a complex system that involves all, specific and geographically bound natural water resources; vast and diverse technical infrastructure; and a strong nexus to lifestyle and consumer behaviour. Therefore the sensitivity to changes, including climate changes, originates from many levels.

We consider a baseline scenario that reflects changes due to socioeconomic and demographic changes as well as a climate change scenario that reflects additional changes due to climate change. Based on changes of units like changes in final demand, new built assets, enlargements, or replacement of assets we attempt to give cost estimates for the WSS sector until 2050 (under the differentiation of the causal nexuses and exemplarily based on empirical data). Based on the estimated costs for the WSS sector macroeconomic effects are calculated, including spill-over effects to other sectors, as well as effects on welfare, GDP and public budgets. Note that both scenarios are subject to various assumptions and considerably high uncertainties and therefore the underlying results must be interpreted with care.

We show that an increase of infrastructure damages in the WSS sector will be mainly caused by floods or landslides due to intense precipitation events. Even higher impacts will originate from changed production costs (e.g. treatment effort, operation and maintenance etc.) due to climate change as more assets and labour will be needed to provide the same service as today or to meet an additional climate change induced consumer demand. In total, the adaptation to socioeconomic and demographic changes will be the bigger challenge than the adaptation to climate changes. However, the costs of climate change will only add up to the total costs for each customer. Despite of all uncertainties involved, investigations on the effects of climate change suggest that there will be hardly any benefits but a lot of different costs for the WSS sector.

In order to adapt the long-living assets of WSS sector in an efficient way, more and early information on the impacts and their magnitudes on the sector will be needed.

While energy savings in buildings is among the key prerequisites for a low-carbon future, our ability to maintain temperatures in buildings within a specific comfort range, and thus our demand for heating and cooling energy, are also highly sensitive to climate change. We quantify two main impact chains: (1) a higher temperature in winter leads to a reduction of heating energy demand and (2) a higher temperature in summer leads to an increase in demand for cooling. The demand for cooling energy depends largely on the future uptake of air conditioning in the building sector and is subject to considerable uncertainty. On quantifying these two impacts for the example of Austria for the period around 2050 a net saving of about 230 million euros per year is found, triggering slightly positive effects on welfare and GDP. The result is depending on the development of energy prices and in particular by the ratio of electricity to fuel price in the heating sector. The results show that, in absolute terms, the energy reduction in heating is much higher than the increased energy demand for cooling for the time horizon and the geographical location investigated. This stems from the fact that energy demand for air conditioning in Austria in 2008 was only 0.4–0.5 % of the final energy demand for heating. The impacts and costs resulting from a strong increase in electricity peak loads in summer are investigated in Chap. 14 (Electricity).

This chapter investigates the impact of climate change on the electricity sector. We quantified two main impact chains: (1) impact of climate change on electricity supply, in particular on hydropower and (2) impact of climate change on electricity demand, in particular for heating and cooling. The combined effects of these two impact chains were investigated using the optimization model HiREPS. This takes the hourly resolution of the electricity system into account and considers, in particular, the interaction of the Austrian and German electricity markets. The results show that by 2050 there is a robust shift in the generation of hydroelectric power from summer to winter periods and a slight overall reduction in hydropower generation. The absolute increase in electricity demand is moderate. However, the electricity peak for cooling approximately reaches the level of the overall electricity load in 2010. These two effects—decreasing hydropower supply and increasing cooling electricity peak load (cf. Chap. 13)—lead to moderate sectoral climate change costs in 2050 compared to the baseline scenario without climate change. Regarding macroeconomic effects coming from climate change impacts on the electricity sector we see negative impacts on welfare as well as GDP. However, significant uncertainties remain and the effect of extreme events and natural hazards on electricity supply and transmission infrastructure also needs further examination. The costs of a potential increase in black out risk may be orders of magnitude higher than the costs indicated in our mid-range scenario.

30 to 50 % of road maintenance costs in Europe are weather-related, with precipitation triggered events, like flooding and mass movement, contributing most. As most transport occurs on roads, damage implications of road transport infrastructure are explicitly relevant. In this chapter, we focus therefore on damages to road transport infrastructure and assess the costs of climate change induced repair and investment for the Austrian road network until mid-century. In addition to changed precipitation patterns, we also take road network expansion into account. We find that precipitation triggered damage costs to the Austrian road network are 18 million euros per year in the period 1981–2010. These damages increase to 27 million euros per year in the period 2016–2045 and 38 million euros in the period 2036–2065. For Austria in total, the lion’s share of this cost increase is caused by an increase in exposed values (road network expansion), not climate change. While some regions are characterised by increases in precipitation, precipitation is decreasing in others, and there is also a seasonal shift. As a consequence, the overall effect of changes in precipitation is modest for Austria in total. The induced additional investment needed for road maintenance due primarily to road network extension and only secondarily to climate change is beneficial for the construction sector, but affects other sectors negatively due to higher prices. As a consequence, the decline in welfare and GDP is about three times larger than the additional investment cost for both periods (2016–2045 and 2036–2065).

The sector “Manufacturing and Trade” exhibits relatively high climate sensitivity as it depends on climate sensitive raw materials and intermediary inputs (such as agricultural products, timber and energy). In addition, changes in climatic stimuli (such as in temperature and relative humidity) may also influence production processes and/or the productivity of workers.

In the present chapter all these effects are discussed qualitatively. The productivity losses of workers, however, are also estimated on the basis of a quantitative model using a relationship between the Wet Bulb Globe Temperature (WBGT) index and the productivity of workers. The Human Capital Approach (HCA) and a GDP per employee approach are used for monetising the direct productivity losses.

Changing working conditions can have serious effects on the productivity of workers and thus on companies. Depending on the climatic development and the degree of adaptation the degree of damage caused can vary significantly. The direct climate impacts observed in the sector “Manufacturing and Trade” are magnified fourfold by associated macroeconomic feedback effects. For the mid-range climate scenario, there is a decline in economic welfare of 6 million euros per year for the period 2016–2045 (and 54 million euros for 2036–2065). For the high-range climate scenario respective welfare losses amount to 58 million euros (296 million euros). As declining demand also triggers price declines, losses in GDP are thus stronger, about 1.5 times the welfare losses. Note, however, that we only estimate the effects of productivity changes within the sector “Manufacturing and Trade”. Similar productivity changes could affect the remaining sectors of the whole economy as well, and thus could increase the economy-wide effects of climate-induced productivity changes above those quantified in the present chapter.

Expansion of urban green is triggered by settlement growth that preserves appropriate urban green shares and—potentially—by explicit policy to counter local temperature increase in urban environments in the future. Both issues are considered here. Green space expansion because of urban growth in Austria’s six larger cities is assumed to reach 144 ha (4.7 %) from 2011 till 2030 and 62 ha (2 %) from 2031 till 2050. Adapting additionally to climate change would result in more expansion: 195 ha (6.4 %) between 2011 and 2030 and 143 ha (4.7 %) between 2031 and 2050 reaching a total of 11 % urban green growth by 2051. Annual investment costs for new parks are estimated at 119 million euros for the period 2011–2030, and 93 million euros for 2031–2050 respectively. Annual costs for maintaining these additional parks are estimated at 7.6 million euros till 2030 and 13.4 million euros till 2050. Such preventative costs are an approximation that can be considered as lower bound of thermal discomfort due to climate change in the six larger Austrian cities.

Losses from natural disasters are on the rise and risk management options for lessening direct as well as indirect consequences are gaining in importance. Riverine flooding is one key concern and climate change is globally projected to increase intensity and frequency of flooding burden - albeit, due to numerous uncertainties there is only low confidence in projected changes. On the other hand, there is high confidence that today’s and future losses are rising as more assets and people are moving in harm’s way. The quantitative assessment of flood risk is complex, as such extreme event risk is characterized by few observations (low probability) associated with massive consequences (high impact), which by definition means substantial uncertainty around any estimates, particularly if future drivers, such as from climate change, need to be addressed as well. The methodology of choice is probabilistic catastrophe modelling, which combines hazard (flood intensity and frequency) with exposure (people and assets) and their vulnerability (susceptibility of exposed people and assets to incur losses for a given hazard). In order to properly account for uncertainty, we present three different catastrophe risk modelling approaches that outline the scope for possible changes in flood risk in Austria over the next 90 years. The analysis and findings are particularly relevant for Austria’s Natural Disaster Fund, which is the primary disaster loss financing vehicle in Austria. Large uncertainties between the different approaches and various limitations restrict our general conclusion as well as a full comparison between the approaches. However, we discuss possibilities to overcome these barriers in the future including suggestions how to arrive at more robust solutions in the face of such large uncertainties.

Tourism ranks amongst those sectors regarded as being highly weather and climate sensitive, since lots of tourism types and activities have a strong link to the environment and to the climate itself. During snow-poor winters, such as 1989/90 and 2006/07, several Austrian regions showed noticeable drops in tourism demand—whereas extraordinary sunny, warm and dry summers, like the one in 2003, coincided with above-average tourism demand increases in lake regions. In order to assess the potential impacts of future climate change on tourism demand in Austria, we (1) use dynamic multiple regression models to quantify the sensitivity of overnight stays towards year-to-year weather for each NUTS 3 region and various seasons, (2) apply the resulting sensitivities on climate change scenarios—based on a general tourism development scenario—and (3) transform the resulting impacts on overnight stays into monetary terms using average tourist expenditures. Outcomes suggest predominantly negative impacts on winter tourism and mainly positive impacts on summer tourism, with the net impact being negative. Finally we (4) evaluate the effects of the negative tourism impacts in a macroeconomic CGE model. Resulting spillover effects to other economic sectors as well as changes in GDP and welfare are found to be even higher than the impacts on tourism. There are considerable uncertainties however, not only with respect to climate change scenarios, but also for instance regarding future tourist preferences and weather/climate sensitivities.

A quantification of climate damages or the costs of inaction faces the inherent uncertainty of future climate scenarios and socio-economic developments. For the appraisal of the long-run cost of inaction in COIN we therefore apply the Delphi technique until 2100 that offers a qualitative assessment by recognised experts rather than quantitative results. The Delphi results suggest pronounced increases in the damage costs in the second half of the twenty-first century. For half of the sectors addressed, there is unanimous consensus among experts that climate damage costs in 2070 will be higher than in 2050. A further increase in costs after 2070 is expected for the majority of sectors. Economic and social developments are considered the most important cost drivers in the long run. Despite this judgement, however, uncertainty of future social, economic and thus cost development is rated considerably high. Extreme events might be key determinants of the long-term cost of inaction.

This chapter evaluates the aggregate macroeconomic effects of the quantifiable impact chains in ten impact fields for Austria: Agriculture, Forestry, Water Supply and Sanitation, Buildings (with a focus on heating and cooling), Electricity, Transport, Manufacturing and Trade, Cities and Urban Green, Catastrophe Management, and Tourism. First, the costing methodology used for each impact chain as well as the respective interface to implement them within the macroeconomic model are reviewed and compared across impact fields. The main finding here is that gaps in costing are mostly the consequence of insufficient data and for that reason, the two important impact fields Ecosystem Services and Human Health could not be assessed in monetary terms. Second, for the subset of impact chains which could be monetised, a computable general equilibrium (CGE) model is then used to assess the macroeconomic effects caused by these. By comparing macroeconomic effects across impact fields, we find that the strongest macroeconomic impacts are triggered by climate change effects arising in Agriculture, Forestry, Tourism, Electricity, and Buildings. The total macroeconomic effect of all impact chains—which could be quantified and monetised—is modest up to the 2050s: both welfare and GDP decline slightly compared to a baseline development without climate change. This is mainly due to (a) all but two impact chains refer to trends only (just riverine flooding damage to buildings and road infrastructure damages cover extreme events), (b) impacts are mostly redistribution of demand, while stock changes occurring as a consequence of extreme events are basically not covered and (c) some of the precipitation-triggered impacts point in opposite directions across sub-national regions, leading to a comparatively small net effect on the national scale.

Analysis of the study results indicate that the current welfare damage of climate and weather induced extreme events in Austria is an annual average of 1 billion euros (large events only). This has the potential to rise to 4–5 billion euros by mid-century (annual average, known knowns of impact chains only), with an uncertainty range of 4–9 billion euros. When extreme events and the tails of their distribution are included, even for a partial analysis focused on extremes, damages are seen to rise significantly, e.g. with an estimated increase to 40 billion euros due to riverine flooding events alone by the end of the century. These highlight the need to consider the distribution of impacts, as well as the central values.