The model describes the economy as a steady state of annual monetary flows between agents and sectors, in which all markets are cleared (= general equilibrium). In order to quantify theimpactsofclimatechange on a macroeconomic level, this equilibrium is disrupted (e.g. by altered production conditions), which leads to quantity and price adjustments, until a new equilibrium is reached where all markets are cleared again. Then, the initial equilibrium is compared to the newly established equilibrium and the sectoral and macroeconomic effects of international climateimpacts become visible. As the underlying input-output structure implies that all sectors in all regions are interconnected either on the supply or demand side, direct effects in one sector or region may spill over to other sectors and other regions. While there are some studies that have already investigated certain climatechangeimpacts on Germany’s foreign trade , this is the first study that analyses the consequences ofglobalclimatechangeforGermany within a consistent macroeconomic framework. The results ofthe study provide an initial impression of how Germany’s foreign trade and thus its domestic economy could be affected by various climatic impacts by the middle ofthe century. Although the present study provides concrete figures about theimpacts, any interpretation should focus on the effects and their interdependencies rather than on the absolute magnitude.
4 Impact functions
The stressor-response methodology is based on the concept that specific road materials and components will have specific responses to external stressors such as precipitation and temperature. The stressor-response factors introduced below have been developed based on the engineering and materials response affects that individual material and elements have based on the specific stressors. These effects are then applied to specific circumstances such as pavement or gravel where the stressors are applied based on theclimate context. The development of these factors is based on multiple inputs. A combination of material science reports, usage studies, case studies, and historic data were used to develop response functions forthe infrastructure categories. Where possible, data from material manufacturers was combined with historical data to obtain an objective response function. However, when these data were not available, response functions were extrapolated based on performance data and case studies from sources such as departments of transportation or government ministries. The stressor-response factors are divided into two general categories: impacts on new construction costs and impacts on maintenance costs. New construction cost factors focus on the additional cost required to adapt the design and construction when rehabilitating an asset to changes in climate expected to occur over the asset’s lifespan. Maintenance cost effects are those maintenance costs, either increases or decreases that are anticipated to be incurred due to climatechange to achieve the design lifespan if construction standards have not been adjusted. In each of these categories, the underlying concept is to retain the design life span forthe structure.
South Africa is the largest economy in Sub-Saharan Africa and a member of several regional and international development organizations including the African Union, the UN Security Council, the G20 and others (DFID 2011). As the highest regional emitter of carbon dioxide and ranked 11th globally, they are taking a leading role in reducing and mitigating climatechangeimpacts (DFID 2011). When compared to other Sub-Saharan African nations, South Africa has a highly developed infrastructure that is particularly vulnerable to potential changes in future climate. Still facing many challenges common to developing nations including further reduction of poverty, development of rural services, and continued economic growth, there are limited funds available to adequately address the threat climatechange poses to the existing infrastructure. The limitations on these available funds are challenging developing countries to identify the threats that are posed by climatechange, develop adaptation approaches to the predicted changes, incorporate changes into mid-range and long-term development plans, and secure funding forthe proposed and necessary adaptations (UNFCCC 2009, 2010).
4 2. Literature Review
The theoretical framework of this study is based on the economic models ofthe family, which generates the approach of multivariate heath outcome functions as advocated by Becker and Lewis (1973). Grossman and Joyce (1988), Rosenzweig and Schultz (1982) and Corman and Grossman (1985) extended this model to identify the theoretical and empirical determinants of birth outcomes. The baseline idea behind the proposed procedure is that the parent’s utility function depends on consumption, number of births and baby survival probability, which are endogenous variables except for consumption. The survival probability depends on the quality of medical care, nutrition and environmental issues during pregnancy. The health production function, in turn, depends on the efficiency ofthe mother in producing health, normally understood by the literature as the mother’s ability or the role of her education (Behrman and Wolfe, 1987a, 1987b and 1989).
The Vale of Evesham constitutes one ofthe most important regions for irrigated horticultural production in England, providing a focus for intensive production of vegetables, salad crops and soft fruit. These high value crops are increasingly dependant on supplemental irrigation to meet the exacting, high quality standards for produce being demanded by the major multiples and processors. As in other parts of England where irrigated production is concentrated, the underlying demand for irrigation in this region is growing steadily. In Worcestershire, these rising abstractions for irrigation, particularly in dry years, are impacting on local surface and groundwater resources, such as the Badsey Brook and Offenham gravels. Indeed, the Warwickshire Avon CAMS Report (EA, 2006) highlights that over the last decade restrictions at the Offenham control point have been applied every year for between 54-246 days to protect the environment from over-abstraction. Climatechange will worsen the situation, with higher summer temperatures, less summer rainfall and more evaporation being predicted (Hulme et al., 2002). Climatechange could therefore result in a reduction in summer water available for abstraction, and an increase in irrigation water demand.
Potentially suitable indicators were either selected from existing indicator systems (e.g., the SEBI—Streamlining European Biodiversity Indicators initiative and theClimateChange Indicators ofthe European Environment Agency), or were newly developed [ 21 ], resulting in a set of forty-four indicators which have been examined, in depth, for their feasibility at the German national level. Out of these, five indicators could be fully calculated (“realized” in Table 1 ) and nine indicators could be developed as “prototypes”; meaning that they could be fully developed on a conceptual level, but the necessary data for their calculation have not been available due to different reasons. Six out of these nine indicator prototypes are currently to be calculated and realized (“prototype in development” in Table 1 ). Thirty indicators, due to different reasons (see Section 4.2 and 5 and Reference [ 21 ]), could not be feasibly developed further. Indicator factsheets for all realized indicators and indicator prototypes describe the indicator and include all relevant information, such as suitability ofthe indicator, legal references and existing political targets, calculation algorithms, data sources, spatial and temporal resolution, as well as graphical and textual representations ofthe determined indicator values. All newly developed indicators have been included in the indicator set ofthe DAS [ 34 ] and one of them (phenological changes in wild plant species) has been added to the indicator set ofthe NBS [ 35 ].
resulting from GHG forcing became available based on updated emission scenarios (Leggett et al., 1992).
Parry et al. (1999) used the same method as Rosenzweig and Parry (1994) to examine the potential impactsofclimatechange on crop yields, world food supply, and the risks of hunger. This study was different from previous studies, mainly because it used GCMs with better spatial resolutions and updated emission scenarios (IS92). These authors ran crop models for three future climate conditions (2020s, 2050s, and 2080s) that were predicted by the GCMs HadCM2 and HadCM3 based on an IS92 scenario. In contrast with other studies conducted during the mid-1990s (Darwin et al., 1995; Adams et al., 1998), this study predicts the actual price increases under modest climatechange. Small detrimental effects on cereal production by 2080 were estimated by the HadCM2 climatechange scenario and were predicted to result in a cereal price increase of 17%. By contrast, the greater negative impacts on the yields projected under HadCM3 resulted in a crop price increase of 45% by 2080, with severe effects regarding the risk of hunger, especially in developing countries. The authors indicate that these global results hide regional differences in theimpactsofclimatechange. For instance, in the HadCEM2 scenarios, yield increases at high and high-mid latitudes resulted in production increases (e.g., in Europe and Canada). By contrast, yield decreases at lower latitudes (tropics) resulted in production decreases, an effect that could be exacerbated where the adaptive capacity is lower than theglobal average. Table 2 presents changes in cereal production that were estimated by Parry et al. (1999) at theglobal and regional levels to occur by 2080.
intimately connected,’ Beddington said. Other eminent scientists, such as James Lovelock in his book The
Vanishing Face of Gaia: A Final Warning, have similarly
urged for a ‘call to arms’ to combat climatechange and warned ofthe perils ahead if we do not reduce our carbon emissions and control population growth. When Thomas
Despite the varying projections regarding the future development of precipitation patterns in Germany, most studies point towards decreases in summer and increases in winter precipitation (KLIWA, 2005, 2005; Middelkoop et al., 2001; Shabalova et al., 2003; UBA and MPI, 2006). This could result in a higher risk of winter or early spring flooding, especially in the south-western parts ofthe country where these changes are expected to occur particularly pronounced. Forthe Rhine Basin, the ATEAM study has consequently pointed towards a shift of maximum monthly discharge from Mai and June in the 1990s (gauge at Kaub) to March in the 2050s (Zebisch et al., 2005), and the International Commission forthe Hydrology ofthe Rhine Basin concluded that the frequency and magnitude of peak discharges was to increase in winter (CHR, 1997). However, due to the different geographical conditions prevailing in the Rhine Basin, it remains difficult to determine a specific season that will show a higher occurrence of flooding in the future. Also, because the spatial and temporal precipitation patterns of each ofthe Rhine’s tributaries strongly influence individual flooding events (Disse and Engel, 2001). To assess theimpactsofclimatechange on flooding characteristics in several subbasins ofthe Rhine, Menzel et al. (2006) have used the ECHAM4/OPYC3 and HadCM3 model under the IS95a scenario. Results ofthe former model showed that in the Lahn, Main, Mosel and Neckar a clear increase in mean flood discharge forthe years 2061-2090 could occur. Projections by the HadCM3 model, however, stayed within the limits of natural variability for most subbasins, highlighting that the uncertainty about future flood discharge in the Rhine remains quite high.
Hence, increased fuel efficiency is important (for several reasons) In addition, cruising aircraft impact climate by NOx and contrails The aviation share in radiative forcing is presently 3 % (range 2-8%) Scenarios of aviation CO 2 emissions show potential increase by
Earth surface temperature series, which provides much better coverage of polar regions than HADCRUT4. We compare these results to a model using the HADCRUT4 data as a robustness check.
Marvel et al. (2016) argue that the efficacy of some forcings is less than that of greenhouse gases and anthropogenic aerosols. They use single-forcing experiments to estimate these efficacies and revise TCR and ECS estimates upward to 1.7K and to 2.6-3.0ºC, depending on the feedbacks included. Armour (2016) highlights the joint (multiplicative) importance ofthe Richardson et al. (2016) and the Marvel et al. (2016) studies, which together should raise observational ECS by 60%, reconciling the discrepancy between observation and model based estimates. We test this idea by estimating models with both total aggregated radiative forcing using a uniform efficacy and radiative forcing adjusted forthe lower efficacy of some forcings. Knutti et al. (2017) carry out an extensive survey ofthe literature, concluding that based on estimates constrained by different lines of evidence an ECS value of 3ºC is most likely. On the other hand, Brown and Caldeira (2017) argue that models that better simulate the current energy budget predict greater future warming and that the mean observationally informed ECS is 3.7ºC with a 25-75% interval of 3-4.2ºC. But Cox et al. (2018) find that based on models that estimate the observed climate variability better, the ECS is 2.8 ºC with a 66% confidence interval of 2.2- 3.4 ºC.
economic impact in the technology policy cases are quantified by comparing GDP and consumption differences relative to the no-policy case. The economic importance of mitigation options in theclimate policy framework are quantified by limiting investments of a mitigation option to the no-policy case and re-run the scenario subject to the limited technology portfolio. The two policy approaches have been addressed in only few scientific contributions although the significance is identified; see Sorrell and Sijm (2004) and Knopf et al. (2010). Kverndokk and Rosendahl (2007) studied the first best and second best policy mix for achieving a given emission target in a generic electricity sector model with low-carbon technologies, where learning-by-doing is a spill-over that needs to be internalized; see also Kverndokk et al. (2004). The interrelationship between climate and R&D policies has attracted more attention and is better understood; see e.g. Gerlagh et al. (2009). Recently a number of studies addressed the significance of having available mitigation options in global energy-economy models to achieve stringent mitigation targets within a climate policy framework; see Bauer et al. (2009), Luderer et al. (2009) and Edenhofer et al. (2010). The technology policy framework for mitigation purposes has not received as much attention in modeling studies so far. It has been mainly put forward by technology analysts asking forthe need to apply low-carbon technologies to replace conventional fossil fuel technologies; see Hoffert et al. (2002) and Pacala and Socolow (2003). These contributions do not focus on the significance ofclimate policies and neglect the emission rebound effect. The analysis of additional costs of inefficient technology policies compared with climate policies to achieve equal emission reductions is a notable exception; see e.g. Rafaij (2005, Ch. 7). Recently, Sinn (2008) highlighted the fossil
A changeof just 0.5 °C more can cause widespread damage and destruction. For example., at 1.5 °C, only half as many people on the planet will be exposed to water stress than at 2 °C.
There is also growing evidence that the loss of permafrost that comes with global warming further accelerates climatechange because ofthe large release ofthe greenhouse gas from these areas, which would subvert, or entirely negate, any meaningful progress in the fight against climatechange. At the current level of commitments, the world is on course for a disastrous 3 °C of warming.
maize, rice is increasingly often sown. Maize plants grow well in the floods, but the harvest is poor. Rice seed (paddy go- rah), on the other hand, flourished last year; as a result, some villagers are considering terracing and irrigation systems. Maize is still cultivated on higher ground. Green beans are also central to food security. In the last few year, the beans planted in the rainy season either drowned in the floods or were destroyed by sediments or salt water. To prevent this happening again, the villagers are planting a fast-growing bean variety at the start of and during the rainy season in areas less affected by flooding. They can harvest these plants before the first floods, so protecting them from sediments. The women describe diversification of varieties in fruit and vegetable production. Fruit varieties which grow on tall plants or trees, such as bananas, coconuts and sugar cane, are becoming more important. Vegetables do not survive the floods, so they are only grown during the rainy season by farmers whose land is located higher up, and in the dry sea-
Changes in globalclimate and the consequently resulting acceleration of sea-level rise require a thorough re-evaluation of coastal protection strategies in many parts ofthe world. This yields also forthe lowlands at the southern North Sea coast which are pro- tected by a line of dykes since about 1,000 years. The anticipation of an accelerated sea- level rise due to global warming has raised the question if this strategy of Keeping the Line will still be appropriate or if alternatives should seriously be taken into considera- tion. This yields the more since furthermore a number of secondary effects ofclimatechange will lead to stronger loads on coastal protection structures: increasing intensity of storms and consequently higher set-ups of storm surges (W OTH 2005) create as well larg- er water depths in front of coastal structures as the delayed adaption of tidal flat levels to an accelerating sea-level rise (M ÜLLER et al. 2007). Since wave heights and periods on tidal flats are strongly depth-controlled (N IEMEYER 1983; N IEMEYER and K AISER 2001) any increase of local water depth is accompanied by corresponding higher wave loads on coastal structures.
Five agro-climatic zones were identified using monthly observations from 30 weather stations forthe period 1976–2007 (see Figure 1). Climate data were aggregated to these zones, taking into consideration the influencing domain of each weather station, namely the Thiessen polygon whose boundary defines the area that is closest to the station relative to all other stations. Average annual rainfall exhibits a downward gradient from north to south (see Table 1). Zone 5 in the north has the highest annual rainfall (1228mm) while zone 1 in the south has the lowest (786mm). We calculated ‘reference evapotranspiration’ (ETo) at each weather station using the Penman-Monteith equation (Allen et al. 1998), a standard method recommended by the Food and Agricultural Organization ofthe United Nations (FAO) for determining evapotranspiration, which is the water being transported to the atmosphere from soil surface and vegetation, in this case, a reference crop. This provides the basis for measuring crop water requirements that, in turn, determine the effect of water availability on crop yields. In contrast to rainfall’s declining northtosouth trend, ETo increases from north to south. This suggests that rainfall is lowest where crop water requirements are highest, thus exposing rain-fed agriculture in the south to greater risk of yield losses (or crop failure during droughts).
model: hydrological, groundwater, biogeochemical and plant growth modules. The model operates on a daily-time step producing time series of discharge, nutrient flows and sediment transport as well as crop yield, and uses climatic, land use, topographic and soil datasets as input. The forcing climatic datasets include daily precipitation, solar radiation, relative humidity, and minimum, maximum and average daily temperatures. The topographical map of a catchment serves as a basis to create a subbasin map, which is later intersected with land use and soil maps to identify the Hydrological Response Units (HRU) - areas within each subbasin, with a unique combination of land use and soil type. Identical HRUs (also called hydrotopes), i.e. those with the same land use and soil types in a subbasin, are assumed to have the same hydrological “behaviour” and are later combined into hydrotope classes within each subbasin. The components ofthe hydrological cycle, nutrient cycling and sediment loads are calculated at the HRU level and the lateral flows are aggregated at the level of sub basins. The flows of water, nutrients and sediments are then routed through the basin, using a conceptual representation ofthe open channel hydraulics – the Muskingum method, taking into account transmission losses. Significant number ofthe successful calibration and validation stories ofthe SWIM model applications has proven the adequacy of this model to simulate the hydrological (e.g. Hattermann et al. [5,134]), biogeochemical as well as hydrochemical (e.g. Huang et al.) and crop growth (e.g. Liersch et al. ) processes in river basins of various sizes, geographical locations and with different data availability (see e.g., Aich et al. [78,82]). A thorough description ofthe success studies, as well as failure cases can be found in Krysanova et al. . The model took part within the frame ofthe ISI-MIP project in the model and impacts intercomparison exercise (e.g. Vetter et al. )
This paper proposes alternatives to the GWP that move one step further down the chain from radiative forcing to represent theglobal-mean surface temperature change. It does so by using a simple model oftheclimate system, in the spirit of designing a transparent metric that may be more widely accepted. However, the framework we present is clearly suitable for extension beyond this by using, for example, output from a sophisticated climate model, and could incorporate other impacts, such as sea-level rise or economic damage, as an end point. Even if the proposed metrics are not acceptable as replacements for GWPs, the method does seem to have value as a pedagogic tool for testing alternative metrics and understanding the behaviour of various climatechange agents and their effects on theclimate system. We will call the new metrics theGlobal Temperature Change Potential for both a pulse emission (GTP P ) and a sustained change in emissions
1999 )) that relates emissions to RPK for different aircraft types and allows aggregation at the ﬂeet level. The approach allowed the modelling ofthe improvements from incorporating more fuel- efﬁcient aircraft into the ﬂeet. Regional forecasts of RPK to 2020 were used from ICAO/FESG to calculate emissions in 2005, 2010, 2015, and 2020. After 2020, global RPK projections to 2050 were calculated using a non-linear Verhulst function with the IPCC Special Report on Emissions Scenarios (SRES) global domestic product (GDP) projections, A1 and B2 ( IPCC, 2000 ), to calculate emissions for 2030, 2040, and 2050 in a similar manner to Hen- derson et al. (1999) . These SRES scenarios, designated here as FAST- A1 and FAST-B2, were chosen because they were the ‘baselines’ against which assessments of mitigation were undertaken by the IPCC within WGIII for AR4. The overall growth of aviation in scenario B2 is not greatly dissimilar to that ofthe mid-range IPCC (1999) scenario, Fa1, and the A1 scenario is likewise similar to the upper-range IPCC (1999) scenario, Fe1. The FAST-A1 and FAST-B2 results are shown in Fig. 3 along with other earlier projections. The FAST-A1 and FAST-B2 scenarios include a scaling by a ﬁxed amount of 64 Tg fuel yr 1 , respectively, in order to be consistent with IEA fuel sales data up to 2005 ( Fig. 3 ). This amount represents the average difference between 1990 and 2000 data from a bottom-up inventory of aviation emissions ( Lee et al., 2005 ), excluding military emissions and IAE data on fuel sales data.
Between 1950 and 2017, world average life-expectancy increased from below-50 to above- 70, while the fertility rate dropped from 5 to about 2.5 children per woman (Figure 1 ). The worldwide rise of life-expectancy and fall of total fertility rate is expected to ro- bustly continue forthe remainder ofthe current century, with the emerging economies catching up the patterns typical for economies that industrialized before. The world- wide demographic trends decreases the ratio of young relative to old and changethe propensity to save ofthe average consumer. Both supply of labour and capital will adjust, and future capital returns will most likely differ from those in the past.