Special Report On Emissions Scenarios Research Articles

Experience from downscaling IPCC-SRES scenarios to specific national-level focus scenarios for ecosystem service management

Scenario analysis is a widely used approach to incorporate uncertainties in global change research. In the context of regional ecosystem service and landscape management where global IPCC climate simulations and their downscaled derivates are applied, it can be useful to work with regional socio-economic scenarios that are coherent with the global IPCC scenarios. The consistency with the original source scenarios, transparency and reproducibility of the methods used as well as the internal consistency of the derived scenarios are important methodological prerequisites for coherently downscaling pre-existing source scenarios. In contrast to well-established systematic-qualitative scenario techniques, we employ here a formal technique of scenario construction which combines expert judgement with a quantitative, indicator-based selection algorithm in order to deduce a formally consistent set of focus scenario. In our case study, these focus scenarios reflect the potential development pathways of major national-level drivers for ecosystem service management in Swiss mountain regions. The integration of an extra impact factor (“Global Trends”) directly referring to the four principle SRES scenario families, helped us to formally internalise base assumptions of IPCC SRES scenarios to regional scenarios that address a different thematic focus (ecosystem service management), spatial level (national) and time horizon (2050). Compared to the well-established systematic-qualitative approach, we find strong similarities between the two methods, including the susceptibility to personal judgement which is only partly reduced by the formal method. However, the formalised scenario approach conveys four clear advantages, (1) the better documentation of the process, (2) its reproducibility, (3) the openness in terms of the number and directions of the finally selected set of scenarios, and (4) its analytical power.

A nonparametric stochastic method for generating daily climate-adjusted streamflows

[1] A daily stochastic streamflow generation model is presented, which successfully replicates statistics of the historical streamflow record and can produce climate-adjusted daily time series. A monthly climate model relates general circulation model (GCM)-scale climate indicators to discrete climate-streamflow states, which in turn control parameters in a daily streamflow generation model. Daily flow is generated by a two-state (increasing/decreasing) Markov chain, with rising limb increments randomly sampled from a Weibull distribution and the falling limb modeled as exponential recession. When applied to the Potomac River, a 38,000 km2 basin in the Mid-Atlantic United States, the model reproduces the daily, monthly, and annual distribution and dynamics of the historical streamflow record, including extreme low flows. This method can be used as part of water resources planning, vulnerability, and adaptation studies and offers the advantage of a parsimonious model, requiring only a sufficiently long historical streamflow record and large-scale climate data. Simulation of Potomac streamflows subject to the Special Report on Emissions Scenarios (SRES) A1b, A2, and B1 emission scenarios predict a slight increase in mean annual flows over the next century, with the majority of this increase occurring during the winter and early spring. Conversely, mean summer flows are projected to decrease due to climate change, caused by a shift to shorter, more sporadic rain events. Date of the minimum annual flow is projected to shift 2–5 days earlier by the 2070–2099 period.

Reliability Assessment of the Water Supply Systems under Uncertain Future Extreme Climate Conditions

Abstract Increase in global mean temperature and changes in rainfall amount, pattern, and distribution over the world are all indicative of climate change events. These changes alter the hydroclimatic condition of regions as well as the availability of water resources. In this study, the data generated by 14 general circulation models (GCMs) developed under the Special Report on Emissions Scenarios (SRES) A1B, A2, and B2 are downscaled and utilized to evaluate climate change impact on the hydroclimatic system of the Karaj River basin located in central Iran. The precipitation and temperature of the study region are downscaled using the change factor approach (CFA). The study analyzes future climate data, extreme changes of future climatic conditions of precipitation, and temperature. The Hydrologiska Byråns Vattenbalansavdelning (HBV) model developed by the Swedish Meteorological and Hydrological Institute (SMHI) is used to simulate streamflow under extreme climate change conditions. Two different sources of uncertainty are investigated in this study. First, the model parameters uncertainty is analyzed with the Monte Carlo procedure, and then different datasets of GCMs projection are investigated under the climate of the twentieth-century climate simulation (20C3M). Results show the GCMs projections range can almost capture the historical records during the 1980s through 2000 for the Karaj basin. By applying the HBV model, considerable range of streamflow changes in the future can be projected that will affect the operation scheme of Karaj Reservoir. In this study, the system dynamics (SD) modeling approach is used to simulate the system behavior through time in an integrated fashion and evaluate its overall reliability in supplying water. The results of this study show that the runoff will decrease in the future under the climate change impact. This will result in more than 50% decrease in reliability of the Karaj Reservoir system under the extreme conditions. As a result, this research predicts that the Karaj Reservoir system will face more than 50% decrease in its reliability under the extreme conditions. Consequently, meeting the increasing water demands would be difficult and application of demand management strategies will be unavoidable.

Uncertainty in Climate Change Projections of the Hadley Circulation: The Role of Internal Variability

Abstract The uncertainty arising from internal climate variability in climate change projections of the Hadley circulation (HC) is presently unknown. In this paper it is quantified by analyzing a 40-member ensemble of integrations of the Community Climate System Model, version 3 (CCSM3), under the Special Report on Emissions Scenarios (SRES) A1B scenario over the period 2000–60. An additional set of 100-yr-long time-slice integrations with the atmospheric component of the same model [Community Atmosphere Model, version 3.0 (CAM3)] is also analyzed. Focusing on simple metrics of the HC—its strength, width, and height—three key results emerge from the analysis of the CCSM3 ensemble. First, the projected weakening of the HC is almost entirely confined to the Northern Hemisphere, and is stronger in winter than in summer. Second, the projected widening of the HC occurs only in the winter season but in both hemispheres. Third, the projected rise of the tropical tropopause occurs in both hemispheres and in all seasons and is, by far, the most robust of the three metrics. This paper shows further that uncertainty in future trends of the HC width is largely controlled by extratropical variability, while those of HC strength and height are associated primarily with tropical dynamics. Comparison of the CCSM3 and CAM3 integrations reveals that ocean–atmosphere coupling is the dominant source of uncertainty in future trends of HC strength and height and of the tropical mean meridional circulation in general. Finally, uncertainty in future trends of the hydrological cycle is largely captured by the uncertainty in future trends of the mean meridional circulation.

An uncoupled dynamical downscaling for the North Sea: Method and evaluation

A reliable regional modeling system for uncoupled dynamical downscaling simulations of potential global climate change scenarios in the North Sea is presented. The HAMSOM regional shelf ocean model is forced with results from the MPIOM global ocean model at the open lateral boundaries of the model domain, and with results from the REMO regional atmosphere model at the air-sea interface. The evaluation of the model chain is based on the North Sea regionalization for the period 1951–2000 of the global historic control run 20C3M for the IPCC SRES scenario runs under the CMIP3 model generation. To reproduce reasonable long-term statistics of hydrodynamic conditions in the North Sea, a bias correction method relative to ERA40 reanalysis data and WOA-2001 climatology is applied to the forcing variables. Comparisons of the HAMSOM model results with observational water temperature and salinity climatologies are presented as well as with previously published research of volume transports, residence and flushing times, NAO correlations, surface heat and fresh water fluxes, and thermocline parameters. In general, the model results agree reasonably with the given references, thereby qualifying the presented concept as an appropriate tool for dynamical downscaling of global scenario runs for the North Sea.

Assessing the effects of climate change on crop production and GHG emissions in Canada

Regions in northern latitudes are likely to be strongly affected by climate change with shifts in weather that may be conducive to increased agricultural productivity. In this study the DNDC model was used to assess the effect of climate change on crop production and GHG emissions at long-term experimental sites in Canada. Crop production in the model was parameterized using measured data, and then simulations were performed using historical weather (1961–1990) and future IPCC SRES climate scenarios (2040–2069). The DNDC model predicted that for western Canada under the SRES scenarios and no change in cultivar, yields of spring wheat would increase by 37% and winter wheat by 70%. Corn responded favorably to an increase in heat units at the eastern site with a 60% increase in yields. At all locations, yields were projected to increase further when new cultivars with higher GDD requirements were assumed. These increases were notable considering that the estimated soil water deficit indices indicated that there could be less water available for crop growth in the future. However, when accounting for increased water use efficiency under elevated CO2, DNDC predicted less crop water stress. Nitrous oxide emissions per ton of wheat were projected to increase across most of western Canada by about 60% on average for the A1b and A2 SRES scenarios and by about 30% for the B1 scenario. Nitrous oxide emissions per unit area were predicted to increase under corn production at the eastern location but to remain stable per ton of grain. Model results indicated that climate change in Canada will favor increased crop production but this may be accompanied by an increase in net GHG emissions for small grain production.

Projection of subtropical gyre circulation and associated sea level changes in the Pacific based on CMIP3 climate models

For all of the IPCC Special Report on Emission Scenarios (SRESs), sea level is projected to rise globally. However, sea level changes are not expected to be geographically uniform, with many regions departing significantly from the global average. Some of regional distributions of sea level changes can be explained by projected changes of ocean density and dynamics. In this study, with 11 available Coupled Model Intercomparison Project Phase 3 climate models under the SRES A1B, we identify an asymmetric feature (not recognised in previous studies) of projected subtropical gyre circulation changes and associated sea level changes between the North and South Pacific, through analysing projected changes of ocean dynamic height (with reference to 2,000 db), depth integrated steric height, Sverdrup stream function, surface wind stress and its curl. Poleward expansion of the subtropical gyres is projected in the upper ocean for both North and South Pacific. Contrastingly, the subtropical gyre circulation is projected to spin down by about 20 % in the subsurface North Pacific from the main thermocline around 400 m to at least 2,000 m, while the South Pacific subtropical gyre is projected to strengthen by about 25 % and expand poleward in the subsurface to at least 2,000 m. This asymmetrical distribution of the projected subtropical gyre circulation changes is directly related to differences in projected changes of temperature and salinity between the North and South Pacific, forced by surface heat and freshwater fluxes, and surface wind stress changes.

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.

Heat-related mortality risk model for climate change impact projection

We previously developed a model for projection of heat-related mortality attributable to climate change. The objective of this paper is to improve the fit and precision of and examine the robustness of the model. We obtained daily data for number of deaths and maximum temperature from respective governmental organizations of Japan, Korea, Taiwan, the USA, and European countries. For future projection, we used the Bergen climate model2 (BCM2) general circulation model, the Special Report on Emissions Scenarios (SRES) A1B socioeconomic scenario, and the mortality projection for the 65+-year-old age group developed by the World Health Organization (WHO). The heat-related excess mortality was defined as follows: The temperature-mortality relation forms a V-shaped curve, and the temperature at which mortality becomes lowest is called the optimum temperature (OT). The difference in mortality between the OT and a temperature beyond the OT is the excess mortality. To develop the model for projection, we used Japanese 47-prefecture data from 1972 to 2008. Using a distributed lag nonlinear model (two-dimensional nonparametric regression of temperature and its lag effect), we included the lag effect of temperature up to 15days, and created a risk function curve on which the projection is based. As an example, we perform a future projection using the above-mentioned risk function. In the projection, we used 1961-1990 temperature as the baseline, and temperatures in the 2030s and 2050s were projected using the BCM2 global circulation model, SRES A1B scenario, and WHO-provided annual mortality. Here, we used the "counterfactual method" to evaluate the climate change impact; For example, baseline temperature and 2030 mortality were used to determine the baseline excess, and compared with the 2030 excess, for which we used 2030 temperature and 2030 mortality. In terms of adaptation to warmer climate, we assumed 0% adaptation when the OT as of the current climate is used and 100% adaptation when the OT as of the future climate is used. The midpoint of the OTs of the two types of adaptation was set to be the OT for 50% adaptation. We calculated heat-related excess mortality for 2030 and 2050. Our new model is considered to be better fit, and more precise and robust compared with the previous model.

High-Resolution Climate Change Impact Analysis on Medium-Sized River Catchments in Germany: An Ensemble Assessment

Abstract The impact of climate change on three small- to medium-sized river catchments (Ammer, Mulde, and Ruhr) in Germany is investigated for the near future (2021–50) following the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. A 10-member ensemble of hydrological model (HM) simulations, based on two high-resolution regional climate models (RCMs) driven by two global climate models (GCMs), with three realizations of ECHAM5 (E5) and one realization of the Canadian Centre for Climate Modelling and Analysis version 3 (CCCma3; C3) is established. All GCM simulations are downscaled by the RCM Community Land Model (CLM), and one realization of E5 is downscaled also with the RCM Weather Research and Forecasting Model (WRF). This concerted 7-km, high-resolution RCM ensemble provides a sound basis for runoff simulations of small catchments and is currently unique for Germany. The hydrology for each catchment is simulated in an overlapping scheme, with two of the three HMs used in the project. The resulting ensemble hence contains for each chain link (GCM–realization–RCM–HM) at least two members and allows the investigation of qualitative and limited quantitative indications of the existence and uncertainty range of the change signal. The ensemble spread in the climate change signal is large and varies with catchment and season, and the results show that most of the uncertainty of the change signal arises from the natural variability in winter and from the RCMs in summer.

An assessment of climate change impacts on the tropical forests of Central America using the Holdridge Life Zone (HLZ) land classification system

Ecological models have predicted shifts in forest biomes, yet there have been very few studies that have looked at the implications on carbon stocks due to these shifts. Carbon is closely correlated to biomass and constitutes an important characteristic of the forest ecosystem. It has implications for conservation and land use practices, especially for climate change mitigation strategies currently under discussion, such as REDD+. This study couples the Holdridge Life Zone (HLZ) classification with the ECHAM5 model, to evaluate the impacts of climate change using the Special Report on Emissions Scenarios (SRES) A2, A1B and B1 for the Central American region. We utilize methodologies which combine biophysical variables with model output to assess the impacts on carbon stocks for two time periods, 2000 and 2100, . Results show that overall, the tropical category of the HLZ classification gains area as a result of one type of HLZ shifting to another forest type. In many cases the shifts result in some categories of HLZ being lost in their entirety. Elevation-associated life zones are particularly vulnerable to future climatic changes. A strong point of our approach is that differences between disaggregate regional and aggregate country levels can be compared. We suggest that a critical focus of conservation and management efforts should be concentrated on where vulnerable biomes are at most risk (biomes that shift and/or reduce fall under the vulnerable category).

LARS-WG 기후자료를 이용한 금호강 유역 모의발생 벼 생산량의 불확실성

This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho river basin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for the Geumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1B and B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and Agricultural Organization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index of agreement (IoA), prediction efficiency (<TEX>$R^2$</TEX>), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were used to evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of 0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed <TEX>$R^2$</TEX> of 0.78, 0.90 and 0.96 respectively after adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projections for Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of <TEX>$4.5^{\circ}C$</TEX> in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddy rice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s, respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and <TEX>$0.173t{\cdot}ha^{-1}$</TEX> for the 2020s, 2050s and 2090s, respectively.

Precipitation extremes over the continental United States in a transient, high‐resolution, ensemble climate model experiment

AbstractUnderstanding future changes in the frequency, intensity, and duration of extreme events in response to increased greenhouse gas forcing is important for formulating adaptation and mitigation strategies that minimize damages to natural and human systems. We quantify transient changes in daily‐scale seasonal extreme precipitation events over the U.S. using a five‐member ensemble of nested, high‐resolution climate model simulations covering the 21st century in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A1B scenario. We find a strong drying trend in annual and seasonal precipitation over the Southwest in autumn, winter, and spring and over the central U.S. in summer. These changes are accompanied by statistically significant increases in dry‐day frequency and dry‐spell lengths. Our results also show substantial increases in the frequency of extreme wet events over the northwestern U.S. in autumn, winter, and spring and the eastern U.S. in spring and summer. In addition, the average precipitation intensity increases relative to the extreme precipitation intensity in all seasons and most regions, with the exception of the Southeast. Further, most regions receive a greater fraction of total seasonal precipitation from extreme events. These results imply fewer but heavier precipitation events in the future, leading to more frequent wet and dry extremes in most regions of the U.S. Our simulations suggest that many of these changes are likely to become statistically significant by the mid‐21st century. Given current vulnerabilities, such changes in extreme precipitation could be expected to increase stress on water resources in many areas of the U.S., including during the near‐term decades.

Multi‐site downscaling of maximum and minimum daily temperature using support vector machine

ABSTRACTClimate change impact assessment studies involve downscaling large‐scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site‐scale meteorological variables. This article presents a least‐square support vector machine (LS‐SVM)‐based methodology for multi‐site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS‐SVM inter‐site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k‐nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi‐site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Climate change impacts on global agriculture

Based on predicted changes in the magnitude and distribution of global precipitation, temperature and river flow under the IPCC SRES A1B and A2 scenarios, this study assesses the potential impacts of climate change and CO2 fertilization on global agriculture. The analysis uses the new version of the GTAP-W model, which distinguishes between rainfed and irrigated agriculture and implements water as an explicit factor of production for irrigated agriculture. Future climate change is likely to modify regional water endowments and soil moisture. As a consequence, the distribution of harvested land will change, modifying production and international trade patterns. The results suggest that a partial analysis of the main factors through which climate change will affect agricultural productivity provide a false appreciation of the nature of changes likely to occur. Our results show that global food production, welfare and GDP fall in the two time periods and SRES scenarios. Higher food prices are expected. No matter which SRES scenario is preferred, we find that the expected losses in welfare are significant. These losses are slightly larger under the SRES A2 scenario for the 2020s and under the SRES A1B scenario for the 2050s. The results show that national welfare is influenced both by regional climate change and climate-induced changes in competitiveness.

IPCC SRES A2와 B1 시나리오에 따른 한반도지역의 여름철 지표 오존의 수치모의

The surface ozone concentrations changes were investigated in response to climate change over the Korean peninsula for summertime using the global-regional one way coupled Integrated Climate and Air quality Modeling System (ICAMS). The future simulations were conducted under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 and B1 scenarios. The modeling system was applied for four 10-year simulations: 1996~2005 as a present-day case, 2016~2025, 2046~2055, and 2091~2100 as future cases. The results in this study showed that the mean surface ozone concentrations increased up to 0.5~3.3 ppb under the A2, but decreased by 0.1~10.9 ppb under the B1 for the future, respectively. However, its increases were lower than an increase of the average daily maximum 8-hour (DM8H) surface ozone concentrations which was projected to increase by 2.8~6.5 ppb under the A2. The DM8H surface ozone concentrations seem to be therefore far more affected by the climate and emissions changes than mean values. The probability of exceeding 60 ppb was projected to increase by 6~19% under the A2. In the case of B1, its changes were presented with an increase of 2.9% in the 2020s but no occurrence in the 2100s due to the effect of the reduced emissions. Future projection on surface ozone concentrations was generally shown to have almost the similar trend as the emissions of and NMVOC.

Measuring future paths of alternative sustainability indicators: an assessment of IPCC SRES scenarios

This study measures various indicators for sustainability in this century for four scenarios of SRES (Special Report on Emissions Scenarios) published by the Intergovernmental Panel on Climate Change (IPCC) to provide a comparable assessment of the scenarios. We assessed the scenarios using a model of Ramsey-type mainframe with cost models for fuel and non-fuel mineral resources, biomass and foods, and an environmental externality. The existing studies have not assessed these SRES scenarios for sustainability, but only for climate change and its policy under the scenarios using CO2 emissions and shadow prices as indicators. The significant contributions of this paper are an assessment of the scenarios using the measured future paths of various sustainability indicators and revealing that the SRES-B1 scenario is the most favorable from a sustainability perspective. The findings of this study contribute to further empirical analysis of the economics of sustainability and climate policy assessments.

Global Atmospheric Emissions of Polycyclic Aromatic Hydrocarbons from 1960 to 2008 and Future Predictions

Global atmospheric emissions of 16 polycyclic aromatic hydrocarbons (PAHs) from 69 major sources were estimated for a period from 1960 to 2030. Regression models and a technology split method were used to estimate country and time specific emission factors, resulting in a new estimate of PAH emission factor variation among different countries and over time. PAH emissions in 2007 were spatially resolved to 0.1° × 0.1° grids based on a newly developed global high-resolution fuel combustion inventory (PKU-FUEL-2007). The global total annual atmospheric emission of 16 PAHs in 2007 was 504 Gg (331-818 Gg, as interquartile range), with residential/commercial biomass burning (60.5%), open-field biomass burning (agricultural waste burning, deforestation, and wildfire, 13.6%), and petroleum consumption by on-road motor vehicles (12.8%) as the major sources. South (87 Gg), East (111 Gg), and Southeast Asia (52 Gg) were the regions with the highest PAH emission densities, contributing half of the global total PAH emissions. Among the global total PAH emissions, 6.19% of the emissions were in the form of high molecular weight carcinogenic compounds and the percentage of the carcinogenic PAHs was higher in developing countries (6.22%) than in developed countries (5.73%), due to the differences in energy structures and the disparities of technology. The potential health impact of the PAH emissions was greatest in the parts of the world with high anthropogenic PAH emissions, because of the overlap of the high emissions and high population densities. Global total PAH emissions peaked at 592 Gg in 1995 and declined gradually to 499 Gg in 2008. Total PAH emissions from developed countries peaked at 122 Gg in the early 1970s and decreased to 38 Gg in 2008. Simulation of PAH emissions from 2009 to 2030 revealed that PAH emissions in developed and developing countries would decrease by 46-71% and 48-64%, respectively, based on the six IPCC SRES scenarios.

Regional climate models downscaling in the Alpine area with multimodel superensemble

Abstract. The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control period.

Assessment of the Impacts of Climate Change on European Ozone Levels

The objective of this study is to investigate the potential impact of future climate change on ozone air quality in Europe. To provide a full assessment, simulations with the global chemical transport model GEOS-CHEM driven by the NASA Goddard Institute for Space Studies general circulation model (NASA/GISS GCM) are conducted. To isolate the effects from changes in climate and anthropogenic emissions four types of simulations are performed: (1) present-day climate and emissions (2) future climate following the IPCC Special Report on Emission Scenarios (SRES) A1B scenario and present-day anthropogenic emissions of ozone precursors (3) present-day climate and future emissions and (4) future climate and future emissions. Results indicate that climate change impact on its own leads to an increase of less than 3 ppb in western and central Europe whereas decreases are evident for the rest of the areas with the highest (about 2.5 ppb) in southeastern Europe (Italy, Greece). Increases are attributed to the increases of isoprene biogenic emissions due to increasing temperatures whereas decreases are associated with the increase of water vapor over sea which tends to decrease the lifetime of ozone as well as the increased wind speeds in the 2050 climate. When future emissions are implemented in the future climate simulations, the greatest increases are seen in the southwest and southeast Mediterranean (about 16 ppb) due to the increased isoprene biogenic emissions under higher levels of NO x in the model. Decreases up to 2 ppb of ozone are shown for France, Switzerland, Northern Italy and northern Europe.