International Institute for Applied Systems Analysis

About: International Institute for Applied Systems Analysis is a nonprofit organization based out in Laxenburg, Austria. It is known for research contribution in the topics: Population & Greenhouse gas. The organization has 1369 authors who have published 5075 publications receiving 280467 citations. The organization is also known as: IIASA.

Insurance against Losses from Natural Disasters in Developing Countries. Evidence, gaps and the way forward.

Abstract: This paper examines recent experience with insurance and other risk-financing instruments in developing countries, informed by experience in developed countries, to provide insights on the effectiveness of insurance for reducing economic insecurity. Insurance and other risk financing strategies are viewed in the overall context of risk management, including the prevention of losses as well as financing the recovery process through risk pooling and transfer strategies. Specific examples of public-private insurance programs for households/businesses, farms and governments are described, including their limitations, especially in light of recent post-Katrina experience in the US. By examining the costs, benefits and risks of public-private risk-financing programs, insights are provided on the effectiveness of insurance as a mechanism for providing economic security to vulnerable communities and governments.

Major components of China's anthropogenic primary particulate emissions

Abstract: This paper presents the first comprehensive estimates of particulate emissions in China by size distribution and major components. Using a technology-based emission inventory approach, we are able to classify particulate emissions into three size ranges, TSP, PM10 and PM2.5 ,a nd identify the contributions of black carbon (BC), organic carbon (OC), Ca and Mg. Total particulate emissions are estimated to be 27.4 Tg for the year 2001, of which 17.8 Tg are PM10 and 12.7 Tg are PM2.5. Industrial processes are the major sources of particles over all three size ranges, but residential biofuel use and transportation sources become increasingly important for PM10 and PM2.5. The industrialized coastal provinces, such as Shandong, Jiangsu and Hebei, are the major sources of particulate emissions. The industrialized and developing regions show different characteristic emission ratios of PM2.5/TSP, (BC + OC)/PM2.5 and (Ca + Mg)/TSP. In the future, we can expect significant reductions in primary particulate emissions and major changes in the patterns of size and species.

The aridity Index under global warming

Abstract: Aridity is a complex concept that ideally requires a comprehensive assessment of hydroclimatological and hydroecological variables to fully understand anticipated changes. A widely used (offline) impact model to assess projected changes in aridity is the Aridity Index (defined as the ratio of potential evaporation to precipitation), summarizing the aridity concept into a single number. Based on the aridity index, it was shown that aridity will generally increase under conditions of increased CO2 and associated global warming. However, assessing the same climate model output directly, suggests a more nuanced response of aridity to global warming, raising the question if the Aridity Index provides a good representation of the complex nature of anticipated aridity changes. By systematically comparing projections of the Aridity Index against projections for various hydroclimatological and ecohydrological variables, we show that the Aridity Index generally provides a rather poor proxy for projected aridity conditions. Direct climate model output is shown to contradict signals of increasing aridity obtained from the Aridity Index in at least half of the global land area with robust change. We further show that part of this discrepancy can be related to the parameterization of potential evaporation. Especially the most commonly used potential evaporation model likely leads to an overestimation of future aridity due to incorrect assumptions under increasing atmospheric CO2. Our results show that AI-based approaches do not correctly communicate changes projected by the fully coupled climate models. The solution is to directly analyse the model outputs rather than use a separate offline impact model. We thus urge for a direct and joint assessment of climate model output when assessing future aridity changes rather than using simple index-based impact models that use climate model output as input and are potentially subject to significant biases.