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.

Reducing emissions from agriculture to meet the 2 °C target

Abstract: More than 100 countries pledged to reduce agricultural greenhouse gas (GHG) emissions in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change. Yet technical information about how much mitigation is needed in the sector vs. how much is feasible remains poor. We identify a preliminary global target for reducing emissions from agriculture of ~1 GtCO2e yr−1 by 2030 to limit warming in 2100 to 2 °C above pre-industrial levels. Yet plausible agricultural development pathways with mitigation cobenefits deliver only 21–40% of needed mitigation. The target indicates that more transformative technical and policy options will be needed, such as methane inhibitors and finance for new practices. A more comprehensive target for the 2 °C limit should be developed to include soil carbon and agriculture-related mitigation options. Excluding agricultural emissions from mitigation targets and plans will increase the cost of mitigation in other sectors or reduce the feasibility of meeting the 2 °C limit.

Global patterns of phosphatase activity in natural soils.

Abstract: Soil phosphatase levels strongly control the biotic pathways of phosphorus (P), an essential element for life, which is often limiting in terrestrial ecosystems. We investigated the influence of climatic and soil traits on phosphatase activity in terrestrial systems using metadata analysis from published studies. This is the first analysis of global measurements of phosphatase in natural soils. Our results suggest that organic P (Porg), rather than available P, is the most important P fraction in predicting phosphatase activity. Structural equation modeling using soil total nitrogen (TN), mean annual precipitation, mean annual temperature, thermal amplitude and total soil carbon as most available predictor variables explained up to 50% of the spatial variance in phosphatase activity. In this analysis, Porg could not be tested and among the rest of available variables, TN was the most important factor explaining the observed spatial gradients in phosphatase activity. On the other hand, phosphatase activity was also found to be associated with climatic conditions and soil type across different biomes worldwide. The close association among different predictors like Porg, TN and precipitation suggest that P recycling is driven by a broad scale pattern of ecosystem productivity capacity.

A Dual-Based Procedure for Dynamic Facility Location

Abstract: In dynamic facility location problems, one desires to select the time-staged establishment of facilities at different locations so as to minimize the total discounted costs for meeting demands specified over time at various customer locations. We formulate a particular dynamic facility location problem as a combinatorial optimization problem. The formulation permits both the opening of new facilities and the closing of existing ones. A branch-and-bound procedure incorporating a dual ascent method is presented and shown, in computational tests, to be superior to previously developed methods. The procedure is comparable to the most efficient methods for solving static single-period location problems. Problems with 25 potential facility locations, 50 customer locations, and 10 time periods have been solved within one second of CPU time on an IBM 3033 computer. Extensions of the dynamic facility location problem that allow price-sensitive demands, linearized concave costs, interdependent projects, multiple stages, and multiple commodities also can be solved by the dual ascent method. The method can serve as a component of a solution process for capacitated dynamic location problems.

Warming-induced increase in aerosol number concentration likely to moderate climate change

Abstract: Atmospheric aerosol particles influence the climate system directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. Apart from black carbon aerosol, aerosols cause a negative radiative forcing at the top of the atmosphere and substantially mitigate the warming caused by greenhouse gases. In the future, tightening of controls on anthropogenic aerosol and precursor vapour emissions to achieve higher air quality may weaken this beneficial effect. Natural aerosols, too, might affect future warming. Here we analyse long-term observations of concentrations and compositions of aerosol particles and their biogenic precursor vapours in continental mid- and high-latitude environments. We use measurements of particle number size distribution together with boundary layer heights derived from reanalysis data to show that the boundary layer burden of cloud condensation nuclei increases exponentially with temperature. Our results confirm a negative feedback mechanism between the continental biosphere, aerosols and climate: aerosol cooling effects are strengthened by rising biogenic organic vapour emissions in response to warming, which in turn enhance condensation on particles and their growth to the size of cloud condensation nuclei. This natural growth mechanism produces roughly 50% of particles at the size of cloud condensation nuclei across Europe. We conclude that biosphere-atmosphere interactions are crucial for aerosol climate effects and can significantly influence the effects of anthropogenic aerosol emission controls, both on climate and air quality. © 2013 Macmillan Publishers Limited. All rights reserved.

Endogenized technological learning in an energy systems model

Abstract: Technology dynamics is endogenized into a bottom-up energy systems model. Mixed integer programming is used to incorporate into the model the non-convex relation between declining specific investment in energy technologies and overall experience or capacities installed. The initial results achieved with this approach show the importance of early investment in new technology developments. New technologies will not become cheaper irrespective of research, development, and demonstration (RD & D) decisions; they will do so only if determined RD&D policies and investment strategies enhance their development.