Consistent economic cross-sectoral climate change impact scenario analysis: Method and application to Austria

AbstractClimate change triggers manifold impacts at the national to local level, which in turn have various economy-wide implications (e.g. on welfare, employment, or tax revenues). In its response, society needs to prioritize which of these impacts to address and what share of resources to spend on each respective adaptation. A prerequisite to achieving that end is an economic impact analysis that is consistent across sectors and acknowledges intersectoral and economy-wide feedback effects. Traditional Integrated Assessment Models (IAMs) are usually operating at a level too aggregated for this end, while bottom-up impact models most often are not fully comprehensive, focusing on only a subset of climate sensitive sectors and/or a subset of climate change impact chains. Thus, we develop here an approach which applies climate and socioeconomic scenario analysis, harmonized economic costing, and sector explicit bandwidth analysis in a coupled framework of eleven (bio)physical impact assessment models and a uniform multi-sectoral computable general equilibrium model. In applying this approach to the alpine country of Austria, we find that macroeconomic feedbacks can magnify sectoral climate damages up to fourfold, or that by mid-century costs of climate change clearly outweigh benefits, with net costs rising two- to fourfold above current damage cost levels. The resulting specific impact information – differentiated by climate and economic drivers – can support sector-specific adaptation as well as adaptive capacity building

Measurements of quantum yields of bromine atoms in the photolysis of bromoform from 266 to 324 nm

The quantum yield for the formation of bromine atoms in the photolysis of bromoform, CHBr_3, has been measured between 266 and 324 nm. For 303 to 306 nm the quantum yields are unity within the experimental uncertainty of the measurements. At longer wavelengths, where the bromoform cross sections decrease rapidly, an apparent trend to slightly lower quantum yields is probably the result of systematic and random errors or incorrect CHBr_3 absorption cross sections. Support for a unit quantum yield for all wavelengths longer than 300 nm comes from the recent theoretical calculations of Peterson and Francisco. At 266 nm the bromine atom quantum yield is 0.76 (±0.03), indicating that at least one additional dissociation channel becomes important at shorter wavelengths. For modeling of the troposphere, it is recommended that a quantum yield of unity be used for wavelengths of 300 nm and longer

The Optimal Single Copy Measurement for the Hidden Subgroup Problem

The optimization of measurements for the state distinction problem has recently been applied to the theory of quantum algorithms with considerable successes, including efficient new quantum algorithms for the non-abelian hidden subgroup problem. Previous work has identified the optimal single copy measurement for the hidden subgroup problem over abelian groups as well as for the non-abelian problem in the setting where the subgroups are restricted to be all conjugate to each other. Here we describe the optimal single copy measurement for the hidden subgroup problem when all of the subgroups of the group are given with equal a priori probability. The optimal measurement is seen to be a hybrid of the two previously discovered single copy optimal measurements for the hidden subgroup problem.Comment: 8 pages. Error in main proof fixe

Strategies for mitigating N2O and N2 emissions from an intensive sugarcane cropping system

In sugarcane cropping systems, high rates of N fertiliser are typically applied as sub-surface bands creating localised zones of high mineral N concentrations. This in combination with high levels of crop residue (trash) retention and a warm and humid climate creates conditions that are known to promote soil denitrification, resulting in high emissions of the potent greenhouse gas N2O. These losses illustrate inefficient use of N fertilisers but total denitrification losses in the form of N2 and N2O remain largely unknown. We used the 15N gas flux method to investigate the effect of cane trash removal and the use of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) on N2 and N2O emissions on a commercial sugarcane farm at Bundaberg, Australia. High gaseous N losses were observed under the standard grower practice where cane trash retention and N fertiliser application (145 kg N ha−1 as urea) resulted in N2 and N2O emissions (36.1 kg N ha−1) from the subsurface N fertiliser band, with more than 50% of these losses emitted as N2O. Cane trash removal reduced N2 emission by 34% and N2O emission by 51%, but had no effect on the N2O/(N2 + N2O) ratio. The use of DMPP lowered N2 and N2O emission by 35% and 98%, respectively, reducing the percentage of these losses (N2 + N2O) emitted as N2O to only 4%. We conclude that the use of DMPP is an effective strategy to reduce N losses, minimise N2O emissions, while keeping the benefits of cane trash retention in sugarcane cropping systems.</p

Simulation of Radiation-Induced Damage Distribution to evaluate Models for Higher-Order Chromosome Organisation

The structure of chromatin at the level of the 30 nm fibre has been studied in considerable detail, but little is known about how this fibre is arranged within the interphase chromosome territory. Over the years, various polymer models were developed to simulate chromosome structure, for example the random-walk/giant-loop (RWGL) model, the multi-loop subcompartment (MLS) model, and the interconnected-fibre-loop model (Friedland et al., 1999). These models differ mainly in the size and arrangement of the chromatin loops and, correspondingly, in the predicted distribution of chromatin density within the nucleus. It occurred to us that densely ionising radiation can be used to probe the actual distribution of chromatin density in human interphase cells. In contrast to sparsely ionising radiation (e.g. X-rays), which induces DNA double-strand breaks (DSB) that are distributed randomly within the nucleus, irradiation with densely ionising accelerated ions leads to spatial clustering of DSB. This inhomogeneity in DSB localisation, together with an inhomogeneity of DNA density within the nucleus, causes an over-dispersion in the resulting distribution of DNA fragment sizes that can be detected by pulsed-field gel electrophoresis. Using the above-mentioned chromosome models, we performed computer simulations to predict the DNA fragment size distributions resulting from irradiation with accelerated ions, and compared the predicted distributions with those obtained experimentally. We found that simulations based on the MLS model, in which local variations in chromatin density are higher than in the other models, resulted in the best agreement between calculation and experiment

The Transcription Factor REST Is Lost in Aggressive Breast Cancer

The function of the tumor suppressor RE1 silencing transcription factor (REST) is lost in colon and small cell lung cancers and is known to induce anchorage-independent growth in human mammary epithelial cells. However, nothing is currently known about the role of this tumor suppressor in breast cancer. Here, we test the hypothesis that loss of REST function plays a role in breast cancer. To assay breast tumors for REST function, we developed a 24-gene signature composed of direct targets of the transcriptional repressor. Using the 24- gene signature, we identified a previously undefined RESTless breast tumor subtype. Using gene set enrichment analysis, we confirmed the aberrant expression of REST target genes in the REST–less tumors, including neuronal gene targets of REST that are normally not expressed outside the nervous system. Examination of REST mRNA identified a truncated splice variant of REST present in the REST–less tumor population, but not other tumors. Histological analysis of 182 outcome-associated breast tumor tissues also identified a subpopulation of tumors that lack full-length, functional REST and over-express the neuroendocrine marker and REST target gene Chromogranin A. Importantly, patients whose tumors were found to be REST–less using either the 24-gene signature or histology had significantly poorer prognosis and were more than twice as likely to undergo disease recurrence within the first 3 years after diagnosis. We show here that REST function is lost in breast cancer, at least in part via an alternative splicing mechanism. Patients with REST–less breast cancer undergo significantly more early disease recurrence than those with fully functional REST, regardless of estrogen receptor or HER2 status. Importantly, REST status may serve as a predictor of poor prognosis, helping to untangle the heterogeneity inherent in disease course and response to treatment. Additionally, the alternative splicing observed in REST–less breast cancer is an attractive therapeutic target

Automated Classification of Airborne Laser Scanning Point Clouds

Making sense of the physical world has always been at the core of mapping. Up until recently, this has always dependent on using the human eye. Using airborne lasers, it has become possible to quickly "see" more of the world in many more dimensions. The resulting enormous point clouds serve as data sources for applications far beyond the original mapping purposes ranging from flooding protection and forestry to threat mitigation. In order to process these large quantities of data, novel methods are required. In this contribution, we develop models to automatically classify ground cover and soil types. Using the logic of machine learning, we critically review the advantages of supervised and unsupervised methods. Focusing on decision trees, we improve accuracy by including beam vector components and using a genetic algorithm. We find that our approach delivers consistently high quality classifications, surpassing classical methods