Global projections of heat exposure of older adults

The global population is aging at the same time as heat exposures are increasing due to climate change. Age structure, and its biological and socio-economic drivers, determine populations’ vulnerability to high temperatures. Here we combine age-stratified demographic projections with downscaled temperature projections to mid-century and find that chronic exposure to heat doubles across all warming scenarios. Moreover, >23% of the global population aged 69+ will inhabit climates whose 95th percentile of daily maximum temperature exceeds the critical threshold of 37.5 °C, compared with 14% today, exposing an additional 177–246 million older adults to dangerous acute heat. Effects are most severe in Asia and Africa, which also have the lowest adaptive capacity. Our results facilitate regional heat risk assessments and inform public health decision-making

Technical Change, Investment and Energy Intensity

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).This paper analyzes the role of different components of technical change on energy intensity by applying a Translog variable cost function setting to the new EU KLEMS dataset for 3 selected EU countries (Italy, Finland and Spain). The framework applied represents an accounting of technical change components, comprising autonomous as well as embodied and induced technical change. The inducement of embodied technical change is introduced by an equation for the physical capital stock that is a fixed factor in the short-run. The dataset on capital services and user costs of capital in EUKLEMS enables explaining capital accumulation depending on factor prices. The model can be used for explaining and tracing back the long-run impact of prices and technical change on energy intensity.This paper is based on the EU KLEMS database, which has been funded by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, “Policy Support and Anticipating Scientific and Technological Needs” (project 502049)

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (U.S.) against U.S. Dept. of Agriculture (USDA) time series for about 1,000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. Majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields

Fossil energy in economic growth: A study of the energy direction of technical change, 1950-2012

Climate change mitigation challenges national economies to increase productivity while reducing fossil energy consumption. Fossil energy-saving technical change has been assumed to accomplish this, yet empirical evidence is scarce. This paper investigates the long-run relationship between the rate and direction of technical change with respect to fossil energy and labor in the world economy. Growth rates of labor productivity and the fossil energy-labor ratio are examined for more than 95 of world output between 1950 and 2012. The average elasticity of the energy-labor ratio with respect to labor productivity is close to one, implying highly energy-using technical change, but no trade-o between factor productivity growth rates. This stylized fact suggests the importance of a cheap, abundant energy supply for robust global growth, and a more important role for renewable energy. Integrated assessment models do not incorporate this restriction which may result in poorly speci ed baseline scenarios

Path dependence in energy systems and economic development

Energy systems are subject to strong and long-lived path dependence, owing to technological, infrastructural, institutional and behavioural lock-ins. Yet, with the prospect of providing accessible cheap energy to stimulate economic development and reduce poverty, governments often invest in large engineering projects and subsidy policies. Here, I argue that while these may achieve their objectives, they risk locking their economies onto energy-intensive pathways. Thus, particularly when economies are industrializing, and their energy systems are being transformed and are not yet fully locked-in, policymakers should take care before directing their economies onto energy-intensive pathways that are likely to be detrimental to their long-run prosperity

Blue and Red Light Modulates SigB-Dependent Gene Transcription, Swimming Motility and Invasiveness in Listeria monocytogenes

Background: In a number of gram-positive bacteria, including Listeria, the general stress response is regulated by the alternative sigma factor B (SigB). Common stressors which lead to the activation of SigB and the SigB-dependent regulon are high osmolarity, acid and several more. Recently is has been shown that also blue and red light activates SigB in Bacillus subtilis. Methodology/Principal Findings: By qRT-PCR we analyzed the transcriptional response of the pathogen L. monocytogenes to blue and red light in wild type bacteria and in isogenic deletion mutants for the putative blue-light receptor Lmo0799 and the stress sigma factor SigB. It was found that both blue (455 nm) and red (625 nm) light induced the transcription of sigB and SigB-dependent genes, this induction was completely abolished in the SigB mutant. The blue-light effect was largely dependent on Lmo0799, proving that this protein is a genuine blue-light receptor. The deletion of lmo0799 enhanced the red-light effect, the underlying mechanism as well as that of SigB activation by red light remains unknown. Blue light led to an increased transcription of the internalin A/B genes and of bacterial invasiveness for Caco-2 enterocytes. Exposure to blue light also strongly inhibited swimming motility of the bacteria in a Lmo0799- and SigB-dependent manner, red light had no effect there. Conclusions/Significance: Our data established that visible, in particular blue light is an important environmental signal with an impact on gene expression and physiology of the non-phototrophic bacterium L. monocytogenes. In natural environments these effects will result in sometimes random but potentially also cyclic fluctuations of gene activity, depending on the light conditions prevailing in the respective habitat

Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk