1,721,045 research outputs found
Real-time forecast of temperature-related excess mortality at small-area level: towards an operational framework.
Full text linkThe development of innovative tools for real-time monitoring and forecasting of environmental health impacts is central to effective public health interventions and resource allocation strategies. Though a need for such generic tools has been previously echoed by public health planners and regional authorities responsible for issuing anticipatory alerts, a comprehensive, robust and scalable real-time system for predicting temperature-related excess deaths at a local scale has not been developed yet. Filling this gap, we propose a flexible operational framework for coupling publicly available weather forecasts with temperature-mortality risk functions specific to small census-based zones, the latter derived using state-of-the-art environmental epidemiological models. Utilising high-resolution temperature data forecast by a leading European meteorological centre, we demonstrate a real-time application to forecast the excess mortality during the July 2022 heatwave over England and Wales. The output, consisting of expected temperature-related excess deaths at small geographic areas on different lead times, can be automated to generate maps at various spatio-temporal scales, thus facilitating preventive action and allocation of public health resources in advance. While the real-case example discussed here demonstrates an application for predicting (expected) heat-related excess deaths, the framework can also be adapted to other weather-related health risks and to different geographical areas, provided data on both meteorological exposure and the underlying health outcomes are available to calibrate the associated risk functions. The proposed framework addresses an urgent need for predicting the short-term environmental health burden on public health systems globally, especially in low- and middle-income regions, where rapid response to mitigate adverse exposures and impacts to extreme temperatures are often constrained by available resources
Historical global gridded degree‐days: A high‐spatial resolution database of CDD and HDD
Full text linkCooling and heating degree‐days (CDD/HDD) are important metrics used in energy studies as a proxy for determining demand and consumption patterns of residential/commercial buildings and work spaces. Driven by the requirements of energy impact modellers, policymakers and building design experts; a new historical high‐spatial resolution, global gridded dataset of degree‐days constructed using various base (threshold) temperatures (Tb) is presented in this study. Derived using sub‐daily temperature from a quality‐controlled reanalysis data product (Global Land Data Assimilation System—GLDAS), the dataset called ‘DegDays_0p25_1970_2018’ includes monthly and annual (i) CDD; (ii) HDD; and (iii) CDD computed using wet‐bulb temperature (CDDwb) at 0.25° × 0.25° gridded resolution, covering 49 years over the period 1970–2018. The Tb used for assembling DegDays_0p25_1970_2018 include 18, 18.3, 22, 23, 24, 25°C for CDD and CDDwb; and 10, 15, 15.5, 16, 17 and 18°C for HDD, respectively. The data of individual indices are made publicly available in the commonly used scientific Network Common Data Form 4 (NetCDF4) and Georeferenced Tagged Image File (GeoTIFF) formats. DegDays_0p25_1970_2018 fills gaps in existing energy indicators’ datasets by being the only high‐resolution historical global gridded time series based on multiple threshold temperatures, thus offering applications in wide‐ranging climate zones and thermal comfort environments. The richness of DegDays_0p25_1970_2018 lies in its flexibility by allowing users to aggregate the degree‐days not only at varying spatial scales (such as administrative levels, national boundaries, economic organizations e.g. OECD; with or without population weights), but also at varying temporal scales (such as seasons), thereby offering climatologists with a potential to examine global teleconnection patterns more discretely
The role of climate datasets in understanding climate extremes
No full textA rapidly growing body of literature routinely employs historical observations to study extremes in past and current climate. The inconsistencies in observations often lead to erroneous results and drawing incorrect inferences when undertaking analyses of climate extremes at regional or global scales. Understanding the potential inhomogeneity in climate datasets is therefore central to the study of climate extremes, especially when attributing any shifts in extremes to a changing climate. Despite the best efforts in assembling quality-controlled input data sources, inconsistencies in data are inherently embedded within long-term records of observations. Knowing the strengths and limitations of climate datasets can potentially facilitate better analyses of climate extremes. This chapter begins with an overview of climate extremes and Climate Extreme Indices (CEIs). The importance of quality control input meteorological variables, tools for assembling the CEIs, and a detailed list of recommended CEIs suitable for examining a broad array of temperature- and precipitation-based extremes are described next. Different sources of global and regional input climate data along with their strengths and limitations for assembling the CEIs form the crux of the next section. Existing datasets of CEIs and recommendations for future research conclude the chapter as the final two sections
Income-dependent expansion of electricity demand for climate change adaptation in Brazil
Full text linkSectoral monthly power demand in Brazil is studied with dynamic econometric models
Power demand responds non-linearly to thermal discomfort
Economic growth triples the additional energy demand required to adapt
Additional 9% - 18% of power demand is required circa 2050 depending on the SSP and RCP
Adaptation-induced additional power demand varies remarkably by region and seaso
A High-Resolution Global Gridded Historical Dataset of Climate Extreme Indices
Full text linkClimate extreme indices (CEIs) are important metrics that not only assist in the analysis of regional and global extremes in meteorological events, but also aid climate modellers and policymakers in the assessment of sectoral impacts. Global high-spatial-resolution CEI datasets derived from quality-controlled historical observations, or reanalysis data products are scarce. This study introduces a new high-resolution global gridded dataset of CEIs based on sub-daily temperature and precipitation data from the Global Land Data Assimilation System (GLDAS). The dataset called “CEI_0p25_1970_2016” includes 71 annual (and in some cases monthly) CEIs at 0.25∘× 0.25∘ gridded resolution, covering 47 years over the period 1970–2016. The data of individual indices are publicly available for download in the commonly used Network Common Data Form 4 (NetCDF4) format. Potential applications of CEI_0p25_1970_2016 presented here include the assessment of sectoral impacts (e.g., Agriculture, Health, Energy, and Hydrology), as well as the identification of hot spots (clusters) showing similar historical spatial patterns of high/low temperature and precipitation extremes. CEI_0p25_1970_2016 fills gaps in existing CEI datasets by encompassing not only more indices, but also by being the only comprehensive global gridded CEI data available at high spatial resolution
The role of residential air circulation and cooling demand for electrification planning: Implications of climate change in sub-Saharan Africa
Full text linkNearly 1 billion people live without electricity at home. Energy poverty limits their ability to take autonomous actions to improve air circulation and the cooling of their homes. It is therefore important that electricity-access planners explicitly evaluate the current and future air circulation and cooling needs of energy-poor households, in addition to other basic energy needs. To address this issue, we combine climate, socio-economic, demographic and satellite data with scenario analysis to model spatially explicit estimates of potential cooling demand from households that currently lack access to electricity. We link these demand factors into a bottom-up electrification model for sub-Saharan Africa, the region with the world's highest concentration of energy poverty. Accounting for cooling needs on top of baseline household demand implies that the average electrification investment requirements grow robustly (a scenario mean of 65.5% more than when considering baseline household demand only), mostly due to the larger generation capacity needed. Future climate change could increase the investment requirements by an additional scenario mean of 4%. Moreover, the share of decentralised systems as the lowest-cost electrification option falls by a scenario mean 4.5 percentage points of all new connections. The crucial determinants for efficient investment pathways are the adoption and use of cooling appliances, the extent of climate change, and the baseline electricity demand. Our results call for a more explicit consideration of climate-adaptative energy needs by infrastructure planners in developing countries
Climate variability, crop and conflict : Exploring the impacts of spatial concentration in agricultural production
Full text linkAlthough substantive agreement exists on the role of climate variability and food scarcity in increasing violence, a limited number of studies have investigated how food resources affect violent conflict. This article explores the complex linkages between climate variability, agricultural production and conflict onset, by focusing on the spatial distribution of crop production in a cross-country setting. We hypothesize that spatial differences in crop production within countries are a relevant factor in shaping the impact of climate variability on conflict in agriculturally -dependent countries. To test this hypothesis, we rely on high-resolution global gridded data on the local yield of four main crops for the period 1982–2015 and aggregate the grid-cell information on crop production to compute an empirical indicator of the spatial concentration of agricultural production within countries. Our results show that the negative impacts of climate variability lead to an increase in the spatial concentration of agricultural production within countries. In turn, the combined effect of climate extremes and crop production concentration increases the predicted probability of conflict onset by up to 14% in agriculturally dependent countries.CLIMSECENERGY
Climate change literacy and migration potential: micro-level evidence from Africa
Full text linkAbstract
While a growing literature studies the effects of climate change on international migration, still only relatively little is known about the individual mechanisms linking migration decisions to climate change. We argue that climate change literacy (i.e., knowledge about climate change) is a major determinant of why some individuals consider migrating to other countries in response to climate change effects. In particular, climate change literacy helps individuals translate their perceptions of temperature changes into an understanding of these changes’ irreversible long-term consequences. We test this hypothesis using highly accurate geo-coded data for 37,000 individuals across 30 African countries. We show that climate change indeed leads to stronger migration intentions among climate literates only. Furthermore, we show that climate change only increases migration intentions among climate literates when it is approximated by long-run increases in local temperatures, but not when operationalized as changing heat wave or precipitation patterns. Further analyses show that climate literates are more likely to live in urban areas, have a higher news consumption, are highly educated, and have demanding occupations. Consequently, climate change may further deprive affected countries of valuable talent
Households’ adaptation in a warming climate. Air conditioning and thermal insulation choices
Full text linkAdjustments in the final use of energy are a critical margin of adaptation for maintaining indoor thermal comfort. This paper explores how households have been adopting air conditioning and thermal insulation to cope with different climatic conditions, and how climatic factors interact with socio-economic, demographic, and household characteristics across eight OECD countries. Changes in the cumulative number of hot and cold days over the year, urbanization, demographics and household characteristics, including attitudes towards energy
efficiency, strongly affect those two margins of adaptation, along with income. If the historically-observed adaptation behaviour is maintained also under future socio-economic pathways and climate scenarios, the impact of global warming and income on air conditioning adoption will be reinforced by urbanization trends, which on the contrary will make it more difficult to improve building thermal insulation
Temperature-related mortality burden and projected change in 1368 European regions: a modelling study.
Full text linkBACKGROUND: Excessively high and low temperatures substantially affect human health. Climate change is expected to exacerbate heat-related morbidity and mortality, presenting unprecedented challenges to public health systems. Since localised assessments of temperature-related mortality risk are essential to formulate effective public health responses and adaptation strategies, we aimed to estimate the current and future temperature-related mortality risk under four climate change scenarios across all European regions. METHODS: We modelled current and future mortality due to non-optimal temperatures across 1368 European regions, considering age-specific characteristics and local socioeconomic vulnerabilities. Overseas territories were excluded from the analysis. We applied a three-stage method to estimate temperature-related risk continuously across age and spatial dimensions. Age and city-specific exposure-response functions were obtained for a comprehensive list of 854 European cities from the Urban Audit dataset of Eurostat. Regional aggregates were calculated using an aggregation and extrapolation method that incorporates the risk incidence in neighbouring cities. Mortality was projected for present conditions observed in 1991-2020 and for four different levels of global warming (1·5°C, 2°C, 3°C, and 4°C increase) by regions, and subregions using an ensemble of 11 climate models produced by the Coordinated Regional Climate Downscaling Experiment-CMIP5 over Europe, and population projection data from EUROPOP2019. FINDINGS: Our results highlight regional disparities in temperature-related mortality across Europe. Between 1991 and 2020, the number of cold-related deaths was 2·5 times higher in eastern Europe than western Europe, and heat-related deaths were 6 times higher in southern Europe than in northern Europe. During the same time period, there were a median of 363 809 cold-related deaths (empirical 95% CI 362 493-365 310) and 43 729 heat-related deaths (39 880-45 921), with a cold-to-heat-related death ratio of 8·3:1. Under current climate policies, aligned with 3°C increase in global warming, it is estimated that temperature-related deaths could increase by 54 974 additional deaths (24 112-80 676) by 2100, driven by rising heat-related deaths and an ageing population, resulting in a cold-to-heat-related death ratio of 2·6:1. Climate change is also expected to widen disparities in regional mortality, particularly impacting southern regions of Europe as a result of a marked increase in heat-related deaths. INTERPRETATION: This study shows that regional disparities in temperature-related mortality risk in Europe are substantial and will continue to increase due to the effects of climate change and an ageing population. The data presented can assist policy makers and health authorities in mitigating increasing health inequalities by prioritising the protection of more susceptible areas and older population groups. We identify the projected areas of heightened risk (southern Europe), where policy intervention aimed at building adaptation and enhancing resilience should be prioritised. FUNDING: European Commission
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