2
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Compound climate-pollution extremes in Santiago de Chile

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Cities in the global south face dire climate impacts. It is in socioeconomically marginalized urban communities of the global south that the effects of climate change are felt most deeply. Santiago de Chile, a major mid-latitude Andean city of 7.7 million inhabitants, is already undergoing the so-called “climate penalty” as rising temperatures worsen the effects of endemic ground-level ozone pollution. As many cities in the global south, Santiago is highly segregated along socioeconomic lines, which offers an opportunity for studying the effects of concurrent heatwaves and ozone episodes on distinct zones of affluence and deprivation. Here, we combine existing datasets of social indicators and climate-sensitive health risks with weather and air quality observations to study the response to compound heat-ozone extremes of different socioeconomic strata. Attributable to spatial variations in the ground-level ozone burden (heavier for wealthy communities), we found that the mortality response to extreme heat (and the associated further ozone pollution) is stronger in affluent dwellers, regardless of comorbidities and lack of access to health care affecting disadvantaged population. These unexpected findings underline the need of a site-specific hazard assessment and a community-based risk management.

          Related collections

          Most cited references40

          • Record: found
          • Abstract: not found
          • Article: not found

          Matplotlib: A 2D Graphics Environment

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Mortality risk attributable to high and low ambient temperature: a multicountry observational study

            Summary Background Although studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures. Methods We collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature–mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2·5th and 97·5th temperature percentiles. Findings We analysed 74 225 200 deaths in various periods between 1985 and 2012. In total, 7·71% (95% empirical CI 7·43–7·91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3·37% (3·06 to 3·63) in Thailand to 11·00% (9·29 to 12·47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80–90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7·29%, 7·02–7·49) than by heat (0·42%, 0·39–0·44). Extreme cold and hot temperatures were responsible for 0·86% (0·84–0·87) of total mortality. Interpretation Most of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios. Funding UK Medical Research Council.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Distributed lag non-linear models

              Environmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure–response relationship. Here we develop the family of distributed lag non-linear models (DLNM), a modelling framework that can simultaneously represent non-linear exposure–response dependencies and delayed effects. This methodology is based on the definition of a ‘cross-basis’, a bi-dimensional space of functions that describes simultaneously the shape of the relationship along both the space of the predictor and the lag dimension of its occurrence. In this way the approach provides a unified framework for a range of models that have previously been used in this setting, and new more flexible variants. This family of models is implemented in the package dlnm within the statistical environment R. To illustrate the methodology we use examples of DLNMs to represent the relationship between temperature and mortality, using data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) for New York during the period 1987–2000. Copyright © 2010 John Wiley & Sons, Ltd.
                Bookmark

                Author and article information

                Contributors
                raul.cordero@usach.cl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                25 April 2023
                25 April 2023
                2023
                : 13
                : 6726
                Affiliations
                [1 ]GRID grid.412179.8, ISNI 0000 0001 2191 5013, Universidad de Santiago de Chile, ; Av. Bernardo O’Higgins 3363, Santiago, Chile
                [2 ]GRID grid.4830.f, ISNI 0000 0004 0407 1981, University of Groningen, ; Wirdumerdijk 34, 8911 CE Leeuwarden, The Netherlands
                [3 ]GRID grid.136304.3, ISNI 0000 0004 0370 1101, Center for Environmental Remote Sensing, , Chiba University, ; 1-33 Yayoicho, Inage Ward, Chiba, 263-8522 Japan
                [4 ]Centro Mario Molina, Antonio Bellet 292, Santiago, Chile
                [5 ]Research Institute for Sustainability – Helmholtz Centre Potsdam (RIFS), Berliner Str. 130, 14467 Potsdam, Germany
                [6 ]GRID grid.7870.8, ISNI 0000 0001 2157 0406, School of Medicine, , Pontificia Universidad Católica de Chile, ; Santiago, Chile
                [7 ]GRID grid.266900.b, ISNI 0000 0004 0447 0018, School of Meteorology & Department of Geography and Environmental Sustainability, , University of Oklahoma, ; 120 David L. Boren Blvd. Suite 5220, Norman, OK 73072 USA
                [8 ]GRID grid.266900.b, ISNI 0000 0004 0447 0018, Department of Geography and Environmental Sustainability, , University of Oklahoma, ; Norman, OK 73019 USA
                [9 ]GRID grid.168010.e, ISNI 0000000419368956, Department of Earth System Science, , Stanford University, ; Stanford, CA 94305-2210 USA
                Article
                33890
                10.1038/s41598-023-33890-w
                10130055
                37185945
                81bb2738-299a-4b9e-bdb3-9debba39f274
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 November 2022
                : 20 April 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100020884, Agencia Nacional de Investigación y Desarrollo;
                Award ID: ACT210046
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100009465, Corporación de Fomento de la Producción;
                Award ID: 19BP-117358
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2023

                Uncategorized
                climate-change impacts,atmospheric science
                Uncategorized
                climate-change impacts, atmospheric science

                Comments

                Comment on this article