Review article
Dependence of future mortality changes on global CO2 concentrations: A review

https://doi.org/10.1016/j.envint.2018.02.024Get rights and content

Highlights

  • This study is the first to review 15 RCP scenario-based previous projection studies.

  • This study performed a novel normalization to overcome the inter-study heterogeneity.

  • 25 locations worldwide showed very diverse percentage changes in mortality.

  • The mean modeling years and the projection results showed an inverse relationship.

Abstract

The heterogeneity among previous studies of future mortality projections due to climate change has often hindered comparisons and syntheses of resulting impacts. To address this challenge, the present study introduced a novel method to normalize the results from projection studies according to different baseline and projection periods and climate scenarios, thereby facilitating comparison and synthesis. This study reviewed the 15 previous studies involving projected climate change-related mortality under Representative Concentration Pathways. To synthesize their results, we first reviewed the important study design elements that affected the reported results in previous studies. Then, we normalized the reported results by CO2 concentration in order to eliminate the effects of the baseline period, projection period, and climate scenario choices. For twenty-five locations worldwide, the normalized percentage changes in temperature-attributable mortality per 100 ppm increase in global CO2 concentrations ranged between 41.9% and 330%, whereas those of total mortality ranged between 0.3% and 4.8%. The normalization methods presented in this work will guide future studies to provide their results in a normalized format and facilitate research synthesis to reinforce our understanding on the risk of climate change.

Introduction

The effects of temperature elevations due to climate change on future mortality have been well studied. Elevated temperatures directly increase thermal stress leading to increased number of heat cramps, heat syncope, heat exhaustion and heat stroke (Patz et al., 2000) as well as cardiorespiratory mortality (Liu et al., 2011). Gasparrini et al. (2015) collected historical data from 384 locations in 13 countries worldwide and showed that the heat-related all-cause (or non-external-cause where not available) mortality increases with temperature in all studied countries. Liu et al. (2011) demonstrated a causal link between the elevated temperature and increased cardiorespiratory mortality in Beijing, China. In addition, shifts in global temperatures are expected to cause the increased intensity and frequency of extreme weather events such as heat waves, floods, storms, and droughts (Forzieri et al., 2017; Lee and Kim, 2017), as well as proliferation of microbial food poisoning and vector-borne infectious diseases (Patz et al., 2000; McMichael et al., 2006).

The Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) concluded that without a successful mitigation of greenhouse gas emissions, the global mean temperature would increase by >2 °C by the end of the 21st century, eventually leading to increases in heat-related mortality (IPCC, 2014). Given the importance of elevated temperature with regard to future human health, many studies initially investigated the associations between temperature and mortality and subsequently attempted to project temperature-related mortality using future temperature profiles obtained from various global circulation models (GCMs) under benchmark climate scenarios such as Representative Concentration Pathways (RCPs).

Although several review studies have attempted to synthesize these previous projection studies (Huang et al., 2011; Hajat and Kosatky, 2010; Boeckmann and Rohn, 2014; Sarofim et al., 2016), to our knowledge, none has successfully achieved a quantitative synthesis or comparison of the magnitudes of future health impacts. We attribute this lack of success to the high levels of heterogeneity among previous studies with respect to the study location and period, climate models, statistical methods, and even the presentation of results. Accordingly, it has not been possible to integrate these studies and reach a comprehensive understanding of the temperature-related mortality risks attributable to climate change. Furthermore, this heterogeneity has increased the difficulty of research synthesis, as the different study designs have influenced the various results. Previous review studies have therefore provided only compilations and categorizations of projected future health effects (Huang et al., 2011; Hajat and Kosatky, 2010; Boeckmann and Rohn, 2014).

As we believe that it is necessary to integrate the projected results if we are to understand the global impacts of climate change on human health, the present study comprises a systematic review of 15 previous studies that projected future temperature-related mortality under RCP scenarios and summarization of the respective methods and major findings. Our method summarization process involved a careful selection of the important study design elements, such as study targets and statistical methods that would have affected the reported results, as well as the popular choices for the elements in previous studies, to provide an insight into the widely accepted methods for projection study design. Next, we normalized the reported mortalities from each study with respect to changes in global CO2 concentrations to provide the first comparison of the magnitude of health effects. Our normalization methods allow a comparison of these various projection results, as well as a research synthesis to obtain a more comprehensive understanding of the mortality risks due to climate change. This study is important because it is the first to review RCP scenario-based projection studies, and because it is also the first to devise a novel normalization method and provide a guide towards research synthesis.

Section snippets

Search strategy and selection criteria

The Google Scholar, Science Direct, PubMed, Scopus, and Web of Science search engines were used from January 1st to February 28th, 2017 to identify published research articles written in English in the scope of epidemiological research. The following keywords were used in this literature search: projection, mortality, climate change, RCP, temperature, heat, and health effect. Three major criteria were used to select published studies for inclusion in this review article. First, the articles

Results

Using our search criteria, we identified 15 studies that had projected future temperature-related mortality under RCP scenarios (Petkova et al., 2017; Gosling et al., 2016; Kim et al., 2016; Kingsley et al., 2016; Lee and Kim, 2016; Li et al., 2016; Marsha et al., 2016; Martinez et al., 2016; Li et al., 2015; Murari et al., 2015; Schwartz et al., 2015; Kim et al., 2014; Stone et al., 2014; Wu et al., 2014; Petkova et al., 2013). We found two additional studies (Hsiang et al., 2017; Gasparrini

Pros and cons of normalization based on global CO2 concentration

The present study normalized the published percentage changes in human mortality with respect to a 100 ppm increase in global CO2 concentrations. This normalization was used to synthesize the previous projection results with various climate scenarios, baseline periods, and projection periods. For achieving the aim, there are other possible normalization options. One alternative is normalizing to regional temperature increase. In this section, we discussed the pros and cons of each normalization

Conclusions

This study reviewed 15 previous studies of future mortality projections under RCP scenarios, with the aim of overcoming the inter-study heterogeneity that has led previous review studies to merely compile and summarize, rather than synthesize the literature. Accordingly, we devised a novel method to normalize the baseline periods, projection periods, and climate scenarios of these 15 studies based on the global CO2 levels, and reported our comparison of the normalized results for each location

Acknowledgements

This study was supported by the Global Research Lab (#K21004000001-10A0500-00710) through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT (Information and Communication Technologies), and Future Planning and also by the Korea Ministry of Environment as “Climate Change Correspondence Program (project number: 2014001310007).”

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