Sanderson Michael, Arbuthnott Katherine, Kovats Sari, Hajat Shakoor, Falloon Pete
Met Office, Exeter, United Kingdom.
Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
PLoS One. 2017 Jul 7;12(7):e0180369. doi: 10.1371/journal.pone.0180369. eCollection 2017.
Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research.
The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis.
A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised.
Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality.
与高温相关的死亡率是公共卫生领域极为关注的问题,对气候变暖情况下未来死亡率的估计对于资源规划和可能的适应措施至关重要。对提供未来与高温相关死亡率预测的论文进行了批判性综述,重点关注气候模型数据的使用情况。并为未来研究提出了一些最佳实践指南。
在电子数据库Web of Science和PubMed/Medline中搜索包含未来与高温相关死亡率定量估计的论文。搜索仅限于截至2017年3月底在同行评审期刊上发表的英文论文。还查阅了相关论文的参考文献列表和引用文献。所研究地点的广泛范围和所使用的气候数据使得无法进行荟萃分析。
去除重复条目后共识别出608篇文章,其中63篇被发现包含对未来炎热天气或热浪导致的死亡率的定量估计。已使用多种死亡率模型和气候模型数据来估计未来死亡率。这些研究中使用的气候模拟中的温度预计会升高。因此,所有论文均表明在气候变暖情况下高温导致的死亡率将会增加。模型对未来气候预测的差异给未来与高温相关死亡率的估计增加了很大的不确定性。然而,许多研究要么没有考虑这种不确定性来源,要么仅使用了少数气候模型的结果。其他研究表明,人口和人口结构变化带来的不确定性以及适应温度升高的方法至少与气候模型不确定性一样重要。在气候数据的使用(例如,使用全球平均温度变化而非特定地点的变化)以及对死亡率影响的解释方面存在一些不一致之处。总结了在估计未来死亡率时未考虑的一些因素。
大多数研究使用了基于温室气体中高排放情景生成的气候数据。需要更多地利用缓解情景RCP2.6中的气候信息来估计未来死亡率,因为该情景是唯一有可能实现将全球变暖限制在2°C或更低的《巴黎协定》的情景。许多将模型数据与当地气候观测相结合的方法过于简单。基于分位数的方法可能提供一种改进的方法,特别是对于分布两端的温度。死亡率模型中对适应温度升高的建模通常是随意且简单的,需要更多研究来更好地量化适应情况。只有少数研究在估计未来死亡率时考虑了人口和人口结构的可能变化,这意味着许多死亡率估计可能偏低。在估计未来死亡率时,源自确定死亡率基线、气候预测、适应和人口变化的不确定性很重要,应予以考虑。