Pannullo Francesca, Lee Duncan, Neal Lucy, Dalvi Mohit, Agnew Paul, O'Connor Fiona M, Mukhopadhyay Sabyasachi, Sahu Sujit, Sarran Christophe
School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QW, UK.
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK.
Environ Health. 2017 Mar 27;16(1):29. doi: 10.1186/s12940-017-0237-1.
Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future.
We conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO); ozone (O); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM), and less than 10 micrometers (PM); and sulphur dioxide (SO). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP).
NO exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO emissions and concentrations.
NO concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time.
在时空生态研究中估算空气污染对健康的长期影响，需要为每个地理单元和时间段构建具有代表性的空气污染物浓度。通常会对空间和时间上的浓度进行平均计算，但对于不同聚合函数估算的健康影响的稳健性了解甚少。另一个研究较少的问题是空气污染在未来可能产生何种影响。
我们对2007年至2011年期间的英格兰进行了一项研究，调查呼吸科住院人数与不同污染物之间的关系：二氧化氮（NO）；臭氧（O）；颗粒物，后者包括空气动力学直径小于2.5微米的颗粒（PM）以及小于10微米的颗粒（PM）；还有二氧化硫（SO）。使用考虑局部时空自相关的贝叶斯泊松回归模型来估算污染对疾病风险的相对风险（RRs），并且针对每种污染物，通过空间和时间平均值及最大值的组合构建了四种代表性浓度。然后，根据多个代表性浓度路径（RCP）的排放预测，利用估算的RRs对2050年代因空气污染导致的可能呼吸科住院人数进行预测。
在所考虑的污染物中，NO与呼吸科住院人数的关联最为显著，浓度每增加一个标准差，估计风险增加0.9%至1.6%。未来，在三种代表性浓度路径（RCPs）：2.6、6.0和8.5下，预计2050年代因NO导致的呼吸科住院人数低于当前水平，这是由于预计未来NO排放和浓度会降低。
无论如何在空间和时间上构建代表性浓度，NO浓度目前都呈现出持续且显著的健康影响。因此，由于预计在英格兰部分城市地区，直到2030年代NO浓度仍将高于欧盟法规设定的限值，在一段时间内它仍将是一个重大的健康风险。
