Atmospheric Science Unit, Department of Environmental Science and Analytical Chemistry, Stockholm University, 11418 Stockholm, Sweden.
Environment and Health Administration, SLB, Box 8136, 104 20 Stockholm, Sweden.
Int J Environ Res Public Health. 2019 Mar 21;16(6):1028. doi: 10.3390/ijerph16061028.
In this study, the effects on daily mortality in Stockholm associated with short-term exposure to ultrafine particles (measured as number of particles with a diameter larger than 4 nm, PNC₄), black carbon (BC) and coarse particles (PM) have been compared with the effects from more common traffic-pollution indicators (PM, PM and NO₂) and O₃ during the period 2000⁻2016. Air pollution exposure was estimated from measurements at a 20 m high building in central Stockholm. The associations between daily mortality lagged up to two days (lag 02) and the different air pollutants were modelled by using Poisson regression. The pollutants with the strongest indications of an independent effect on daily mortality were O₃, PM and PM. In the single-pollutant model, an interquartile range (IQR) increase in O₃ was associated with an increase in daily mortality of 2.0% (95% CI: 1.1⁻3.0) for lag 01 and 1.9% (95% CI: 1.0⁻2.9) for lag 02. An IQR increase in PM was associated with an increase in daily mortality of 0.8% (95% CI: 0.1⁻1.5) for lag 01 and 1.1% (95% CI: 0.4⁻1.8) for lag 02. PM was associated with a significant increase only at lag 02, with 0.8% (95% CI: 0.08⁻1.4) increase in daily mortality associated with an IQR increase in the concentration. NO₂ exhibits negative associations with mortality. The significant excess risk associated with O₃ remained significant in two-pollutant models after adjustments for PM, BC and NO₂. The significant excess risk associated with PM remained significant in a two-pollutant model after adjustment for NO₂. The significantly negative associations for NO₂ remained significant in two-pollutant models after adjustments for PM, O₃ and BC. A potential reason for these findings, where statistically significant excess risks were found for O₃, PM and PM, but not for NO₂, PM, PNC₄ and BC, is behavioral factors that lead to misclassification in the exposure. The concentrations of O₃ and PM are in general highest during sunny and dry days during the spring, when exposure to outdoor air tend to increase, while the opposite applies to NO₂, PNC₄ and BC, with the highest concentrations during the short winter days with cold weather, when people are less exposed to outdoor air.
在这项研究中，比较了短期暴露于超细颗粒（以直径大于 4nm 的颗粒数表示，PNC4）、黑碳（BC）和粗颗粒（PM）与更常见的交通污染指标（PM、PM 和 NO2）和 O3 在 2000-2016 年期间对斯德哥尔摩每日死亡率的影响。空气污染暴露是根据斯德哥尔摩中心一栋 20 米高建筑物的测量结果估算的。使用泊松回归模型对每日死亡率滞后 2 天（滞后 02）的不同空气污染物进行建模。结果表明，O3、PM 和 PM 对每日死亡率的影响最大。在单污染物模型中，O3 浓度每增加一个四分位距（IQR），与滞后 01 时每日死亡率增加 2.0%（95%CI：1.1-3.0）和滞后 02 时每日死亡率增加 1.9%（95%CI：1.0-2.9）相关。PM 浓度每增加一个 IQR，与滞后 01 时每日死亡率增加 0.8%（95%CI：0.1-1.5）和滞后 02 时每日死亡率增加 1.1%（95%CI：0.4-1.8）相关。PM 仅在滞后 02 时与死亡率显著相关，与 IQR 浓度增加相关的每日死亡率增加 0.8%（95%CI：0.08-1.4）。NO2 与死亡率呈负相关。在调整 PM、BC 和 NO2 后，O3 与死亡率显著相关的超额风险在双污染物模型中仍然显著。在调整 NO2 后，PM 与死亡率显著相关的超额风险在双污染物模型中仍然显著。在调整 PM、O3 和 BC 后，NO2 的显著负相关在双污染物模型中仍然显著。这些发现的一个可能原因是，O3、PM 和 PM 存在统计学意义上的超额风险，但 NO2、PM、PNC4 和 BC 则不然，这是由于行为因素导致暴露分类错误。O3 和 PM 的浓度通常在春季阳光明媚和干燥的日子里最高，此时人们接触室外空气的时间增加，而相反的情况则适用于 NO2、PNC4 和 BC，它们的浓度在寒冷天气的短暂冬季日子里最高，此时人们接触室外空气的时间减少。
