Department of Environmental Science, Faculty of Science, Chulalongkorn University, Pathumwan, Bangkok, Thailand.
PLoS One. 2022 Sep 20;17(9):e0274444. doi: 10.1371/journal.pone.0274444. eCollection 2022.
The policymakers need research studies indicating the role of different pollutants with morbidity for polluted cities to install a strategic air quality management system. This study critically assessed the air pollution of Delhi for 2016-18 to found out the role of air pollutants in respiratory morbidity under the ICD-10, J00-J99. The critical assessment of Delhi air pollution was done using various approaches. The mean PM2.5 and PM10 concentrations during the measurement period exceeded both national and international standards by a wide margin. Time series charts indicated the interdependence of PM2.5 and PM10 and connection with hospital visits due to respiratory diseases. Violin plots showed that daily respiratory disease hospital visits increased during the winter and autumn seasons. The winter season was the worst from the city's air pollution point of view, as revealed by frequency analyses. The single and multi-pollutant GAM models indicated that short-term exposure to PM10 and SO2 led to increased hospital visits due to respiratory diseases. Per 10 units increase in concentrations of PM10 brought the highest increase in hospital visits of 0.21% (RR: 1.00, 95% CI: 1.001, 1.002) at lag0-6 days. This study found the robust effect of SO2 persisted in Delhi from lag0 to lag4 days and lag01 to lag06 days for single and cumulative lag day effects, respectively. While every 10 μg m-3 increase of SO2 concentrations on the same day (lag0) led to 32.59% (RR: 1.33, 95% CI: 1.09, 1.61) rise of hospital visits, the cumulative concentration of lag0-1 led to 37.21% (RR: 1.37, 95% CI:1.11, 1.70) rise in hospital visits which further increased to even 83.33% (RR: 1.83, 95% CI:1.35, 2.49) rise at a lag0-6 cumulative concentration in Delhi. The role of SO2 in inducing respiratory diseases is worrying as India is now the largest anthropogenic SO2 emitter in the world.
政策制定者需要研究表明不同污染物与污染城市发病率之间关系的研究报告,以便为其安装战略性空气质量管理系统。本研究对 2016-18 年德里的空气污染情况进行了批判性评估,以确定 ICD-10 编码 J00-J99 下的呼吸道发病率与空气污染物之间的关系。对德里空气污染的批判性评估采用了多种方法。在测量期间,PM2.5 和 PM10 的平均值浓度远远超过了国家和国际标准。时间序列图表表明 PM2.5 和 PM10 之间存在相互依存关系,并且与因呼吸道疾病而住院的情况有关。小提琴图显示,冬季和秋季,每日呼吸道疾病住院人数增加。从城市空气污染的角度来看,冬季是最糟糕的季节,这一点从频率分析中可以看出。单污染物和多污染物 GAM 模型表明,短期接触 PM10 和 SO2 会导致因呼吸道疾病而住院的人数增加。PM10 浓度每增加 10 个单位,就会导致住院人数增加 0.21%(RR:1.00,95%CI:1.001,1.002),滞后 0-6 天。本研究发现,在德里,SO2 的单一和累积滞后日效应分别从滞后 0 到滞后 4 天和滞后 01 到滞后 06 天都具有稳健的效应。虽然 SO2 浓度每天增加 10 μg m-3(滞后 0)会导致住院人数增加 32.59%(RR:1.33,95%CI:1.09,1.61),但滞后 0-1 的累积浓度会导致住院人数增加 37.21%(RR:1.37,95%CI:1.11,1.70),在德里,滞后 0-6 的累积浓度甚至会增加到 83.33%(RR:1.83,95%CI:1.35,2.49)。印度现在是世界上最大的人为 SO2 排放国,SO2 对引发呼吸道疾病的作用令人担忧。