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Association of air pollution and meteorological variables with COVID-19 incidence: Evidence from five megacities in India

机译:空气污染与气象变量与Covid-19发病率的结合:印度五大兆的证据

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Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM_(2.5), PM_(10) and CO), Ground level ozone (O_3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM_(2.5)1 PM_(10),CO, O_3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r = 0.54;0.25) and unlock period (r = 0.66;0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10-11% and 4-6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases.
机译:虽然工业和运输部门的锁定并留在家庭咨询来抵消Covid-19大流行表明,在此期间,空气质量有所改善,众所周知的是环境空气污染物和气象促进其传输的作用。本文介绍了一项研究的研究结果,以评估空气质量指数(AQI),三次污染物(PM_(2.5),PM_(10)和CO),地层臭氧(O_3)和三种气象变量(温度,相对湿度,风速)促进了印度五大特征中的Covid-19传播。结果表明PM_(2.5),PM_(10),CO,O_3浓度,AQI和气象参数的显着相关性,并且在锁定期间与确诊病例和死亡。在考虑的气象变量中,温度与锁定期间的Covid-19病例和死亡强烈相关(r = 0.54; 0.25)和解锁时段(r = 0.66; 0.25)。在污染物,臭氧和气象变量中,温度分别解释了最高可变性,分别为Covid-19确诊和死亡的最高可变性,高达34%和30%。 AQI不是解释确诊和死亡案例的变化的重要参数。 WS和RH可以解释Covid-19案件的10-11%和4-6%的变化。 GLM模型可以解释在锁定期间确认病例和死亡的74%和35%的可变性,在解锁期间有66%和19%的变化。结果表明,气象参数可能促进了Covid-19发病率,特别是确诊的病例。我们的调查结果可能会鼓励未来的研究探讨环境空气污染物和气象对Covid-19和类似传染病的作用。

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