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Pre-to-post lockdown impact on air quality and the role of environmental factors in spreading the COVID-19 cases - a study from a worst-hit state of India
International Journal of Biometeorology ( IF 3.2 ) Pub Date : 2020-10-09 , DOI: 10.1007/s00484-020-02019-3
Prafulla Kumar Sahoo 1, 2 , Sherry Mangla 3 , Ashok Kumar Pathak 3 , Gabriel Negreiros Salãmao 4 , Dibyendu Sarkar 5
Affiliation  

The present study aims to examine the changes in air quality during different phases of the COVID-19 pandemic, including the lockdown (LD 1–4 ) and unlock period (UL 1–2 ) (post-lockdown) as compared to pre-lockdown (PL 1–3 ) and to establish the relationships of the environmental and demographic variables with COVID-19 cases in the state of Maharashtra, the worst-hit state in India. Atmospheric pollutants such as PM 2.5 , PM 10 , NO x , and CO were substantially reduced during the lockdown and unlock phases with the greatest reduction in cities having larger traffic volumes. Compared with the immediate pre-lockdown period (PL 3 ), the averaged PM 2.5 and PM 10 reduced by up to 51% and 47% respectively during the lockdown periods, which resulted in ‘satisfactory’ level of air quality index (AQI) as a result of reduced vehicular traffic and industrial closing. These parameters continued to reduce as much as 80% during the unlock periods due to the additive impact of weather (rainfall and temperature) combined with the lockdown conditions. Kendall’s correlation matrix showed a significant negative correlation between temperature and air pollutants ( r = − 0.35 to − 057). Conversely, SO 2 and O 3 did not improve, and in some cases, they increased during the lockdown and unlocking. COVID-19 spreading incidences were strongly and positively correlated with temperature ( r < 0.62) and dew point ( r < 0.73). Thus, this indicates that the increase in temperature and dew point cannot weaken the transmission of this virus. The number of COVID-19 cases relative to air pollutants was negatively correlated ( r = − 0.33 to − 0.74), which may be a mere coincidence as a result of lockdown. However, based on pre-lockdown air quality data and demographic factors, it was found that particulate matter (PM 2.5 and PM 10 ) and population density are closely linked with higher morbidity and mortality although a more in-depth research is required in this direction to validate this finding. The onset of COVID-19 has allowed us to determine that ‘immediate’ changes in air quality within densely populated/industrialized areas can improve livelihood based on pollution mitigation. These findings could be used by policymakers to set new benchmarks for air pollution that would improve the quality of life for major sectors of the World’s population. COVID-19 has shown us that we can make changes when necessary, and findings may pave the way for future research to inform policy on the tough choices we will have to make between quality of life and survival. Also, our results will enrich the ongoing discussion on the role of environmental factors on the transmission of COVID-19 and will help to take necessary steps for its control.

中文翻译:

封锁前后对空气质量的影响以及环境因素在传播 COVID-19 病例中的作用——来自印度受灾最严重的州的一项研究

本研究旨在检查 COVID-19 大流行不同阶段的空气质量变化,包括与锁定前相比的锁定 (LD 1-4) 和解锁期 (UL 1-2)(锁定后) (PL 1-3),并在印度受灾最严重的马哈拉施特拉邦建立环境和人口变量与 COVID-19 病例的关系。PM 2.5 、PM 10 、NO x 和CO 等大气污染物在锁定和解锁阶段大幅减少,其中交通量较大的城市减少幅度最大。与封锁前(PL 3 )相比,封锁期间的平均 PM 2.5 和 PM 10 分别减少了高达 51% 和 47%,由于车辆流量减少和工业关闭,空气质量指数 (AQI) 达到“令人满意”的水平。由于天气(降雨和温度)以及锁定条件的附加影响,这些参数在解锁期间继续减少多达 80%。Kendall 的相关矩阵显示温度和空气污染物之间存在显着的负相关(r = - 0.35 到 - 057)。相反,SO 2 和 O 3 没有改善,在某些情况下,它们在锁定和解锁期间增加。COVID-19 传播率与温度 (r < 0.62) 和露点 (r < 0.73) 呈强正相关。因此,这表明温度和露点的升高并不能削弱这种病毒的传播。与空气污染物相关的 COVID-19 病例数呈负相关(r = - 0.33 至 - 0.74),这可能只是封锁导致的巧合。然而,根据封锁前的空气质量数据和人口因素,发现颗粒物(PM 2.5 和 PM 10 )和人口密度与较高的发病率和死亡率密切相关,尽管这方面需要进行更深入的研究来验证这一发现。COVID-19 的爆发使我们能够确定,在人口稠密/工业化地区,空气质量的“即时”变化可以通过减少污染来改善生计。政策制定者可以利用这些发现为空气污染制定新的基准,从而提高世界主要人口的生活质量。COVID-19 向我们表明,我们可以在必要时做出改变,研究结果可能为未来的研究铺平道路,从而为我们在生活质量和生存之间做出艰难选择的政策提供信息。此外,我们的结果将丰富正在进行的关于环境因素对 COVID-19 传播的作用的讨论,并将有助于采取必要的措施来控制它。
更新日期:2020-10-09
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