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2019冠状病毒病相关因素与空气污染之间的联系

The Nexus Between COVID-19 Factors and Air Pollution.

作者信息

Parvin Rehana

机构信息

Department of Statistics, International University of Business Agriculture and Technology, Dhaka, Bangladesh.

出版信息

Environ Health Insights. 2023 Apr 12;17:11786302231164288. doi: 10.1177/11786302231164288. eCollection 2023.

Abstract

BACKGROUND AND OBJECTIVE

There have been significant effects of the current coronavirus-19 (COVID-19) infection outbreak on many facets of everyday life, particularly the environment. Despite the fact that a number of studies have already been published on the topic, an analysis of those studies' findings on COVID-19's effects on environmental pollution is still lacking. The goal of the research is to look into greenhouse gas emissions and air pollution in Bangladesh when COVID-19 is under rigorous lockdown. The specific drivers of the asymmetric relationship between air pollution and COVID-19 are being investigated.

METHODS

The nonlinear relationship between carbon dioxide ( ) emissions, fine particulate matter and COVID-19, as well as its precise components, are also being investigated. To examine the asymmetric link between COVID-19 factors on emissions and we employed the nonlinear autoregressive distributed lag (NARDL) model. Daily positive cases and daily confirmed death by COVID-19 are considered the factors of COVID-19, with lockdown as a dummy variable.

RESULTS

The bound test confirmed the existence of long-run and short-run relationships between variables. Bangladesh's strict lockdown, enforced in reaction to a surge of COVID-19 cases, reduced air pollution and dangerous gas emissions, mainly according to the dynamic multipliers graph.

摘要

背景与目的

当前的新型冠状病毒肺炎(COVID-19)感染疫情对日常生活的许多方面,尤其是环境,产生了重大影响。尽管已经有许多关于该主题的研究发表,但对这些研究中关于COVID-19对环境污染影响的结果分析仍然缺乏。该研究的目的是调查在COVID-19严格封锁期间孟加拉国的温室气体排放和空气污染情况。正在研究空气污染与COVID-19之间不对称关系的具体驱动因素。

方法

还在研究二氧化碳( )排放、细颗粒物 与COVID-19及其精确成分之间的非线性关系。为了检验COVID-19因素对 排放和 的不对称联系,我们采用了非线性自回归分布滞后(NARDL)模型。将COVID-19的每日阳性病例和每日确诊死亡病例视为COVID-19的因素,将封锁作为一个虚拟变量。

结果

边界检验证实了变量之间存在长期和短期关系。根据动态乘数图,孟加拉国为应对COVID-19病例激增而实施的严格封锁减少了空气污染和危险气体排放,主要是 。

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