Season, not lockdown, improved air quality during COVID-19 State of Emergency in Nigeria

Atmospheric Boundary Layer Over Ahmedabad, Western Indian Region: Impact of COVID-19 Nationwide Lockdown

The government of India imposed a nationwide lockdown to tackle the outbreak of COVID-19 in 2020. This period witnessed record low anthropogenic activity, which had severe socio-economic impacts but also had orthogonal effects on the ambient air quality of the atmosphere. This study focuses on the variations in the atmospheric boundary layer (ABL) over a western Indian urban region in the light of COVID-19. Continuous backscatter recorded by a ceilometer, stationed at Ahmedabad, was used in this study to monitor the ABL during the national lockdown (NLD) in 2020 and state restrictions in 2021, and compared with the control year of 2019. In parallel, improvement in air quality during the NLD was observed by the SAFAR air quality station at Ahmedabad, with decreased particulate matter concentrations. The ground-based observations were substantiated by the ERA5 reanalysis dataset. A decline in the ABL height was recorded during the NLD, which showed improvement in 2021 but which was shy of the ABL in 2019. This was correlated with rain events during the observational period, recorded by an automatic weather station.

Analysis of the lockdown effects due to the COVID-19 on air pollution in Brescia (Lombardy)

SARS-CoV-2 virus (COVID-19) pandemic has impacted several countries, with also some differences at local levels. When lockdown restrictions were imposed, the concentrations of some air pollutants were reduced, as reported in some other cities in the world. This was often considered a positive by-product of the pandemic. However, often literature reporting the connection of air quality (AQ) and lockdown, suffers of limited and incomplete data analysis, not considering, for example, some confounding factors. This work presents a methodology, and the results of its application, to assess the impact of pandemic restrictions on AQ (in particular nitrogen oxides, NO₂ and particulate matter, PM₁₀) in spring 2020 in Brescia, located in one of the most affected areas in terms of virus diffusion and in one of the most polluted areas in Europe (Po Valley, Italy). In particular, the proposed methodology integrates data and AQ modelling simulations to distinguish between the changes in the PM₁₀ and NO₂ pollutants concentration that occurred due to the restriction measures and due to other factors, like spatial-temporal characteristics (for example the seasonality), meteorological factors, and governmental actions that were introduced in the past to improve the air quality. Results show that NO₂ is strongly dependent to traffic emission. On the contrary, although the expected decrease in PM₁₀ concentrations, the results highlight that the reduction of transport emission would not help to avoid severe air pollution, due to the other pollution sources that contribute to its origin. The results presented for the first time in this work are of particular interest because they may be used as a basis to investigate in more details the sources that can impact on the air quality in Brescia, with the aim to propose effective measures able to reduce it.

Can the Indian national ambient air quality standard protect against the hazardous constituents of PM2.5?

Globally, exposure to ambient fine particulate matter (PM_2.5) pollution claims ∼9 million lives, yearly, and a quarter of this deaths occurs in India. Regulation of PM_2.5 pollution in India is based on compliance with its National Ambient Air Quality Standard (NAAQS) of 40 μg/m³, which is eight times the revised global air quality guideline (AQG) of 5 μg/m³. But, whether the NAAQS provides adequate protection against the hazardous components in PM_2.5 is still not clear. Here, we examined the risk to health associated with exposure to PM_2.5-bound polychlorinated biphenyls (PCB), heavy metals and polycyclic aromatic hydrocarbons (PAHs) in an Indian district averaging below the NAAQS. The annual average concentrations of PM_2.5 mass, Σ₂₈PCB and Σ₁₃PAHs were 34 ± 17 μg/m³, 21 ± 12 ng/m³ and 458 ± 246 ng/m³, respectively. Concentrations of As, Cr, Mn and Ni in PM_2.5 surpassed the screening levels for residential air. Substantial level of risks to health were associated with exposure to dioxin-like PCBs (Σ₁₂dlPCB), PAHs, As, Cr and Ni. The hazard index or lifetime cancer risk were 240, or 9 cases per 1000 population, respectively. The estimated risks to health through exposure to hazardous components, except Ni, were greatest in rural areas, having a lower average PM_2.5 concentration, than urban or peri-urban areas, suggesting higher toxicity potential of rural combustion sources. The large disparity between the estimated risk values and the acceptable risk level suggests that it would take a more stringent standard, such as the global AQG, to protect vulnerable populations in India from hazardous components in PM_2.5.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM1, PM2.5 and PM10 fractions were measured at an urban background sampling site in Zagreb, Croatia from 2009 to late 2020. For the purpose of meteorological normalization, the mass concentrations were fed alongside meteorological and temporal data to Random Forest (RF) and LightGBM (LGB) models tuned by Bayesian optimization. The models' predictions were subsequently de-weathered by meteorological normalization using repeated random resampling of all predictive variables except the trend variable. Three pollution periods in 2020 were examined in detail: January and February, as pre-lockdown, the month of April as the lockdown period, as well as June and July as the "new normal". An evaluation using normalized mass concentrations of particulate matter and Analysis of variance (ANOVA) was conducted. The results showed that no significant differences were observed for PM1, PM2.5 and PM10 in April 2020-compared to the same period in 2018 and 2019. No significant changes were observed for the "new normal" as well. The results thus indicate that a reduction in mobility during COVID-19 lockdown in Zagreb, Croatia, did not significantly affect particulate matter concentration in the long-term..

Empirical evidence shows that air quality changes during COVID-19 pandemic lockdown in Jakarta, Indonesia are due to seasonal variation, not restricted movements

Implementing a lockdown or activity restriction to reduce the spread of COVID-19 cases is assumed to improve air quality in highly populated cities. The effect of lockdown on air quality is often quantified by comparing pre- and during-lockdown air quality parameters without considering confounding meteorological factors. We demonstrated that rainfall can explain changes in PM10 and PM2.5 parameters in the city of Jakarta during lockdown. This article shows that comparing air quality pre- and during lockdown is misleading. Variables affecting air quality such as meteorological variables should be taken into account. The air quality in Jakarta as measured by PM10 and PM2.5 did not change significantly during the lockdown period after removing the seasonal effect.

Differential health and economic impacts from the COVID-19 lockdown between the developed and developing countries: Perspective on air pollution

It is enlightening to determine the discrepancies and potential reasons for the degree of impact from the COVID-19 control measures on air quality as well as the associated health and economic impacts. Analysis of air quality, socio-economic factors, and meteorological data from 447 cities in 46 countries indicated that the COVID-19 control measures had significant impacts on the PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) concentrations in 20 (reduced PM2.5 concentrations of -7.4-29.1 μg m-3) of the selected 46 countries. In these 20 countries, the robustly distinguished changes in the PM2.5 concentrations caused by the control measures differed between the developed (95% confidence interval (CI): -2.7-5.5 μg m-3) and developing countries (95% CI: 8.3-23.2 μg m-3). As a result, the COVID-19 lockdown reduced death and hospital admissions change from the decreased PM2.5 concentrations by 7909 and 82,025 cases in the 12 developing countries, and by 78 and 1214 cases in the eight developed countries. The COVID-19 lockdown reduced the economic cost from the PM2.5 related health burden by 54.0 million dollars in the 12 developing countries and by 8.3 million dollars in the eight developed countries. The disparity was related to the different chemical compositions of PM2.5. In particular, the concentrations of primary PM2.5 (e.g., BC) in cities of developing countries were 3-45 times higher than those in developed countries, so the mass concentration of PM2.5 was more sensitive to the reduced local emissions in developing countries during the COVID-19 control period. The mass fractions of secondary PM2.5 in developed countries were generally higher than those in developing countries. As a result, these countries were more sensitive to the secondary atmospheric processing that may have been enhanced due to reduced local emissions.

COVID-19 pandemic in Uttarakhand, India: Environmental recovery or degradation?

The human coronavirus disease-2019 (COVID-19) caused by SARS-CoV-2 is now a global pandemic. Personal hygiene such as hand-washing, the use of personal protective equipment, and social distancing via local and national lockdowns are used to reduce the risk of transmission of SARS-CoV-2. COVID-19 and the associated lockdowns may have significant impacts on environmental quality and ergonomics. However, limited studies exists on the impacts of COVID-19 and the associated lockdowns on environmental quality and ergonomics in low-income settings. Therefore, the present study investigated the impacts of the COVID-19 outbreak on socioeconomics, ergonomics and environment (water quality, air quality and noise) in Uttarakhand, India. Approximately 55% of respondents experienced headaches, and the other common health-related issue was back pain, with 45% of respondents having problems with their backs. Water and air quality significantly improved during the lockdown relative to the pre-lockdown period, but was observed to return to their previous characteristics afterwards. Lockdowns significant increased the concentration of indoor air pollutants while noise pollution levels significantly declined. In summary, lockdowns have adverse impacts on ergonomics, resulting in work-related human health risks. The impacts of lockdowns on environmental quality are mixed: temporary improvements on water and air quality, and noise reduction were observed, but indoor air quality deteriorated. Therefore, during lockdowns there is a need to minimize the adverse environmental and ergonomic impacts of lockdowns while simultaneously enhancing the beneficial impacts.