Strict lockdown measures reduced PM2.5 concentrations during the COVID-19 pandemic in Kolkata, India.

ObjectiveTo investigate how trends in incidence of anxiety and depressive disorders have been affected by the COVID-19 pandemic.DesignPopulation-based cohort study.SettingRetrospective cohort study from 2018 to 2021 using the Information System...

This research was carried out using the open-source database system along with the continuous air quality monitoring station results from global data sets during the COVID-19 pandemic lockdown in India and the global. Our purpose of this research is to study the improvement of air quality and human mortality rates in countries worldwide during the COVID-19 pandemic lockdown. Worldwide air quality data were collected from > 12,000 continuous air quality monitoring stations on six continents covering 1000 major cities from over 100 countries. Here, we discussed the implementation of the open-source data set of basic air pollutants such as PM 2.5, NO2, temperature, relative humidity, and Air Quality Index variation during the pre-lockdown and lockdown pandemic COVID-19 in India and described the global aspect. An average concentration of PM 2.5 (145.51 μg/m3), NO2 (21.64 μg/m3), and AQI index (55.58) continuously decreased. The variation of PM 2.5, NO2, normally shows more than 25 μg/m3 every year, but during the COVID-19 lockdown period (April 2020) continuously decreased below 20 μg/m3. Similarly, the AQI index and meteorological factors such as temperature, relative humidity, and wind speed variation decreased significantly in the many countries in the world. In Asian countries, air quality improved during the national lockdown especially in the most polluted cities globally such as Beijing, Delhi, and Nanjing and also in developed cities like Madrid, New York, Paris, Seoul, Sydney, Tokyo. Furthermore, the reduction of particulate matter was in about 46%, and other gaseous pollutants during the lockdown period were observed in a 54% reduction. We are witnessing pollution reductions which add significantly to improvements in air quality. This is due to the massive decrease in the use of fossil fuel, which in turn reduces production and traffic in general. People nowadays are now willing to see a comparatively healthier world with bleached skies and natural ecosystems. This research finding demonstrates potential safety benefits associated with improving air quality and mortality rates during the COVID-19 pandemic, resulting in decreases in mortality rates in India and around the world.Electronic supplementary materialThe online version of this article (10.1007/s11869-020-00892-w) contains supplementary material, which is available to authorized users.

The COVID lockdown has posted a great challenge to paediatric patients with type 1 diabetes (T1D) and their caregivers on the disease management. This systematic review and meta-analysis sought to compare the glycaemic control among paediatric patients with T1D (aged under 18 years) pre- during, and post-lockdown period. We did a systematic search of three databases (PubMed, Embase, and the WHO COVID-19 Global literature) for the literature published between 1 Jan 2019 to 10 Sep 2022. Studies meeting the following inclusion criteria were eligible for this study: (1) a COVID-19 related study; (2) inclusion of children aged 18 years old or under with established T1D; (3) comparing the outcomes of interest during or after the COVID lockdown with that before the lockdown. Study endpoints included mean difference (MD) in HbA1c, blood glucose, time in range (TIR, 70-180 mg/dl), time above range (TAR, >180mg/dl), time below range (TBR,<70mg/dl) and glucose variability (coefficient of variation [CV]) between pre-lockdown and during lockdown and/or between pre- and post-lockdown period. The MD and its corresponding 95% CI of each endpoint were pooled using random-effect model considering the potential between-study heterogeneity in COVID restrictions and T1D management. Initial search identified 4488 records and 22 studies with 2106 paediatric patients with T1D were included in the final analysis. Compared with pre-lockdown period, blood glucose was significantly decreased by 0.11 mmol/L (95%CI: -0.18, -0.04) during lockdown period and by 0.42 mmol/L (95%CI: -0.73, -0.11) after lockdown. The improvement was also found for TIR, TAR, TBR, and CV during and post-lockdown (all p values<0.05) except for the post-lockdown TBR (p =0.35). No significant change in HbA1c was observed during and post- lockdown period when compared with the pre-lockdown value. There was moderate to high between-study heterogeneity for most of the analyses. Compared with pre-lockdown period, there was significant improvement in T1D paediatric patients' glucose metrics during and post-lockdown. The underlying reasons for this positive impact warrant further investigation to inform future paediatric diabetes management. https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022359213.

The unprecedented lockdown of human activities during the COVID-19 pandemic have significantly influenced the social life in China. However, understanding of the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorology variations during COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations of multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measurement with NOx emissions decreased substantially by ~40 %. However, emissions of other air pollutants were found only decreased by ~10 %, both because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over North China Plain (NCP) during lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions, and even led to substantial increases of O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over NCP, which contributed 90 % of the PM2.5 reductions over most parts of NCP region. Meanwhile, our results also suggest that the local stagnant meteorological conditions together with inefficient reductions in PM2.5 emissions were the main drivers of the unexpected COVID-19 haze in Beijing. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.

<strong class="journal-contentHeaderColor">Abstract.</strong> A knowledge gap exists concerning how chemical composition and sources respond to implemented policy control measures for aerosols, particularly in a semi-arid region. To address this, a single year's offline measurement was conducted in Hohhot, a semi-arid city in northern China, to reveal the driving factors of severe air pollution in a semi-arid region and assess the impact of the COVID-19 lockdown measures on chemical characteristics and sources of PM<span class="inline-formula">_2.5</span>. Organic matter, mineral dust, sulfate and nitrate accounted for 31.5 %, 14.2 %, 13.4 % and 12.3 % of the total PM<span class="inline-formula">_2.5</span> mass, respectively. Coal combustion, vehicular emission, crustal source and secondary inorganic aerosols were the main sources of PM<span class="inline-formula">_2.5</span> in Hohhot, at 38.3 %, 35.0 %, 13.5 %, and 11.4 %, respectively. Due to the coupling effect of emission reduction and improved atmospheric conditions, the concentration of secondary inorganic components, organic matter and elemental carbon declined substantially from the pre-lockdown (pre-LD) period to the lockdown (LD) and post-lockdown (post-LD) periods. The source contribution of secondary inorganic aerosols increased (from 21.1 % to 37.8 %), whereas the contribution of vehicular emission reduced (from 35.5 % to 4.4 %) due to lockdown measures. The rapid generation of secondary inorganic components caused by unfavorable meteorological conditions during lockdown led to serious pollution. This study elucidates the complex relationship between air quality and environmental policy.

COVID-19 lockdown impact on air quality and associated health benefit in two contrasting urban cities in Eastern Indo Gangetic Plain

Lockdown seems the most effective way to prevent the spread of Coronavirus disease (COVID-19) as no vaccine is available in the market to cure it. Thus, India has enforced nation-wide lockdown from 25th March to lower the spread of this contagious virus and associated illness. Thus, the anthropogenic activities have reduced significantly, as a result of which a decline in the air pollution levels is expected. This study aims to quantify the changes in pollution levels during the COVID-19 lockdown over 17 cities of India for 5 major criteria pollutants using publicly available air quality data. Hourly averaged data is accessed from the fixed air quality monitoring stations during the lockdown and immediate pre-lockdown periods and also corresponding data from the previous year (2019) to account for meteorological differences. After four weeks of lockdown, PM2.5, PM10, NO2, and CO reduced significantly with relatively little changes in meteorological condition compared to pre-lockdown period. The major decline is observed at the ~09:00 and ~21:00 hours of the day for PM, NO2, and CO with >40% reduction. The major impact is seen over metropolitan cities, with significant reduction in air pollutants levels (in particular in PM2.5 and PM10) resulting in 100% days during lockdown within the permissible air quality standards. PM2.5 and PM10 show ~70% decline in pollution levels for Delhi which is the highest among all the cities. Overall, the Northern and the Southern regions show more improvement in air quality during lockdown than other regions. The strict lockdown due to COVID-19, resulting in shutdown of many anthropogenic activities, has helped India to improve the air quality across the cities.

There are around 300 night markets in Taiwan, and they have been drawing an increasing number of tourists in recent years. As a result, public awareness over air quality in the night markets has grown tremendously. In response to this, a specific night market in Kaohsiung City was chosen for this study in order to characterize the existing air quality in and around the night markets. In this present study, we employed an Industrial Source Complex Short-Term (ISCST3) air quality model for the simulation of PM2.5 diffusions. The model as a technique can simulate the pollutants emissions, diffusions, transportation, and pollution sources in specific areas and subsequently evaluate the influence between the source and the receiver. Therefore, we compared pollutants emissions data from several air quality monitoring stations with our sampling data of three different sampling sites in Kaohsiung City. The findings of this study showed that the average concentration of PM2.5 was in the range of 29−61 µg m−3 during opening hours of the night market, whereas the average concentration of PM2.5 range was between 22−38 µg m−3 before the night market opening hours. The concentration of metallic elements (ME) (Mg, Na, Cr, Mn, Fe, Cu, Al, Ba, Cd, Pb and Ca) was determined with the support of Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). During the night market opening hours, the result disclosed that the ME concentrations in PM2.5 was in an increasing order as follows: Na > Fe > Al > Ca. With respect to the concentration of carbonaceous species, our results showed that the highest total carbon (TC) concentration was found to be 6.52 µg m−3 during the downwind sampling interval. The highest elemental carbon (EC) and organic carbon (OC) concentration were found to be 6.53 µg m−3 and 2.70 µg m−3 of the PM2.5 concentration, respectively. This study’s findings have significant consequences for Taiwan policymakers and urban planners, particularly those responsible for coordinating environmental protection and economic development in cities. Therefore, policy actions to abate urban air pollution can be attained on diverse governing echelons, resulting in synergistic effects such as a reduction in climate change impacts.

Change in Hospitalizations and 30-Day Mortality of Patients With Acute Myocardial Infarction During the First COVID-19 Lockdown – A Pure Social Isolation Effect?

Compensatory effect of biomass burning on black carbon concentrations during COVID-19 lockdown at a high-altitude station in SW India

A spatial feature engineering algorithm for creating air pollution health datasets

We aimed to evaluate the effects of COVID-19 social restrictions on maternal and newborn outcomes in Shanghai from April 1 to May 31 of 2022. We conducted a retrospective, cross-sectional analysis of all Live deliveries between April 1 and September 30 for the years 2021 and 2022 at our hospitals. Patients were assigned to three groups: “pre-lockdown” (April 1 to September 30, 2021), “during lockdown” (April 1 to May 31, 2022), and “post-lockdown” (June 1 to September 30, 2022). Cesarean delivery rate, pregnancy complications and neonatal outcomes were evaluated. Linear regression was used to model the continuous outcomes of birth weight and birth length, and logistic regression was implemented to model the binary outcomes of delivery mode, gestational diabetes mellitus (GDM), hypertension in pregnancy, neonatal asphyxia, fetal growth restriction (FGR), and preterm birth. A total of 2891 patients were enrolled in our study. Upon multivariate regression analysis and after adjustment for study epoch and patient characteristics, the lockdown period was associated with lower GDM (Exp(B) = 0.498; 95%CI, 0.379–0.655). The post-lockdown period was associated with a higher birth length (β = 0.040; 95%CI, 0.032–0.317) and more hypertension in pregnancy (Exp(B) = 1.683; 95%CI, 1.087–2.604) than the pre-lockdown period. The overall rates of cesarean delivery, preterm birth, neonatal asphyxia and FGR were not associated with the lockdown; however, maternal COVID-19 infection during lockdown was associated with a mean reduction of 150 g (95% CI, 11–288 g) in birth Weight at 37–39 weeks of gestation (p = 0.035). The lockdown period was associated with a diminution in GDM, and unlike the pre-lockdown period, the post-lockdown period was associated with an increase in birth weight and hypertension in pregnancy. Maternal COVID-19 infection during lockdown was also associated with lower neonatal birth Weight in deliveries at 37–39 weeks of gestation. Lockdown played a certain degree of impact on pregnancy complications and neonatal outcomes.

Background.The Nepalese government announced a nationwide lockdown beginning on March 24, 2020 as an attempt to restrain the spread of COVID-19. The prohibition in flight operations and movement of vehicles, factory shutdowns and restriction in people's movement due to the lockdown led to a significant reduction in the amounts of pollutants degrading air quality in many countries.Objectives.The present study aimed to analyze changes in particulate matter (PM) emissions and the air quality index (AQI) of six cities in Nepal i.e., Damak, Simara, Kathmandu, Pokhara, Nepalgunj and Surkhet due to the nationwide lockdown in response to the COVID-19 outbreak.Methods.Daily PM concentrations of each of the six study cities from January 24 to September 21, 2020 were obtained from the World Air Quality Index project (https://aqicn.org) and analyzed using R Studio software. The drop percentage was calculated to determine the change in PM2.5 and PM10 concentration during different time periods. Independent sample Mann–Whitney U tests were performed to test the significance of differences in mean concentration for each site during the lockdown period (24 March–24 July 2020) and its corresponding period in 2019. Similarly, the significance of differences in mean concentrations between the lockdown period and the period immediately before lockdown (23 January–23 March) was also examined using the same test.Results.During the lockdown period, in overall Nepal, AQIPM2.5 and AQIPM10 were within the moderate zone for the maximum number of days. As a result of the lockdown, the highest immediate and final drop of PM2.5 was observed in Damak (26.37%) and Nepalgunj (80.86%), respectively. Similarly, the highest immediate drop of PM10 was observed in Surkhet (37.22%) and finally in Nepalgunj (81.14%). Analysis with the Mann–Whitney U test indicated that for both PM types, all sites showed a statistically significant (p < 0.05) difference in mean concentrations during lockdown and the corresponding period in 2019.Conclusions.The present study explored the positive association between vehicular movement and PM emissions, highlighting the need for alternative fuel sources to improve air quality and human health.Competing Interests.The authors declare no competing financial interests.

Objective To investigate the relationship between air pollutants and hospitalization rate of children with respiratory disease (asthmatic attack, asthmatoid bronchitis, neumonia) in Shijiazhuang city. Methods The data of air quality monitoring in Shijiazhuang in Hebei Province from January 2016 to December 2016 were recorded, and hospitalization rate of children respiratory disease (asthmatic attack, asthmatoid bronchitis, pneumonia) in Hebei Children′s Hospital were enrolled, and the analysis of the linear regression was done for the correlation of air pollutants and hospitalization rate of children respiratory disease. Results The analysis result showed that the asthmatoid bronchitis hospitalization rate was positively correlated with the average concentration of SO2 and NO2, the correlation coefficient was 0.598 and 0.626 (P<0.05). The results showed that the average concentration of PM10, CO, PM2.5 and O3 did not have linear correlation with asthmatoid bronchitis hospitalization rate.The pneumonia hospitalization rate was positively correlated with the average concentration of SO2, NO2, PM10, CO and PM2.5, and the correlation coefficient was 0.867, 0.811, 0.825, 0.931 and 0.860, respectively (all P<0.05), but was independent with the average concentration of O3.It showed that if the index of concentration of contaminations increase of 10, hospitalization rate of asthmatoid bronchitis increased 0.1% and increased 2.4% of pneumonia. Conclusions The increase of PM10, PM2.5, NO2, SO2 and CO air pollutants could make a corresponding increase in the hospitalization rate of children with respiratory diseases. Key words: Air pollutants; PM2.5; Children; Disease of repiratory system

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;The COVID-19 pandemic has forced governments to implement rigorous containment measures on reduction or cessation of human mobility, transportation and economic activities, to control the spread of the virus. This is considered as a unique opportunity to study the impact of local lockdowns periods, especially, on the vehicle emission levels, and urban air quality in cities with high pollution levels, such as Bogota, Colombia. The first case was confirmed in Colombia on March 6, 2020, since then to prevent its propagation, the government declared a national lockdown starting from March 20 until August 31, 2020. Therefore, this study attempted to analyse the air quality in Bogota by assessing the concentrations of the atmospheric pollutants NO₂, SO₂, O₃, CO, PM₂.₅ and PM₁₀ during the lockdown period and the corresponding concentrations levels during the same period in 2018 and 2019. The data for this pilot study was obtained from the air quality monitoring stations of Bogota. The present work applied a descriptive and inferential statistical analysis of the data to quantify the average variation in concentration levels for each air pollutant and their trend before and during the lockdown period, in addition with a discussion about possible correlation with the volume flow rate of traffic. The lockdown period indicated a considerable reduction in traffic flow patterns and a drop in emission levels by -13% and -22% in NO&lt;sub&gt;2&lt;/sub&gt;, -11% and -20% in SO&lt;sub&gt;2&lt;/sub&gt;, -23% and -34% in CO, -7% and -15% in PM&lt;sub&gt;2.5&lt;/sub&gt;, -25 % and -16% in PM&lt;sub&gt;10&lt;/sub&gt; compared to base values of 2018 and 2019 respectively; On the contrary, levels of atmospheric ozone were found to be increased by 31.3% and 14.1% from reference values. The analysis suggests possible correlations between the atmospheric O₃ and the NO&lt;sub&gt;2&lt;/sub&gt; levels during lockdown period. The outcome of this pilot study will enable the policy makers to forecast the impact of electrification of transportation on atmospheric ozone levels in urban areas.&lt;/div&gt;&lt;/div&gt;