Abnormally Shallow Boundary Layer Associated With Severe Air Pollution During the COVID-19 Lockdown in China.
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ABSTRACT:
SUBMITTER: Su T
PROVIDER: S-EPMC7537024 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Severe air pollution episodes have been frequent in China during the recent years. While high emissions are the primary reason for increasing pollutant concentrations, the ultimate cause for the most severe pollution episodes has remained unclear. Here we show that a high concentration of particulate matter (PM) will enhance the stability of an urban boundary layer, which in turn decreases the boundary layer height and consequently cause further increases in PM concentrations. We estimate the strength of this positive feedback mechanism by combining a new theoretical framework with ambient observations. We show that the feedback remains moderate at fine PM concentrations lower than about 200 μg m(-3), but that it becomes increasingly effective at higher PM loadings resulting from the combined effect of high surface PM emissions and massive secondary PM production within the boundary layer. Our analysis explains why air pollution episodes are particularly serious and severe in megacities and during the days when synoptic weather conditions stay constant.
| S-EPMC4709519 | biostudies-literature
Project description:The rapid spread of COVID-19 resulted in various public lockdowns across the globe. Previous studies showed that resultant travel restrictions improved air quality. The novel results presented here focus on source-specific changes and compare air quality for multiple years controlled for precipitation. This study sought to analyze air pollution changes in Pittsburgh, a city where an industrial past and present has led to elevated levels of particulate matter with representative diameter of ≤ 2.5μm (PM2.5). Data from the Allegheny County Health Department, from monitors located near a variety of site types, were analyzed with generalized linear models that used a gamma distribution with a log link to determine the magnitude and significance of changes in air pollution during the COVID-19 lockdown. The hypothesis was that nitrogen dioxide (NO2), which is primarily linked to vehicular traffic, would decrease significantly while potential decreases in particulate matter (PM2.5 and PM10) would be less apparent. Results of the regression models showed that NO2 was significantly reduced during lockdown at both monitoring sites and that PM10 was also significantly reduced at the majority of monitoring sites. However, decreases in PM2.5 pollution were only observed at half of the monitoring locations, and the location which observed the greatest decreases is located adjacent to an industrial source. Decreases in PM2.5 at this monitoring site were likely a result of reduced industrial processes both dependent and independent of the COVID-19 lockdown. This study suggests that industrial sources are a larger contributor of particulate matter than vehicular transportation in the city of Pittsburgh and that future air pollution reduction efforts should focus attention on emission reduction at these industrial facilities.
| S-EPMC8638247 | biostudies-literature
Project description:BackgroundAmbient and household air pollution are found to lead to premature deaths from all-cause or cause-specific death. The national lockdown measures in China during COVID-19 were found to lead to abrupt changes in ambient surface air quality, but indoor air quality changes were neglected. In this study, we aim to investigate the impacts of lockdown measures on both ambient and household air pollution as well as the short-term health effects of air pollution changes.MethodsIn this study, an up-to-date emission inventory from January to March 2020 in China was developed based on air quality observations in combination with emission-concentration response functions derived from chemical transport modeling. These emission inventories, together with the emissions data from 2017 to 2019, were fed into the state-of-the-art regional chemistry transport model to simulate the air quality in the North China Plain. A hypothetical scenario assuming no lockdown effects in 2020 was also performed to determine the effects of the lockdown on air quality in 2020. A difference-to-difference approach was adopted to isolate the effects on air quality due to meteorological conditions and long-term decreasing emission trends by comparing the PM2.5 changes during lockdown to those before lockdown in 2020 and in previous years (2017-2019). The short-term premature mortality changes from both ambient and household PM2.5 changes were quantified based on two recent epidemiological studies, with uncertainty of urban and rural population migration considerations.FindingsThe national lockdown measures during COVID-19 led to a reduction of 5.1 µg m-3 in ambient PM2.5 across the North China Plain (NCP) from January 25th to March 5th compared with the hypothetical simulation with no lockdown measures. However, a difference-to-difference method showed that the daily domain average PM2.5 in the NCP decreased by 9.7 µg m-3 between lockdown periods before lockdown in 2020, while it decreased by 7.9 µg m-3 during the same periods for the previous three-year average from 2017 to 2019, demonstrating that lockdown measures may only have caused a 1.8 µg m-3 decrease in the NCP. We then found that the integrated population-weighted PM2.5, including both ambient and indoor PM2.5 exposure, increased by 5.1 µg m-3 during the lockdown periods compared to the hypothetical scenario, leading to additional premature deaths of 609 (95% CI: 415-775) to 2,860 (95% CI: 1,436-4,273) in the short term, depending on the relative risk chosen from the epidemiological studies.InterpretationOur study indicates that lockdown measures in China led to abrupt reductions in ambient PM2.5 concentration but also led to significant increases in indoor PM2.5 exposure due to confined indoor activities and increased usages of household fuel for cooking and heating. We estimated that hundreds of premature deaths were added as a combination of decreased ambient PM2.5 and increased household PM2.5. Our findings suggest that the reduction in ambient PM2.5 was negated by increased exposure to household air pollution, resulting in an overall increase in integrated population weighted exposure. Although lockdown measures were instrumental in reducing the exposure to pollution concentration in cities, rural areas bore the brunt, mainly due to the use of dirty solid fuels, increased population density due to the large-scale migration of people from urban to rural areas during the Chinese New Year and long exposure time to HAP due to restrictions in outdoor movement.
| S-EPMC8502102 | biostudies-literature
Project description:Compared with the 21-year climatological mean over the same period during 2000-2020, the aerosol optical depth (AOD) and Angstrom exponent (AE) during the COVID-19 lockdown (January 24-February 29, 2020) decreased and increased, respectively, in most regions of Central-Eastern China (CEC). The AOD (AE) values decreased (increased) by 39.2% (29.4%) and 31.0% (45.3%) in Hubei and Wuhan, respectively, because of the rigorous restrictions. These inverse changes reflected the reduction of total aerosols in the air and the contribution of the increase in fine-mode particles during the lockdown. The surface PM2.5 had a distinct spatial distribution over CEC during the lockdown, with high concentrations in North China and East China. In particular, relatively high PM2.5 concentrations were notable in the lower flatlands of Hubei Province in Central China, where six PM2.5 pollution events were identified during the lockdown. Using the observation data and model simulations, we found that 50% of the pollution episodes were associated with the long-range transport of air pollutants from upstream CEC source regions, which then converged in the downstream Hubei receptor region. However, local pollution was dominant for the remaining episodes because of stagnant meteorological conditions. The long-range transport of air pollutants substantially contributed to PM2.5 pollution in Hubei, reflecting the exceptional importance of meteorology in regional air quality in China.
| S-EPMC7473012 | biostudies-literature
Project description:Long-range transport (LRT) of air pollutants from East Asia during the northeast monsoon season impacts several downwind locations. In 2020, the initial COVID-19 lockdowns in China overlapped with Week 3 of the Chinese New Year (CNY) holiday, and an Asian outflow event. Thus, movement of the Chinese populace from city to city was already greatly reduced by the time of the LRT episode, although the reductions in industrial output are less clear. We found NO2 column concentrations were reduced by 24% during the CNY Week 3 this year compared to previous years. The attenuated transport event arrived to northern Taiwan with a PM2.5 concentration <45 μg m-3 and most often <35 μg m-3, which is 2-3 times lower than LRT episodes of similar back-trajectory and synoptic patterns. The whole episode persisted for about 60 h, longer than most LRT episodes from China to Taiwan. CMAQ v5.2.1 modeling of the LRT event with 100% emission and reduced emission scenarios, revealed emissions in China were approximately 50% less than normal periods. Due to the length of the episode and the significant reduction in emissions, Taiwan avoided a PM2.5 surplus of 19.2 μg m-3 on average during the episode, equivalent to a 0.5 μg m-3 reduction for the whole 3-month winter season. Employing the 100% emission model scenario and scaling up to the average episode hours each winter, the PM2.5 surplus delivered via plumes on the northeast monsoon is equivalent to a 0.5 μg m-3 surplus for the whole year.
| S-EPMC7295523 | biostudies-literature
Project description:The strict nationwide lockdown imposed in India starting from 25th March 2020 to prevent the spread of COVID-19 disease reduced the mobility and interrupted several important anthropogenic emission sources thereby creating a temporary air quality improvement. This study conducts a multi-scale (national-regional-city), multi-species, and multi-platform analysis of air pollutants and meteorological data by synergizing surface and satellite observations. Our analysis suggests a significant reduction in surface measurements of nitrogen dioxide (NO2) (46-61 %) and fine particulate matter (PM2.5) (42-60 %) during the lockdown period that are also corroborated by the reduction in satellite observed aerosol optical depth (AOD) (3-56 %) and tropospheric NO2 column density (25-50 %) data over multiple cities. Other species, namely coarse particulate matter (PM10) (24-62 %), ozone (22-56 %) also showed a substantial reduction whereas carbon monoxide (16-46 %), exhibited a moderate decline. In contrast, sulfur dioxide (SO2) levels did not show any defined reduction trend but rather increased in Mumbai, Bengaluru, and Kolkata. The temporary air quality improvement achieved by the painful natural experiment of this pandemic has helped demonstrate the importance of reducing emissions from other sectors along with transportation and industry to achieve the national air quality targets in the future.
| S-EPMC7771315 | biostudies-literature
Project description:The abrupt reduction in the human activities during the first lockdown of the COVID-19 pandemic created unprecedented changes in the background atmospheric conditions. Several studies reported the anthropogenic and air quality changes observed during the lockdown. However, no attempts are made to investigate the lockdown effects on the Atmospheric Boundary Layer (ABL) and background instability processes. In this study, we assess the lockdown impacts on the ABL altitude and instability parameters (Convective Available Potential Energy (CAPE) and Convective Inhibition Energy (CINE)) using WRF model simulations. Results showed a unique footprint of COVID-19 lockdown in all these parameters. Increase in the visibility, surface temperature and wind speed and decrease in relative humidity during the lockdown is noticed. However, these responses are not uniform throughout India and are significant in the inland compared to the coastal regions. The spatial variation of temperature (wind speed) and relative humidity shows an increase and decrease over the Indo Gangetic Plain (IGP) and central parts of India by 20% (100%) and 40%, respectively. Increase (80%) in the ABL altitude is larger over the IGP and central parts of India during lockdown of 2020 compared to similar time period in 2015-2019. This increase is attributed to the stronger insolation due to absence of anthropogenic activity and other background conditions. At the same time, CAPE decreased by 98% in the IGP and central parts of India, where it shows an increase in other parts of India. A prominent strengthening of CINE in the IGP and a weakening elsewhere is also noticed. These changes in CAPE and CINE are mainly attributed to the dearth of saturation in lower troposphere levels, which prevented the development of strong adiabatic ascent during the lockdown. These results provide a comprehensive observation and model-based insight for lockdown induced changes in the meteorological and thermo-dynamical parameters.
| S-EPMC8975591 | biostudies-literature
Project description:Highlights • Variations in air quality in terms of CO, SO2, PM10, O3 and NO2 levels were studied.• The lockdown of Spain was not able to reduce severe air pollution in all its forms.• Significant reductions of NO2 levels were achieved in most cities.• Increases of O3 pollution levels were found in several cities. The COVID-19 pandemic has escalated into one of the largest crises of the 21st Century. The new SARS-CoV-2 coronavirus, responsible for COVID-19, has spread rapidly all around the world. The Spanish Government was forced to declare a nationwide lockdown in view of the rapidly spreading virus and high mortality rate in the nation. This study investigated the impact of short-term lockdown during the period from March 15th to April 12th 2020 on the atmospheric levels of CO, SO2, PM10, O3, and NO2 over 11 representative Spanish cities. The possible influence of several meteorological factors (temperature, precipitation, wind, sunlight hours, minimum and maximum pressure) on the pollutants' levels were also considered. The results obtained show that the 4-week lockdown had significant impact on reducing the atmospheric levels of NO2 in all cities except for the small city of Santander as well as CO, SO2, and PM10 in some cities, but resulted in increase of O3 level. Graphical abstract Image, graphical abstract
| S-EPMC7402215 | biostudies-literature
Project description:Until 31 May 2020, more than six million confirm COVID-19 cases had been reported worldwide. Lockdown has resulted in significant air quality improvement, especially in urban regions. The lockdown has acted as a natural experiment empowering researchers, policymakers, and governing bodies. The present study focuses on quantifying and analysing the effect of lockdown on India’s metropolitan cities, namely New Delhi, Mumbai, Kolkata, Chennai, and Bangalore. The study analyses the phase-wise and diurnal variations in the air quality from 24 March 2020 to 31 May 2020 while focussing on-peak and off-peak duration concentrations. To investigate the reason behind pollutant reduction, correlation of drop percentages in pollutant concentrations with vehicle population, extent of construction activity, and meteorological parameters are analysed. The 24-h drop in PM10 and PM2.5 showed a high correlation (R2 = 0.97 and 0.72, respectively) with the city’s vehicle population. During peak hours, the inland cities (Delhi and Bangalore), with a more extensive vehicle fleet, recorded a higher drop in PM10 and PM2.5 concentrations than coastal cities (Mumbai, Chennai, and Kolkata). With respect to 2019 concentration, the maximum decrease in pollutant concentrations averaged across the five study locations was recorded in NO2 (46%), followed by PM2.5 (40%), PM10 (37%), and CO (19%). SO2 and O3 contrarily recorded an overall increase of 40% and 41%. These results wherein vehicular pollutants recorded the maximum drop indicate that reduced vehicular traffic primarily influenced air quality improvement during the lockdown. Supplementary Information The online version contains supplementary material available at 10.1007/s12517-021-07777-x.
| S-EPMC8284691 | biostudies-literature
Project description:Recent studies demonstrate that air quality improved during the coronavirus pandemic due to the imposition of social lockdowns. We investigate the impact of COVID-19 on air pollution in the two largest cities in Taiwan, which were not subject to economic or mobility restrictions. Using a difference-in-differences approach and real-time data on air quality and transportation, we estimate that anthropogenic air pollution from local sources increased during working days and decreased during non-working days during the COVID-19 pandemic. This led to a 3-7 percent increase in CO, O3, SO2, PM10 and PM2.5. We demonstrate that the increase in air pollution resulted from a shift in preferred mode of travel away from public transportation and towards personal motor vehicles during working days. In particular, metro and shared bicycle usage decreased between 8 and 18 percent, on average, while automobile and scooter use increased between 11 and 21 percent during working days. Similar COVID-19 prevention behaviors in regions or countries emerging from lockdowns could likewise result in an increase in air pollution. Taking action to reduce the transmissibility of COVID-19 on metro cars, trains and buses could help policymakers limit the substitution of personal motor vehicles for public transit, and mitigate increases in air pollution when lifting mobility restrictions.
| S-EPMC8352669 | biostudies-literature