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1.
Environ Monit Assess ; 195(6): 763, 2023 May 30.
Article in English | MEDLINE | ID: covidwho-20240403

ABSTRACT

The spatiotemporal variation of the death and tested positive cases is poorly understood during the respiratory coronavirus disease 2019 (COVID-19) pandemic. On the other hand, COVID-19's spread was not significantly slowed by pandemic maps. The aim of this study is to investigate the connection between COVID-19 distribution and airborne PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm). Long-term exposure to high levels of PM2.5 is significantly connected to respiratory diseases in addition to being a potential carrier of viruses. Between April 2020 and March 2021, data on COVID-19-related cases were gathered for all prefectures in Japan. There were 9159, 109,078, and 451,913 cases of COVID-19 that resulted in death, severe illness, and positive tests, respectively. Additionally, we gathered information on PM2.5 from 1119 air quality monitoring stations that were deployed across the 47 prefectures. By using the statistical analysis tools in the Geographical Information System (GIS) software, it was found that the residents of prefectures with high PM2.5 concentrations were the most susceptible to COVID-19. Additionally, the World Health Organization-Air Quality Guidelines (WHO-AQG) relative risk (RR) of 1.04 (95% CI: 1.01-1.08), which was used to compute the PM2.5-caused deaths, was employed as well. Approximately 1716 (95% CI: 429-3,432) cases of PM2.5-related deaths were thought to have occurred throughout the study period. Despite the possibility that the actual numbers of both COVID19 and PM2.5-caused deaths are higher, humanitarian actors could use PM2.5 data to localize the efforts to minimize the spread of COVID-19.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Relief Work , Humans , COVID-19/epidemiology , Air Pollutants/analysis , Environmental Monitoring/methods , Particulate Matter/analysis , Air Pollution/analysis , Environmental Exposure/analysis
2.
Environ Int ; 176: 107967, 2023 06.
Article in English | MEDLINE | ID: covidwho-20238659

ABSTRACT

BACKGROUND: A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE: We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS: Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS: The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 µg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 µg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 µg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION: In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.


Subject(s)
Air Pollutants , Air Pollution , Humans , Air Pollutants/analysis , Nitrogen Dioxide/analysis , Air Pollution/adverse effects , Air Pollution/analysis , China/epidemiology , Risk Factors , Particulate Matter/analysis , Environmental Exposure/adverse effects
3.
Huan Jing Ke Xue ; 44(5): 2430-2440, 2023 May 08.
Article in Chinese | MEDLINE | ID: covidwho-20237414

ABSTRACT

To investigate the change characteristics of secondary inorganic ions in PM2.5 at different pollution stages before and after COVID-19, the online monitoring of winter meteorological and atmospheric pollutant concentrations in Zhengzhou from December 15, 2019 to February 15, 2020 was conducted using a high-resolution (1 h) online instrument. This study analyzed the causes of the haze process of COVID-19, the diurnal variation characteristics of air pollutants, and the distribution characteristics of air pollutants at different stages of haze.The results showed that Zhengzhou was mainly controlled by the high-pressure ridge during the haze process, and the weather situation was stable, which was conducive to the accumulation of air pollutants. SNA was the main component of water-soluble ions, accounting for more than 90%. Home isolation measures during COVID-19 had different impacts on the distribution characteristics of air pollutants in different haze stages. After COVID-19, the concentration of PM2.5 in the clean, occurrence, and dissipation stages increased compared with that before COVID-19 but significantly decreased in the development stage. The home isolation policy significantly reduced the high value of PM2.5. The concentrations of NO2, SO2, NH3, and CO were the highest in the haze development stage, showing a trend of first increasing and then decreasing. The concentration of O3 was lowest in the pre-COVID-19 development stage but highest in the post-COVID-19 development stage. The linear correlation between[NH4+]/[SO42-] and[NO3-]/[SO42-] at different time periods before and after COVID-19 was strong, indicating that the home isolation policy of COVID-19 did not change the generation mode of NO3-, and the corresponding reaction was always the main generation mode of NO3-. The correlation between[excess-NH4+] and[NO3-] was high in different periods before COVID-19, and NO3- generation was related to the increase in NH3 or NH4+ in the process of PM2.5 pollution in Zhengzhou.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Particulate Matter/analysis , Environmental Monitoring/methods , COVID-19/epidemiology , Respiratory Aerosols and Droplets , Air Pollutants/analysis , Air Pollution/analysis , Ions/analysis , Seasons , China/epidemiology
5.
Environ Monit Assess ; 195(6): 764, 2023 May 30.
Article in English | MEDLINE | ID: covidwho-20232589

ABSTRACT

The lockdowns and curfews during the COVID-19 pandemic have halted economic and transportation activities across the world. This study aims to investigate air pollution levels in the Marmara region, particularly in Istanbul, before and during the COVID-19 pandemic. The study used real data provided by the General Directorate of Meteorology and applied three machine learning algorithms (ANN, RBFreg, and SMOreg) to analyze air pollution data. In addition, a one-sample t-test was performed to compare air pollution levels before and during the COVID-19 pandemic in the Marmara region and Istanbul. The results of the study showed a significant reduction in the particulate matter (PM) value, which indicates the degree of air pollution, in both the Marmara region and Istanbul during the COVID-19 pandemic. The one-sample t-test results showed that the reduction in air pollution levels was statistically significant in both areas (t = 11.45, p < .001 for the Marmara region, and t = 3.188, p < .001 for Istanbul). These findings have important practical implications for decision-makers planning for a more sustainable environment. Overall, the study provides valuable insights into the impact of the COVID-19 pandemic on air pollution levels in the Marmara region, particularly in Istanbul. The application of machine learning algorithms and statistical analysis provides a rigorous approach to the investigation of this important issue by comparing before and during the COVID-19 outbreak.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , Air Pollutants/analysis , SARS-CoV-2 , Pandemics , Environmental Monitoring , Communicable Disease Control , Air Pollution/analysis , Particulate Matter/analysis
6.
Environ Sci Pollut Res Int ; 30(30): 76253-76262, 2023 Jun.
Article in English | MEDLINE | ID: covidwho-20232023

ABSTRACT

The effect of environmental and socioeconomic conditions on the global pandemic of COVID-19 had been widely studied, yet their influence during the early outbreak remains less explored. Unraveling these relationships represents a key knowledge to prevent potential outbreaks of similar pathogens in the future. This study aims to determine the influence of socioeconomic, infrastructure, air pollution, and weather variables on the relative risk of infection in the initial phase of the COVID-19 pandemic in China. A spatio-temporal Bayesian zero-inflated Poisson model is used to test for the effect of 13 socioeconomic, urban infrastructure, air pollution, and weather variables on the relative risk of COVID-19 disease in 122 cities of China. The results show that socioeconomic and urban infrastructure variables did not have a significant effect on the relative risk of COVID-19. Meanwhile, COVID-19 relative risk was negatively associated with temperature, wind speed, and carbon monoxide, while nitrous dioxide and the human modification index presented a positive effect. Pollution gases presented a marked variability during the study period, showing a decrease of CO. These findings suggest that controlling and monitoring urban emissions of pollutant gases is a key factor for the reduction of risk derived from COVID-19.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , Air Pollutants/analysis , Pandemics , Bayes Theorem , Particulate Matter/analysis , Air Pollution/analysis , Carbon Monoxide/analysis , China/epidemiology , Environmental Monitoring
7.
Int J Environ Res Public Health ; 20(11)2023 May 31.
Article in English | MEDLINE | ID: covidwho-20244000

ABSTRACT

Social distancing measures and shelter-in-place orders to limit mobility and transportation were among the strategic measures taken to control the rapid spreading of COVID-19. In major metropolitan areas, there was an estimated decrease of 50 to 90 percent in transit use. The secondary effect of the COVID-19 lockdown was expected to improve air quality, leading to a decrease in respiratory diseases. The present study examines the impact of mobility on air quality during the COVID-19 lockdown in the state of Mississippi (MS), USA. The study region is selected because of its non-metropolitan and non-industrial settings. Concentrations of air pollutants-particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ozone (O3), nitrogen oxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)-were collected from the Environmental Protection Agency, USA from 2011 to 2020. Because of limitations in the data availability, the air quality data of Jackson, MS were assumed to be representative of the entire region of the state. Weather data (temperature, humidity, pressure, precipitation, wind speed, and wind direction) were collected from the National Oceanic and Atmospheric Administration, USA. Traffic-related data (transit) were taken from Google for the year 2020. The statistical and machine learning tools of R Studio were used on the data to study the changes in air quality, if any, during the lockdown period. Weather-normalized machine learning modeling simulating business-as-scenario (BAU) predicted a significant difference in the means of the observed and predicted values for NO2, O3, and CO (p < 0.05). Due to the lockdown, the mean concentrations decreased for NO2 and CO by -4.1 ppb and -0.088 ppm, respectively, while it increased for O3 by 0.002 ppm. The observed and predicted air quality results agree with the observed decrease in transit by -50.5% as a percentage change of the baseline, and the observed decrease in the prevalence rate of asthma in MS during the lockdown. This study demonstrates the validity and use of simple, easy, and versatile analytical tools to assist policymakers with estimating changes in air quality in situations of a pandemic or natural hazards, and to take measures for mitigating if the deterioration of air quality is detected.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , Nitrogen Dioxide/analysis , Mississippi/epidemiology , Communicable Disease Control , Air Pollution/analysis , Air Pollutants/analysis , Particulate Matter/analysis , Nitric Oxide , Environmental Monitoring/methods
8.
Environ Sci Pollut Res Int ; 30(33): 80655-80675, 2023 Jul.
Article in English | MEDLINE | ID: covidwho-20243708

ABSTRACT

Taxis pose a higher threat to global climate change and human health through air emissions. However, the evidence on this topic is scarce, especially, in developing countries. Therefore, this study conducted estimation of fuel consumption (FC) and emission inventories on Tabriz taxi fleet (TTF), Iran. A structured questionnaire to obtain operational data of TTF, municipality organizations, and literature review were used as data sources. Then modeling was used to estimate fuel consumption ratio (FCR), emission factors (EFs), annual FC, and emissions of TTF using uncertainty analysis. Also, the impact of COVID-19 pandemic period was considered on the studied parameters. The results showed that TTF have high FCRs of 18.68 L/100 km (95% CI=17.67-19.69 L/100 km), which are not affected by age or mileage of taxis, significantly. The estimated EFs for TTF are higher than Euro standards, but the differences are not significant. However, it is critical as can be an indication of inefficiency of periodic regulatory technical inspection tests for TTF. COVID-19 pandemic caused significant decrease in annual total FC and emissions (9.03-15.6%), but significant increase in EFs of per-passenger-kilometer traveled (47.9-57.3%). Annual vehicle-kilometer-traveled by TTF and the estimated EFs for gasoline-compressed natural gas bi-fueled TTF are the main influential parameters in the variability of annual FC and emission levels. More studies on sustainable FC and emissions mitigation strategies are needed for TTF.


Subject(s)
Air Pollutants , COVID-19 , Humans , Air Pollutants/analysis , Vehicle Emissions/analysis , Iran , Pandemics , Uncertainty , Gasoline/analysis , Motor Vehicles , Environmental Monitoring/methods
10.
Sci Total Environ ; 892: 164456, 2023 Sep 20.
Article in English | MEDLINE | ID: covidwho-2328296

ABSTRACT

The hourly Himawari-8 version 3.1 (V31) aerosol product has been released and incorporates an updated Level 2 algorithm that uses forecast data as an a priori estimate. However, there has not been a thorough evaluation of V31 data across a full-disk scan, and V31 has yet to be applied in the analysis of its influence on surface solar radiation (SSR). This study firstly investigates the accuracy of V31 aerosol products, which includes three categories of aerosol optical depth (AOD) (AODMean, AODPure, and AODMerged) as well as the corresponding Ångström exponent (AE), using ground-based measurements from the AERONET and SKYNET. Results indicate that V31 AOD products are more consistent with ground-based measurements compared to previous products (V30). The highest correlation and lowest error were seen in the AODMerged, with a correlation coefficient of 0.8335 and minimal root mean square error of 0.1919. In contrast, the AEMerged shows a larger discrepancy with measurements unlike the AEMean and AEPure. Error analysis reveals that V31 AODMerged has generally stable accuracy across various ground types and geometrical observation angles, however, there are higher uncertainties in areas with high aerosol loading, particularly for fine aerosols. The temporal analysis shows that V31 AODMerged performs better compared to V30, particularly in the afternoon. Finally, the impacts of aerosols on SSR based on the V31 AODMerged are investigated through the development of a sophisticated SSR estimation algorithm in the clear sky. Results demonstrate that the estimated SSR is significant consistency with those of well-known CERES products, with preservation of 20 times higher spatial resolution. The spatial analysis reveals a significant reduction of AOD in the North China Plain before and during the COVID-19 outbreak, resulting in an average 24.57 W m-2 variation of the surface shortwave radiative forcing in clear sky daytime.


Subject(s)
Air Pollutants , COVID-19 , Humans , Air Pollutants/analysis , Uncertainty , Respiratory Aerosols and Droplets , Disease Outbreaks , Environmental Monitoring/methods
11.
J Environ Manage ; 343: 118252, 2023 Oct 01.
Article in English | MEDLINE | ID: covidwho-2328110

ABSTRACT

The study aimed to investigate the PM2.5 variations in different periods of COVID-19 control measures in Northern Taiwan from Quarter 1 (Q1) 2020 to Quarter 2 (Q2) 2021. PM2.5 sources were classified based on long-range transport (LRT) or local pollution (LP) in three study periods: one China lockdown (P1), and two restrictions in Taiwan (P2 and P3). During P1 the average PM2.5 concentrations from LRT (LRT-PM2.5-P1) were higher at Fuguei background station by 27.9% and in the range of 4.9-24.3% at other inland stations compared to before P1. The PM2.5 from LRT/LP mix or pure LP (Mix/LP-PM2.5-P1) was also higher by 14.2-39.9%. This increase was due to higher secondary particle formation represented by the increase in secondary ions (SI) and organic matter in PM2.5-P1 with the largest proportion of 42.17% in PM2.5 from positive matrix factorization (PMF) analysis. A similar increasing trend of Mix/LP-PM2.5 was found in P2 when China was still locked down and Taiwan was under an early control period but the rapidly increasing infected cases were confirmed. The shift of transportation patterns from public to private to avoid virus infection explicated the high correlation of the increasing infected cases with the increasing PM2.5. In contrast, the decreasing trend of LP-PM2.5-P3 was observed in P3 with the PM2.5 biases of ∼45% at all the stations when China was not locked down but Taiwan implemented a semi-lockdown. The contribution of gasoline vehicle sources in PM2.5 was reduced from 20.3% before P3 to 10% in P3 by chemical signatures and source identification using PMF implying the strong impact of strict control measures on vehicle emissions. In summary, PM2.5 concentrations in Northern Taiwan were either increased (P1 and P2) or decreased (P3) during the COVID-19 pandemic depending on control measures, source patterns and meteorological conditions.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Air Pollutants/analysis , Taiwan/epidemiology , Particulate Matter/analysis , COVID-19/epidemiology , Pandemics , Communicable Disease Control , Air Pollution/analysis , Vehicle Emissions/analysis , Environmental Monitoring
12.
Sci Total Environ ; 892: 164527, 2023 Sep 20.
Article in English | MEDLINE | ID: covidwho-2328052

ABSTRACT

To prevent the fast spread of COVID-19, worldwide restrictions have been put in place, leading to a reduction in emissions from most anthropogenic sources. In this study, the impact of COVID-19 lockdowns on elemental (EC) and organic (OC) carbon was explored at a European rural background site combining different approaches: - "Horizontal approach (HA)" consists of comparing concentrations of pollutants measured at 4 m a.g.l. during pre-COVID period (2017-2019) to those measured during COVID period (2020-2021); - "Vertical approach (VA)" consists of inspecting the relationship between OC and EC measured at 4 m and those on top (230 m) of a 250 m-tall tower in Czech Republic. The HA showed that the lockdowns did not systematically result in lower concentrations of both carbonaceous fractions unlike NO2 (25 to 36 % lower) and SO2 (10 to 45 % lower). EC was generally lower during the lockdowns (up to 35 %), likely attributed to the traffic restrictions whereas increased OC (up to 50 %) could be attributed to enhanced emissions from the domestic heating and biomass burning during this stay-home period, but also to the enhanced concentration of SOC (up to 98 %). EC and OC were generally higher at 4 m suggesting a greater influence of local sources near the surface. Interestingly, the VA revealed a significantly enhanced correlation between EC and OC measured at 4 m and those at 230 m (R values up to 0.88 and 0.70 during lockdown 1 and 2, respectively), suggesting a stronger influence of aged and long distance transported aerosols during the lockdowns. This study reveals that lockdowns did not necessarily affect aerosol absolute concentrations but it certainly influenced their vertical distribution. Therefore, analyzing the vertical distribution can allow a better characterization of aerosol properties and sources at rural background sites, especially during a period of significantly reduced human activities.


Subject(s)
Air Pollutants , COVID-19 , Humans , Aged , Air Pollutants/analysis , Particulate Matter/analysis , Environmental Monitoring , Seasons , COVID-19/prevention & control , Communicable Disease Control , Respiratory Aerosols and Droplets , Carbon/analysis , China
13.
Chemosphere ; 335: 139056, 2023 Sep.
Article in English | MEDLINE | ID: covidwho-2328007

ABSTRACT

Carbonaceous aerosols have great adverse impacts on air quality, human health, and climate. However, there is a limited understanding of carbonaceous aerosols in semi-arid areas. The correlation between carbonaceous aerosols and control measures is still unclear owing to the insufficient information regarding meteorological contribution. To reveal the complex relationship between control measures and carbonaceous aerosols, offline and online observations of carbonaceous aerosols were conducted from October 8, 2019 to October 7, 2020 in Hohhot, a semi-arid city. The characteristics and sources of carbonaceous aerosols and impacts of anthropogenic emissions and meteorological conditions were studied. The annual mean concentrations (± standard deviation) of fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) were 42.81 (±40.13), 7.57 (±6.43), and 2.25 (±1.39) µg m-3, respectively. The highest PM2.5 and carbonaceous aerosol concentrations were observed in winter, whereas the lowest was observed in summer. The result indicated that coal combustion for heating had a critical role in air quality degradation in Hohhot. A boost regression tree model was applied to quantify the impacts of anthropogenic emissions and meteorological conditions on carbonaceous aerosols. The results suggested that the anthropogenic contributions of PM2.5, OC, and EC during the COVID-19 lockdown period were 53.0, 15.0, and 2.36 µg m-3, respectively, while the meteorological contributions were 5.38, 2.49, and -0.62 µg m-3, respectively. Secondary formation caused by unfavorable meteorological conditions offset the emission reduction during the COVID-19 lockdown period. Coal combustion (46.4% for OC and 35.4% for EC) and vehicular emissions (32.0% for OC and 50.4% for EC) were the predominant contributors of carbonaceous aerosols. The result indicated that Hohhot must regulate coal use and vehicle emissions to reduce carbonaceous aerosol pollution. This study provides new insights and a comprehensive understanding of the complex relationships between control strategies, meteorological conditions, and air quality.


Subject(s)
Air Pollutants , COVID-19 , Humans , Air Pollutants/analysis , Environmental Monitoring , Communicable Disease Control , Respiratory Aerosols and Droplets , Particulate Matter/analysis , Vehicle Emissions/analysis , Coal/analysis , Seasons , Carbon/analysis , China
14.
Sci Total Environ ; 891: 164402, 2023 Sep 15.
Article in English | MEDLINE | ID: covidwho-2327896

ABSTRACT

Over four thousand portable air cleaners (PACs) with high-efficiency particulate air (HEPA) filters were distributed by Public Health - Seattle & King County to homeless shelters during the COVID-19 pandemic. This study aimed to evaluate the real-world effectiveness of these HEPA PACs in reducing indoor particles and understand the factors that affect their use in homeless shelters. Four rooms across three homeless shelters with varying geographic locations and operating conditions were enrolled in this study. At each shelter, multiple PACs were deployed based on the room volume and PAC's clean air delivery rate rating. The energy consumption of these PACs was measured using energy data loggers at 1-min intervals to allow tracking of their use and fan speed for three two-week sampling rounds, separated by single-week gaps, between February and April 2022. Total optical particle number concentration (OPNC) was measured at 2-min intervals at multiple indoor locations and an outdoor ambient location. The empirical indoor and outdoor total OPNC were compared for each site. Additionally, linear mixed-effects regression models (LMERs) were used to assess the relationship between PAC use time and indoor/outdoor total OPNC ratios (I/OOPNC). Based on the LMER models, a 10 % increase in the hourly, daily, and total time PACs were used significantly reduced I/OOPNC by 0.034 [95 % CI: 0.028, 0.040; p < 0.001], 0.051 [95 % CI: 0.020, 0.078; p < 0.001], and 0.252 [95 % CI: 0.150, 0.328; p < 0.001], respectively, indicating that keeping PACs on resulted in significantly lower I/OOPNC. The survey suggested that keeping PACs on and running was the main challenge when operating them in shelters. These findings suggested that HEPA PACs were an effective short-term strategy to reduce indoor particle levels in community congregate living settings during non-wildfire seasons and the need for formulating practical guidance for using them in such an environment.


Subject(s)
Air Pollutants , Air Pollution, Indoor , COVID-19 , Humans , Particulate Matter/analysis , Air Pollution, Indoor/prevention & control , Air Pollution, Indoor/analysis , Washington , Pandemics , COVID-19/prevention & control , Dust , Air Pollutants/analysis
15.
Sci Total Environ ; 892: 164496, 2023 Sep 20.
Article in English | MEDLINE | ID: covidwho-2327808

ABSTRACT

COVID-19 has notably impacted the world economy and human activities. However, the strict urban lockdown policies implemented in various countries appear to have positively affected pollution and the thermal environment. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and aerosol optical depth (AOD) data were selected, combined with Sentinel-5P images and meteorological elements, to analyze the changes and associations among air pollution, LST, and urban heat islands (UHIs) in three urban agglomerations in mainland China during the COVID-19 lockdown. The results showed that during the COVID-19 lockdown period (February 2020), the levels of the AOD and atmospheric pollutants (fine particles (PM2.5), NO2, and CO) significantly decreased. Among them, PM2.5 and NO2 decreased the most in all urban agglomerations, by >14 %. Notably, the continued improvement in air pollution attributed to China's strict control policies could lead to overestimation of the enhanced air quality during the lockdown. The surface temperature in all three urban agglomerations increased by >1 °C during the lockdown, which was mainly due to climate factors, but we also showed that the lockdown constrained positive LST anomalies. The decrease in the nighttime urban heat island intensity (UHIInight) in the three urban agglomerations was greater than that in the daytime quantity by >25 %. The reduction in surface UHIs at night was mainly due to the reduced human activities and air pollutant emissions. Although strict restrictions on human activities positively affected air pollution and UHIs, these changes were quickly reverted when lockdown policies were relaxed. Moreover, small-scale lockdowns contributed little to environmental improvement. Our results have implications for assessing the environmental benefits of city-scale lockdowns.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , Cities , Hot Temperature , Temperature , East Asian People , Nitrogen Dioxide , Environmental Monitoring , Communicable Disease Control , Respiratory Aerosols and Droplets , Air Pollution/analysis , Air Pollutants/analysis , Particulate Matter/analysis
16.
Environ Pollut ; 331(Pt 2): 121886, 2023 Aug 15.
Article in English | MEDLINE | ID: covidwho-2327767

ABSTRACT

In December 2019, the New Crown Pneumonia (the COVID-19) outbroke around the globe, and China imposed a nationwide lockdown starting as early as January 23, 2020. This decision has significantly impacted China's air quality, especially the sharp decrease in PM2.5 (aerodynamic equivalent diameter of particulate matter less than or equal to 2.5 µm) pollution. Hunan Province is located in the central and eastern part of China, with a "horseshoe basin" topography. The reduction rate of PM2.5 concentrations in Hunan province during the COVID-19 (24.8%) was significantly higher than the national average (20.3%). Through the analysis of the changing character and pollution sources of haze pollution events in Hunan Province, more scientific countermeasures can be provided for the government. We use the Weather Research and Forecasting with Chemistry (WRF-Chem, V4.0) model to predict and simulate the PM2.5 concentrations under seven scenarios before the lockdown (2020.1.1-2020.1.22) and during the lockdown (2020.1.23-2020.2.14). Then, the PM2.5 concentrations under different conditions is compared to differentiate the contribution of meteorological conditions and local human activities to PM2.5 pollution. The results indicate the most important cause of PM2.5 pollution reduction is anthropogenic emissions from the residential sector, followed by the industrial sector, while the influence of meteorological factors contribute only 0.5% to PM2.5. The explanation is that emission reductions from the residential sector contribute the most to the reduction of seven primary contaminants. Finally, we trace the source and transport path of the air mass in Hunan Province through the Concentration Weight Trajectory Analysis (CWT). We found that the external input of PM2.5 in Hunan Province is mainly from the air mass transported from the northeast, accounting for 28.6%-30.0%. To improve future air quality, there is an urgent need to burn clean energy, improve the industrial structure, rationalize energy use, and strengthen cross-regional air pollution synergy control.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Air Pollutants/analysis , Communicable Disease Control , Air Pollution/analysis , Particulate Matter/analysis , China/epidemiology
17.
Environ Res ; 228: 115835, 2023 07 01.
Article in English | MEDLINE | ID: covidwho-2322230

ABSTRACT

Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (-34% to -55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (-1 to -4% change in annual means of PM2.5 and PM10), 3) heterogeneous responses in ground-level ozone concentrations (-2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO2-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , Communicable Disease Control , Air Pollution/analysis , Air Pollutants/toxicity , Air Pollutants/analysis , Particulate Matter/analysis , Environmental Monitoring/methods
18.
Stud Health Technol Inform ; 302: 901-902, 2023 May 18.
Article in English | MEDLINE | ID: covidwho-2326086

ABSTRACT

It has been reported that the severity and lethality of Covid-19 are associated with coexisting underlying diseases (hypertension, diabetes, etc.) and cardiovascular diseases (coronary artery disease, atrial fibrillation, heart failure, etc.) that increase with age, but environmental exposure such as air pollutants may also be a risk factor for mortality. In this study, we investigated patient characteristics at admission and prognostic factors of air pollutants in Covid-19 patients using a machine learning (random forest) prediction model. Age, Photochemical oxidant concentration one month prior to admission, and level of care required were shown to be highly important for the characteristics, while the cumulative concentrations of air pollutants SPM, NO2, and PM2.5 one year prior to admission were the most important characteristics for patients aged 65 years and older, suggesting the influence of long-term exposure.


Subject(s)
Air Pollutants , Air Pollution , Atrial Fibrillation , COVID-19 , Humans , Infant , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/analysis , Prognosis , Environmental Exposure/adverse effects , Environmental Exposure/analysis
19.
Epidemiol Prev ; 47(3): 125-136, 2023.
Article in Italian | MEDLINE | ID: covidwho-2318464

ABSTRACT

BACKGROUND: after the outbreak of the SARS-CoV-2 pandemic in 2020, several waves of pandemic cases have occurred in Italy. The role of air pollution has been hypothesized and investigated in several studies. However, to date, the role of chronic exposure to air pollutants in increasing incidence of SARS-CoV-2 infections is still debated. OBJECTIVES: to investigate the association between long-term exposure to air pollutants and the incidence of SARS-CoV-2 infections in Italy. DESIGN: a satellite-based air pollution exposure model with 1-km2 spatial resolution for entire Italy was applied and 2016-2019 mean population-weighted concentrations of particulate matter < 10 micron (PM10), PM <2.5 micron (PM2.5), and nitrogen dioxide (NO2) was calculated to each municipality as estimates of chronic exposures. A principal component analysis (PCA) approach was applied to 50+ area-level covariates (geography and topography, population density, mobility, population health, socioeconomic status) to account for the major determinants of the spatial distribution of incidence rates of SARS-CoV-2 infection. Detailed information was further used on intra- and inter-municipal mobility during the pandemic period. Finally, a mixed longitudinal ecological design with the study units consisting of individual municipalities in Italy was applied. Generalized negative binomial models controlling for age, gender, province, month, PCA variables, and population density were estimated. SETTING AND PARTICIPANTS: individual records of diagnosed SARS-2-CoV-2 infections in Italy from February 2020 to June 2021 reported to the Italian Integrated Surveillance of COVID-19 were used. MAIN OUTCOME MEASURES: percentage increases in incidence rate (%IR) and corresponding 95% confidence intervals (95% CI) per unit increase in exposure. RESULTS: 3,995,202 COVID-19 cases in 7,800 municipalities were analysed (total population: 59,589,357 inhabitants). It was found that long-term exposure to PM2.5, PM10, and NO2 was significantly associated with the incidence rates of SARS-CoV-2 infection. In particular, incidence of COVID-19 increased by 0.3% (95%CI 0.1%-0.4%), 0.3% (0.2%-0.4%), and 0.9% (0.8%-1.0%) per 1 µg/m3 increment in PM2.5, PM10 and NO2, respectively. Associations were higher among elderly subjects and during the second pandemic wave (September 2020-December 2020). Several sensitivity analyses confirmed the main results. The results for NO2 were especially robust to multiple sensitivity analyses. CONCLUSIONS: evidence of an association between long-term exposure to ambient air pollutants and the incidence of SARS-CoV-2 infections in Italy was found.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Aged , Incidence , Nitrogen Dioxide/adverse effects , Environmental Exposure/adverse effects , Environmental Exposure/analysis , COVID-19/epidemiology , SARS-CoV-2 , Italy/epidemiology , Air Pollution/adverse effects , Air Pollution/analysis , Air Pollutants/adverse effects , Air Pollutants/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis
20.
Environ Sci Pollut Res Int ; 30(26): 68591-68608, 2023 Jun.
Article in English | MEDLINE | ID: covidwho-2318324

ABSTRACT

Burning of fossil fuels in the form of coal or gasoline in thermal power plants, industries, and automobiles is a prime source of nitrogen dioxide (NO2), a major air pollutant causing health problems. In this paper, spatio-temporal unevenness of NO2 concentrations via both spaceborne Sentinel-5P and ground-based in situ data have been studied for the period of 2017-2021. Annual and seasonal distribution of TROPOMI-NO2 depict consistency over the Jharkhand region, highlighting six hotspot regions. As compared to 2019, a notable dip of 11% in the spatial annual average TROPOMI-NO2 was achieved in 2020, which were elevated again by 22% in 2021 as the lockdown gradually goes out of the picture. Among eight ground-monitoring stations, Tata and Golmuri stations always displayed a higher level of TROPOMI-NO2 ranges up to 15.2 ×1015molecules.cm-2 and 16.9 ×1015molecules.cm-2 respectively, as being located in the highly industrialised district of Jamshedpur. A big percentage reduction of up to 30% in TROPOMI-NO2 has been reported in Jharia and Bastacola stations in Dhanbad in the lockdown phase of 2020 compared to 2019. Good agreement between TROPOMI-NO2 and surface-NO2 has been achieved with R = 0.8 and R = 0.71 during winter and post-monsoon respectively. Among four meteorological parameters, TROPOMI-NO2 was majorly found to be influenced by precipitation, having R = 0.6-0.8 for almost all stations. More advanced satellite algorithms and ground-based data may be used to estimate NO2 in places where monitoring facilities are limited and thus can help in air pollution control policy.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Air Pollution/analysis , Nitrogen Dioxide/analysis , Environmental Monitoring , Communicable Disease Control , Air Pollutants/analysis
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