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1.
Sensors (Basel) ; 21(12)2021 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-34204182

RESUMO

Low-cost optical particle counters effectively measure particulate matter (PM) mass concentrations once calibrated. Sensor calibration can be established by deriving a linear regression model by performing side-by-side measurements with a reference instrument. However, calibration differences between environmental and occupational settings have not been demonstrated. This study evaluated four commercially available, low-cost PM sensors (OPC-N3, SPS30, AirBeam2, and PMS A003) in both settings. The mass concentrations of three aerosols (salt, Arizona road dust, and Poly-alpha-olefin-4 oil) were measured and compared with a reference instrument. OPC-N3 and SPS30 were highly correlated (r = 0.99) with the reference instrument for all aerosol types in environmental settings. In occupational settings, SPS30, AirBeam2, and PMS A003 exhibited high correlation (>0.96), but the OPC-N3 correlation varied (r = 0.88-1.00). Response significantly (p < 0.001) varied between environmental and occupational settings for most particle sizes and aerosol types. Biases varied by particle size and aerosol type. SPS30 and OPC-N3 exhibited low bias for environmental settings, but all of the sensors showed a high bias for occupational settings. For intra-instrumental precision, SPS30 exhibited high precision for salt for both settings compared to the other low-cost sensors and aerosol types. These findings suggest that SPS30 and OPC-N3 can provide a reasonable estimate of PM mass concentrations if calibrated differently for environmental and occupational settings using site-specific calibration factors.


Assuntos
Poluentes Atmosféricos , Exposição Ocupacional , Aerossóis , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Laboratórios , Exposição Ocupacional/análise , Tamanho da Partícula , Material Particulado/análise
2.
Sensors (Basel) ; 21(12)2021 Jun 19.
Artigo em Inglês | MEDLINE | ID: mdl-34205429

RESUMO

We designed and built a network of monitors for ambient air pollution equipped with low-cost gas sensors to be used to supplement regulatory agency monitoring for exposure assessment within a large epidemiological study. This paper describes the development of a series of hourly and daily field calibration models for Alphasense sensors for carbon monoxide (CO; CO-B4), nitric oxide (NO; NO-B4), nitrogen dioxide (NO2; NO2-B43F), and oxidizing gases (OX-B431)-which refers to ozone (O3) and NO2. The monitor network was deployed in the Puget Sound region of Washington, USA, from May 2017 to March 2019. Monitors were rotated throughout the region, including at two Puget Sound Clean Air Agency monitoring sites for calibration purposes, and over 100 residences, including the homes of epidemiological study participants, with the goal of improving long-term pollutant exposure predictions at participant locations. Calibration models improved when accounting for individual sensor performance, ambient temperature and humidity, and concentrations of co-pollutants as measured by other low-cost sensors in the monitors. Predictions from the final daily models for CO and NO performed the best considering agreement with regulatory monitors in cross-validated root-mean-square error (RMSE) and R2 measures (CO: RMSE = 18 ppb, R2 = 0.97; NO: RMSE = 2 ppb, R2 = 0.97). Performance measures for NO2 and O3 were somewhat lower (NO2: RMSE = 3 ppb, R2 = 0.79; O3: RMSE = 4 ppb, R2 = 0.81). These high levels of calibration performance add confidence that low-cost sensor measurements collected at the homes of epidemiological study participants can be integrated into spatiotemporal models of pollutant concentrations, improving exposure assessment for epidemiological inference.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Calibragem , Monóxido de Carbono/análise , Monitoramento Ambiental , Estudos Epidemiológicos , Humanos , Óxido Nítrico/análise , Dióxido de Nitrogênio/análise , Ozônio/análise , Material Particulado/análise
3.
Sensors (Basel) ; 21(12)2021 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-34208309

RESUMO

Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility. In this paper, we present AirKit, which was developed as an integrated and open source "social IoT technology". AirKit enables a comprehensive approach to citizen-sensing air quality through several integrated components: (1) the Dustbox 2.0, a particulate matter sensor; (2) Airsift, a data analysis platform; (3) a reliable and automatic remote firmware update system; (4) a "Data Stories" method and tool for communicating citizen data; and (5) an AirKit logbook that provides a guide for designing and running air quality projects, along with instructions for building and using AirKit components. Developed as a social technology toolkit to foster open processes of research co-creation and environmental action, Airkit has the potential to generate expanded engagements with IoT and air quality by improving the accuracy, legibility and use of sensors, data analysis and data communication.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Monitoramento Ambiental , Humanos , Material Particulado/análise , Reprodutibilidade dos Testes
4.
Huan Jing Ke Xue ; 42(7): 3099-3106, 2021 Jul 08.
Artigo em Chinês | MEDLINE | ID: mdl-34212635

RESUMO

This study analyzed the impacts of meteorological conditions and changes in air pollutant emissions on PM2.5 across the country during the first quarter of 2020 based on the WRF-CMAQ model. Results showed that the variations in meteorological conditions led to a national PM2.5 concentration decreased of 1.7% from 2020-01 to 2020-03, whereas it increased by 1.6% in January and decreased by 1.3% and 7.9% in February and March, respectively. The reduction of pollutants emissions led to a decrease of 14.1% in national PM2.5 concentration during the first quarter of 2020 and a decrease of 4.0%, 25.7%, and 15.0% in January, February, and March, respectively. Compared to the same period last year, the PM2.5 concentration measured in Wuhan City decreased more than in the entire country. This was caused by improved meteorological conditions and a higher reduction of pollutant emissions in Wuhan City. PM2.5 in Beijing increased annually before the epidemic outbreak and during the strict control period, mainly due to unfavorable meteorological conditions. However, the decrease in PM2.5 in Beijing compared to March 2019 was closely related to the substantial reduction of emissions. The measured PM2.5 in the "2+26" cities, the Fenwei Plain and the Yangtze River Delta (YRD) decreased during the first quarter of 2020, with the largest drop occurring in the Yangtze River Delta due to higher YRD emissions reductions. The meteorological conditions of "2+26" cities and Fenwei Plain were unfavorable before the epidemic outbreak and greatly improved during the strict control period, whereas the Yangtze River Delta had the most favorable meteorological conditions in March. The decrease in PM2.5 concentration caused by the reduction of pollutant emissions in the three key areas was highest during the strict control period.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Epidemias , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Pequim , China , Cidades , Monitoramento Ambiental , Meteorologia , Material Particulado/análise
5.
Huan Jing Ke Xue ; 42(7): 3107-3117, 2021 Jul 08.
Artigo em Chinês | MEDLINE | ID: mdl-34212636

RESUMO

Spatial features of PM2.5 concentration in the Yangtze River Delta in 2016 were analyzed using remote sensing data. Selecting factors among meteorology, topography, vegetation, and emission list of air pollutants, factors and their interaction effects on the spatial distribution of PM2.5 concentration were studied based on GAM, with an evaluation unit of 0.25°×0.25° for the grid. It showed that:① With a more significant difference between the north and south, PM2.5 concentration was generally higher in the north and west but lower in the south and east. In the southern part of the delta, the concentration was mostly lower than 35 µg·m-3, with noncompliance of the PM2.5 concentration scattered in urban areas like islands. Meanwhile, PM2.5 concentration is generally over 35 µg·m-3, and the pollution appeared like sheets. ② Besides, PM2.5 concentration showed an apparent positive spatial autocorrelation with "High-High" PM2.5 agglomeration areas in the north of the delta and "Low-Low" PM2.5 agglomeration areas in the south. ③ Based on GAM, hypsography, temperature, and precipitation negatively affected PM2.5 concentration, whereas pollutant emissions positively affected it. The effect of wind was minor when its speed <2.5 m·s-1, and more negatively significant when its speed ≥ 2.5 m·s-1. Hypsography, temperature, and precipitation were higher in the southern part of the delta, but they were lower in the northern part, leading to a higher PM2.5 concentration in the northern parts and lower in the southern parts. A higher wind speed in the east and lower in the west also led to a concentration difference between them. ④ All factors had passed a significant pair interaction test, except for hypsography and PM2.5 emission, and they all showed a significant interaction effect on the distribution of PM2.5 in the Yangtze River Delta.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , China , Monitoramento Ambiental , Material Particulado/análise , Rios
6.
Huan Jing Ke Xue ; 42(7): 3136-3146, 2021 Jul 08.
Artigo em Chinês | MEDLINE | ID: mdl-34212639

RESUMO

The spread of atmospheric pollutants in the Sichuan Basin is difficult because of its unique topography, static wind, high humidity, and other meteorological conditions. Owing to the acceleration of urbanization and industrialization, PM2.5 pollution in the region is becoming increasingly severe, and the Sichuan Basin has become one of the key areas of national air pollution prevention and control. In this study, based on the remote sensing inversion product of PM2.5 concentration, spatial autocorrelation and gray correlation analyses are used to evaluate the spatial and temporal distribution characteristics and influencing factors of PM2.5 concentration in the Sichuan Basin. The results show that PM2.5 concentration has significant spatial aggregation; the high-high aggregation types are concentrated, low-low aggregation types are more dispersed, and coniferous forest has a significantly higher inhibitory effect on the absorption of PM2.5 than the shrub, grassland, and other vegetation types. The main meteorological factors affecting PM2.5 concentration in the Sichuan Basin are wind speed and temperature; population density and economic scale are the main human-activity factors affecting PM2.5 concentration in the Sichuan Basin, and the change in the industrial structure and scale also has a certain influence on the PM2.5 concentration.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , China , Monitoramento Ambiental , Análise Fatorial , Humanos , Material Particulado/análise , Estações do Ano
7.
Sensors (Basel) ; 21(12)2021 Jun 08.
Artigo em Inglês | MEDLINE | ID: mdl-34201377

RESUMO

Over the last decade, manufacturers have come forth with cost-effective sensors for measuring ambient and indoor particulate matter concentration. What these sensors make up for in cost efficiency, they lack in reliability of the measured data due to their sensitivities to temperature and relative humidity. These weaknesses are especially evident when it comes to portable or mobile measurement setups. In recent years many studies have been conducted to assess the possibilities and limitations of these sensors, however mostly restricted to stationary measurements. This study reviews the published literature until 2020 on cost-effective sensors, summarizes the recommendations of experts in the field based on their experiences, and outlines the quantile-mapping methodology to calibrate low-cost sensors in mobile applications. Compared to the commonly used linear regression method, quantile mapping retains the spatial characteristics of the measurements, although a common correction factor cannot be determined. We conclude that quantile mapping can be a useful calibration methodology for mobile measurements given a well-elaborated measurement plan assures providing the necessary data.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Calibragem , Monitoramento Ambiental , Material Particulado/análise , Reprodutibilidade dos Testes
8.
Artigo em Inglês | MEDLINE | ID: mdl-34203886

RESUMO

Air pollution is one of the major environmental problems that endanger human health. The COVID-19 pandemic provided an excellent opportunity to investigate the possible methods to improve Beijing's air quality meanwhile considering Beijing's economic impact. We used the TVP-VAR model to analyze the dynamic relationship among the pandemic, economy and air quality based on the daily data from 1 January to 30 August 2020. The result shows that the COVID-19 pandemic indeed had a positive effect on air governance which was good for human health, while doing business as usual would gradually weaken this effect. It shows that the Chinese authority's production restriction effectively deals with air pollution in a short period of time since the pandemic is just like a quasi-experiment that suddenly suspended all the companies. However, as the limitation stops, the improvement decreases. It is not sustainable. In addition, a partial quarantine also has a positive impact on air quality, which means a partial limitation was also helpful in improving air quality and also played an important role in protecting people's health. Second, the control measures really hurt Beijing's economy. However, the partial quarantine had fewer adverse effects on the economy than the lockdown. It is supposed to be a reference for air governance and pandemic control. Third, the more the lag periods were, the smaller their impact. Thus, restrictions on production can only be used in emergencies, such as some international meetings, while it is hard to improve the air quality and create a healthy and comfortable living environment only by limitation in the long-term.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Poluição do Ar/prevenção & controle , Pequim/epidemiologia , Cidades , Controle de Doenças Transmissíveis , Monitoramento Ambiental , Humanos , Pandemias/prevenção & controle , Material Particulado/análise , SARS-CoV-2
9.
Artigo em Inglês | MEDLINE | ID: mdl-34206915

RESUMO

The impact of Coronavirus Disease 2019 (COVID-19) on cause-specific mortality has been investigated on a global scale. However, less is known about the excess all-cause mortality and air pollution-human activity responses. This study estimated the weekly excess all-cause mortality during COVID-19 and evaluated the impacts of air pollution and human activities on mortality variations during the 10th to 52nd weeks of 2020 among sixteen countries. A SARIMA model was adopted to estimate the mortality benchmark based on short-term mortality during 2015-2019 and calculate excess mortality. A quasi-likelihood Poisson-based GAM model was further applied for air pollution/human activity response evaluation, namely ground-level NO2 and PM2.5 and the visit frequencies of parks and workplaces. The findings showed that, compared with COVID-19 mortality (i.e., cause-specific mortality), excess all-cause mortality changed from -26.52% to 373.60% during the 10th to 52nd weeks across the sixteen countries examined, revealing higher excess all-cause mortality than COVID-19 mortality in most countries. For the impact of air pollution and human activities, the average country-level relative risk showed that one unit increase in weekly NO2, PM2.5, park visits and workplace visits was associated with approximately 1.54% increase and 0.19%, 0.23%, and 0.23% decrease in excess all-cause mortality, respectively. Moreover, compared with the impact on COVID-19 mortality, the relative risks of weekly NO2 and PM2.5 were lower, and the relative risks of weekly park and workplace visits were higher for excess all-cause mortality. These results suggest that the estimation based on excess all-cause mortality reduced the potential impact of air pollution and enhanced the influence of human activities compared with the estimation based on COVID-19 mortality.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Epidemias , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/toxicidade , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Exposição Ambiental/análise , Atividades Humanas , Humanos , Mortalidade , Material Particulado/análise , Material Particulado/toxicidade , SARS-CoV-2
10.
Artigo em Inglês | MEDLINE | ID: mdl-34203568

RESUMO

Although cancer is traditionally considered a genetic disease, the epigenetic abnormalities, including DNA hypermethylation, histone deacetylation, and/or microRNA dysregulation, have been demonstrated as a hallmark of cancer. Compared with gene mutations, aberrant epigenetic changes occur more frequently, and cellular epigenome is more susceptible to change by environmental factors. Excess cancer risks are positively associated with exposure to occupational and environmental chemical carcinogens, including those from gasoline combustion exhausted in vehicles. Of note, previous studies proposed particulate matter index (PMI) as a measure for gasoline sooting tendency, and showed that, compared with the other molecules in gasoline, 1,2,4-Trimethylbenzene, 2-methylnaphthalene and toluene significantly contribute to PMI of the gasoline blends. Mechanistically, both epigenome and genome are important in carcinogenicity, and the genotoxicity of chemical agents has been thoroughly studied. However, less effort has been put into studying the epigenotoxicity. Moreover, as the blending of ethanol into gasoline substitutes for carcinogens, like benzene, toluene, xylene, butadiene, and polycyclic aromatic hydrocarbons, etc., a reduction of secondary aromatics has been achieved in the atmosphere. This may lead to diminished cancer initiation and progression through altered cellular epigenetic landscape. The present review summarizes the most important findings in the literature on the association between exposures to carcinogens from gasoline combustion, cancer epigenetics and the potential epigenetic impacts of biofuels.


Assuntos
Poluentes Atmosféricos , Neoplasias , Poluentes Atmosféricos/análise , Etanol/toxicidade , Gasolina/análise , Gasolina/toxicidade , Neoplasias/induzido quimicamente , Neoplasias/epidemiologia , Material Particulado/análise , Tolueno , Emissões de Veículos/análise
11.
Artigo em Inglês | MEDLINE | ID: mdl-34204140

RESUMO

In this research, we take a multivariate, multi-method approach to predicting the incidence of lung cancer in the United States. We obtain public health and ambient emission data from multiple sources in 2000-2013 to model lung cancer in the period 2013-2017. We compare several models using four sources of predictor variables: adult smoking, state, environmental quality index, and ambient emissions. The environmental quality index variables pertain to macro-level domains: air, land, water, socio-demographic, and built environment. The ambient emissions consist of Cyanide compounds, Carbon Monoxide, Carbon Disulfide, Diesel Exhaust, Nitrogen Dioxide, Tropospheric Ozone, Coarse Particulate Matter, Fine Particulate Matter, and Sulfur Dioxide. We compare various models and find that the best regression model has variance explained of 62 percent whereas the best machine learning model has 64 percent variance explained with 10% less error. The most hazardous ambient emissions are Coarse Particulate Matter, Fine Particulate Matter, Sulfur Dioxide, Carbon Monoxide, and Tropospheric Ozone. These ambient emissions could be curtailed to improve air quality, thus reducing the incidence of lung cancer. We interpret and discuss the implications of the model results, including the tradeoff between transparency and accuracy. We also review limitations of and directions for the current models in order to extend and refine them.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Neoplasias Pulmonares , Adulto , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Monitoramento Ambiental , Humanos , Neoplasias Pulmonares/epidemiologia , Material Particulado/análise , Saúde Pública , Estados Unidos/epidemiologia , Emissões de Veículos/análise , Emissões de Veículos/toxicidade
12.
Artigo em Inglês | MEDLINE | ID: mdl-34205027

RESUMO

Air pollution, especially fine particulate matter (PM2.5), is a major environmental risk factor for human health in Europe. Monitoring of air quality takes place using expensive reference stations. Low-cost sensors are a promising addition to this official monitoring network as they add spatial and temporal resolution at low cost. Moreover, low-cost sensors might allow for better characterization of personal exposure to PM2.5. In this study, we use 500 dust (PM2.5) sensors mounted on bicycles to estimate typical PM2.5 levels to which cyclists are exposed in the province of Utrecht, the Netherlands, in the year 2020. We use co-located sensors at reference stations to calibrate and validate the mobile sensor data. We estimate that the average exposure to traffic related PM2.5, on top of background concentrations, is approximately 2 µg/m3. Our results suggest that cyclists close to major roads have a small, but consistently higher exposure to PM2.5 compared to routes with less traffic. The results allow for a detailed spatial representation of PM2.5 concentrations and show that choosing a different cycle route might lead to a lower exposure to PM2.5. Finally, we conclude that the use of mobile, low-cost sensors is a promising method to estimate exposure to air pollution.


Assuntos
Poluentes Atmosféricos , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Europa (Continente) , Humanos , Países Baixos , Material Particulado/análise
13.
Environ Monit Assess ; 193(8): 486, 2021 Jul 10.
Artigo em Inglês | MEDLINE | ID: mdl-34245364

RESUMO

Particulate matter (PM) is the primary air pollutant in northern China. The PM2.5/PM10 ratio has been used increasingly as an indicator to reflect anthropogenic PM pollution, but its advantages compared with individual PM2.5 or PM10 concentrations have not been proven sufficiently by experimental data. By dividing Hebei Province (China) into seven natural ecological regions, this study investigated the spatial characteristics of the PM2.5/PM10 ratio and its relationships with PM2.5, PM10, economic density, and wind speed. Results showed that the PM2.5/PM10 ratio decreased from east to west and from south to north, with an annual average value in 2019 of 0.439-0.559. The characteristics of the spatial variation of the PM2.5/PM10 ratio were different to those of either PM2.5 or PM10 concentration, indicating that PM pollution reflected by the PM2.5/PM10 ratio is not entirely consistent with that by PM2.5 and PM10 concentrations. In comparison with PM2.5 or PM10 concentration, the PM2.5/PM10 ratio had higher (lower) correlation with economic density (wind speed), indicating that the PM2.5/PM10 ratio is a better indicator used to reflect the intensity of anthropogenic emissions of PM pollutants. According to the characteristics of the spatial variations of the PM2.5/PM10 ratio and the PM2.5 and PM10 concentrations, the seven ecological regions of Hebei Province were categorized into four different types of atmospheric PM pollution: "three low regions," "three high regions," "one high and two low regions," and "one low and two high regions." This reflects the comprehensive effect of the intensity of anthropogenic PM emissions and the atmospheric diffusion conditions.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , China , Monitoramento Ambiental , Material Particulado/análise , Estações do Ano
14.
Artigo em Inglês | MEDLINE | ID: covidwho-1270059

RESUMO

Air pollution is one of the major environmental problems that endanger human health. The COVID-19 pandemic provided an excellent opportunity to investigate the possible methods to improve Beijing's air quality meanwhile considering Beijing's economic impact. We used the TVP-VAR model to analyze the dynamic relationship among the pandemic, economy and air quality based on the daily data from 1 January to 30 August 2020. The result shows that the COVID-19 pandemic indeed had a positive effect on air governance which was good for human health, while doing business as usual would gradually weaken this effect. It shows that the Chinese authority's production restriction effectively deals with air pollution in a short period of time since the pandemic is just like a quasi-experiment that suddenly suspended all the companies. However, as the limitation stops, the improvement decreases. It is not sustainable. In addition, a partial quarantine also has a positive impact on air quality, which means a partial limitation was also helpful in improving air quality and also played an important role in protecting people's health. Second, the control measures really hurt Beijing's economy. However, the partial quarantine had fewer adverse effects on the economy than the lockdown. It is supposed to be a reference for air governance and pandemic control. Third, the more the lag periods were, the smaller their impact. Thus, restrictions on production can only be used in emergencies, such as some international meetings, while it is hard to improve the air quality and create a healthy and comfortable living environment only by limitation in the long-term.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Poluição do Ar/prevenção & controle , Pequim/epidemiologia , Cidades , Controle de Doenças Transmissíveis , Monitoramento Ambiental , Humanos , Pandemias/prevenção & controle , Material Particulado/análise , SARS-CoV-2
15.
Artigo em Inglês | MEDLINE | ID: covidwho-1264456

RESUMO

Long-term PM2.5 exposure might predispose populations to SARS-CoV-2 infection and intervention policies might interrupt SARS-CoV-2 transmission and reduce the risk of COVID-19. We conducted an ecologic study across the United States, using county-level COVID-19 incidence up to 12 September 2020, to represent the first two surges in the U.S., annual average of PM2.5 between 2000 and 2016 and state-level facemask mandates and stay home orders. We fit negative binomial models to assess COVID-19 incidence in association with PM2.5 and policies. Stratified analyses by facemask policy and stay home policy were also performed. Each 1-µg/m3 increase in annual average concentration of PM2.5 exposure was associated with 7.56% (95% CI: 3.76%, 11.49%) increase in COVID-19 risk. Facemask mandates and stay home policies were inversely associated with COVID-19 with adjusted RRs of 0.8466 (95% CI: 0.7598, 0.9432) and 0.9193 (95% CI: 0.8021, 1.0537), respectively. The associations between PM2.5 and COVID-19 were consistent among counties with or without preventive policies. Our study added evidence that long-term PM2.5 exposure increased the risk of COVID-19 during each surge and cumulatively as of 12 September 2020, in the United States. Although both state-level implementation of facemask mandates and stay home orders were effective in preventing the spread of COVID-19, no clear effect modification was observed regarding long-term exposure to PM2.5 on the risk of COVID-19.


Assuntos
COVID-19 , Humanos , Incidência , Máscaras , Material Particulado/análise , SARS-CoV-2 , Estados Unidos/epidemiologia
16.
J Environ Sci (China) ; 106: 26-38, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: covidwho-1046321

RESUMO

To investigate the air quality change during the COVID-19 pandemic, we analyzed spatiotemporal variations of six criteria pollutants in nine typical urban agglomerations in China using ground-based data and examined meteorological influences through correlation analysis and backward trajectory analysis under different responses. Concentrations of PM2.5, PM10, NO2, SO2 and CO in urban agglomerations respectively decreased by 18%-45% (30%-62%), 17%-53% (22%-39%), 47%-64% (14%-41%), 9%-34% (0%-53%) and 16%-52% (23%-56%) during Lockdown (Post-lockdown) period relative to Pre-lockdown period. PM2.5 pollution events occurred during Lockdown in Beijing-Tianjin-Hebe (BTH) and Middle and South Liaoning (MSL), and daily O3 concentration rose to grade Ⅱ standard in Post-lockdown period. Distinct from the nationwide slump of NO2 during Lockdown period, a rebound (∼40%) in Post-lockdown period was observed in Cheng-Yu (CY), Yangtze River Middle-Reach (YRMR), Yangtze River Delta (YRD) and Pearl River Delta (PRD). With slightly higher wind speed compared with 2019, the reduction of PM2.5 (51%-62%) in Post-lockdown period is more than 2019 (15%-46%) in HC (Harbin-Changchun), MSL, BTH, CP (Central Plain) and SP (Shandong-Peninsula), suggesting lockdown measures are effective to PM2.5 alleviation. Although O3 concentrations generally increased during the lockdown, its increment rate declined compared with 2019 under similar sunlight duration and temperature. Additionally, unlike HC, MSL and BTH, which suffered from additional (> 30%) air masses from surrounding areas after the lockdown, the polluted air masses reaching YRD and PRD mostly originated from the long-distance transport, highlighting the importance of joint regional governance.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Pequim , China , Cidades , Controle de Doenças Transmissíveis , Monitoramento Ambiental , Humanos , Pandemias , Material Particulado/análise , SARS-CoV-2
17.
Artigo em Inglês | MEDLINE | ID: covidwho-1285375

RESUMO

INTRODUCTION: Responding to the coronavirus pandemic, Greece implemented the largest quarantine in its history. No data exist regarding its impact on PM2.5 pollution. We aimed to assess PM2.5 levels before, during, and after lockdown (7 March 2020-16 May 2020) in Volos, one of Greece's most polluted industrialized cities, and compare PM2.5 levels with those obtained during the same period last year. Meteorological conditions were examined as confounders. METHODS: The study period was discriminated into three phases (pre-lockdown: 7 March-9 March, lockdown: 10 March-4 May, and post-lockdown period: 5 May-16 May). A wireless sensors network was used to collect PM2.5, temperature, relative humidity, rainfall, and wind speed data every 2 s. RESULTS: The lockdown resulted in a significant drop of PM2.5 by 37.4% in 2020, compared to 2019 levels. The mean daily concentrations of PM2.5 exceeded the WHO's guideline value for 24-h mean levels of PM2.5 35% of the study period. During the strictest lockdown (23 March to 4 May), the mean daily PM2.5 levels exceeded the standard 41% of the time. The transition from the pre-lockdown period into lockdown or post-lockdown periods was associated with lower PM2.5 concentrations. CONCLUSIONS: A reduction in the mean daily PM2.5 concentration was found compared to 2019. Lockdown was not enough to avoid severe exceedances of air pollution in Volos.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Cidades , Controle de Doenças Transmissíveis , Monitoramento Ambiental , Grécia/epidemiologia , Humanos , Pandemias , Material Particulado/análise , SARS-CoV-2
18.
Environ Pollut ; 284: 117483, 2021 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-34261212

RESUMO

Exposure to ambient air pollution is associated with maternal and child health. Some air pollutants exhibit similar behavior in the atmosphere, and some interact with each other; thus, comprehensive assessments of individual air pollutants are required. In this study, we developed national-scale monthly models for six air pollutants (NO, NO2, SO2, O3, PM2.5, and suspended particulate matter (SPM)) to obtain accurate estimates of pollutant concentrations at 1 km × 1 km resolution from 2010 through 2015 for application to the Japan Environment and Children's Study (JECS), which is a large-scale birth cohort study. We developed our models in the land use regression framework using random forests in conjunction with kriging. We evaluated the model performance via 5-fold location-based cross-validation. We successfully predicted monthly NO (r2 = 0.65), NO2 (r2 = 0.84), O3 (r2 = 0.86), PM2.5 (r2 = 0.79), and SPM (r2 = 0.64) concentrations. For SO2, a satisfactory model could not be developed (r2 = 0.45) because of the low SO2 concentrations in Japan. The performance of our models is comparable to those reported in previous studies at similar temporal and spatial scales. The model predictions in conjunction with the JECS will reveal the critical windows of prenatal and infancy exposure to ambient air pollutants, thus contributing to the development of environmental policies on air pollution.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Criança , Estudos de Coortes , Monitoramento Ambiental , Humanos , Japão , Material Particulado/análise
19.
Artigo em Inglês | MEDLINE | ID: mdl-34201596

RESUMO

INTRODUCTION: Responding to the coronavirus pandemic, Greece implemented the largest quarantine in its history. No data exist regarding its impact on PM2.5 pollution. We aimed to assess PM2.5 levels before, during, and after lockdown (7 March 2020-16 May 2020) in Volos, one of Greece's most polluted industrialized cities, and compare PM2.5 levels with those obtained during the same period last year. Meteorological conditions were examined as confounders. METHODS: The study period was discriminated into three phases (pre-lockdown: 7 March-9 March, lockdown: 10 March-4 May, and post-lockdown period: 5 May-16 May). A wireless sensors network was used to collect PM2.5, temperature, relative humidity, rainfall, and wind speed data every 2 s. RESULTS: The lockdown resulted in a significant drop of PM2.5 by 37.4% in 2020, compared to 2019 levels. The mean daily concentrations of PM2.5 exceeded the WHO's guideline value for 24-h mean levels of PM2.5 35% of the study period. During the strictest lockdown (23 March to 4 May), the mean daily PM2.5 levels exceeded the standard 41% of the time. The transition from the pre-lockdown period into lockdown or post-lockdown periods was associated with lower PM2.5 concentrations. CONCLUSIONS: A reduction in the mean daily PM2.5 concentration was found compared to 2019. Lockdown was not enough to avoid severe exceedances of air pollution in Volos.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Cidades , Controle de Doenças Transmissíveis , Monitoramento Ambiental , Grécia/epidemiologia , Humanos , Pandemias , Material Particulado/análise , SARS-CoV-2
20.
Huan Jing Ke Xue ; 42(7): 3099-3106, 2021 Jul 08.
Artigo em Chinês | MEDLINE | ID: covidwho-1296234

RESUMO

This study analyzed the impacts of meteorological conditions and changes in air pollutant emissions on PM2.5 across the country during the first quarter of 2020 based on the WRF-CMAQ model. Results showed that the variations in meteorological conditions led to a national PM2.5 concentration decreased of 1.7% from 2020-01 to 2020-03, whereas it increased by 1.6% in January and decreased by 1.3% and 7.9% in February and March, respectively. The reduction of pollutants emissions led to a decrease of 14.1% in national PM2.5 concentration during the first quarter of 2020 and a decrease of 4.0%, 25.7%, and 15.0% in January, February, and March, respectively. Compared to the same period last year, the PM2.5 concentration measured in Wuhan City decreased more than in the entire country. This was caused by improved meteorological conditions and a higher reduction of pollutant emissions in Wuhan City. PM2.5 in Beijing increased annually before the epidemic outbreak and during the strict control period, mainly due to unfavorable meteorological conditions. However, the decrease in PM2.5 in Beijing compared to March 2019 was closely related to the substantial reduction of emissions. The measured PM2.5 in the "2+26" cities, the Fenwei Plain and the Yangtze River Delta (YRD) decreased during the first quarter of 2020, with the largest drop occurring in the Yangtze River Delta due to higher YRD emissions reductions. The meteorological conditions of "2+26" cities and Fenwei Plain were unfavorable before the epidemic outbreak and greatly improved during the strict control period, whereas the Yangtze River Delta had the most favorable meteorological conditions in March. The decrease in PM2.5 concentration caused by the reduction of pollutant emissions in the three key areas was highest during the strict control period.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Epidemias , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Pequim , China , Cidades , Monitoramento Ambiental , Meteorologia , Material Particulado/análise
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