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1.
J Environ Sci (China) ; 102: 110-122, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33637237

RESUMEN

To control the spread of COVID-19, rigorous restrictions have been implemented in China, resulting in a great reduction in pollutant emissions. In this study, we evaluated the air quality in the Yangtze River Delta during the COVID-19 lockdown period using satellite and ground-based data, including particle matter (PM), trace gases, water-soluble ions (WSIs) and black carbon (BC). We found that the impacts of lockdown policy on air quality cannot be accurately assessed using MODIS aerosol optical depth (AOD) data, whereas the tropospheric nitrogen dioxide (NO2) vertical column density can well reflect the influences of these restrictions on human activities. Compared to the pre-COVID period, the PM2.5, PM10, NO2, carbon monoxide (CO), BC and WSIs during the lockdown in Suzhou were observed to decrease by 37.2%, 38.3%, 64.5%, 26.1%, 53.3% and 58.6%, respectively, while the sulfur dioxide (SO2) and ozone (O3) increased by 1.5% and 104.7%. The WSIs ranked in the order of NO3- > NH4+ > SO42- > Cl- > Ca2+ > K+ > Mg2+ > Na+ during the lockdown period. By comparisons with the ion concentrations during the pre-COVID period, we found that the ions NO3-, NH4+, SO42-, Cl-, Ca2+, K+ and Na+ decreased by 66.3%, 48.8%, 52.9%, 56.9%, 57.9% and 76.3%, respectively, during the lockdown, in contrast to Mg2+, which increased by 30.2%. The lockdown policy was found to have great impacts on the diurnal variations of Cl-, SO42-, Na+ and Ca2+.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Aerosoles/análisis , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Control de Enfermedades Transmisibles , Monitoreo del Ambiente , Humanos , Material Particulado/análisis , Ríos
2.
J Environ Sci (China) ; 102: 138-147, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33637239

RESUMEN

This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network (AQMN). It requires to be constituted by a minimum and reliable number of measurement sites. Nevertheless, the AQMN efficiency should be assessed over time, as a consequence of the possible emergence of new emission sources of air pollutants, which could lead to variations on their spatial distribution within the target area. PM10 particles data monitored by the Community of Madrid's (Spain) AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance. The annual spatial distribution of average PM10 levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system (GIS), and the percentage of similarity between both postulates was quantified using simple linear regression (> 95%). As one innovative tool of this study, the practical application of the proposed methodology was validated using PM10 particles data measured by AQMN during 2007 and 2018, reaching a similitude degree higher than 95%. The influence of temporal variation on the proposed methodological framework was around 20%. The proposed methodology sets criteria for identifying non-redundant stations within AQMN, it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations, which could help to tackle efforts to improve the air quality management.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Conservación de los Recursos Naturales , Monitoreo del Ambiente , Material Particulado/análisis
3.
J Environ Sci (China) ; 102: 363-372, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33637261

RESUMEN

The pollution characteristics of surfactant substances in fine particles (PM2.5) in spring were studied in the Beibu Gulf Region of China, 68 samples of PM2.5 were collected at Weizhou Island in Beihai City from March 12 to April 17, 2015. The Anionic Surfactant Substances (ASS) and Cationic Surfactant Substances (CSS) in the samples were analyzed using Byethyl Violet Spectrophotometry and Disulfide Blue Spectrophotometry, respectively. Combined with the data from backward trajectory simulation, the effects of air pollutants from remote transport on the pollution characteristics of surfactant substances in PM2.5 in the Beibu Gulf Region were analyzed and discussed. The results showed that the daily mean concentrations of ASS and CSS in spring in the Beibu Gulf Region were 165.20 pmol/m3 and 8.05pmol/m3, and the variation ranges were 23.21-452.55 pmol/m3 and 0.65-31.31 pmol/m3, accounting for 1.82‰ ± 1.65‰ and 0.12‰ ± 0.11‰ of the mass concentration of PM2.5, respectively. These concentrations were lower than those in comparable regions around the world. There was no clear correlation between the concentrations of ASS and CSS in PM2.5 and the mass concentrations of PM2.5. Tourism and air transport had a positive contribution on the concentrations of ASS. The concentration of surfactant substances in PM2.5 was significantly impacted by wind speed and wind direction. Atmospheric temperature, air pressure and precipitation had little effect on the concentrations of surfactant substances. Surfactant substances in PM2.5 significantly impacted visibility. Results also showed that the main sources of surfactant substances were from the southern China and Southeast Asia.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Ciudades , Monitoreo del Ambiente , Material Particulado/análisis , Estaciones del Año , Tensoactivos
4.
Environ Pollut ; 274: 116498, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33524649

RESUMEN

Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia's most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series' of nitrogen dioxide (NO2), ozone (O3), carbon monoxide CO and particulate matter with diameter < 2.5 µm (PM2.5), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM2.5 (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM2.5 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6-343.) excess deaths and 3490.0 (95% CI 1325.9-5653.5) additional hospitalisations were likely as a result of PM2.5 and O3 exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO2 decreased by 21.5 and 8% in Victoria and NSW respectively. O3 and PM2.5 remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Afroamericanos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Ciudades , Control de Enfermedades Transmisibles , Monitoreo del Ambiente , Humanos , Nueva Gales del Sur , Pandemias , Material Particulado/análisis , Estaciones del Año , Victoria
5.
Environ Pollut ; 274: 116574, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33529896

RESUMEN

Satellite-derived aerosol optical depth (AOD) has been widely used to predict ground-level fine particulate matter (PM2.5) concentrations, although its utility can be limited due to missing values. Despite recent attempts to address this issue by imputing missing satellite AOD values, the uncertainty associated with the AOD imputation and its impacts on PM2.5 predictions have been understudied. To fill this gap, we developed a missing data imputation model for the AOD derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and PM2.5 prediction models using several machine learning methods. We also examined how the uncertainty associated with the imputed AOD and a choice of machine learning algorithm were propagated to PM2.5 predictions. The application of the proposed imputation model to the data from New York State in the U.S. achieved a superior performance than those related studies, with a cross-validated R2 of 0.94 and a Root Mean Square Error of 0.017. We also found that there was considerable uncertainty in PM2.5 predictions associated with the use of imputed AOD values, although it was not as high as the uncertainty from the machine learning algorithms used in PM2.5 prediction models. We concluded that the quantification of uncertainties for both AOD imputation and its propagation to AOD-based PM2.5 prediction is necessary for accurate and reliable PM2.5 predictions.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Aerosoles/análisis , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Monitoreo del Ambiente , New York , Material Particulado/análisis , Incertidumbre
6.
Environ Pollut ; 274: 116268, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33545528

RESUMEN

Air pollution coming from industrial activities is a matter of interest since their emissions can seriously affect to the human health of nearby populations. A more detailed study about industrial emissions is required in order to discriminate different activities contributing to pollutant sources. In this sense, gaseous pollutants (NO2, SO2 and O3) and PM10 levels has been studied in a complex industrial area in the southwest of Spain (La Rabida and the nearby city of Huelva) during the period 1996-2017. Hourly, daily, monthly and annual variations of PM10 and gaseous pollutants concentrations point to the industrial activity as the main SO2 source. Furthermore, traffic and resuspension emissions contribute to the NO2 and PM10 levels, respectively. Results from chemical composition of PM10 at both sites during the period 2015-2017 are characterized by high concentrations of the crustal components derived from natural and local resuspension. Arsenic is found to be the main geochemical anomaly at La Rabida (annual mean of 7 ng m-3), exceeding the European annual target of 6 ng m-3, which supposes a risk for the nearby population. An emission source from Cu-smelter has been identified in La Rabida and Huelva. A second source corresponding to emissions from polymetallic sulfides handling in a port area has been described for the first time in La Rabida. In addition, arsenic speciation results have identified three different As impacts scenarios as a function of the dominant wind direction, the SO2 episodes and the As extraction efficiency: impact of the Cu-smelter, impact of the bulk polymetallic sulfides and a mixed impact of both sources.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Arsénico , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Ciudades , Monitoreo del Ambiente , Humanos , Material Particulado/análisis , España
7.
Environ Pollut ; 274: 116513, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33548669

RESUMEN

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R2 annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R2 for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Monitoreo del Ambiente , Dióxido de Nitrógeno/análisis , Material Particulado/análisis , Sudáfrica
8.
Sci Rep ; 11(1): 4285, 2021 02 19.
Artículo en Inglés | MEDLINE | ID: mdl-33608603

RESUMEN

On January 30, 2020, India recorded its first COVID-19 positive case in Kerala, which was followed by a nationwide lockdown extended in four different phases from 25th March to 31st May, 2020, and an unlock period thereafter. The lockdown has led to colossal economic loss to India; however, it has come as a respite to the environment. Utilizing the air quality index (AQI) data recorded during this adverse time, the present study is undertaken to assess the impact of lockdown on the air quality of Ankleshwar and Vapi, Gujarat, India. The AQI data obtained from the Central Pollution Control Board was assessed for four lockdown phases. We compared air quality data for the unlock phase with a coinciding period in 2019 to determine the changes in pollutant concentrations during the lockdown, analyzing daily AQI data for six pollutants (PM10, PM2.5, CO, NO2, O3, and SO2). A meta-analysis of continuous data was performed to determine the mean and standard deviation of each lockdown phase, and their differences were computed in percentage in comparison to 2019; along with the linear correlation analysis and linear regression analysis to determine the relationship among the air pollutants and their trend for the lockdown days. The results revealed different patterns of gradual to a rapid reduction in most of the pollutant concentrations (PM10, PM2.5, CO, SO2), and an increment in ozone concentration was observed due to a drastic reduction in NO2 by 80.18%. Later, increases in other pollutants were also observed as the restrictions were eased during phase-4 and unlock 1. The comparison between the two cities found that factors like distance from the Arabian coast and different industrial setups played a vital role in different emission trends.


Asunto(s)
Contaminación del Aire/estadística & datos numéricos , Control de Enfermedades Transmisibles/normas , Monitoreo del Ambiente/estadística & datos numéricos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , /transmisión , Ciudades/estadística & datos numéricos , Humanos , India , Industrias/normas , Material Particulado/análisis
9.
Artículo en Inglés | MEDLINE | ID: mdl-33573007

RESUMEN

Recent works have demonstrated that particulate matter (PM) and specific meteorological conditions played an important role in the airborne transmission of the SARS-CoV-1 and MERS-CoV. These studies suggest that these parameters could influence the transmission of SARS-CoV-2. In the present investigation, we sought to investigate the association between air pollution, meteorological data, and the Lombardy region COVID-19 outbreak caused by SARS-CoV-2. We considered the number of detected infected people at the regional and provincial scale from February to March 2020. Air pollution data were collected over the Lombardy region, nominally, sulphur dioxide, ammonia, nitrogen dioxide, nitrogen monoxide, carbon monoxide, ozone, and suspended particulate matter measuring less than 10 µm (PM10) and less than 2.5 µm (PM2.5). Meteorological data have been collected over the same region for temperature, relative humidity, and wind speed. In this work, we evaluated the combined impact of environmental pollutants and climate conditions on the COVID-19 outbreak. The analysis evidenced a positive correlation between spatial distribution of COVID-19 infection cases with high concentrations of suspended particulate matter and a negative relationship with ozone. Moreover, suspended particulate matter concentration peaks in February correlated positively with infection peaks according to the virus incubation period. The obtained results suggested that seasonal weather conditions and concentration of air pollutants seemed to influence COVID-19 epidemics in Lombardy region.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Material Particulado , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Monitoreo del Ambiente , Humanos , Italia/epidemiología , Material Particulado/análisis
10.
Waste Manag ; 123: 15-22, 2021 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-33548745

RESUMEN

Despite the clear link between air pollution and health, research to investigate the relationship between municipal solid waste management and air pollution and health has not been prioritized. Such research may generate scientific information that would help reduce population exposure to air pollutants. This paper examines the case study of Accra in Ghana, a city dealing with serious waste management problems. The paper proposes a methodology to estimate the impact of waste management on urban air pollution and health. The analysis is described in the following four steps: (1) collecting data on the waste sector; (2) modeling the emissions arising from waste management; (3) transforming emissions to concentration values and (4) estimating the burdens on health. The assessment has been conducted using the CCAC SWEET tool and WHO AirQ+. The method presented can be used in different locations, depending on data availability, when analyzing the impact of and potential changes to waste sector policies. The results of this health impact assessment indicate that, based on the emissions of PM2.5 from the waste sector in Accra, a change from the business-as-usual to more sustainable options would reduce air pollutants emissions and avert 120 premature deaths in 2030. Levels of air pollution in Accra are significant and interventions to reduce PM2.5 exposure should be promoted. The detailed analysis of the current situation provides suggestions for waste management policies in terms of impacts on health and ideas to reconsider the waste policies in Accra.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Administración de Residuos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Ciudades , Ghana , Residuos Sólidos
11.
J Environ Manage ; 284: 112071, 2021 Apr 15.
Artículo en Inglés | MEDLINE | ID: mdl-33561762

RESUMEN

The State Council of China had issued the Air Pollution Prevention and Control Action Plan (abbreviated as "Clean Air Actions"), which ended in 2017. To evaluate the implementation effect of the clean air actions and provide the scientific basis on the future control policy, a Geographical Detector was used to quantify the impact of natural and socioeconomic factors on the PM2.5 concentration and its reductions in China from the years of 2014-2017. In terms of the impact on PM2.5 reduction, the industrial sulfur dioxide (SO2) and industrial soot emissions are the only two factors shown significant influences. So the controls of industrial emission were the major policies during the implementation of the Clean Air Actions. In terms of the impact on the PM2.5 concentrations, industrial emission was the strongest socioeconomic factor in the beginning of the Clean Air Actions, but its dominance was then declining. In contrast, the influences of population density had been enhancing and became the greatest factor in the final year. So the new control measures should focus on the urbanization regulation. In addition, the interactions between different socioeconomic factors are proved to bivariate enhance the influences on the PM2.5 concentration levels. Multiple factors should thus be taken into account when any new control policies are going to be established.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire/prevención & control , China , Monitoreo del Ambiente , Material Particulado/análisis , Factores Socioeconómicos
12.
Ecotoxicol Environ Saf ; 208: 111726, 2021 Jan 15.
Artículo en Inglés | MEDLINE | ID: mdl-33396057

RESUMEN

BACKGROUND: It remains unclear which size of particles has the strongest effects on heart rate variability (HRV). OBJECTIVE: To explore the association between HRV parameters and daily variations of size-fractionated particle number concentrations (PNCs). METHODS: We conducted a longitudinal repeated-measure study among 78 participants with a 24-h continuous ambulatory Holter electrocardiographic recorder in Shanghai, China, from January 2015 to June 2019. Linear mixed-effects models were employed to evaluate the changes of HRV parameters associated with PNCs of 7 size ranges from 0.01 to 10 µm after controlling for environmental and individual confounders. RESULTS: On the concurrent day, decreased HRV parameters were associated with increased PNCs of 0.01-0.3 µm, and smaller particles showed greater effects. For an interquartile range increase in ultrafine particles (UFP, those < 0.1 µm, 2453 particles/cm3), the declines in very-low-frequency power, low-frequency power, high-frequency power, standard deviation of normal R-R intervals, root mean square of the successive differences between R-R intervals and percentage of adjacent normal R-R intervals with a difference ≥ 50 ms were 5.06% [95% confidence interval (CI): 2.09%, 7.94%], 7.65% (95%CI: 2.73%, 12.32%), 9.49% (95%CI: 4.64%, 14.09%), 5.10% (95%CI: 2.21%, 7.91%), 8.09% (95%CI: 4.39%, 11.65%) and 24.98% (95%CI: 14.70%, 34.02%), respectively. These results were robust to the adjustment of criteria air pollutants, temperature at different lags, and the status of heart medication. CONCLUSIONS: Particles less than 0.3 µm (especially UFP) may dominate the acute effects of particulate air pollution on cardiac autonomic dysfunction.


Asunto(s)
Contaminantes Atmosféricos/análisis , Contaminación del Aire/estadística & datos numéricos , Exposición a Riesgos Ambientales/estadística & datos numéricos , Material Particulado/análisis , Contaminación del Aire/análisis , China , Femenino , Cardiopatías , Frecuencia Cardíaca/efectos de los fármacos , Humanos , Masculino , Persona de Mediana Edad , Tamaño de la Partícula , Temperatura
13.
Environ Int ; 146: 106316, 2021 01.
Artículo en Inglés | MEDLINE | ID: mdl-33395952

RESUMEN

Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 mortality in England using high geographical resolution. In this nationwide cross-sectional study in England, we included 38,573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level (n = 32,844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. We find a 0.5% (95% credible interval: -0.2%, 1.2%) and 1.4% (95% CrI: -2.1%, 5.1%) increase in COVID-19 mortality risk for every 1 µg/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect equal to 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/toxicidad , Contaminación del Aire/efectos adversos , Contaminación del Aire/análisis , Teorema de Bayes , Estudios Transversales , Inglaterra/epidemiología , Exposición a Riesgos Ambientales/efectos adversos , Exposición a Riesgos Ambientales/análisis , Humanos , Dióxido de Nitrógeno/análisis , Dióxido de Nitrógeno/toxicidad , Material Particulado/análisis , Material Particulado/toxicidad , Análisis Espacial
14.
Environ Pollut ; 274: 116523, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33508716

RESUMEN

With the implementation of clean air strategies, PM2.5 pollution abatement has been observed in the "2 + 26" cities in the Beijing-Tianjin-Hebei (BTH) region (referred to as the BTH2+26) and their surrounding areas. To identify the drivers for PM2.5 concentration decreases in the BTH2+26 cites from the 2016/17 heating season (HS1617) to the 2017/18 heating season (HS1718), we investigated the contributions of meteorological conditions and emission-reduction measures by Community Multi-Scale Air Quality (CMAQ) model simulations. The source apportionments of five sector sources (i.e., agriculture, industry, power plants, traffic and residential), and regional sources (i.e., local, within-BTH: other cities within the BTH2+26 cities, outside-BTH, and boundary conditions (BCON)) to the PM2.5 decreases in the BTH2+26 cities were estimated with the Integrated Source Apportionment Method (ISAM). Mean PM2.5 concentrations in the BTH2+26 cities substantially decreased from 77.4 to 152.5 µg m-3 in HS1617 to 52.9-101.9 µg m-3 in HS1718, with the numbers of heavy haze (daily PM2.5 ≥150 µg m-3) days decreasing from 17-77 to 5-30 days. The model simulation results indicated that the PM2.5 concentration decreases in most of the BTH2+26 cities were attributed to emission reductions (0.4-55.0 µg m-3, 2.3-81.6% of total), but the favorable meteorological conditions also played important roles (1.9-25.4 µg m-3, 18.4-97.7%). Residential sources dominated the PM2.5 reductions, leading to decreases in average PM2.5 concentrations by more than 30 µg m-3 in severely polluted cities (i.e., Shijiazhuang, Baoding, Xingtai, and Beijing). Regional source analyses showed that both local and within-BTH sources were significant contributors to PM2.5 concentrations for most cities. Emission controls in local and within-BTH sources in HS1718 decreased the average PM2.5 concentrations by 0.1-47.2 µg m-3 and 0.3-22.1 µg m-3, respectively, relative to those in HS1617. Here we demonstrate that a combination of favorable meteorological conditions and anthropogenic emission reductions contributed to the improvement of air quality from HS1617 to HS1718 in the BTH2+26 cities.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Beijing , China , Ciudades , Monitoreo del Ambiente , Calefacción , Material Particulado/análisis , Mejoramiento de la Calidad , Estaciones del Año
15.
Environ Pollut ; 274: 116512, 2021 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-33516954

RESUMEN

Amid the COVID-19 pandemic, there has been an unprecedented cessation of outdoor anthropogenic activities leading to a significant improvement of the environment across the world. However, the positive impacts on the environment are not expected to last long as countries have started to gradually come out of lockdown and engage in aggressive measures to regain the pre-COVID-19 levels of economic activity. The present study provides for an assessment of air quality changes during the period of lockdown and unlocking across 9 major cities in the Indian state of Uttar Pradesh, including three cities (Ghaziabad, Noida, and Greater Noida) in the national capital region, which have frequently been included among the most polluted cities in the world. The pollutant load in a vertical column of air during March-July 2020 has been analyzed and compared with the corresponding period's pollution load in 2019. In addition, a detailed analysis of the ground-level changes in pollution load for Ghaziabad, Noida, and Greater Noida is also presented, along with the changes in local meteorology. A significant reduction in the total column density of NO2, CO and ground-level pollution load of PM10, PM2.5, NO2, and SO2 have been observed. In contrast, an increase in total column density of SO2 across all the cities (except Kanpur) and ground-level concentration of CO (in Noida and Greater Noida) and O3 (in Noida) was evident. The improvement in air quality (with respect to particulate matter) can primarily be attributed to the restrictions on construction and demolition activities, reduced re-suspension of roadside dust, and the restrictions on the movement of vehicles. A significant decline in the average summer temperature was recorded, and it can plausibly be attributed to lower radiative forcing due to reduced pollutant load in the atmosphere.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Ciudades , Control de Enfermedades Transmisibles , Monitoreo del Ambiente , Humanos , Pandemias , Material Particulado/análisis
16.
Ecotoxicol Environ Saf ; 208: 111590, 2021 Jan 15.
Artículo en Inglés | MEDLINE | ID: mdl-33396113

RESUMEN

AIMS: To assess possible effect of air quality improvements, we investigated the temporal change in hospital admissions for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) associated with pollutant concentrations. METHODS: We collected daily concentrations of particulate matter (i.e., PM2.5, PM10 and PMcoarse), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and admissions for AECOPD for 21 cities in Guangdong from 2013 to 2017. We examined the association of air pollution with AECOPD admissions using two-stage time-series analysis, and estimated the annual attributable fractions, numbers, and direct hospitalization costs of AECOPD admissions with principal component analysis. RESULTS: From 2013-2017, mean daily concentrations of SO2, PM10 and PM2.5 declined by nearly 40%, 30%, and 26% respectively. As the average daily 8 h O3 concentration increased considerably, the number of days exceeding WHO target (i.e.,100 µg/m³) increased from 103 in 2015-152 in 2017. For each interquartile range increase in pollutant concentration, the relative risks of AECOPD admission at lag 0-3 were 1.093 (95% CI 1.06-1.13) for PM2.5, 1.092 (95% CI 1.08-1.11) for O3, and 1.092 (95% CI 1.05-1.14) for SO2. Attributable fractions of AECOPD admission advanced by air pollution declined from 9.5% in 2013 to 4.9% in 2016, then increased to 6.0% in 2017. A similar declining trend was observed for direct AECOPD hospitalization costs. CONCLUSION: Declined attributable hospital admissions for AECOPD may be associated with the reduction in concentrations of PM2.5, PM10 and SO2 in Guangdong, while O3 has emerged as an important risk factor. Summarizes the main finding of the work: Reduction in PM may result in declined attributable hospitalizations for AECOPD, while O3 has emerged as an important risk factor following an intervention.


Asunto(s)
Contaminantes Atmosféricos/toxicidad , Contaminación del Aire/estadística & datos numéricos , Hospitalización/estadística & datos numéricos , Contaminación del Aire/análisis , Monóxido de Carbono/análisis , China , Hospitales , Humanos , Dióxido de Nitrógeno/análisis , Ozono/análisis , Material Particulado/análisis , Enfermedad Pulmonar Obstructiva Crónica/etiología , Factores de Riesgo , Dióxido de Azufre/análisis
17.
Environ Monit Assess ; 193(1): 29, 2021 Jan 04.
Artículo en Inglés | MEDLINE | ID: mdl-33398550

RESUMEN

Like all infectious diseases, the infection rate of COVID-19 is dependent on many variables. In order to effectively prepare a localized plan for infectious disease management, it is important to find the relationship between COVID-19 infection rate and other key variables. This study aims to understand the spatial relationships between COVID-19 infection rate and key variables of air pollution, geo-meteorological, and social parameters in Dhaka, Bangladesh. The relationship was analyzed using Geographically Weighted Regression (GWR) model and Geographic Information System (GIS) by means of COVID-19 infection rate as a dependent variable and 17 independent variables. This study revealed that air pollution parameters like PM2.5 (p < 0.02), AOT (p < 0.01), CO (p < 0.05), water vapor (p < 0.01), and O3 (p < 0.01) were highly correlated with COVID-19 infection rate while geo-meteorological parameters like DEM (p < 0.01), wind pressure (p < 0.01), LST (p < 0.04), rainfall (p < 0.01), and wind speed (p < 0.03) were also similarly associated. Social parameters like population density (p < 0.01), brickfield density (p < 0.02), and poverty level (p < 0.01) showed high coefficients as the key independent variables to COVID-19 infection rate. Significant robust relationships between these factors were found in the middle and southern parts of the city where the reported COVID-19 infection case was also higher. Relevant agencies can utilize these findings to formulate new and smart strategies for reducing infectious diseases like COVID-19 in Dhaka and in similar urban cities around the world. Future studies will have more variables including ecological, meteorological, and economical to model and understand the spread of COVID-19.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Bangladesh/epidemiología , Ciudades , Monitoreo del Ambiente , Humanos , Material Particulado/análisis
19.
Environ Monit Assess ; 193(2): 66, 2021 Jan 15.
Artículo en Inglés | MEDLINE | ID: mdl-33452599

RESUMEN

The growing populations around the world are closely associated with rising levels of air pollution. The impact is not restricted to outdoor areas. Moreover, the health of building occupants is also deteriorating due to poor indoor air quality. As per the World Health Organization, indoor air pollution is a leading cause of 1.6 million premature deaths annually. Therefore, numerous companies have started the development of low-cost sensors to monitor indoor air pollution with the Internet of Things-based applications. However, due to the close association of air pollution levels to the mortality and morbidity rates, communities face several limitations while selecting sensors to address this public health challenge. The main contribution of this systematic review is to present a qualitative and quantitative evaluation of low-cost sensors while providing deep insights into the selection criteria for adequate monitoring. The authors in this paper discussed studies published after the year 2015, and it includes an analysis of papers published in the English language only. Moreover, this study highlights crucial research questions, states answers, and provides recommendations for future research studies. The outcomes of this paper will be useful for students, researchers, and industry members concerning the upcoming research and manufacturing activities. The results show that 28 studies (70%) include indoor thermal comfort assessment, 26 (65%) and 12 (30%) studies include CO2 and CO sensors, respectively. In total, 32 (45.7%) out of 71 sensors (whose prices are available) discussed in this study are available in a price below the US $20 over online marketplaces. Furthermore, the authors conclude that 77.5% of the analyzed literature does not include calibration details, and the accuracy specification is missing for 39.4% sensors.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire Interior , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire Interior/análisis , Monitoreo del Ambiente , Humanos , Internet de las Cosas
20.
Ecotoxicol Environ Saf ; 211: 111937, 2021 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-33476848

RESUMEN

In order to investigate the pollution characteristics of size-segregated particles and metal elements (MEs) after the Chinese Air Pollution Prevention Action Plan was released in 2013, an intensive field campaign was conducted in the suburban area of Chaoyang District, Beijing in winter 2016. The size distributions of particle mass concentrations were bimodal, with the first peak in the fine fraction (0.4-2.1 µm) and the second peak in the coarse fraction (3.3-5.8 µm). Moreover, the proportion of fine particles increased and the proportion of coarse particles decreased as the pollution level was more elevated. It was found that the composition of coarse particles is as important as that of fine particles when pollution of aerosol metals in the atmosphere in 2016 were compared to 2013. In addition, according to the size distribution characteristics, 23 MEs were divided into three groups: (a) Fe, Co, Sr, Al, Ti, Ba, and U, which concentrated in coarse mode; (b) Zn, As, Cd, Tl, and Pb, which concentrated in fine mode; and (c) Na, K, Be, V, Cr, Mn, Ni, Cu, Mo, Ag, and Sn, showing bimodal distribution. Under clean air, slight pollution and moderate pollution conditions, most elements maintained their original size distributions, while under severe pollution, the unimodal distributions of most MEs became bimodal distributions. The factors analysis combined with size distributions indicated that Na, Zn, Mo, Ag, Cd, and Tl, showing the moderate to severe contamination on environment, were significantly influenced by diffuse regional emissions or anthropogenic source emissions (vehicle exhaust emissions and combustion process). The environmental risk assessment revealed that the heavy metal loading in the atmospheric particles collected had a high potential for ecological risk to the environment during sampling period because of the high contribution of Cd, Tl, Zn and Pb.


Asunto(s)
Contaminantes Atmosféricos/análisis , Monitoreo del Ambiente , Metales Pesados/análisis , Material Particulado/análisis , Aerosoles/análisis , Contaminación del Aire/análisis , Atmósfera , Beijing , Tamaño de la Partícula , Medición de Riesgo , Estaciones del Año
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