Toxics

Research

19 pages, 3234 KiB

Open AccessArticle

Predicting of Daily PM_2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China

by Qingchun Guo, Zhenfang He and Zhaosheng Wang

Toxics 2023, 11(1), 51; https://doi.org/10.3390/toxics11010051 - 3 Jan 2023

Cited by 20 | Viewed by 1819

Abstract

Anthropogenic sources of fine particulate matter (PM_2.5) threaten ecosystem security, human health and sustainable development. The accuracy prediction of daily PM_2.5 concentration can give important information for people to reduce their exposure. Artificial neural networks (ANNs) and wavelet-ANNs (WANNs) are [...] Read more.

Anthropogenic sources of fine particulate matter (PM_2.5) threaten ecosystem security, human health and sustainable development. The accuracy prediction of daily PM_2.5 concentration can give important information for people to reduce their exposure. Artificial neural networks (ANNs) and wavelet-ANNs (WANNs) are used to predict daily PM_2.5 concentration in Shanghai. The PM_2.5 concentration in Shanghai from 2014 to 2020 decreased by 39.3%. The serious COVID-19 epidemic had an unprecedented effect on PM_2.5 concentration in Shanghai. The PM_2.5 concentration during the lockdown in 2020 of Shanghai is significantly reduced compared to the period before the lockdown. First, the correlation analysis is utilized to identify the associations between PM_2.5 and meteorological elements in Shanghai. Second, by estimating twelve training algorithms and twenty-one network structures for these models, the results show that the optimal input elements for daily PM_2.5 concentration predicting models were the PM_2.5 from the 3 previous days and fourteen meteorological elements. Finally, the activation function (tansig-purelin) for ANNs and WANNs in Shanghai is better than others in the training, validation and forecasting stages. Considering the correlation coefficients (R) between the PM_2.5 in the next day and the input influence factors, the PM_2.5 showed the closest relation with the PM_2.5 1 day lag and closer relationships with minimum atmospheric temperature, maximum atmospheric pressure, maximum atmospheric temperature, and PM_2.5 2 days lag. When Bayesian regularization (trainbr) was used to train, the ANN and WANN models precisely simulated the daily PM_2.5 concentration in Shanghai during the training, calibration and predicting stages. It is emphasized that the WANN1 model obtained optimal predicting results in terms of R (0.9316). These results prove that WANNs are adept in daily PM_2.5 concentration prediction because they can identify relationships between the input and output factors. Therefore, our research can offer a theoretical basis for air pollution control. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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15 pages, 5239 KiB

Open AccessArticle

Indoor Particle’s Pollution in Bucharest, Romania

by Lelia Letitia Popescu, Razvan Stefan Popescu and Tiberiu Catalina

Toxics 2022, 10(12), 757; https://doi.org/10.3390/toxics10120757 - 5 Dec 2022

Cited by 3 | Viewed by 1923

Abstract

Air pollution risk factor on human health was surpassed only by high blood pressure, tobacco use and poor diet. Total number of deaths due to air pollution worldwide was estimated to 6.67 million people in 2019. In the European Union, 97% of the [...] Read more.

Air pollution risk factor on human health was surpassed only by high blood pressure, tobacco use and poor diet. Total number of deaths due to air pollution worldwide was estimated to 6.67 million people in 2019. In the European Union, 97% of the urban population is exposed to levels of fine particulate matter above the latest guideline levels set by the World Health Organization. Air pollution accounts for 20% of newborn deaths worldwide, most related to complications of low birth weight and preterm birth. Low birth weight and preterm birth are responsible for 1.8 million deaths worldwide. Bucharest is the capital city of Romania and one of the most polluted cities in Europe, ranking in the 9th position out of 96 of the top cities from Europe and in the 4th position out of 32 of the top cities in Eastern Europe, data from June 2022. The aim of this study was to measure the real time level of indoor particulate pollution levels in different indoor environments from Bucharest, during the pandemic period. The PM_2.5/PM₁₀ ratio and its rate of change were also determined for the measured data. The PM_2.5/PM₁₀ ratio and its rate of change were also calculated based on the measurement data. The PM_2.5/PM₁₀ ratio showed an upward trend on weekends compared to weekdays, suggesting a relationship with outdoor PM where leisure activities and traffic infiltrated the indoors. The fluctuation range of the PM_2.5/PM₁₀ ratio was 0.44~0.95, and low measured values were detected on weekdays. Of the seasons, the proportion of particulate in autumn and its rate of change tended to be higher than in summer. It was suggested that outdoor air may have permeated the room. In addition, the relationship was considered, such as it is a holiday period, there are few rainy days, the concentration of coarse particles is high, and the number of residents in the city decreases. When it comes to indoor air quality, the higher this ratio, the more serious the air pollution. PM₁₀ concentrations decreased by 29.1% in the absence of human activity and increased by 35.1% in the presence of humans. PM_2.5 concentration decreased by 30.3% without human activity and increased by 3.1% with the presence of humans. Certain trends were suggested for the resumption of human activity and an increase in PM_2.5 concentrations. The average relative difference between October 2021, a pandemic period, and October 2022, a post pandemic period, was 64% for PM₁₀ and 47% for PM_2.5. The pandemic period brought a significantly better indoor air quality from the particulate pollution point of view. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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Graphical abstract

12 pages, 2022 KiB

Open AccessArticle

Evolution of Pollution Levels from COVID-19 Lockdown to Post-Lockdown over India

by Bhishma Tyagi, Naresh Krishna Vissa and Sachin D. Ghude

Toxics 2022, 10(11), 653; https://doi.org/10.3390/toxics10110653 - 29 Oct 2022

Cited by 3 | Viewed by 1558

Abstract

The spread of the COVID-19 pandemic forced the administration to lock down in many countries globally to stop the spread. As the lockdown phase had only the emergency use of transportation and most of the industries were shut down, there was an apparent [...] Read more.

The spread of the COVID-19 pandemic forced the administration to lock down in many countries globally to stop the spread. As the lockdown phase had only the emergency use of transportation and most of the industries were shut down, there was an apparent reduction in pollution. With the end of the lockdown period, pollution is returning to its regular emission in most places. Though the background was abnormally low in emissions (during the lockdown phase) and the reduced pollution changed the radiation balance in the northern hemispheric summer period, a modified pollution pattern is possible during the unlock phases of 2020. The present study analysed the unlock 1 and 2 stages (June–July) of the COVID-19 lockdown over India. The rainfall, surface temperature and cloud cover anomalies of 2020 for understanding the differences in pollutants variation were also analysed. The unlock phases show remarkable differences in trends and mean variations of pollutants over the Indian region compared to climatological variations. The results indicated changing high-emission regions over India to climatological variations and identified an AOD dipole with future emissions over India. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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17 pages, 2851 KiB

Open AccessArticle

Human Health Risks and Air Quality Changes Following Restrictions for the Control of the COVID-19 Pandemic in Thailand

by Jenjira Kaewrat, Rungruang Janta, Surasak Sichum, Chuthamat Rattikansukha, Wittaya Tala and Thongchai Kanabkaew

Toxics 2022, 10(9), 520; https://doi.org/10.3390/toxics10090520 - 31 Aug 2022

Cited by 5 | Viewed by 2356

Abstract

The coronavirus (COVID-19) pandemic first impacted Thailand in early 2020. The government imposed lockdown measures from April to May 2020 to control the spread of infection. Daily lifestyles then morphed into a so-called new normal in which activities were conducted at home and [...] Read more.

The coronavirus (COVID-19) pandemic first impacted Thailand in early 2020. The government imposed lockdown measures from April to May 2020 to control the spread of infection. Daily lifestyles then morphed into a so-called new normal in which activities were conducted at home and people avoided congregation in order to prevent the spread of an infectious disease. This study evaluated the long-term air quality improvement which resulted from the restrictions enforced on normal human activities in Thailand. The air quality index (AQI) of six criteria pollutants and health risk assessments were evaluated in four areas, including metropolitan, suburban, industrial, and tourism areas in Thailand. The results showed that, after the restriction measures, the overall AQI improved by 30%. The subindex of each pollutant (sub-AQI) of most pollutants significantly improved (by 30%) in metropolitan areas after human activities changed due to the implementation of lockdown measures. With regard to industrial and tourism areas, only the sub-AQI of traffic-related pollutants decreased (34%) while the sub-AQIs of other pollutants before and after lockdown were similar. However, the changes in human activities were not clearly related to air quality improvement in the suburban area. The overall hazard index (HI) after lockdown decreased by 23% because of the reduction of traffic-related pollutants. However, the HI value remained above the recommended limits for the health of the adult residents in all areas. Therefore, strict regulations to control other pollutant sources, such as industry and open burning, will also be necessary for air quality improvement in Thailand. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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10 pages, 2337 KiB

Open AccessFeature PaperArticle

Assessing the Impact of Meteorological Factors on COVID-19 Seasonality in Metropolitan Chennai, India

by Thodhal Yoganandham Suman, Rajendiran Keerthiga, Rajan Renuka Remya, Amali Jacintha and Junho Jeon

Toxics 2022, 10(8), 440; https://doi.org/10.3390/toxics10080440 - 1 Aug 2022

Cited by 2 | Viewed by 1877

Abstract

Meteorological factors may influence coronavirus disease 2019 (COVID-19) transmission. Due to the small number of time series studies, the relative importance of seasonality and meteorological factors is still being debated. From March 2020 to April 2021, we evaluated the impact of meteorological factors [...] Read more.

Meteorological factors may influence coronavirus disease 2019 (COVID-19) transmission. Due to the small number of time series studies, the relative importance of seasonality and meteorological factors is still being debated. From March 2020 to April 2021, we evaluated the impact of meteorological factors on the transmission of COVID-19 in Chennai, India. Understanding how the COVID-19 pandemic spreads over the year is critical to developing public health strategies. Correlation models were used to examine the influence of meteorological factors on the transmission of COVID-19. The results revealed seasonal variations in the number of COVID-19-infected people. COVID-19 transmission was greatly aggravated by temperature, wind speed, nitric oxide (NO) and barometric pressure (BP) during summer seasons, whereas wind speed and BP aggravated COVID-19 transmission during rainy seasons. Furthermore, PM 2.5, NO and BP aggravated COVID-19 transmission during winter seasons. However, their relationships fluctuated seasonally. Our research shows that seasonal influences must be considered when developing effective interventions. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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10 pages, 16670 KiB

Open AccessArticle

Exacerbation of Fatality Rates Induced by Poor Air Quality Due to Open-Air Mass Funeral Pyre Cremation during the Second Wave of COVID-19

by M. G. Manoj, M. K. Satheesh Kumar, K. T. Valsaraj, Soumya K. Vijayan and T. Nishanth

Toxics 2022, 10(6), 306; https://doi.org/10.3390/toxics10060306 - 6 Jun 2022

Cited by 4 | Viewed by 2228

Abstract

This study investigates the air pollution-induced mortality rate during the second wave of COVID-19, which claimed several thousand lives in the capital city of India, New Delhi, even during a lockdown period. Delhi is a hotspot of unhealthy air quality. During the second [...] Read more.

This study investigates the air pollution-induced mortality rate during the second wave of COVID-19, which claimed several thousand lives in the capital city of India, New Delhi, even during a lockdown period. Delhi is a hotspot of unhealthy air quality. During the second wave of COVID-19 in 2021, surface ozone levels were observed to be higher, which had a direct impact on lung function, thereby making people more susceptible to COVID-19. The correlation coefficient between surface ozone concentration and mortality has been observed to be 0.74 at a 95% confidence level. This work focuses on the plausible impact and feedback of poor air quality induced by the burning of open-air funeral pyres due to the increased COVID-19 mortality rate in New Delhi, estimated by using an epidemiological model (AirQ+) of the World Health Organization. The mortality rate estimated quantitatively with the aid of AirQ+ is 1.27 excess deaths per 100,000 population due to surface ozone from pyre burning. The findings suggest transformational system goals before the resurgence of a subsequent wave. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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24 pages, 11407 KiB

Open AccessArticle

Transport Characteristics and Transmission Risk of Virus-Containing Droplets from Coughing in Outdoor Windy Environment

by Guoyi Jiang, Fengjiao Li and Tingting Hu

Toxics 2022, 10(6), 294; https://doi.org/10.3390/toxics10060294 - 29 May 2022

Cited by 5 | Viewed by 1768

Abstract

Particle dispersions have been widely studied inside rooms, but few databases have examined the transmission risk of respiratory droplets outdoors. This study investigated the wind effect on the dispersion of coughed droplets and the influence of social distancing on the infection risk in [...] Read more.

Particle dispersions have been widely studied inside rooms, but few databases have examined the transmission risk of respiratory droplets outdoors. This study investigated the wind effect on the dispersion of coughed droplets and the influence of social distancing on the infection risk in different susceptible persons using computational fluid dynamics simulations. Infection risk was evaluated based on direct depositions and exposure fractions. The results indicated that a reverse and upward flow formed in front of an infected man, and it enhanced as the wind strengthened, which transported more medium particles higher and increased the deposition on both infected and susceptible persons. Small particles moved above the neck, and they rarely deposited on the body. Medium particles larger than 60 μm were more likely to deposit and could reach the head of a healthy person under stronger winds. The exposure fraction achieved peak values when numerous particles passed the breathing zone. Although longer social distancing could alleviate the particle deposition on the face and delay the most dangerous time, its effect on infection risk was ambiguous. The infection risk was larger for a shorter susceptible person because more particles were deposited on the face, and the exposure fraction contributed by particles above the neck was larger. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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14 pages, 3315 KiB

Open AccessArticle

Modelling the Effect of COVID-19 Lockdown on Air Pollution in Makkah Saudi Arabia with a Supervised Machine Learning Approach

by Turki M. Habeebullah, Said Munir, Jahan Zeb and Essam A. Morsy

Toxics 2022, 10(5), 225; https://doi.org/10.3390/toxics10050225 - 29 Apr 2022

Cited by 8 | Viewed by 2160

Abstract

To reduce the spread of COVID-19, lockdowns were implemented in almost every single country in the world including Saudi Arabia. In this paper, the effect of COVID-19 lockdown on O₃, NO₂, and PM₁₀ in Makkah was analysed using [...] Read more.

To reduce the spread of COVID-19, lockdowns were implemented in almost every single country in the world including Saudi Arabia. In this paper, the effect of COVID-19 lockdown on O₃, NO₂, and PM₁₀ in Makkah was analysed using air quality and meteorology data from five sites. Two approaches were employed: (a) comparing raw measured concentrations for the lockdown period in 2019 and 2020; and (b) comparing weather-corrected concentrations estimated by the machine learning approach with observed concentrations during the lockdown period. According to the first approach, the average levels of PM₁₀ and NO₂ decreased by 12% and 58.66%, respectively, whereas the levels of O₃ increased by 68.67%. According to the second approach, O₃ levels increased by 21.96%, while the levels of NO₂ and PM₁₀ decreased by 13.40% and 9.66%, respectively. The machine learning approach after removing the effect of changes in weather conditions demonstrated relatively less reductions in the levels of NO₂ and PM₁₀ and a smaller increase in the levels of O₃. This showed the importance of adjusting air pollutant levels for meteorological conditions. O₃ levels increased due to its inverse correlation with NO₂, which decreased during the lockdown period. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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14 pages, 1885 KiB

Open AccessArticle

Moss Biomonitoring of Atmospheric Pollution with Trace Elements in the Moscow Region, Russia

by Konstantin Vergel, Inga Zinicovscaia, Nikita Yushin, Omari Chaligava, Pavel Nekhoroshkov and Dmitrii Grozdov

Toxics 2022, 10(2), 66; https://doi.org/10.3390/toxics10020066 - 2 Feb 2022

Cited by 14 | Viewed by 1965

Abstract

For the first time, moss biomonitoring covering the territory of the entire Moscow region, without including Moscow, was performed in 2020. Moss Pleurozium schreberi collected at 156 sampling sites were analyzed using neutron activation analysis and atomic absorption spectrometry. A total of 34 [...] Read more.

For the first time, moss biomonitoring covering the territory of the entire Moscow region, without including Moscow, was performed in 2020. Moss Pleurozium schreberi collected at 156 sampling sites were analyzed using neutron activation analysis and atomic absorption spectrometry. A total of 34 elements were determined in moss samples. Obtained data were compared with the results of the moss surveys performed in the Vladimir and Yaroslavl regions in 2018 and with the data of moss surveys conducted in the Moscow region on a limited number of sampling sites in 2004 and 2014. The Moscow region showed to be more polluted than the Vladimir and Yaroslavl regions. In the the Moscow region, the decrease of the content of the main part of the elements over time was noted. Trace elements emission sources were identified and characterized using factor analysis. Contamination Factor, Pollution Load Index, and Ecological Risk were calculated to assess the level of the region contamination and elements effect on human health. In general, the Moscow region can be characterized as unpolluted to moderately polluted with a low ecological risk of human exposure. The cities satellites around Moscow were determined to experience particular environmental stress, even in the period of the COVID-19 restrictions. Full article

(This article belongs to the Special Issue Air Pollution and COVID-19)

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