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1.
Environ Sci Pollut Res Int ; 29(15): 21682-21691, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1826837

ABSTRACT

As an air pollutant closely related to urban traffic and heavy industrial capacity, the variation of NO2 (nitrogen dioxide) concentration can directly reflect the strength of socioeconomic activities. Using the weekly average results of daily product synthesis of tropospheric NO2 column concentrations from OMI (Ozone Monitoring Instrument) satellite inversion, a weekly-scale variation series of standardized socioeconomic activity index during the Spring Festival period of 2019-2021 is constructed. The results show that the OMI-NO2 satellite data are in good consistency with ground-based monitoring data; the Spring Festival holiday also suppresses socioeconomic activity in normal years, but the coronavirus disease 2019 (COVID-19) epidemic leads to an extended period of 2-3 weeks of weakened socioeconomic activity in China after the holiday, while the minimum value of socioeconomic activity intensity decreases by 0.12. Although socioeconomic activity is significantly suppressed in the short term, the intensity of socioeconomic activity rises steadily with the gradual resumption of work and production everywhere from the third week after the Chinese Spring Festival and has reached 60.91% of the highest level before the holiday in the seventh week after the holiday. OMI-NO2 satellite data can be used for a rapid assessment of the intensity of air pollution emissions and the level of socioeconomic activity in different regions.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , China , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Socioeconomic Factors
3.
Nat Commun ; 13(1): 1839, 2022 Apr 05.
Article in English | MEDLINE | ID: covidwho-1778601

ABSTRACT

India as a hotspot for air pollution has heavy black carbon (BC) and dust (DU) loadings. BC has been identified to significantly impact the Indian climate. However, whether BC-climate interactions regulate Indian DU during the premonsoon season is unclear. Here, using long-term Reanalysis data, we show that Indian DU is positively correlated to northern Indian BC while negatively correlated to southern Indian BC. We further identify the mechanism of BC-dust-climate interactions revealed during COVID-19. BC reduction in northern India due to lockdown decreases solar heating in the atmosphere and increases surface albedo of the Tibetan Plateau (TP), inducing a descending atmospheric motion. Colder air from the TP together with warmer southern Indian air heated by biomass burning BC results in easterly wind anomalies, which reduces dust transport from the Middle East and Sahara and local dust emissions. The premonsoon aerosol-climate interactions delay the outbreak of the subsequent Indian summer monsoon.


Subject(s)
Air Pollutants , COVID-19 , Aerosols/analysis , Air Pollutants/analysis , COVID-19/epidemiology , Carbon/analysis , Communicable Disease Control , Dust , Environmental Monitoring/methods , Humans , India/epidemiology , Seasons
4.
Huan Jing Ke Xue ; 43(4): 1747-1755, 2022 Apr 08.
Article in Chinese | MEDLINE | ID: covidwho-1776689

ABSTRACT

Volatile organic compounds (VOCs) are the key precursors of the ozone (O3) formation processes in the troposphere and are important control objects for the coordinated governance of O3 and PM2.5. The Spring Festival of 2020 was affected by the novel coronavirus (COVID-19) pneumonia epidemic:companies stopped work and production, and traffic was restricted, providing scientific experimentation opportunities for pollutant emission reduction research. This study analyzed the variety of the composition, chemical reaction activity, and sources of VOCs in the Pearl River Delta during the Spring Festival and the epidemic control period, using real-time online monitoring data of VOCs obtained at four sites(Guangzhou, Dongguan, Zhongshan, and Duanfen)in the Pearl River Delta from January 1, 2020 to February 29, 2020. The results showed that during the Spring Festival and the epidemic control period, the average of φ (VOCs) in the Pearl River Delta was 15.89×10-9, and the maximum hourly average concentration was 45.43×10-9, values that were 44% and 60% lower, respectively, than those before the Spring Festival holiday. Among the VOCs component concentration decreases, the aromatic hydrocarbon component decreased the most, and the decrease in the urban area of the Pearl River Delta (74%) was significantly greater than that in the suburban area (56%). As a result, the contribution rate of aromatic hydrocarbons to the total VOCs was reduced to less than 10%. The analysis of the·OH reaction activity of VOCs(L·OH)and ozone formation potential(OFP)showed that the L·OH and OFP of VOCs decreased significantly in the Pearl River Delta during the Spring Festival and the epidemic control period. Compared with those before the Spring Festival holiday, the total L·OH and total OFP decreased by an average of 60% and 63% in the urban area of the Pearl River Delta, respectively. Additionally, the atmospheric oxidation had also been significantly reduced, which showed a 28% decrease in ρ(Ox). The ratio of toluene/benzene showed that the influence of industrial sources had almost disappeared during the Spring Festival and the epidemic control period, and the total points of the representative components of industrial-related solvent-use sources such as toluene, ethylbenzene, and m/p-xylene dropped by 72% to 91%. The results of this study suggest that solvent-use sources and vehicle exhaust emission sources are the current sources of VOCs that need to be paid attention to in the prevention and control of O3 pollution in the Pearl River Delta region, and the impact of petrochemical sources cannot be ignored in the work of further reducing the background concentration of O3.


Subject(s)
Air Pollutants , COVID-19 , Ozone , Volatile Organic Compounds , Air Pollutants/analysis , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Environmental Monitoring/methods , Holidays , Humans , Ozone/analysis , Solvents/analysis , Toluene/analysis , Vehicle Emissions/analysis , Volatile Organic Compounds/analysis
5.
Front Public Health ; 10: 843862, 2022.
Article in English | MEDLINE | ID: covidwho-1776053

ABSTRACT

From 2013 to 2017, progress has been made by implementing the Air Pollution Prevention and Control Action Plan. Under the background of the 3 Year Action Plan to Fight Air Pollution (2018-2020), the pollution status of PM2.5, a typical air pollutant, has been the focus of continuous attention. The spatiotemporal specificity of PM2.5 pollution in the Chinese urban atmospheric environment from 2018 to 2020 can be summarized to help conclude and evaluate the phased results of the battle against air pollution, and further, contemplate the governance measures during the period of the 14th Five-Year Plan (2021-2025). Based on PM2.5 data from 2018 to 2020 and taking 366 cities across China as research objects, this study found that PM2.5 pollution has improved year by year from 2018 to 2020, and that the heavily polluted areas were southwest Xinjiang and North China. The number of cities with a PM2.5 concentration in the range of 25-35 µg/m3 increased from 34 in 2018 to 86 in 2019 and 99 in 2020. Moreover, the spatial variation of the PM2.5 gravity center was not significant. Concretely, PM2.5 pollution in 2018 was more serious in the first and fourth quarters, and the shift of the pollution's gravity center from the first quarter to the fourth quarter was small. Global autocorrelation indicated that the space was positively correlated and had strong spatial aggregation. Local Moran's I and Local Geti's G were applied to identify hotspots with a high degree of aggregation. Integrating national population density, hotspots were classified into four areas: the Beijing-Tianjin-Hebei region, the Fenwei Plain, the Yangtze River Delta, and the surrounding areas were selected as the key hotspots for further geographic weighted regression analysis in 2018. The influence degree of each factor on the average annual PM2.5 concentration declined in the following order: (1) the proportion of secondary industry in the GDP, (2) the ownership of civilian vehicles, (3) the annual grain planting area, (4) the annual average population, (5) the urban construction land area, (6) the green space area, and (7) the per capita GDP. Finally, combined with the spatiotemporal distribution of PM2.5, specific suggestions were provided for the classified key hotspots (Areas A, B, and C), to provide preliminary ideas and countermeasures for PM2.5 control in deep-water areas in the 14th Five-Year Plan.


Subject(s)
Environmental Monitoring , Particulate Matter , Socioeconomic Factors , China/epidemiology , Cities , Environmental Monitoring/methods , Humans , Particulate Matter/analysis , Policy , Spatio-Temporal Analysis
6.
Environ Sci Pollut Res Int ; 29(15): 21682-21691, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1750807

ABSTRACT

As an air pollutant closely related to urban traffic and heavy industrial capacity, the variation of NO2 (nitrogen dioxide) concentration can directly reflect the strength of socioeconomic activities. Using the weekly average results of daily product synthesis of tropospheric NO2 column concentrations from OMI (Ozone Monitoring Instrument) satellite inversion, a weekly-scale variation series of standardized socioeconomic activity index during the Spring Festival period of 2019-2021 is constructed. The results show that the OMI-NO2 satellite data are in good consistency with ground-based monitoring data; the Spring Festival holiday also suppresses socioeconomic activity in normal years, but the coronavirus disease 2019 (COVID-19) epidemic leads to an extended period of 2-3 weeks of weakened socioeconomic activity in China after the holiday, while the minimum value of socioeconomic activity intensity decreases by 0.12. Although socioeconomic activity is significantly suppressed in the short term, the intensity of socioeconomic activity rises steadily with the gradual resumption of work and production everywhere from the third week after the Chinese Spring Festival and has reached 60.91% of the highest level before the holiday in the seventh week after the holiday. OMI-NO2 satellite data can be used for a rapid assessment of the intensity of air pollution emissions and the level of socioeconomic activity in different regions.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , China , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Socioeconomic Factors
7.
Environ Monit Assess ; 194(4): 272, 2022 Mar 11.
Article in English | MEDLINE | ID: covidwho-1739367

ABSTRACT

Coronavirus disease 2019 (COVID-19) pandemic adversely affected human beings. The novel coronavirus has claimed millions of lives all over the globe. Most countries around the world, including Pakistan, restricted people's social activities and ordered strict lockdowns throughout the country, to control the fatality of the novel coronavirus. The persuaded lockdown impact on the local environment was estimated. In the present study, we assessed air quality changes in four cities of Pakistan, namely Islamabad, Karachi, Lahore, and Peshawar, based on particulate matter (PM2.5), using "Temtop Airing 1000," which is capable of detecting and quantifying PM2.5. The Air Quality Index (AQI) was evaluated in three specific time spans: the COVID-19 pandemic pre- and post-lockdown period (January 1, 2020 to March 20, 2020, and May 16, 2020 to June 30, 2020 respectively), and the COVID-19 pandemic period (March 21 2020 to May 15, 2020). We compared land-monitored AQI levels for the above three periods of time. For validation, air quality was navigated by the Moderate Resolution Imaging Spectrometer (MODIS) satellite during the first semester (January 1 to June 30) of 2019 and 2020. It is seen that the concentration of PM2.5 was considerably reduced in 2020 (more than 50%), ranging from ~ 0.05 to 0.3 kg⋅m3, compared to the same period in 2019. The results revealed that the AQI was considerably reduced during the lockdown period. This finding is a very promising as the inhabitants of the planet Earth can be guaranteed the possibility of a green environment in the future.


Subject(s)
Air Pollutants , COVID-19 , Environmental Restoration and Remediation , Air Pollutants/analysis , COVID-19/epidemiology , Communicable Disease Control , Environmental Monitoring/methods , Humans , Pakistan/epidemiology , Pandemics , SARS-CoV-2
8.
Huan Jing Ke Xue ; 43(3): 1268-1276, 2022 Mar 08.
Article in Chinese | MEDLINE | ID: covidwho-1732501

ABSTRACT

Many restrictive measures were implemented in China from January-February 2020 to control the rapid spread of COVID-19. Many studies reported that the COVID-19 lockdown impacted PM2.5, SO2, volatile organic compounds (VOCs), etc. VOCs play important roles in the production of ozone and PM2.5. Ambient VOCs in Xiong'an were measured from December 25, 2019 to January 24, 2020 (prior to epidemic prevention, P1) and from January 25, 2020 to February 24, 2020 (during epidemic prevention, P2) through a VOCs online instrument. In the study, VOCs characteristics and ozone generation potential (OFP) of ambient VOCs were analyzed, and source apportionment of VOCs were analyzed by using Positive Matrix Factorization (PMF). The results showed that φ(TVOCs) during epidemic prevention and control was 45.1×10-9, which was approximately half of that before epidemic prevention and control (90.5×10-9). The chemical composition of VOCs showed significant changes after epidemic prevention and control, the contribution rate of alkanes increased from 37.6% to 53.8%, and the contribution rate of aromatic hydrocarbons and halogenated hydrocarbons decreased from 13.3% and 12.0% to 7.5% and 7.8%, respectively. Aromatic hydrocarbons, halogenated hydrocarbons, and OVOCs decreased by more than 60%. Seven types of the top ten species were the same before and during the epidemic prevention and control, mainly low-carbon alkanes, olefins, aldehydes, and ketones. Dichloromethane, trichloromethane, and BTEXs decreased significantly. The OPP was 566 µg·m-3 and 231 µg·m-3 in P1 and P2, respectively. The OPP of VOCs decreased by more than 30%. The proportion of OFP contribution of aromatic hydrocarbons decreased significantly after the epidemic prevention and control, and the proportion of OFP contribution of alkanes and alkynes increased significantly. Positive matrix factorization (PMF) was then applied for VOCs sources apportionment. Six sources were identified, including background sources, oil-gas volatile sources, combustion sources, industrial sources, solvent use sources, and vehicle exhaust sources. The results showed that after the epidemic prevention and control, the contribution rate of solvent use sources to TVOCs decreased from 24% to 9%. The contribution rates of background sources, oil-gas volatile sources, and combustion sources increased from 13%, 34%, and 24% to 6%, 14%, and 13%, respectively. The relative contributions of vehicle exhaust sources before and after epidemic prevention and control were 21% and 18%, respectively. The observation points were affected by the emission of VOCs from paroxysmal industrial sources before the epidemic prevention and control. The emission was stopped after the epidemic prevention and control, and its contribution rate was reduced from 22% before the epidemic prevention and control to 1%. The concentrations of industrial sources, solvent sources, motor vehicle tail gas sources, and combustion sources decreased by 97%, 82%, 61%, and 15%, respectively, after the epidemic prevention and control. The concentration of background sources remained stable, and the concentration of oil and gas volatile sources increased by 7%. The control of production and traffic activities cannot reduce the emission of VOCs from oil and gas volatile sources, which is the focus of VOCs control in Xiong'an.


Subject(s)
Air Pollutants , COVID-19 , Ozone , Volatile Organic Compounds , Air Pollutants/analysis , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Communicable Disease Control , Environmental Monitoring/methods , Humans , Ozone/analysis , SARS-CoV-2 , Vehicle Emissions/analysis , Volatile Organic Compounds/analysis
9.
Int J Environ Res Public Health ; 19(4)2022 02 21.
Article in English | MEDLINE | ID: covidwho-1715324

ABSTRACT

Airborne pollen monitoring has been an arduous task, making ecological applications and allergy management virtually disconnected from everyday practice. Over the last decade, intensive research has been conducted worldwide to automate this task and to obtain real-time measurements. The aim of this study was to evaluate such an automated biomonitoring system vs. the conventional 'gold-standard' Hirst-type technique, attempting to assess which may more accurately provide the genuine exposure to airborne pollen. Airborne pollen was monitored in Augsburg since 2015 with two different methods, a novel automatic Bio-Aerosol Analyser, and with the conventional 7-day recording Hirst-type volumetric trap, in two different sites. The reliability, performance, accuracy, and comparability of the BAA500 Pollen Monitor (PoMo) vs. the conventional device were investigated, by use of approximately 2.5 million particles sampled during the study period. The observations made by the automated PoMo showed an average accuracy of approximately 85%. However, it also exhibited reliability problems, with information gaps within the main pollen season of between 17 to 19 days. The PoMo automated algorithm had identification issues, mainly confusing the taxa of Populus, Salix and Tilia. Hirst-type measurements consistently exhibited lower pollen abundances (median of annual pollen integral: 2080), however, seasonal traits were more comparable, with the PoMo pollen season starting slightly later (median: 3 days), peaking later (median: 5 days) but also ending later (median: 14 days). Daily pollen concentrations reported by Hirst-type traps vs. PoMo were significantly, but not closely, correlated (r = 0.53-0.55), even after manual classification. Automatic pollen monitoring has already shown signs of efficiency and accuracy, despite its young age; here it is suggested that automatic pollen monitoring systems may be more effective in capturing a larger proportion of the airborne pollen diversity. Even though reliability issues still exist, we expect that this new generation of automated bioaerosol monitoring will eventually change the aerobiological era, as known for almost 70 years now.


Subject(s)
Allergens , Environmental Monitoring , Environmental Monitoring/methods , Pollen , Reproducibility of Results , Seasons
10.
Water Res ; 215: 118241, 2022 May 15.
Article in English | MEDLINE | ID: covidwho-1713026

ABSTRACT

Information regarding water clarity at large spatiotemporal scales is critical for understanding comprehensive changes in the water quality and status of ecosystems. Previous studies have suggested that satellite observation is an effective means of obtaining such information. However, a reliable model for accurately mapping the water clarity of global lakes (reservoirs) is still lacking due to the high optical complexity of lake waters. In this study, by using gated recurrent units (GRU) layers instead of full-connected layers from Artificial Neural Networks (ANNs) to capture the efficient sequence information of in-situ datasets, we propose a novel and transferrable hybrid deep-learning-based recurrent model (DGRN) to map the water clarity of global lakes with Landsat 8 Operational Land Imager (OLI) images. We trained and further validated the model using 1260 pairs of in-situ measured water clarity and surface reflectance of Landsat 8 OLI images with Google Earth Engine. The model was subsequently utilized to construct the global pattern of temporal and spatial changes in water clarity (lake area>10 km2) from 2014 to 2020. The results show that the model can estimate water clarity with good performance (R2 = 0.84, MAE = 0.55, RMSE = 0.83, MAPE = 45.13%). The multi-year average of water clarity for global lakes (16,475 lakes) ranged from 0.0004 to 9.51 m, with an average value of 1.88 ± 1.24 m. Compared to the lake area, elevation, discharge, residence time, and the ratio of area to depth, water depth was the most important factor that determined the global spatial distribution pattern of water clarity. Water clarity of 15,840 global lakes between 2014 and 2020 remained stable (P ≥ 0.05); while there was a significant increase in 243 lakes (P < 0.05) and a decrease in 392 lakes (P < 0.05). However, water clarity in 2020 (COVID-19 period) showed a significant increase in most global lakes, especially in China and Canada, suggesting that the worldwide lockdown strategy due to COVID-19 might have improved water quality, espically water clarity, dueto the apparent reduction of anthropogenic activities.


Subject(s)
COVID-19 , Deep Learning , Communicable Disease Control , Ecosystem , Environmental Monitoring/methods , Humans , Lakes , Water Quality
11.
Environ Monit Assess ; 194(3): 195, 2022 Feb 17.
Article in English | MEDLINE | ID: covidwho-1694440

ABSTRACT

The COVID-19 pandemic has created a major threat to human beings and huge losses over the globe. In order to control the pandemic spread, almost all parts of the world imposed lockdown. The imposed lockdown drastically impacted on reduction in the atmospheric pollutions and also resulted in net decrease in aerosol optical depth (AOD) in the atmosphere. In this study, the reduction in the AOD during the COVID-19 lockdown over the Indian subcontinent is being assessed using the moderate resolution imaging spectroradiometer (MODIS) satellite data available in Giovanni version 4.34 developed by NASA. The long-term mean analysis is computed considering 20 years (i.e., 2000-2019) data on Terra platform with a temporal resolution of daily and monthly and spatial resolution of 1 degree. The dataset of AOD with a temporal resolution of monthly was used for investigation of AOD anomaly for March, April and May 2020, and the seasonal variation (March to May 2020) is also assessed. Similarly, the daily scale dataset was used to investigate the percentage change in AOD during pre-lockdown and lockdown period with respect to long-term mean. The key findings in the present study show that reduction in AOD level over Indian subcontinent is approximately 14.75% during the lockdown period with spatial variation in the magnitude from region to region. The level of AOD is greatly reduced in the northern part of India (~ 22.53%), whereas changes in the southern part of India are much less (~ -0.31%); this may be due to ongoing anthropogenic activities during the lockdown period in this region. Furthermore, a positive AOD anomaly was observed in the eastern and central regions of India (i.e., over the states of Odisha, Chhattisgarh, Telangana, Jharkhand, West Bengal, Part of Maharashtra and Karnataka). However, negative AOD anomaly was observed in the north and northwest regions of India, whereas not much change in the AOD anomaly in other parts of the country. The overall assessment of the AOD level shows a net decrease over the Indian subcontinent during the lockdown period, i.e., March to May 2020. This kind of assessment study will surely help the government for the sustainable policy decisions for atmospheric pollution control by implementing proper lockdown procedures over various parts of the country.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Aerosols/analysis , Air Pollutants/analysis , Air Pollution/analysis , Communicable Disease Control , Environmental Monitoring/methods , Humans , India , Pandemics , SARS-CoV-2
12.
Mar Pollut Bull ; 175: 113356, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1683416

ABSTRACT

This study investigated the year-to-year variability in the occurrence, abundance and sources of oil spills in the Eastern Arabian Sea (EAS) using sentinel-1 imagery and identified the potential oil spills vulnerable zones. The four consecutive year's data acquired from 2017 to 2020 (March-May) reveal three oil spill hot spot zones. The ship-based oil spills were dominant over zone's-1 (off Gujarat) and 3 (off Karnataka and Kerala), and the oil field based over zone-2 (off Maharashtra). The abundance of oil spills was significantly low in zone-1, only 14.30km2 (1.2%) during lock-down due to the covid-19 pandemic. Whereas, the year-to-year oil spills over zone's 2 and 3 are not significantly varied (170.29 km2 and 195.01 km2), further suggesting the influence of oil exploration and international tanker traffic are in operation during the lock-down. This study further recommends that manual clustering is the best method to study the distribution of unknown oil spills.


Subject(s)
COVID-19 , Petroleum Pollution , Communicable Disease Control , Environmental Monitoring/methods , Humans , India , Pandemics , Petroleum Pollution/analysis , SARS-CoV-2 , Ships
13.
Sci Total Environ ; 817: 153002, 2022 Apr 15.
Article in English | MEDLINE | ID: covidwho-1648802

ABSTRACT

COVID-19 lockdown brought to a drastic reduction of anthropic impacts on the environment worldwide, including the marine-coastal system. Earth-Observation (EO) data have the potential to monitor and diagnose the effects of the lockdown in terms of water quality. Here we connect the dots among some coastal environmental changes that occurred during the Italian COVID-19 lockdown by using EO data, also seeking to assess connectivity between inland and marine systems. We present a holistic analysis of spatial and temporal variability of environmental parameters in the North Adriatic Sea, Mediterranean basin, exploiting the synergy of different satellite sensors, as well as hydrologic data from in situ observations. Our analysis indicates a favourable interplay of environmental variability that resulted in negative anomalies of Chlorophyll-a concentration, with respect to the climatologic values. Peculiar meteo-oceanographic and hydrological conditions made hard to disentangle potential anthropogenic effects. However, a multi-year hierarchical cluster analysis of riverine remote sensing reflectances groups together the optical properties of inland waters during the lockdown. This emergent cluster highlights the possibility of a second-order, anthropogenic effect that, superimposed to the (first-order) environmental natural causes, may have enhanced water quality during the lockdown.


Subject(s)
COVID-19 , COVID-19/epidemiology , Chlorophyll A , Communicable Disease Control , Environmental Monitoring/methods , Humans , Perception , SARS-CoV-2
14.
Sci Total Environ ; 823: 153786, 2022 Jun 01.
Article in English | MEDLINE | ID: covidwho-1676913

ABSTRACT

In response to the COVID-19 pandemic, governments declared severe restrictions throughout 2020, presenting an unprecedented scenario of reduced anthropogenic emissions of air pollutants derived mainly from traffic sources. To analyze the effect of these restrictions derived from COVID-19 pandemic on air quality levels, relative changes in NO, NO2, O3, PM10 and PM2.5 concentrations were calculated at urban traffic sites in the most populated Spanish cities over different periods with distinct restrictions in 2020. In addition to the changes calculated with respect to the observed air pollutant levels of previous years (2013-2019), relative changes were also calculated using predicted pollutant levels for the different periods over 2020 on a business-as-usual scenario using Multiple Linear Regression (MLR) models with meteorological and seasonal predictors. MLR models were selected among different data mining techniques (MLR, Random Forest (RF), K-Nearest Neighbors (KNN)), based on their higher performance and accuracy obtained from a leave-one-year-out cross-validation scheme using 2013-2019 data. A q-q mapping post-correction was also applied in all cases in order to improve the reliability of the predictions to reproduce the observed distributions and extreme events. This approach allows us to estimate the relative changes in the studied air pollutants only due to COVID-19 restrictions. The results obtained from this approach show a decreasing pattern for NOx, with the largest reduction in the lockdown period above -50%, whereas the increase observed for O3 contrasts with the NOx patterns with a maximum increase of 23.9%. The slight reduction in PM10 (-4.1%) and PM2.5 levels (-2.3%) during lockdown indicates a lower relationship with traffic sources. The developed methodology represents a simple but robust framework for exploratory analysis and intervention detection in air quality studies.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Cities , Communicable Disease Control , Data Mining , Environmental Monitoring/methods , Humans , Pandemics , Particulate Matter/analysis , Reproducibility of Results , Spain
15.
Sci Total Environ ; 824: 153756, 2022 Jun 10.
Article in English | MEDLINE | ID: covidwho-1676911

ABSTRACT

During the first period of the SARS-CoV-2 pandemic, the lack of specific therapeutic treatments led to the provisional use of a number of drugs, with a continuous review of health protocols when new scientific evidence emerged. The management of this emergency sanitary situation could not take care of the possible indirect adverse effects on the environment, such as the release of a large amount of pharmaceuticals from wastewater treatment plants. The massive use of drugs, which were never used so widely until then, implied new risks for the aquatic environment. In this study, a suspect screening approach using Liquid Chromatography-High Resolution Mass Spectrometry techniques, allowed us to survey the presence of pharmaceuticals used for COVID-19 treatment in three WWTPs of Lombardy region, where the first European cluster of SARS-CoV-2 cases was detected. Starting from a list of sixty-three suspect compounds used against COVID-19 (including some metabolites and transformation products), six compounds were fully identified and monitored together with other target analytes, mainly pharmaceuticals of common use. A monthly monitoring campaign was conducted in a WWTP from April to December 2020 and the temporal trends of some anti-COVID-19 drugs were positively correlated with those of COVID-19 cases and deaths. The comparison of the average emission loads among the three WWTPs evidenced that the highest loads of hydroxychloroquine, azithromycin and ciprofloxacin were measured in the WWTP which received the sewages from a hospital specializing in the treatment of COVID-19 patients. The monitoring of the receiving water bodies evidenced the presence of eight compounds of high ecological concern, whose risk was assessed in terms of toxicity and the possibility of inducing antibiotic and viral resistance. The results clearly showed that the enhanced, but not completely justified, use of ciprofloxacin and azithromycin represented a risk for antibiotic resistance in the aquatic ecosystems.


Subject(s)
COVID-19 , Water Pollutants, Chemical , Azithromycin/adverse effects , COVID-19/drug therapy , COVID-19/epidemiology , Ciprofloxacin/analysis , Ecosystem , Environmental Monitoring/methods , Humans , Pharmaceutical Preparations , SARS-CoV-2 , Waste Water/chemistry , Water Pollutants, Chemical/analysis
16.
Yakugaku Zasshi ; 142(1): 11-15, 2022.
Article in Japanese | MEDLINE | ID: covidwho-1609123

ABSTRACT

The polio eradication program, launched in 1988, has successfully decreased the number of poliomyelitis patients worldwide. However, in areas with immunization gaps where oral polio vaccine coverage has dropped, outbreaks of more virulent vaccine-derived polioviruses (VDPVs) have become a threat to public health. In Japan, inactivated polio vaccine replaced oral polio vaccine as the routine immunization in 2012. Polio environmental surveillance (ES) has been conducted nationwide since 2013 to efficiently monitor the wild type poliovirus or VDPV, which may be imported from overseas. ES may also be utilized to detect other viruses in stool samples. We propose a method of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection based on the polio ES network, and establish a procedure to detect fragments of SARS-CoV-2 genome in wastewater solids. Our findings suggest that polio ES can be used to simultaneously monitor SARS-CoV-2 RNA fragments in sewage waters.


Subject(s)
Environmental Monitoring/methods , Poliovirus/isolation & purification , SARS-CoV-2/isolation & purification , Sewage/virology , Waste Water/virology , Disease Eradication , Humans , Japan , Poliovirus Vaccine, Inactivated , RNA, Viral/isolation & purification , SARS-CoV-2/genetics
17.
Viruses ; 13(7)2021 07 13.
Article in English | MEDLINE | ID: covidwho-1597522

ABSTRACT

Environmental surveillance was recommended for risk mitigation in a novel oral polio vaccine-2 (nOPV2) clinical trial (M5-ABMG) to monitor excretion, potential circulation, and loss of attenuation of the two nOPV2 candidates. The nOPV2 candidates were developed to address the risk of poliovirus (PV) type 2 circulating vaccine-derived poliovirus (cVDPV) as part of the global eradication strategy. Between November 2018 and January 2020, an environmental surveillance study for the clinical trial was conducted in parallel to the M5-ABMG clinical trial at five locations in Panama. The collection sites were located upstream from local treatment plant inlets, to capture the excreta from trial participants and their community. Laboratory analyses of 49 environmental samples were conducted using the two-phase separation method. Novel OPV2 strains were not detected in sewage samples collected during the study period. However, six samples were positive for Sabin-like type 3 PV, two samples were positive for Sabin-like type 1 PV, and non-polio enteroviruses NPEVs were detected in 27 samples. One of the nOPV2 candidates has been granted Emergency Use Listing by the World Health Organization and initial use started in March 2021. This environmental surveillance study provided valuable risk mitigation information to support the Emergency Use Listing application.


Subject(s)
Environmental Monitoring/methods , Poliomyelitis/prevention & control , Poliovirus/immunology , Humans , Panama/epidemiology , Poliomyelitis/virology , Poliovirus/pathogenicity , Poliovirus Vaccine, Oral/analysis , Risk Assessment/methods , Sewage/virology , Vaccines
18.
PLoS One ; 16(12): e0259996, 2021.
Article in English | MEDLINE | ID: covidwho-1592627

ABSTRACT

OBJECTIVES: To evaluate (1) the relationship between heating, ventilation, and air conditioning (HVAC) systems and bioaerosol concentrations in hospital rooms, and (2) the effectiveness of laminar air flow (LAF) and high efficiency particulate air (HEPA) according to the indoor bioaerosol concentrations. METHODS: Databases of Embase, PubMed, Cochrane Library, MEDLINE, and Web of Science were searched from 1st January 2000 to 31st December 2020. Two reviewers independently extracted data and assessed the quality of the studies. The samples obtained from different areas of hospitals were grouped and described statistically. Furthermore, the meta-analysis of LAF and HEPA were performed using random-effects models. The methodological quality of the studies included in the meta-analysis was assessed using the checklist recommended by the Agency for Healthcare Research and Quality. RESULTS: The mean CFU/m3 of the conventional HVAC rooms and enhanced HVAC rooms was lower than that of rooms without HVAC systems. Furthermore, the use of the HEPA filter reduced bacteria by 113.13 (95% CI: -197.89, -28.38) CFU/m3 and fungi by 6.53 (95% CI: -10.50, -2.55) CFU/m3. Meanwhile, the indoor bacterial concentration of LAF systems decreased by 40.05 (95% CI: -55.52, -24.58) CFU/m3 compared to that of conventional HVAC systems. CONCLUSIONS: The HVAC systems in hospitals can effectively remove bioaerosols. Further, the use of HEPA filters is an effective option for areas that are under-ventilated and require additional protection. However, other components of the LAF system other than the HEPA filter are not conducive to removing airborne bacteria and fungi. LIMITATION OF STUDY: Although our study analysed the overall trend of indoor bioaerosols, the conclusions cannot be extrapolated to rare, hard-to-culture, and highly pathogenic species, as well as species complexes. These species require specific culture conditions or different sampling requirements. Investigating the effects of HVAC systems on these species via conventional culture counting methods is challenging and further analysis that includes combining molecular identification methods is necessary. STRENGTH OF THE STUDY: Our study was the first meta-analysis to evaluate the effect of HVAC systems on indoor bioaerosols through microbial incubation count. Our study demonstrated that HVAC systems could effectively reduce overall bioaerosol concentrations to maintain better indoor air quality. Moreover, our study provided further evidence that other components of the LAF system other than the HEPA filter are not conducive to removing airborne bacteria and fungi. PRACTICAL IMPLICATION: Our research showed that HEPA filters are more effective at removing bioaerosols in HVAC systems than the current LAF system. Therefore, instead of opting for the more costly LAF system, a filter with a higher filtration rate would be a better choice for indoor environments that require higher air quality; this is valuable for operating room construction and maintenance budget allocation.


Subject(s)
Air Conditioning/instrumentation , Air Pollution, Indoor/prevention & control , Environmental Monitoring/methods , Filtration/standards , Heating/instrumentation , Hospitals/standards , Ventilation/instrumentation , Air Pollution, Indoor/analysis , Environmental Monitoring/instrumentation , Equipment and Supplies, Hospital , Humans
19.
Sci Rep ; 11(1): 23378, 2021 12 16.
Article in English | MEDLINE | ID: covidwho-1585808

ABSTRACT

Emissions of black carbon (BC) particles from anthropogenic and natural sources contribute to climate change and human health impacts. Therefore, they need to be accurately quantified to develop an effective mitigation strategy. Although the spread of the emission flux estimates for China have recently narrowed under the constraints of atmospheric observations, consensus has not been reached regarding the dominant emission sector. Here, we quantified the contribution of the residential sector, as 64% (44-82%) in 2019, using the response of the observed atmospheric concentration in the outflowing air during Feb-Mar 2020, with the prevalence of the COVID-19 pandemic and restricted human activities over China. In detail, the BC emission fluxes, estimated after removing effects from meteorological variability, dropped only slightly (- 18%) during Feb-Mar 2020 from the levels in the previous year for selected air masses of Chinese origin, suggesting the contributions from the transport and industry sectors (36%) were smaller than the rest from the residential sector (64%). Carbon monoxide (CO) behaved differently, with larger emission reductions (- 35%) in the period Feb-Mar 2020, suggesting dominance of non-residential (i.e., transport and industry) sectors, which contributed 70% (48-100%) emission during 2019. The estimated BC/CO emission ratio for these sectors will help to further constrain bottom-up emission inventories. We comprehensively provide a clear scientific evidence supporting mitigation policies targeting reduction in residential BC emissions from China by demonstrating the economic feasibility using marginal abatement cost curves.


Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , COVID-19/prevention & control , Particulate Matter/analysis , SARS-CoV-2/isolation & purification , Soot/analysis , Algorithms , Atmosphere/analysis , COVID-19/epidemiology , COVID-19/virology , China , Climate Change , Environmental Monitoring/methods , Environmental Monitoring/statistics & numerical data , Geography , Human Activities , Humans , Models, Theoretical , Pandemics , Residence Characteristics , SARS-CoV-2/physiology , Seasons , Wind
20.
PLoS One ; 16(12): e0259713, 2021.
Article in English | MEDLINE | ID: covidwho-1546943

ABSTRACT

Observing social/physical distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically detect pairs of humans in a crowded scenario who are not maintaining social distancing, i.e. about 2 meters of space between them using an autonomous mobile robot and existing CCTV (Closed-Circuit TeleVision) cameras. The robot is equipped with commodity sensors, namely an RGB-D (Red Green Blue-Depth) camera and a 2-D lidar to detect social distancing breaches within their sensing range and navigate towards the location of the breach. Moreover, it discreetly alerts the relevant people to move apart by using a mounted display. In addition, we also equip the robot with a thermal camera that transmits thermal images to security/healthcare personnel who monitors COVID symptoms such as a fever. In indoor scenarios, we integrate the mobile robot setup with a static wall-mounted CCTV camera to further improve the number of social distancing breaches detected, accurately pursuing walking groups of people etc. We highlight the performance benefits of our robot + CCTV approach in different static and dynamic indoor scenarios.


Subject(s)
COVID-19/prevention & control , Environmental Monitoring/methods , Physical Distancing , Robotics , Algorithms , COVID-19/transmission , COVID-19/virology , Environmental Monitoring/instrumentation , Humans , Photography , SARS-CoV-2/isolation & purification
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