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1.
Int J Environ Res Public Health ; 19(23), 2022.
Article in English | PubMed | ID: covidwho-2163358

ABSTRACT

The mutual relationship among daily averaged PM(10), PM(2.5), and NO(2) concentrations in two megacities (Seoul and Busan) connected by the busiest highway in Korea was investigated using an artificial neural network model (ANN)-sigmoid function, for a novel coronavirus (COVID-19) pandemic period from 1 January to 31 December 2020. Daily and weekly mean concentrations of NO(2) in 2020 under neither locked down cities, nor limitation of the activities of vehicles and people by the Korean Government have decreased by about 15%, and 12% in Seoul, and Busan cities, than the ones in 2019, respectively. PM (10) (PM(2.5)) concentration has also decreased by 15% (10%), and 12% (10%) in Seoul, and Busan, with a similar decline of NO(2), causing an improvement in air quality in each city. Multilayer perception (MLP), which has a back-propagation training algorithm for a feed-forward artificial neural network technique with a sigmoid activation function was adopted to predict daily averaged PM(10), PM(2.5), and NO(2) concentrations in two cities with their interplay. Root mean square error (RMSE) with the coefficient of determination (R(2)) evaluates the performance of the model between the predicted and measured values of daily mean PM(10), PM(2.5), and NO(2,) in Seoul were 2.251 with 0.882 (1.909 with 0.896;1.913 with 0.892), 0.717 with 0.925 (0.955 with 0.930;0.955 with 0.922), and 3.502 with 0.729 (2.808 with 0.746;3.481 with 0.734), in 2 (5;7) nodes in a single hidden layer. Similarly, they in Busan were 2.155 with 0.853 (1.519 with 0.896;1.649 with 0.869), 0.692 with 0.914 (0.891 with 0.910;1.211 with 0.883), and 2.747 with 0.667 (2.277 with 0.669;2.137 with 0.689), respectively. The closeness of the predicted values to the observed ones shows a very high Pearson r correlation coefficient of over 0.932, except for 0.818 of NO(2) in Busan. Modeling performance using IBM SPSS-v27 software on daily averaged PM(10), PM(2.5), and NO(2) concentrations in each city were compared by scatter plots and their daily distributions between predicted and observed values.

2.
Beijing Gongye Daxue Xuebao/Journal of Beijing University of Technology ; 48(11):1168-1174, 2022.
Article in Chinese | Scopus | ID: covidwho-2145244

ABSTRACT

The air pollution characteristics were analyzed during the coronavirus disease (COVID-19) in Beijing. The hybrid single particle lagrangian integrated trajectory (Hysplit), potential source contribution function (PSCF), and concentration weighted trajectory (CWT) were also applied to study the main transport pathways and potential source regions of air masses during heavy pollution. Results show that compared with before COVID-19 (January 1-22, 2020) and the same period of 2019, the concentration of PM2.5 (aerodynamic diameter of <2.5 μm) after COVID-19 (January, 23-31, 2020) increased by 149.7% and 62.2%, respectively, while increased by 40.6% and 6.8% for sulfur dioxide (SO2), 42.6% and 37.8% for carbon monoxide (CO), and 73.6% and 28.0% for ozone (O3). Nitrogen dioxide (NO2) concentrations after COVID-19 decreased by 27.9% and 21.6%, respectively, compared with before COVID-19 and the same period of 2019. The most polluted day in January 28 was selected to analyze the backward trajectory and potential source regions. The air masses from the surrounding of Beijing were the main transport pathways of heavy pollution episode. The main potential source regions mainly concentrated in Beijing, northern Langfang, and northern Tianjin. The long-distance transmission from central and western Inner Mongolia and northern Beijing had little impact on this heavy pollution episode. Therefore, it is still necessary to conduct the regional joint prevention and control to improve the air quality in Beijing. © 2022, Editorial Department of Journal of Beijing University of Technology. All right reserved.

3.
Environmental Engineering Research ; 27(5), 2022.
Article in English | Scopus | ID: covidwho-2144610

ABSTRACT

Several measures have been taken to mitigate the effects of the COVID-19 pandemic. In this context, almost all non-essential activities in Morocco have been halted since March 20, 2020. From that date, Morocco announced the lockdown for one month and it was extended until June 10, 2020. The main objective of this paper is to study the effects of the lockdown measures on air quality, by analyzing dust PM2.5, NO2, and O3. The dust PM2.5 analysis was carried out from 2016 to 2020. NO2 and O3 analysis was carried out in 2019 and 2020. This study, which is based on satellite data from TROPOMI Sentinel 5P and MERRA, has shown that Morocco has experienced an improvement in air quality during the lockdown. A significant reduction in surface dust PM2.5 and tropospheric NO2 was observed (-10%,-4%, respectively on average). The total column of ozone recorded a slight increase on average of around 1%. Moreover, we demonstrate that a significant part of particulate pollution and NO2 emissions are incoming mainly from the northern and northern-eastern borders of Morocco. © 2022 Korean Society of Environmental Engineers.

4.
Environmental Research Letters ; 17(12):123001, 2022.
Article in English | ProQuest Central | ID: covidwho-2134662

ABSTRACT

Since 2013, China has taken a series of actions to relieve serious PM2.5 pollution. As a result, the annual PM2.5 concentration decreased by more than 50% from 2013 to 2021. However, ozone pollution has become more pronounced, especially in the North China Plain. Here, we review the impacts of anthropogenic emissions, meteorology, and atmospheric processes on ambient PM2.5 loading and components and O3 pollution in China. The reported influence of interannual meteorological changes on PM2.5 and O3 pollution during 2013–2019 ranged from 10%–20% and 20%–40%, respectively. During the same period, the anthropogenic emissions of NOx, SO2, primary PM2.5, NMVOC and NH3 are estimated to decrease by 38%, 51%, 35%, 11% and 17%, respectively. Such emission reduction is the main cause for the decrease in PM2.5 concentration across China. However, the imbalanced reductions in various precursors also result in the variation in nitrate gas-particle partitioning and hence an increase in the nitrate fraction in PM2.5. The increase of ozone concentration and the enhancement of atmospheric oxidation capacity can also have substantial impact on the secondary components of PM2.5, which partly explained the growth of organic aerosols during haze events and the COVID-19 shutdown period. The uneven reduction in NOx and NMVOC is suggested to be the most important reason for the rapid O3 increase after 2013. In addition, the decrease in PM2.5 may also have affected O3 formation via radiation effects and heterogeneous reactions. Moreover, climate change is expected to influence both anthropogenic emissions and atmospheric processes. However, the extent and pathways of the PM2.5-O3 interplay and how it will be impacted by the changing emission and atmospheric conditions making the synergetic control of PM2.5 and O3 difficult. Further research on the interaction of PM2.5 and O3 is needed to provide basis for a scientifically-grounded and effective co-control strategy.

5.
Stoch Environ Res Risk Assess ; : 1-15, 2022 Nov 18.
Article in English | MEDLINE | ID: covidwho-2128658

ABSTRACT

As a key node city of the "Silk Road Economic Belt" Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. This study analyzed the air quality before and during the COVID-19 (Coronavirus disease 2019) pandemic and its potential health effects based on the data of PM2.5, PM10, SO2, NO2, CO, and O3_8h levels from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021. As per the results, the concentrations of the air pollutants PM2.5, PM10, SO2, NO2, CO, and O3_8h in Urumqi from 2017 to 2021 showed a cyclical trend, and the implementation of COVID-19 prevention and control measures could effectively reduce the concentration(ρ) of air pollutants. The mean value of ρ(PM2.5) decreased from 2017 to 2021, whereas ρ(O3_8h) showed a waveform change trend (increased in 2017-2018, decreased in 2018-2020, and increased after 2020). Meanwhile, the maximum annual average values of ρ(PM2.5) and ρ(O3_8h) for the six monitoring stations during 2017-2021 occurred at sites S2 (74.37 µg m-3) and S6 (91.80 µg m-3), respectively; rapid industrialization had a greater impact on PM2.5 and O3_8h concentrations compared to commercial and residential areas. In addition, the air quality index data series can characterize the fluctuation trend of PM2.5. The high pollution levels (Class IV and V) of the air pollutants PM2.5 and O3_8h in Urumqi have been decreasing annually, and good days can account for 80-95% of the total number of days in the year, indicating that the number of days with a potential threat to residents' health is gradually decreasing. Therefore, more attention should be paid in controlling and managing air pollution in Urumqi.

6.
Sci Total Environ ; 859(Pt 1): 160172, 2022 Nov 15.
Article in English | MEDLINE | ID: covidwho-2120207

ABSTRACT

Unexpected outbreak of the 2019 novel coronavirus (COVID-19) has profoundly altered the way of human life and production activity, which posed visible impacts on PM2.5 and its chemical species. The abruptly emergency reduction in human activities provided an opportunity to explore the synergetic impacts of multi-factors on shaping PM2.5 pollution. Here, we conducted two comprehensive observation measurements of PM2.5 and its chemical species from 1 January to 16 February in Beijing 2020 and the same lunar date in 2021, to investigate temporal variations and reveal the driving factors of haze before and after Chinese New Year (CNY). Results show that mean PM2.5 concentrations during the whole observation were 63.83 and 66.86 µg/m3 in 2020 and 2021, respectively. Higher secondary inorganic species were observed after CNY, and K+, Cl- showed three prominent peaks which associated closely with fireworks burnings from suburb Beijing and surroundings, verifying that they could be used as two representative tracers of fireworks. Further, we explored the impacts of meteorological conditions, regional transportation as well as chemical reactions on PM2.5. We found that unfavorable meteorological conditions accounted for 11.0 % and 16.9 % of PM2.5 during CNY holidays in 2020 and 2021, respectively. Regional transport from southwest and southeast (south) played an important role on PM2.5 during the two observation periods. Higher ratio of NO3-/SO42- were observed under high OX and low RH conditions, suggesting the major pathway of NO3- and SO42- formation could be photochemical process and aqueous-phase reaction. Additionally, nocturnal chemistry facilitated the formation of secondary components of both inorganic and organic. This study promotes understandings of PM2.5 pollution in winter under the influence of COVID-19 pandemic and provides a well reference for haze and PM2.5 control in future.

7.
Sensors (Basel) ; 22(22)2022 Nov 20.
Article in English | MEDLINE | ID: covidwho-2116069

ABSTRACT

In this paper, a comparative analysis between the PM2.5 concentration in downtown Quito, Ecuador, during the COVID-19 pandemic in 2020 and the previous five years (from 2015 to 2019) was carried out. Here, in order to fill in the missing data and achieve homogeneity, eight datasets were constructed, and 35 different estimates were used together with six interpolation methods to put in the estimated value of the missing data. Additionally, the quality of the estimations was verified by using the sum of squared residuals and the following correlation coefficients: Pearson's r, Kendall's τ, and Spearman's ρ. Next, feature vectors were constructed from the data under study using the wavelet transform, and the differences between feature vectors were studied by using principal component analysis and multidimensional scaling. Finally, a robust method to impute missing data in time series and characterize objects is presented. This method was used to support the hypothesis that there were significant differences between the PM2.5 concentration in downtown Quito in 2020 and 2015-2019.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , Communicable Disease Control , Research Design , Particulate Matter
8.
Frontiers in Environmental Science ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2109749

ABSTRACT

In response to the COVID-19 outbreak, severe steps have been taken to control its rapid spread by countries globally. A nationwide lockdown was executed at the end of January 2020 in China, which resulted in a significant change and an improvement in air quality patterns. In this study, the objectives were to assess the spatiotemporal impact of the COVID-19 lockdown on air quality in Nanjing, China. The present study researched the six air pollutant parameters, namely, PM10, PM2.5, SO2, NO2, CO, and O-3. The data were divided into six periods, P1-P3: pre-lockdown, during lockdown, and after lockdown periods, P4-P6: 2017-19 (same dates of lockdown). The results reveal that during the COVID-19 control period, a significant drop and an improvement in air quality were observed. According to our findings, the PM10, PM2.5, SO2, NO2, and CO concentrations were reduced by -33.03%, -35.41%, -21.26%, -39.79%, and -20.65%, respectively, while the concentration of O-3 significantly increased by an average of 104.85% in Nanjing. From the previous 3 years to lockdown variations, PM10 (-40.60%), PM2.5 (-40.02%), SO2 (-54.19%), NO2 (-33.60%), and CO (23.16%) were also reduced, while O-3 increased (10.83%). Moreover, compared with those in the COVID-19 period, the levels of PM10, SO2, NO2, CO, and O-3 increased by 2.84%, 28.55%, 4.68%, 16.44%, and 37.36%, respectively, while PM2.5 reduced by up to -14.34% after the lockdown in Nanjing. The outcomes of our study provide a roadmap for the scientific community and local administration to make policies to control air pollution.

9.
Atmos Pollut Res ; 13(11): 101594, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2104373

ABSTRACT

Nowadays, there has been a substantial proliferation in the use of low-cost particulate matter (PM) sensors and facilitating as an indicator of overall air quality. However, during COVID-19 epidemics, air pollution sources have been deteriorated significantly, and given offer to evaluate the impact of COVID-19 on air quality in the world's most polluted city: Delhi, India. To address low-cost PM sensors, this study aimed to a) conduct a long-term field inter-comparison of twenty-two (22) low-cost PM sensors with reference instruments over 10-month period (evaluation period) spanning months from May 2019 to February 2020; b) trend of PM mass and number count; and c) probable local and regional sources in Delhi during Pre-CVOID (P-COVID) periods. The comparison of low-cost PM sensors with reference instruments results found with R2 ranging between 0.74 and 0.95 for all sites and confirm that PM sensors can be a useful tool for PM monitoring network in Delhi. Relative reductions in PM2.5 and particle number count (PNC) due to COVID-outbreaks showed in the range between (2-5%) and (4-13%), respectively, as compared to the P-COVID periods. The cluster analysis reveals air masses originated ∼52% from local, while ∼48% from regional sources in P-COVID and PM levels are encountered 47% and 66-70% from local and regional sources, respectively. Overall results suggest that low-cost PM sensors can be used as an unprecedented aid in air quality applications, and improving non-attainment cities in India, and that policy makers can attempt to revise guidelines for clean air.

10.
Promet-Traffic & Transportation ; 34(5):813-823, 2022.
Article in English | Web of Science | ID: covidwho-2102079

ABSTRACT

The pandemic caused by the coronavirus COVID-19 is having a worldwide impact that affects health, economy and air pollution in cities indirectly. In Slovenia, as well as in all other countries, the number of cases of infected people increased continually in 2020, which affected the health system and caused movement restrictions, which, in turn, affected the air pollution in the country. This article presents the indirect effect produced by this pandemic on air pollution in Maribor, Slovenia. Traffic and air quality data were used to perform the evaluation, in particular PM10 and PM2.5 daily concentrations from the monitoring station in Maribor. By observing the de-tailed traffic data and particulate matter concentrations acquired in the Maribor city centre before and during the pandemic times, we show the influence of COVID-19 on particulate matter concentrations in that part of the town. The results show slightly lower particulate matter con-centrations, which could be explained by the significantly lower traffic volume values in the lockdown months.

11.
Journal of Korean Society for Atmospheric Environment ; 38(4):610-623, 2022.
Article in English | Web of Science | ID: covidwho-2100249

ABSTRACT

Since 2019, Korean Ministry of Environment has implemented the 1st -3rd PM2.5 Seasonal Management Plans(SMP) to reduce PM2.5 concentration during high PM2.5 concentration period. In this study, we quantitatively evaluated the major drivers(meteorology, foreign emissions, and domestic emissions) of which changes led to change of PM2.5 concen-trations in South Korea during the PM2.5 SMP periods(S1, Dec. 2019-Mar. 2020;S2, Dec. 2020-Mar. 2021;S3, Dec. 2021-Mar. 2022) based on observational data and Community Multiscale Air Quality(CMAQ) simulation results. The nation-wide period mean PM2.5 concentration in S1, S2, and S3 decreased by 8.7, 9.1, and 10.1 mu g/m3 compared to that during Dec. 2018-Mar. 2019. Results show that anthropogenic emission reductions in Northeast Asia decreased the PM2.5 concentration by 5.9, 5.5, and 8.8 mu g/m3 respectively during S1-S3. Note that the effect of the regional emission reduction includes not only domestic emission reduction but also reductions in foreign emission impact. The combined impact of meteorology and foreign emission changes explained 65%, 61% of the total PM2.5 decreases over South Korea and the Seoul Metropolitan Area(SMA) respectively during the S1-S3. Consequently, domestic emission reductions including governmental air quality management plans(i.e., the PM2.5 SMP) and socioeconomic changes(i.e., COVID-19 outbreak) led to PM2.5 concentration decrease in South Korea by 35% during the periods. Among seventeen provinces in South Korea, the impacts of domestic emission reduction on the PM2.5 concentration decreases were as high as 39% and 56% in the SMA and Chungnam where the major emission sources such as transportation, power generation facilities, and industrial complex locate and where the PM2.5 SMP measures were probably penetrated. It implies that the effects of domestic emission controls were meaningful to lower PM2.5concentrations during the periods.

12.
Atmos Pollut Res ; 13(11): 101587, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2095049

ABSTRACT

To prevent the rapid spreading of the COVID-19 pandemic, the Egyptian government had imposed partial lockdown restrictions which led emissions reduction. This served as ideal conditions for a natural experiment, for study the effect of partial lockdown on the atmospheric aerosol chemistry and the enhanced secondary inorganic aerosol production in a semi-desert climate area like Egypt. To achieve this objective, SO2, NO2, and PM2.5 and their chemical compositions were measured during the pre-COVID, COVID partial lockdown, and post-COVID periods in 2020 in a suburb of Greater Cairo, Egypt. Our results show that the SO2, NO2, PM2.5 and anthropogenic elements concentrations follow the pattern pre-COVID > post-COVID > COVID partial lockdown. SO2 and NO2 reductions were high compared with their secondary products during the COVID partial lockdown compared with pre-COVID. Although, PM2.5, anthropogenic elements, NO2, SO2, SO4 2-, NO3 -, and NH4 + decreased by 39%, 38-55%, 38%, 32.9%. 9%, 14%, and 4.3%, respectively, during the COVID partial lockdown compared with pre-COVID, with the secondary inorganic ions (SO4 2-, NO3 -, and NH4 +) being the dominant components in PM2.5 during the COVID partial lockdown. Moreover, the enhancement of NO3 - and SO4 2- formation during the COVID partial lockdown was high compared with pre-COVID. SO4 2- and NO3 - formation enhancements were significantly positive correlated with PM2.5 concentration. Chemical forms of SO4 2- and NO3 - were identified in PM2.5 based on their NH4 +/SO4 2- molar ratio and correlation between NH4 + and both NO3 - and SO4 2-. The particles during the COVID partial lockdown were more acidic than those in pre-COVID.

13.
Int J Environ Res Public Health ; 19(21)2022 Oct 30.
Article in English | MEDLINE | ID: covidwho-2090189

ABSTRACT

Many studies have shown that air pollution may be closely associated with increased morbidity and mortality due to COVID-19. It has been observed that exposure to air pollution leads to reduced immune response, thereby facilitating viral penetration and replication. In our study, we combined information on confirmed COVID-19 daily new cases (DNCs) in one of the most polluted regions in the European Union (EU) with air-quality monitoring data, including meteorological parameters (temperature, relative humidity, atmospheric pressure, wind speed, and direction) and concentrations of particulate matter (PM10 and PM2.5), sulfur dioxide (SO2), nitrogen oxides (NO and NO2), ozone (O3), and carbon monoxide (CO). Additionally, the relationship between bacterial aerosol (BA) concentration and COVID-19 spread was analyzed. We confirmed a significant positive correlation (p < 0.05) between NO2 concentrations and numbers of confirmed DNCs and observed positive correlations (p < 0.05) between BA concentrations and DNCs, which may point to coronavirus air transmission by surface deposits on bioaerosol particles. In addition, wind direction information was used to show that the highest numbers of DNCs were associated with the dominant wind directions in the region (southern and southwestern parts).


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Ozone , Humans , Air Pollutants/analysis , Nitrogen Dioxide/analysis , COVID-19/epidemiology , Poland/epidemiology , Respiratory Aerosols and Droplets , Air Pollution/adverse effects , Air Pollution/analysis , Particulate Matter/analysis , Ozone/analysis , China
14.
Environ Sci Pollut Res Int ; 2022 Oct 21.
Article in English | MEDLINE | ID: covidwho-2085533

ABSTRACT

To control the spread of COVID-19, Shijiazhuang implemented two lockdowns of different magnitudes in 2020 (lockdown I) and 2021 (lockdown II). We analyzed the changes in air quality index (AQI), PM2.5, O3, and VOCs during the two lockdowns and the same period in 2019 and quantified the effects of anthropogenic sources during the lockdowns. The results show that AQI decreased by 13.2% and 32.4%, and PM2.5 concentrations decreased by 12.9% and 42.4% during lockdown I and lockdown II, respectively, due to the decrease in urban traffic mobility and industrial activity levels. However, the sudden and unreasonable emission reductions led to an increase in O3 concentrations by 160.6% and 108.4%, respectively, during the lockdown period. To explore the causes of the O3 surge, the major precursors NOx and VOCs were studied separately, and the main VOCs species affecting ozone formation during the lockdown period and the source variation of VOCs were identified, and it is important to note that the relationship between diurnal variation characteristics of VOCs and cooking became apparent during the lockdown period. These findings suggest that regional air quality can be improved by limiting production, but attention should be paid to the surge of O3 caused by unreasonable emission reductions, clarifying the control priorities for urban O3 management.

15.
Frontiers in Environmental Science ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2083024

ABSTRACT

A series of lockdown measures in response to the Corona Virus Disease 2019 (COVID-19) outbreak resulted in a drop in anthropogenic emissions and changes in concentrations of PM2.5 and O-3. Backward trajectories analysis, cluster analysis, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) technologies were conducted to reveal the characteristics and potential source areas of pollutants in Beijing before the COVID-19 outbreak (BCO period), during the outbreak (COB period) and after the outbreak (ACO period), as well as the contemporaneous period in 2019 (CCO period), which is critical for exploring the efficient control measures and making policy. The results indicated that despite the significant reduction in anthropogenic emissions during the epidemic, the PM2.5 concentrations increased by 1.0% caused by unfavorable meteorological conditions. O-3 concentrations increased by 174.8% compared to that during the BCO period due to the increased temperature and inappropriate precursor reduction ratios. A considerable decrease of NO3- in PM2.5 was observed under the influence of significant reductions in vehicle emissions during the lockdown. The cluster analysis revealed that short-range transport played a significant role in the accumulation of local PM2.5 pollution, while long-range northwest airflows contributed more to O-3 accumulation, and weakened as the season changed. The PSCF and CWT analysis demonstrated that potential source areas of PM2.5 were mostly located in the central and southern Hebei, the southwestern Shandong in the CCO period, and expanded to central Inner Mongolia and northern Shanxi in the COB period. These areas were highly compatible with the high emission areas of the emission inventory statistics. After the outbreak, the source areas of O-3 were centered in the Beijing-Tianjin-Hebei region and Shandong province, with a radial dispersion in all directions, while they were distributed in the central Mongolia and Inner Mongolia during the other periods.

16.
Spatial Information Research ; 30(3):417-426, 2022.
Article in English | Web of Science | ID: covidwho-2082968

ABSTRACT

The present study analysed the spatial distribution of Aerosol Optical Depth (AOD) over India during the COVID-19 lockdown phase -1 (March 25 to April 15, 2020) using MODIS Terra (MOD04) AOD data (550 nm) during 2001-2020. Air temperature, rainfall, forest fire incidents, and wind patterns were analysed to understand their effect on the distribution of aerosols over India during the lockdown phase-1. Moderate absorption fine aerosol type is predominant but sparsely distributed over India during the study period compared to the reference period indicating the positive influence of the lockdown. Mean AOD has reduced by 9% over India during the lockdown phase-1 compared to the corresponding mean of the past 19 years (2001-2019). About 70% of the states/UTs of India showed a reduction in mean AOD due to restrictions on non-essential economic activities and rainfall occurrence. However, some states showed an increase in aerosol loading over specific pockets despite the restrictions on economic activities (Arunachal Pradesh, Assam, Gujarat, Orissa, Andhra Pradesh, Madhya Pradesh, Chhattisgarh, Maharashtra, Assam, Nagaland, Manipur and Karnataka) because of active forest fire cases. This study would be helpful for planners and policymakers to adopt suitable measures to control the rising concentrations of aerosols over hotspot regions of India.

17.
Pathog Glob Health ; : 1-9, 2022 Oct 19.
Article in English | MEDLINE | ID: covidwho-2077523

ABSTRACT

Air pollution may be involved in spreading dengue fever (DF) besides rainfalls and warmer temperatures. While particulate matter (PM), especially those with diameter of 10 µm (PM10) or 2.5 µm or less (PM25), and NO2 increase the risk of coronavirus 2 infection, their roles in triggering DF remain unclear. We explored if air pollution factors predict DF incidence in addition to the classic climate factors. Public databases and DF records of two southern cities in Taiwan were used in regression analyses. Month order, PM10 minimum, PM2.5 minimum, and precipitation days were retained in the enter mode model, and SO2 minimum, O3 maximum, and CO minimum were retained in the stepwise forward mode model in addition to month order, PM10 minimum, PM2.5 minimum, and precipitation days. While PM2.5 minimum showed a negative contribution to the monthly DF incidence, other variables showed the opposite effects. The sustain of month order, PM10 minimum, PM2.5 minimum, and precipitation days in both regression models confirms the role of classic climate factors and illustrates a potential biological role of the air pollutants in the life cycle of mosquito vectors and dengue virus and possibly human immune status. Future DF prevention should concern the contribution of air pollution besides the classic climate factors.

18.
Atmosphere ; 13(9), 2022.
Article in English | Web of Science | ID: covidwho-2071181

ABSTRACT

In this study, the levels of fine particulate matter (PM2.5), polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs (NPAHs) in PM2.5 samples were determined from 2020 to 2021 in Singapore. For analysis convenience, the sampling period was classified according to two monsoon periods and the inter-monsoon period. Considering Singapore's typically tropical monsoon climate, the four seasons were divided into the northeast monsoon season (NE), southwest monsoon season (SW), presouthwest monsoon season (PSW) and prenortheast monsoon season (PNE)). The PM2.5 concentration reached 17.1 +/- 8.38 mu g/m(3), which was slightly higher than that in 2015, and the average PAH concentration continuously declined during the sampling period compared to that reported in previous studies in 2006 and 2015. This is the first report of NPAHs in Singapore indicating a concentration of 13.1 +/- 10.7 pg/m(3). The seasonal variation in the PAH and NPAH concentrations in PM2.5 did not obviously differ owing to the unique geographical location and almost uniform climate changes in Singapore. Diagnostic ratios revealed that PAHs and NPAHs mainly originated from local vehicle emissions during all seasons. 2-Nitropyrene (2-NP) and 2-nitrofluoranthene (2-NFR) in Singapore were mainly formed under the daytime OH-initiated reaction pathway. Combined with airmass backward trajectory analysis, the Indonesia air mass could have influenced Singapore's air pollution levels in PSW. However, these survey results showed that no effect was found on the concentrations of PAHs and NPAHs in PM2.5 in Indonesia during SW because of Indonesia's efforts in the environment. It is worth noting that air masses from southern China could impact the PAH and NPAH concentrations according to long-range transportation during the NE. The results of the total incremental lifetime cancer risk (ILCR) via three exposure routes (ingestion, inhalation and dermal absorption) for males and females during the four seasons indicated a low long-term potential carcinogenic risk, with values ranging from 10(-10) to 10(-7). This study systematically explains the latest pollution conditions, sources, and potential health risks in Singapore, and comprehensively analyses the impact of the tropical monsoon system on air pollution in Singapore, providing a new perspective on the transmission mechanism of global air pollution.

19.
Int J Environ Res Public Health ; 19(19)2022 Oct 08.
Article in English | MEDLINE | ID: covidwho-2066081

ABSTRACT

Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Ozone , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Carbon Monoxide/analysis , China/epidemiology , Communicable Disease Control , Environmental Monitoring/methods , Humans , Nitrogen Dioxide/analysis , Ozone/analysis , Particulate Matter/analysis , Sulfur Dioxide/analysis
20.
Int J Environ Res Public Health ; 19(19)2022 Oct 02.
Article in English | MEDLINE | ID: covidwho-2066023

ABSTRACT

Air pollution may change people's gym sports behavior. To test this claim, first, we used big data crawler technology and ordinary least square (OLS) models to investigate the effect of air pollution on people' gym visits in Beijing, China, especially under the COVID-19 pandemic of 2019-2020, and the results showed that a one-standard-deviation increase in PM2.5 concentration (fine particulate matter with diameters equal to or smaller than 2.5 µm) derived from the land use regression model (LUR) was positively associated with a 0.119 and a 0.171 standard-deviation increase in gym visits without or with consideration of the COVID-19 variable, respectively. Second, using spatial autocorrelation analysis and a series of spatial econometric models, we provided consistent evidence that the gym industry of Beijing had a strong spatial dependence, and PM2.5 and its spatial spillover effect had a positive impact on the demand for gym sports. Such a phenomenon offers us a new perspective that gym sports can be developed into an essential activity for the public due to this avoidance behavior regarding COVID-19 virus contact and pollution exposure.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Beijing/epidemiology , COVID-19/epidemiology , China/epidemiology , Environmental Monitoring/methods , Exercise , Humans , Pandemics , Particulate Matter/analysis
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