Source identification of PM2.5 during the COVID-19 lockdown in Bangkok and the metropolitan region by ion beam analysis (IBA) and positive matrix factorization (PMF) techniques

PM2.5 pollution has significant impacts on human health and has been a persistent problem in Bangkok and its metropolitan area for many decades. To effectively address the issue, source identification is crucial. This study was aimed at determining the sources of PM2.5 in three regions;Pathumwan district in Bangkok, Mueang district in Samut Sakhon province, and Mueang district in Samut Prakan province. PM2.5 sampling was performed according to the Federal Reference Method (FRM). A combined total of 135 samples were collected across all three locations, over a 24-h period from December 2021 to February 2022 with 46.2 mm polytetrafluoroethylene (PTFE) membranes. The filters were analyzed using particle accelerator-based ion beam analysis techniques;Proton-induced X-ray emission, proton-induced gamma-ray emission, and proton elastic scattering analysis. Positive matrix factorization was used for source apportionment for the three locations. The results indicated that the main contributors to PM2.5 in Bangkok, Samut Prakan, and Samut Sakhon were biomass/solid waste burning (45.6%), traffic (43.7%), and construction (36.0%), respectively. These preliminary findings further supported the need for expanding these types of studies to implement specific strategies for a reduction of PM2.5 level in high activity cities and which could then be applied to other urban areas around the world.

Sources of water-soluble organic carbon in fine particles at a southern European urban background site

In this study, the temporal evolution and sources of water-soluble organic carbon (WSOC) in submicron particles at an urban background site in Elche (Spain) were investigated. Measurements of PM1 (N = 200) were carried out over one year (2021). Samples were analysed for organic carbon (OC), elemental carbon (EC), WSOC, levoglucosan, elements and major ions. A positive matrix factorization (PMF) analysis was performed in order to identify the sources of WSOC on an annual and a monthly basis. During the study period, traffic restrictions due to COVID-19 led to lower concentrations of PM1 and carbonaceous compounds than expected. The WSOC annual average mass concentration was 0.95 mugm-3, with maximum values during the colder months. The apportionment results indicate that the biomass burning (BB) source contributed 30.63% to WSOC levels, road traffic (RT) accounted for 23.90% of the WSOC, while the contribution of a source related to secondary organic aerosol formation (ammonium sulfate-AS) was 33.80%. Minor sources of WSOC were: soil dust (SD) and secondary nitrate (SN), which contributed 7.44% and 4.22%, respectively, to WSOC concentrations. The WSOC/OC ratio did not exhibit significant variations during the study period, since source contributions were similar for WSOC and OC. The highest values of this ratio were recorded in summer, due to the higher contribution from the AS source to WSOC concentrations.Copyright © 2023 The Authors

Positive Matrix Factorization as Source Apportionment of Paddy Soil Heavy Metals in Black Shale Areas in Western Zhejiang Province, China

The source apportionment of pollutants is the key to preventing and controlling the pollution caused by heavy metals in soils. The aim of this study was to investigate the main sources of heavy metals in the soils of black shale areas in western Zhejiang, China. Based on geostatistical spatial analysis, this research employed positive matrix factorization (PMF) for the source apportionment of heavy metals in paddy soil. The results showed that contaminated arable soils were concentrated in the western and southern study areas. At least five major sources of heavy metals were screened in this study: natural sources (39.66%), traffic emissions (32.85%), industrial emissions (9.23%), agricultural activities (9.17%), and mining (9.10%). To be specific, Cd was mainly from mining;As originated from agricultural inputs such as fertilizers and pesticides;and Hg, as an industrial pollutant, was transported by atmospheric deposition in the study area. The accumulation of Pb, Zn, and Cu was mainly influenced by natural sources and anthropogenic sources, i.e., traffic emissions, while that of Cr and Ni was controlled by natural sources.

Size-resolved Compositional Analysis and Source Apportionment of Submicron Aerosol during Lockdown Period Using HR-ToF-AMS

The size-resolved compositional analysis of non-refractory submicron aerosol (NR-PM1) was conducted using the Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) instrument over Pune, India during the COVID-19 lockdown period. The aerosol composition data shows the predominant presence of organics (Org) in the mass fraction followed by sulfate, ammonium, nitrate, and chloride during the pre-lockdown and lockdown periods. The size-resolved analysis showed the unimodal size distribution of organic and inorganic constituents with peaks at 550 nm, implying the dominant presence of mixed and aged aerosol species. The stoichiometric neutralization analysis showed the almost neutralized nature of submicron aerosol with an average aerosol neutralization ratio (ANR) of 0.8. The back trajectories, cluster analysis, and potential source contribution function (PSCF) showed the industrial belt located in the western part of the study location to be the potential source regions of NR-PM1. Positive matrix factorization (PMF) analyses have been applied to investigate the source apportionments of organic aerosols (OA). Four distinct OA factors, i.e., hydrocarbon-like OA (HOA), biomass burning OA (BBOA), low-volatile oxygenated OA (LVOOA), and semi-volatile oxygenated OA (SVOOA) were identified during the study period. Among these factors, HOA contributes nearly a quarter to the OA mass, and OOA accounted for nearly 60% of the total OA mass. The high-resolution positive matrix factorization (HR-PMF) analysis and the elemental ratios of H/C, O/C, and OM/OC showed distinct characteristics during different periods. The density of organic aerosol has been estimated using the elemental ratios and found to be 1.14, 1.28, and 1.35 respectively during the different lockdown periods, similar to 1.30 g cm–3 as mentioned in the literature. This study provides new insights into the chemical composition and source apportionment of the organic fraction of submicron aerosols for the first time over Pune using HR-ToF-AMS and HR-PMF.

Impact of COVID-19 lockdown on carbonaceous aerosols in a polluted city: Composition characterization, source apportionment, influence factors of secondary formation.

Carbonaceous fractions throughout the normal period and lockdown period (LP) before and during COVID-19 outbreak were analyzed in a polluted city, Zhengzhou, China. During LP, fine particulate matters, elemental carbon (EC), and secondary organic aerosol (SOC) concentrations fell significantly (29%, 32% and 21%), whereas organic carbon (OC) only decreased by 4%. Furthermore, the mean OC/EC ratio increased (from 3.8 to 5.4) and the EC fractions declined dramatically, indicating a reduction in vehicle emission contribution. The fact that OC1-3, EC, and EC1 had good correlations suggested that OC1-3 emanated from primary emissions. OC4 was partly from secondary generation, and increased correlations of OC4 with OC1-3 during LP indicated a decrease in the share of SOC. SOC was more impacted by NO2 throughout the research phase, thereby the concentrations were lower during LP when NO2 levels were lower. SOC and relative humidity (RH) were found to be positively associated only when RH was below 80% and 60% during the normal period (NP) and LP, respectively. SOC, Coal combustion, gasoline vehicles, biomass burning, diesel vehicles were identified as major sources by the Positive Matrix Factorization (PMF) model. Contribution of SOC apportioned by PMF was 3.4 and 3.0 µg/m3, comparable to the calculated findings (3.8 and 3.0 µg/m3) during the two periods. During LP, contributions from gasoline vehicles dropped the most, from 47% to 37% and from 7.1 to 4.3 µg/m3, contribution of biomass burning and diesel vehicles fell by 3% (0.6 µg/m3) and 1% (0.4 µg/m3), and coal combustion concentrations remained nearly constant. The findings of this study highlight the immense importance of anthropogenic source reduction in carbonaceous component variations and SOC generation, and provide significant insight into the temporal variations and sources of carbonaceous fractions in polluted cities.

Local and transboundary impacts of PM2.5 sources identified in Seoul during the early stage of the COVID-19 outbreak.

Countries in Northeast Asia have been regulating PM2.5 sources and studying their local and transboundary origins since PM2.5 causes severe impacts on public health and economic losses. However, the separation of local and transboundary impacts is not fully realized because it is impossible to change air pollutant emissions from multiple countries experimentally. Exceptionally, the early stage of the COVID-19 outbreak (January-March 2020) provided a cross-country experiment to separate each impact of PM2.5 sources identified in Seoul, a downwind area of China. We evaluated the contributions of PM2.5 sources compared to 2019 using dispersion normalized positive matrix factorization (DN-PMF) during three meteorological episodes. Episodes 1 and 2 revealed transboundary impacts and were related to reduced anthropogenic emissions and accumulated primary pollutants in Northeast China. Anthropogenic emissions, except for the residential sector, decreased, but primary air pollutants accumulated by residential coal combustion enhanced secondary aerosol formation. Thus, the contributions of sulfate and secondary nitrate increased in Seoul during episode 1 but then decreased maximally with other primary sources (biomass burning, district heating and incineration, industrial sources, and oil combustion) during episode 2 under meteorological conditions favorable to long-range transport. Local impact was demonstrated by atmospheric stagnation during episode 3. Meteorological condition unfavorable to local dispersion elevated the contributions of mobile and coal combustion and further contributed to PM2.5 high concentration events (HCE). Our study separates the local and transboundary impacts and highlights that cooperations in Northeast Asia on secondary aerosol formation and management of local sources are necessary.

[Concentration Variation and Source Analysis of Metal Elements in PM2.5 During COVID-19 Control in Suzhou].

To study the variation in concentration and source analysis of metal elements during COVID-19 control in Suzhou, a multi-metal online monitor was used to determine hourly online data of 14 metal elements from December 1, 2019 to March 31, 2020. This study analyzed variation in concentration and source analysis of metal elements using a PMF model before, during, and after shutdown during COVID-19 control. The results showed that the concentrations of Cr, Mn, Zn, and Fe during shutdown decreased the most, by 87.6%, 85.6%, 78.3%, and 72.2%, respectively, compared with those before shutdown. The concentrations of Mn, Cr, Zn, and Fe after shutdown increased the most, by 227.0%, 215.4%, 147.4%, and 113.4%, respectively, compared with those of the previous stage. The diurnal variation in K differed at three stages. Zn showed a single peak shape at three stages, but the peak width and peak time were different. Unlike the concentrations, the diurnal variations in Fe, Mn, Pb, Se, and Hg were not significantly changed. The daily variation characteristics of Ca, Ba, Cu, As, Cr, and Ni during and after shutdown were significantly different from those before shutdown. The results of source analysis by the PMF model showed that metal elements mainly came from dust, motor vehicle, coal burning, industrial smelting, and mixed-combustion sources. Among them, the concentration of industrial smelting sources changed greatly, with the concentration decreasing by 89.0% during shutdown and increasing by 358.0% after shutdown.

[Influence of COVID-19 Prevention and Control Measures on PM2.5 Concentration, Particle Size Distribution, Chemical Composition, and Source in Zhengzhou, China].

The COVID-19 lockdown was a typical occurrence of extreme emission reduction, which presented an opportunity to study the influence of control measures on particulate matter. Observations were conducted from January 16 to 31, 2020 using online observation instruments to investigate the characteristics of PM2.5 concentration, particle size distribution, chemical composition, source, and transport before (January 16-23, 2020) and during (January 24-31, 2020) the COVID-19 lockdown in Zhengzhou. The results showed that the atmospheric PM2.5 concentration decreased by 4.8% during the control period compared with that before the control in Zhengzhou. The particle size distribution characteristics indicated that there was a significant decrease in the mass concentration and number concentration of particles in the size range of 0.06 to 1.6 µm during the control period. The chemical composition characteristics of PM2.5 showed that secondary inorganic ions (sulfate, nitrate, and ammonium) were the dominant component of PM2.5, and the significant increase in PM2.5 was mainly owing to the decrease in NO3- concentration during the control period. The main sources of PM2.5 identified by the positive matrix factorization (PMF) model were secondary sources, combustion sources, vehicle sources, industrial sources, and dust sources. The emissions from vehicle sources, industrial sources, and dust sources decreased significantly during the control period. The results of analyses using the backward trajectory method and potential source contribution factor method indicated that the effects of transport from surrounding areas on PM2.5 concentration decreased during the control period. In summary, vehicle and industrial sources should be continuously controlled, and regional combined prevention and control should be strengthened in the future in Zhengzhou.

Source Apportionment of Atmospheric PM10 in Makkah Saudi Arabia by Modelling Its Ion and Trace Element Contents with Positive Matrix Factorization and Generalised Additive Model.

In this paper, the emission sources of PM10 are characterised by analysing its trace elements (TE) and ions contents. PM10 samples were collected for a year (2019-2020) at five sites and analysed. PM10 speciated data were analysed using graphical visualization, correlation analysis, generalised additive model (GAM), and positive matrix factorization (PMF). Annual average PM10 concentrations (µg/m3) were 304.68 ± 155.56 at Aziziyah, 219.59 ± 87.29 at Misfalah, 173.90 ± 103.08 at Abdeyah, 168.81 ± 82.50 at Askan, and 157.60 ± 80.10 at Sanaiyah in Makkah, which exceeded WHO (15 µg/m3), USEPA (50 µg/m3), and the Saudi Arabia national (80 µg/m3) annual air quality standards. A GAM model was developed using PM10 as a response and ions and TEs as predictors. Among the predictors Mg, Ca, Cr, Al, and Pb were highly significant (p < 0.01), Se, Cl, and NO2 were significant (p < 0.05), and PO4 and SO4 were significant (p < 0.1). The model showed R-squared (adj) 0.85 and deviance explained 88.1%. PMF identified four main emission sources of PM10 in Makkah: (1) Road traffic emissions (explained 51% variance); (2) Industrial emissions and mineral dust (explained 27.5% variance); (3) Restaurant and dwelling emissions (explained 13.6% variance); and (4) Fossil fuel combustion (explained 7.9% variance).

Source identification of the elemental fraction of particulate matter using size segregated, highly time-resolved data and an optimized source apportionment approach

Source emissions with high covariance degrade the performance of multivariate models, and often highly-time resolved data is needed to accurately extract the contribution of different emissions. Here, we use highly time-resolved size segregated elemental composition data to apportion the sources of the elemental fraction of PM in Zürich (May 2019–May 2020). For data collection, we have used an ambient metals monitor, Xact 625i, equipped with a sampling inlet alternating between PM2.5 and PM10. By implementing interpolation and a newly proposed uncertainty estimation methodology, it was possible to obtain and use in PMF a combined dataset of PM2.5 and PMcoarse (PM10-2.5) having data from only one instrument. The combination of the inlet switching system, the instrument's high time resolution, and the use of advanced source apportionment approaches yielded improved source apportionment results in terms of the number of identified sources, as the model, additionally to the diurnal and seasonal variation of the dataset, also utilizes the variation from the size segregated data. Thirteen sources of elements were identified, i.e., sea salt (5.4%), biomass burning (7.2%), construction (4.3%), industrial (3.3%), light-duty vehicles (5.4%), Pb (0.7%), Zn (0.7%), dust (22.1%), transported dust (9.5%), sulfates (15.4%), heavy-duty vehicles (17%), railway (6.6%) and fireworks (2.4%). The Covid-19 lockdown effect in PM sources in the area was also quantified. High-intensity events disproportionally affect the PMF solution, and in many cases, they are getting discarded before analysis, removing thus valuable information from the dataset. In this study, a three-step source apportionment approach was used to get a well-resolved unmixed solution when firework data points were included in the analysis. This approach can also be used for other sources and/or events with very high contributions that distort source apportionment analysis. Optimized source apportionment techniques are necessary for effective air pollution monitoring.

Remdesivir interactions with sulphobutylether-beta-cyclodextrins: A case study using selected substitution patterns

Modified cyclodextrins (CDs) consist of a distribution of different structures with different number and location of the substituted groups. Among the most important applications of these molecules is their use as an enabling excipient in pharmaceutical formulations to provide the necessary solubility, stability and bioavailability for a drug to be effectively used. The most typical interaction mechanism of small molecular groups with CDs is the formation of host-guest inclusion complexes. The thermodynamic affinity constant between CDs and drugs should not be too strong, since then the biological activity could be negated by the formation of the complex. In the opposite scenario, if the affinity constant is too weak, the complex is barely formed and the amount of CD required in the formulation may become too great. Thus, a balance between the affinity of the CD and the drug is necessary for an optimal formulation. Additionally in the case of modified CDs and specific drug complexes there are further questions concerning the effect that the locations and number of substitutions plays in complexation. In the present work, this question is explored by using sulphobutylether-beta-cyclodextrin and remdesivir, the only antiviral medication currently approved by the United States Food and Drug Administration for treating COVID-19, as a case study. This paper presents results from an orthogonal study using isothermal titration calorimetry measurements and biased molecular dynamics simulations that provide complementary information. Isothermal titration calorimetry delves into the global impact of the species distribution while molecular dynamics simulations deals with specific chemical structures. The goal is to provide useful information to optimize pharmaceutical formulations based on modified CDs, specifically in the case of remdesivir, used to treat SARS-CoV-2 infection, although the main conclusions could be extended to the interaction of other drugs with modified cyclodextrins. (C) 2021 The Authors. Published by Elsevier B.V.

[Characteristics, Ozone Formation Potential, and Source Apportionment of VOCs During the COVID-19 Epidemic in Xiong'an].

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.

THE CONTRIBUTION OF AIR EMISSION TO THE ENVIRONMENT OF GEELONG BASED ON THE PMF RECEPTOR MODEL*

The research aimed to evaluate the gas pollutant emission in a relatively closed and stable environment, specifically in the Geelong area on Corio Bay, Victoria state, Australia, under the circumstances of the global respiratory epidemic. During this pandemic, owing to the small local population and a limited number of travelers, industrial emissions have become the only vital factor to interfere with air quality, excluding the impact of ordinary daily traffic. PM10 (ug/m3) data were measured every hour by the Victorian Government, uninterruptedly from 2017 Janu-ary 1st to 2020 December 31th. The emission of industrial waste gas and the leakage of fossil oil jointly determine local air conditions, which can be reflected in the numerical value of the PM10 in the Geelong area. Sample data of PM10 were analyzed through the US EPA Positive Matrix Factorization model (PMF 5.0) to show the tested factor and contribution output. The results demonstrate the actual air condition in a local environment, which reflects the impact of regional factories on the environment. In addition, the model result will be compared to the annals data to testify its accuracy and precision;moreover, it will forecast the next year’s air condition, which is of practical significance for treatment of waste gas emissions from factories and for the development of environmental protection. © 2021, Polish Society Magnesium Research. All rights reserved.

Probing the formation, structure and free energy relationships of M protein dimers of SARS-CoV-2.

The M protein of the novel coronavirus 2019 (SARS-CoV-2) is the major structural component of the viral envelope and is also the minimum requirement for virus particle budding. M proteins generally exist as dimers. In virus assembly, they are the main driving force for envelope formation through lateral interactions and interactions with other viral structural proteins that play a central role. We built 100 candidate models and finally analyzed the six most convincing structural features of the SARS-CoV-2 M protein dimer based on long-timescale molecular dynamics (MD) simulations, multiple free energy analyses (potential mean force (PMF) and molecular mechanics Poisson-Boltzmann surface area (MMPBSA)) and principal component analysis (PCA) to obtain the most reasonable structure. The dimer stability was found to depend on the Leu-Ile zipper motif and aromatic amino acids in the transmembrane domain (TMD). Furthermore, the C-terminal domain (CTD) effects were relatively small. These results highlight a model in which there is sufficient binding affinity between the TMDs of M proteins to form dimers through the residues at the interface of the three transmembrane helices (TMHs). This study aims to help find more effective inhibitors of SARS-CoV-2 M dimers and to develop vaccines based on structural information.

Elucidating the responses of highly time-resolved PM2.5 related elements to extreme emission reductions.

China's unprecedented lockdown to contain the spread of the novel coronavirus disease (COVID-19) in early 2020, provided a tragic natural experiment to investigate the responses of atmospheric pollution to emission reduction at regional scale. Primarily driven by primary emissions, particulate trace elements is vitally important due to their disproportionally adverse impacts on human health and ecosystem. Here 14 trace elements in PM2.5 were selected for continuous measurement hourly in urban representative site of Shanghai, for three different phases: pre-control period (1-23 January 2020), control period (24 January-10 February 2020; overlapped with Chinese Lunar New Year holiday) and post control period (11-26 February 2020) the city's lockdown measures. The results show that all meteorological parameters (including temperature, RH, mixing layer height et al.) were generally consistent among different periods. Throughout the study period, the concentrations of most species displayed a "V-shaped" trend, suggesting significant effects by the restriction measures imposed during the lockdown period. While this is not the case for species like K, Cu and Ba, indicating their unusual origins. As a case study, the geographical origins of Cu were explored. Seven major sources, i.e., Vehicle-related emission (including road dust; indicative of Ca, Fe, Ba, Mn, Zn, Cu; accounting for 30.1%), shipping (Ni; 5.0%), coal combustion (As, Pb; 4.2%), Se and Cr industry (24.9%), nonferrous metal smelting (Au, Hg; 7.5%) and fireworks burning (K, Cu, Ba; 28.3%) were successfully pinpointed based on positive matrix factorization (PMF) analysis. Our source apportionment results also highlight fireworks burning was one of the dominant source of trace elements during the Chinese Lunar New Year holiday. It is worth noting that 56% of the total mass vehicular emissions are affiliated with non-exhaust sources (tire wear, brake wear, and road surface abrasion).

Effects of COVID-19 lockdown on PM10 composition and sources in the Rome Area (Italy) by elements' chemical fractionation-based source apportionment

During the national lockdown imposed by Italian government (from March 9th to May 18th 2020) to counter the Covid-19 pandemic, 24-h PM10 samples were collected at three sites in the Rome area (Central Italy), two urban (Sapienza and Via Saredo, highly impacted by vehicular traffic) and one peri-urban (Montelibretti, more impacted by biomass domestic heating). Further, at Sapienza and Montelibretti PM10 daily sampling had been carried out in the period immediately before lockdown, and at Via Saredo samples were additionally collected also after the end of lockdown. PM10 was chemically speciated for main components (major elements, inorganic ions, EC, OC, levoglucosan), and trace elements. The latter were chemically fractionated and considered for their water-soluble and insoluble fractions, which proved to be more source-selective than total element. Three datasets were thus built and analyzed by Positive Matrix Factorization (PMF), with the aim of identifying and apportioning mass contributions of sources acting in the periods before, during and after lockdown, in the Rome area. Identified emission sources were mostly from long-range advection (two different contributions of mineral dust, fresh sea spray, heavy oil combustion), while local sources (vehicular traffic and biomass burning) were strongly abated during lockdown, with respect to previous sampling period, and inorganic secondary aerosol showed a progressive increment of sulfates, driven by seasonal evolution from winter to spring. Since the lockdown interrupted all non-essential productive and work activities, thus reducing the chemical fingerprinting of local sources, this occurrence allowed to clearly describe both profiles and source contribution estimates of long-range transported PM10 components. Moreover, it allowed assessing the reduction of the impact of anthropogenic sources (such as vehicular traffic) and the efficiency of mitigation measures generally taken to control PM10 mass concentration. Acidic sulfates (bisulfate and letovicite) resulted associated to mineral dust transport events, and the role of chemically fractionated elements as source-specific tracers was further confirmed.

Variations and Sources of Organic Aerosol in Winter Beijing under Markedly Reduced Anthropogenic Activities During COVID-2019.

The COVID-19 outbreak provides a "controlled experiment" to investigate the response of aerosol pollution to the reduction of anthropogenic activities. Here we explore the chemical characteristics, variations, and emission sources of organic aerosol (OA) based on the observation of air pollutants and combination of aerosol mass spectrometer (AMS) and positive matrix factorization (PMF) analysis in Beijing in early 2020. By eliminating the impacts of atmospheric boundary layer and the Spring Festival, we found that the lockdown effectively reduced cooking-related OA (COA) but influenced fossil fuel combustion OA (FFOA) very little. In contrast, both secondary OA (SOA) and O3 formation was enhanced significantly after lockdown: less-oxidized oxygenated OA (LO-OOA, 37% in OA) was probably an aged product from fossil fuel and biomass burning emission with aqueous chemistry being an important formation pathway, while more-oxidized oxygenated OA (MO-OOA, 41% in OA) was affected by regional transport of air pollutants and related with both aqueous and photochemical processes. Combining FFOA and LO-OOA, more than 50% of OA pollution was attributed to combustion activities during the whole observation period. Our findings highlight that fossil fuel/biomass combustion are still the largest sources of OA pollution, and only controlling traffic and cooking emissions cannot efficiently eliminate the heavy air pollution in winter Beijing.

Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China.

Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and total solar radiation or oxidants to reduce the effects of dispersion and chemical loss. These methods were applied to hourly speciated VOC data from November 2019 to March 2020 including during the COVID-19 shutdown. Various comparisons were made to assess the influences of these fluctuation drivers by time of day. Dispersion normalized PMF (DN-PMF) reduced the dispersion variations. Dispersion-radiation normalized PMF (DRN-PMF) reduced the impact of chemical loss, especially at night, which was better than Dispersion-Ox normalized PMF (DON-PMF). The conditional bivariate probability function (CBPF) plots of DRN-PMF results were consist with actual source locations. The DN-PMF, DRN-PMF, and DON-PMF results were consistent between 10:00 and 15:00, suggesting dispersion was significantly more influential than photochemical reactions during these times. The DRN-PMF results indicated that the highest VOC contributors during the COVID-19 shutdown were liquefied petroleum gas (LPG) (28.8%), natural gas (25.2%), and pulverized coal boilers emissions (19.6%). Except for petrochemical-related enterprises and LPG, the contribution concentrations of all other sources decreased substantially during the COVID-19 shutdown, by 94.7%, 90.6%, and 86.8% for vehicle emissions, gasoline evaporation, and the mixed source of diesel evaporation and solvent use, respectively. Controlling the use of motor vehicles and related volatilization of diesel fuel and gasoline can be effective in controlling VOCs in the future.

Mechanism of the enhancing effect of glycyrrhizin on nifedipine penetration through a lipid membrane.

The saponin glycyrrhizin from liquorice root shows the ability to enhance the therapeutic activity of other drugs when used as a drug delivery system. Due to its amphiphilic properties, glycyrrhizin can form self-associates (dimers, micelles) and supramolecular complexes with a wide range of hydrophobic drugs, which leads to an increase in their solubility, stability and bioavailability. That is why the mechanism of the biological activity of glycyrrhizin is of considerable interest and has been the subject of intensive physical and chemical research in the last decade. Two mechanisms have been proposed to explain the effect of glycyrrhizin on drug bioavailability, namely, the increase in drug solubility in water and enhancement of the membrane permeability. Interest in the membrane-modifying ability of glycyrrhizic acid (GA) is also growing at present due to its recently discovered antiviral activity against SARS-CoV-2 Bailly and Vergoten (2020) [1]. In the present study, the passive permeability of the DOPC lipid membrane for the calcium channel blocker nifedipine was elucidated by parallel artificial membrane permeability assay (PAMPA) and full atomistic molecular dynamics (MD) simulation with free energy calculations. PAMPA experiments show a remarkable increase in the amount of nifedipine (NF) permeated with glycyrrhizin compared to free NF. In previous studies, we have shown using MD techniques that glycyrrhizin molecules can integrate into the lipid bilayer. In this study, MD simulation demonstrates a significant decrease in the energy barrier of NF penetration through the lipid bilayer in the presence of glycyrrhizin both in the pure DOPC membrane and in the membrane with cholesterol. This effect can be explained by the formation of hydrogen bonds between NF and GA in the middle of the bilayer.

[High-frequency Responses to the COVID-19 Shutdown of Heavy Metal Elements in PM2.5 in Shanghai].

To study the evolution and sources of heavy metal elements in the urban atmosphere before, during (overlapped with Chinese Lunar New Year), and after China's COVID-19 shutdown, a multi-metal online analyzer was deployed to determine the trace elements in PM2.5 in Shanghai from January 1 to February 26, 2020. Meanwhile, source apportionment of the hourly measured heavy metal concentrations was performed using a PMF model, in which eight sources were identified. The results show that the concentrations of most elements presented a "V-shaped" trend, which was mainly influenced by emissions from fireworks (K, Cu, Ba as indicative elements), Se-related industry, road dust (Ca, Fe, Ba), and motor vehicles (Mn, Zn, Fe, Cu). However, during the COVID-19 shutdown period, the concentrations of K, Ba, and Cu were high. Case-specific analysis suggested that prior to the shutdown period, the high concentrations of Cu were significantly influenced by long-range transport, which shifted to a dominant contribution from local fireworks during the shutdown period.