Variation in chemical composition and sources of PM2.5 during the COVID-19 lockdown in Delhi

Exploring the chemical composition and processes of submicron aerosols in Delhi using aerosol chemical speciation monitor driven factor analysis

Wintertime non-refractory submicron particulate matter (NR-PM1) species were measured in Delhi with an Aerodyne Aerosol Chemical Speciation Monitor (ACSM) during February-March 2018. The average NR-PM1 mass concentration throughout the study was 58.0 ± 42.6 µg m-3, where the contribution of organic aerosol (OA) was 69% of the total NR-PM1. In Delhi, chloride (10%) was the main inorganic contributor, followed by ammonium (8%), sulfate (7%), and nitrate (6%), contrasting with the prevalence of sulfate in most urban environments. Source apportionment analysis of the OA identified five major factors, including three primary contributors: hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-related OA (COA) and two secondary contributors: oxygenated primary OA (OPOA), and more-oxidized oxygenated OA (MO-OOA). A 19% rise in OPOA concentration was observed during high chloride episodes, suggesting the potential role of chloride in the atmospheric chemical transformation of OA. Traffic emissions significantly contribute to ambient OA, accounting for at least 41% of the total OA mass. Furthermore, the OA exhibited low oxidation levels regardless of its source. The f44:f43 analysis revealed slower atmospheric oxidization of OA compared to other urban locations worldwide. Further investigations, including chamber experiments tailored to the Delhi atmosphere, are necessary to elucidate the atmospheric oxidants and the genesis of secondary OA alongside primary emissions.

Application of a near real-time technique for the assessment of atmospheric arsenic and metals emissions from a copper smelter in an urban area of SW Europe

Emissions of metals and metalloids as a result of industrial processes, entail a great risk to human health. A high time resolution study on arsenic levels in PM10 in the city of Huelva (SW Spain) was carried out between September 2021 and September 2022. Hourly data obtained with a near real-time technique based on X-ray fluorescence were inter-compared with other offline analytical instrumentation. The results showed that the main origin of As and other metal(loid)s such as Zn and Pb, was the copper smelter located southwest to the city. Although the mean concentration of As during the study period (2.8 ng m-3) was lower than the target value (6 ng m-3) proposed by the European Directive 2004/107/EC, hourly peaks of up to 311 ng m-3 were measured. The highest concentrations of arsenic were reached in the early afternoon, related to the influence of breeze. A source apportionment study has identified five major sources of PM10: mineral, marine, combustion, regional and industry. The industrial source is characterized by high concentrations of As, Cu, Pb and Zn, contributing 1% of the total concentration of PM10 and related to copper smelter emissions. In addition, the analysis of two extreme North African dust outbreak events that affected southwestern Europe in March 2022, showed that this natural source contributed slightly to arsenic levels. The need to carry out high time resolution studies is demonstrated to better understand the variability in exposure to industrial metal(loid)s by the population, compared to conventional 24-h studies.

Sources and Specified Health Risks of 12 PM2.5-Bound Metals in a Typical Air-Polluted City in Northern China during the 13th Five-Year Plan

The continuous monitoring of PM2.5 (including 12 metal elements) was conducted in Jinan, a city with poor air quality in China, during the 13th Five-Year Plan (2016-2020). Positive matrix factorization (PMF) was used to identify emission sources of PM2.5-bound metals, and the health risks of the metals and their emission sources were assessed. During the study period, the concentration of most metals showed a decreasing trend (except Al and Be), and a significant seasonal difference was found: winter > fall > spring > summer. The PMF analysis showed that there were four main sources of PM2.5-bound metals, and their contributions to the total metals (TMs) were dust emissions (54.3%), coal combustion and industrial emissions (22.3%), vehicle emissions (19.3%), and domestic emissions (4.1%). The results of the health risk assessment indicated that the carcinogenic risk of metals (Cr and As) exceeded the acceptable level (1 × 10-6), which was of concern. Under the influence of emission reduction measures, the contribution of emission sources to health risks changes dynamically, and the emission sources that contribute more to health risks were coal combustion and industrial emissions, as well as vehicle emissions. In addition, our findings suggest that a series of emission reduction measures effectively reduced the health risk from emission sources of PM2.5-bound metals.

Study of secondary organic aerosol formation and aging using ambient air in an oxidation flow reactor during high pollution events over Delhi

Secondary aerosols constitute a significant fraction of atmospheric aerosols, yet our understanding of their formation mechanism and fate is very limited. In this work, the secondary organic aerosol (SOA) formation and aging of ambient air of Delhi are studied using a potential aerosol mass (PAM) reactor, an oxidation flow reactor (OFR), coupled with aerosol chemical speciation monitor (ACSM), proton transfer reaction time of flight mass spectrometer (PTR-ToF-MS), and scanning mobility particle sizer with counter (SMPS + C). The setup mimics atmospheric aging of up to several days with the generation of OH radicals. Variations in primary volatile organic compounds (VOCs) and oxygenated volatile organic compounds (OVOCs) as a function of photochemical age were investigated. Primary VOCs such as benzene, toluene, xylene, trimethyl benzene, etc. decrease and OVOCs like formic acid, formaldehyde, acetone, ethanol, etc. increase substantially upon oxidation in OFR. The highest organic aerosol (OA) enhancement was observed for the 4.2 equivalent photochemical days of aging i.e., 1.84 times the ambient concentration, and net OA loss was observed at very high OH exposure, typically after 8.4 days of photochemical aging due to heterogeneous oxidation followed by fragmentation/evaporation. In ambient air, OA enhancement is highest during nighttime due to the high concentrations of precursor VOCs in the atmosphere. SMPS + C results demonstrated substantial new particle formation upon aging and decrement in preexisting aerosol mass. This is the first experimental study conducting an in-situ evaluation of potential SOA mass generated from the ambient aerosols in India.

Assessment of metals and metalloids agglutinated to airborne suspended particulate matter in selected plant species during the pre-and post-monsoon in the urban area

The elemental accumulation has emerged as a major environmental concern due to various anthropogenic sources such as vehicles, road dust, and industrial activities, contributing to the agglutination of elements to airborne Suspended Particulate Matter (SPM). SPM-bound elements accumulate on plant surfaces impact air quality and human health due to their noxiousness. Therefore, plants' ability to capture and mitigate air pollutants plays a crucial role in urban areas. This study aimed to investigate the levels and distribution of twenty-six elements, comprised of heavy metals (Cd, Pb, Cr, Cu Zn, Co, Ni, Fe, Mn, Ag, Mo, V, Ga, and Bi), light metals (B, As, Te, and Se), and metalloids (Al, Li, Sr, K, Mg, Na, Ca, and Ba) accumulated on the surface and inside the leaves of dominant plant species during the pre-and post-monsoon at six categorized (commercial, traffic-prone, residential, educational, greenbelt and industrial areas) locations in Delhi, India. In addition, the Metal Accumulation Index (MAI) was determined, and the statistical analysis was conducted using two-way ANOVA, Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA). In the pre-and post-monsoon, two-way ANOVA revealed significant differences (P < 0.05) in metal concentrations. During the pre-monsoon plants exhibited the highest metal accumulation (∼21%) at the Anand Vihar (commercial) in Delhi, with the maximum average concentrations of Cr (118.25 mg/kg), Cu (204.38 mg/kg), Zn (293.27 mg/kg), and Fe (2721.17 mg/kg). Ficus benghalensis L exhibited the maximum 213.73 MAI at the Anand Vihar in the pre-monsoon. Ni and Cr indicated the highest correlation (P < 0.05, r = 0.82) in the PCA test. HCA test revealed similarity (∼87.7%) at ITO (traffic-prone) and Okhla Phase-2 (industrial) in F. religiosa regarding metal concentration patterns. Findings highlighted seasonal elemental pollutants uptake dynamics of plant species and explored species-specific metal accumulation, revealing potential implications of metal-tolerant plants for urban greenbelt.

Chemical characterization and source apportionment of PM2.5 in a Northeastern China city during the epidemic period

To investigate the influence of COVID-19 lockdown measures on PM2.5 and its chemical components in Shenyang, PM2.5 samples were continuously collected from January 1 to May 31, 2020. The samples were then analyzed for water-soluble inorganic ions, metal elements, organic carbon, and elemental carbon. The findings indicated a significant decrease in PM2.5 and its various chemical components during the lockdown period, compared to pre-lockdown levels (p < 0.05), suggesting a substantial improvement in air quality. Water-soluble inorganic ions (WSIIs) were identified as the primary contributors to PM2.5, accounting for 47% before the lockdown, 46% during the lockdown, and 37% after the lockdown. Ionic balance analysis revealed that PM2.5 exhibited neutral, weakly alkaline, and alkaline characteristics before, during, and after the lockdown, respectively. NH4+ was identified as the main balancing cation and was predominantly present in the form of NH4NO3 in the absence of complete neutralization of SO42- and NO3-. Moreover, the higher sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), along with the significant increase in PM2.5/EC, suggested intense secondary transformation during the lockdown period. The elevated OC/EC ratio during the lockdown period implied higher secondary organic carbon (SOC), and the notable increase in SOC/EC ratio indicated a significant secondary transformation of total carbon. The enrichment factor (EF) results revealed that during the lockdown, 9 metal elements (As, Sn, Pb, Zn, Cu, Sb, Ag, Cd, and Se) were substantially impacted by anthropogenic emissions. Source analysis of PMF was employed to identify the sources of PM2.5 in Shenyang during the study period, and the analysis identified six factors: secondary sulfate and vehicle emissions, catering fume sources, secondary nitrate and coal combustion emissions, dust sources, biomass combustion, and industrial emissions, with secondary sulfate and vehicle emissions and catering fume sources contributing the most to PM2.5.

A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown

COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 μg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 μg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

Assessing the effect of COVID 19 lockdowns on the composition of organic compounds and potential source of PM2.5 in Hanoi, Vietnam

The ambient air quality during COVID-19 lockdowns has been improved in many cities in the world. This study is to assess the changes in persistent organic pollutants in PM2.5 during the COVID-19 lockdown in Hanoi. Individual organic species in PM2.5 ((e.g., polycyclic aromatic hydrocarbons (PAHs), polychlorobiphenyls (PCBs), and organochlorine pesticides (OCPs)) were measured in an urban residential area in Hanoi from before the March 10th to April 22nd, 2020, including before the partial lockdown (BL) and the partial lockdown (PL) phases. During the PL phase, the concentration of Σ14PAHs and Σ28PCBs was reduced by 38 and 52% compared with the BL period, respectively. The diagnostic ratio method implied that the sources of PAHs within the PL phase had a less effect on traffic and industrial activities than in the BL phase. The characteristic ratio method indicated that PCBs were mixed by commercial product and combustion process in both the BL and the PL periods, however, the source of PCBs in the BL phase was influenced by municipal waste incineration more than those in the PL phase. The decreasing concentration of Σ20OCPs during the partial lockdown was attributed to the restriction of human activities during the quarantine period. The results suggested that the source of OCPs was probably derived from the usage of pesticides in current and, historical degradation or the transportation of pesticides from the soil to the atmosphere.

Estimating morning and evening commute period O3 concentration in Taiwan using a fine spatial-temporal resolution ensemble mixed spatial model with Geo-AI technology

Elevated levels of ground-level ozone (O3) can have harmful effects on health. While previous studies have focused mainly on daily averages and daytime patterns, it's crucial to consider the effects of air pollution during daily commutes, as this can significantly contribute to overall exposure. This study is also the first to employ an ensemble mixed spatial model (EMSM) that integrates multiple machine learning algorithms and predictor variables selected using Shapley Additive exExplanations (SHAP) values to predict spatial-temporal fluctuations in O3 concentrations across the entire island of Taiwan. We utilized geospatial-artificial intelligence (Geo-AI), incorporating kriging, land use regression (LUR), machine learning (random forest (RF), categorical boosting (CatBoost), gradient boosting (GBM), extreme gradient boosting (XGBoost), and light gradient boosting (LightGBM)), and ensemble learning techniques to develop ensemble mixed spatial models (EMSMs) for morning and evening commute periods. The EMSMs were used to estimate long-term spatiotemporal variations of O3 levels, accounting for in-situ measurements, meteorological factors, geospatial predictors, and social and seasonal influences over a 26-year period. Compared to conventional LUR-based approaches, the EMSMs improved performance by 58% for both commute periods, with high explanatory power and an adjusted R2 of 0.91. Internal and external validation procedures and verification of O3 concentrations at the upper percentile ranges (in 1%, 5%, 10%, 15%, 20%, and 25%) and other conditions (including rain, no rain, weekday, weekend, festival, and no festival) have demonstrated that the models are stable and free from overfitting issues. Estimation maps were generated to examine changes in O3 levels before and during the implementation of COVID-19 restrictions. These findings provide accurate variations of O3 levels in commute period with high spatiotemporal resolution of daily and 50m * 50m grid, which can support control pollution efforts and aid in epidemiological studies.

Chemical composition, sources, and health risks of PM2.5 in small cities with different urbanization during 2020 Chinese Spring Festival

To investigate the impact of quarantine measures and fireworks banning policy on chemical composition and sources of PM2.5 and associated health risks in small, less developed cities, we sampled in Guigang (GG), Shaoyang (SY), and Tianshui (TS), located in eastern, central, and north-western China, in 2020 Spring Festival (CSF). Mass concentration, carbonaceous, metals, and WSIIs of PM2.5 were analyzed. The study found high levels of PM2.5 pollution with the average concentration of 168.05 µg/m3 in TS, 134.59 µg/m3 in SY, and 125.71 µg/m3 in GG. A negative correlation was found between the urbanization level and PM2.5 pollution. Lockdown measures reduced PM2.5 mass and industrial elements. In non-control period (NCP), combustion and fireworks were the major sources of PM2.5 in GG and TS, and industry source accounted for a significant proportion in the relatively more urbanized SY. Whereas on control period (CP), soil dust, combustion, and road dust were the main source in GG, secondary aerosols dominated in SY and TS. Our health risk assessment showed unacceptable levels of non-carcinogenic and carcinogenic risks over the study areas, despite lockdown measures reducing health risks. As and Cr(VI), as the major pollutants, their associated sources, industry sources, and fireworks sources, posed the greatest risk to people at the sampling sites after exposure to PM2.5. This work supports the improvement of PM2.5 control strategies in small Chinese cities during the CSF.

Elemental composition of atmospheric PM10 during COVID-19 lockdown and recovery periods in Moscow (April-July 2020)

Changes in the concentrations of PM10-bound potentially toxic elements (PTEs) during the COVID-19 lockdown period and after the revocation of restrictions were analyzed using the data received at the Aerosol Complex of Moscow State University in April-July 2020. During the lockdown, the input of biomass combustion products enriched in PTEs from the Moscow region hindered the decrease in pollutant concentrations. After the introduction of the self-isolation regime, lower concentrations of most PTEs occurred due to the decrease in anthropogenic activity and the rainy meteorological conditions. After the revocation of restrictive measures, the PTE concentrations began to increase. Multivariate statistical analysis (APCA-MLR) identified the main sources of atmospheric pollutants as urban dust, non-exhaust traffic emissions, and combustion and exhaust traffic emissions. PM10 particles were significantly enriched with Sb, Cd, Sn, Bi, S, Pb, Cu, Mo, and Zn. The total non-carcinogenic and carcinogenic risks, calculated according to the U.S. EPA model, decreased by 24% and 23% during the lockdown; after the removal of restrictions, they increased by 61% and 72%, respectively. The study provides insight into the PTE concentrations and their main sources at different levels of anthropogenic impact.

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study

BACKGROUND

Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources.

METHODS

We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways.

RESULTS

We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic.

CONCLUSIONS

Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.

Spatiotemporal variability and health risk assessment of PM2.5 and NO2 over the Indo-Gangetic Plain: A three years long study (2019-21)

Studying the spatiotemporal variability of pollutants is necessary to identify the pollution hotspots with high health risk and enable the agencies to implement pollution abatement strategies in a targeted manner. Present study reports the spatio-temporal variability and health risk assessment (HRA) of PM2.5 (Particulate matter with aerodynamic diameter <2.5μm) and NO2 over IGP from 2019-2021. The HRA is expressed as passively smoked cigarettes (PSC) for four different health outcomes i.e., low birth weight (LBW), percentage decreased lung function (DLF) in school aged children, lung cancer (LC), and cardiovascular mortality (CM). The findings confirm very high PM2.5 and NO2 mass concentrations and high health risk over middle IGP and Delhi as compared to upper and lower IGP. Within Delhi, north Delhi region is the most polluted and at highest risk as compared to central and south Delhi. The health risk associated with PM2.5 over IGP is highest for DLF, equivalent to 21.63 PSCs daily, followed by CM (11.69), LBW (8.27) and LC (6.94). For NO2, the health risk is highest for DLF (3.09 PSCs) and CM (2.95), followed by LC (1.47) and LBW (1.04). PM2.5 and NO2 concentrations, along with the associated health risks, are highest during the post-monsoon and winter seasons and lowest during the monsoon season.

Short-Term Effects: Elemental and Morphological Assessment of Aerosols Over Old Delhi Region, India

This study presents morphological and elemental characteristics of aerosols for the duration January-June, 2021, using Scanning Electron Microscope coupled with Energy Dispersive X-Ray (SEM–EDX). The results revealed that there were numerous spherical particles (D α ≤ 2.5 µm) but did not produced the expected EDX-spectra for elemental constituents. Limited deposited particles were observed which showed definite elemental constitutions. The results show that Cl, S, Al, Ca, K, Fe, Zn, Na, Mg, N, Tb, Ti, Ni, F, Cd, Cu, Mn, P and Cr were the overall determined elements, out of which Cl, S, Al, Ca, K, Fe, Zn, Na and Mg were the major constituents. Variation in particles’ shapes whether definite or irregular, columnar or spherical, flaky or aggregate or crystal-accumulation were attained on the basis of the major constituting element, majorly Ca-rich, S-rich, Cl-rich and Fe-rich. Interestingly, the physical characteristics of the particles varied with variation in elemental composition. All these indicate that there were specific sources contributing toward distinct particle-morphs. Ti, Tb and Cd need more analytical studies for their percent contribution. S, Cl and K contributed the most to the elemental composition as revealed by elemental relative proportion. Atomic weight percent curves for elements were slightly scattered during May. These probably played important role in defining the diversity indices, which was highest for April (2.17 ± 0.12). Particles containing six (P 6) to nine (P 9) elements dominated in this study, and particles containing seven elements (P 7) were generally observed.

Analysis of aerosol liquid water content and its role in visibility reduction in Delhi

Aerosols undergo significant changes due to water uptake under high RH conditions, leading to changes in physical, optical, and chemical properties. Detailed assessment and investigation are needed to understand better aerosol liquid water content (ALWC) characteristics in highly polluted regions like Delhi. Therefore, in this study, we examined the mass concentration and the factors governing the ALWC associated with PM_2.5 in Delhi for two winters (Dec 2019 to Jan 2020 and Dec 2020 to Feb 2021) using the real-time measurements of NR-PM_2.5 from Aerodyne aerosol chemical speciation monitor (ACSM) and the application of thermodynamic modeling (ISORROPIA II). The average NR-PM_2.5 mass concentration in the 2020-2021 winter was 152 μg/m³, about 50 % higher than the average mass concentration of 102 μg/m³ in 2019-2020. Consequently, the ALWC was also 60 % higher during 2020-2021, with an average mass concentration of 150 μg/m³. ALWC increased exponentially with RH and is significant when RH > 80 %. Further, all the inorganic components of NR-PM_2.5 were found to contribute significantly to ALWC uptake; however, the relative contribution varied in different RH conditions. Ammonium sulphate dominated the ALWC uptake among the inorganic components at low RH, but ammonium nitrate was the dominant contributor at high RH. The decreased chloride mass fraction in inorganics in the recent winters reduced its relative contribution to ALWC. High ALWC mass concentration during high PM_2.5 and high RH leads to a significant reduction in visibility. We further validated this visibility reduction by estimating the enhanced light scattering coefficient (f(RH)) and found that the hygroscopic growth is responsible for the enhanced visibility reduction during high RH conditions (> 85 %) when light scattering efficiency increased by a factor of >3.5. Sensitivity tests of f(RH) on mass concentration of inorganic salts showed that all the salts contributed almost equally. As revealed in our study, variations in PM_2.5 mass concentration and composition despite similar meteorological conditions between different winters indicate changing regional aerosol emissions. Therefore, long-term observations of ALWC and PM_2.5 chemical composition are required to arrive at actionable measures and mitigation strategies. Further, the focus should be on reducing the overall inorganic mass concentrations of PM_2.5 in general, decreasing the absolute ALWC, and improving visibility.

Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India

The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM2.5 concentrations and an enhancement in the O3 concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O3 formation, comprising 89.4%, 83.1%, and 88.9% of the O3 sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O3 concentrations at the surface layer. Compared with the Pre1 period, the O3 enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O3 removal rate by horizontal transport. During the Tri period, a slower consumption of O3 by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O3. Emission and aerosol processes constituted the major positive contributions to the net surface PM2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM2.5 production from emission and aerosol processes. The increased vertical transport rate of PM2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM2.5 during the Lock periods.

Impact of waste of COVID-19 protective equipment on the environment, animals and human health: a review

During the Corona Virus Disease 2019 (COVID-19) pandemic, protective equipment, such as masks, gloves and shields, has become mandatory to prevent person-to-person transmission of coronavirus. However, the excessive use and abandoned protective equipment is aggravating the world's growing plastic problem. Moreover, above protective equipment can eventually break down into microplastics and enter the environment. Here we review the threat of protective equipment associated plastic and microplastic wastes to environments, animals and human health, and reveal the protective equipment associated microplastic cycle. The major points are the following:1) COVID-19 protective equipment is the emerging source of plastic and microplastic wastes in the environment. 2) protective equipment associated plastic and microplastic wastes are polluting aquatic, terrestrial, and atmospheric environments. 3) Discarded protective equipment can harm animals by entrapment, entanglement and ingestion, and derived microplastics can also cause adverse implications on animals and human health. 4) We also provide several recommendations and future research priority for the sustainable environment. Therefore, much importance should be attached to potential protective equipment associated plastic and microplastic pollution to protect the environment, animals and humans.

Changes in stoichiometric characteristics of ambient air pollutants pre-to post-COVID-19 in China

To prevent the Corona Virus Disease 2019 (COVID-19) spreading, Chinese government takes a series of corresponding measures to restrict human mobility, including transportation lock-down and industries suspension, which significantly influenced the ambient air quality and provided vary rare time windows to assess the impacts of anthropological activities on air pollution. In this work, we divided the studied timeframe (2019/12/24-2020/2/24) into four periods and selected 88 cities from 31 representative urban agglomerations. The indicators of PM_2.5/PM₁₀ and NO₂/SO₂ were applied, for the first time, to analyze the changes in stoichiometric characteristics of ambient air pollutants pre-to post-COVID-19 in China. The results indicated that the ratios of NO₂/SO₂ presented a responding decline, especially in YRD (-5.01), YH (-3.87), and MYR (-3.84), with the sharp reduction of traffic in post-COVID-19 periods (P3-P4: 2.34 ± 0.94 m/m) comparing with pre-COVID-19 periods (P1-P2: 4.49 ± 2.03 m/m). Whereas the ratios of PM_2.5/PM₁₀ increased in P1-P3, then decreased in P4 with relatively higher levels (>0.5) in almost all urban agglomerations. Furthermore, NO₂ presented a stronger association with PM_2.5/PM₁₀ variation than CO; and PM_2.5 with NO₂/SO₂ variation than PM₁₀. In summary, the economic structure, lockdown measures and meteorological conditions could explain the noteworthy variations in different urban agglomerations. These results would be in great help for improving air quality in the post-epidemic periods.

Meteorology governs the variation of Delhi's high particulate-bound chloride levels

A significant number of past studies have reported Delhi to witness some of the highest levels of particulate-bound chloride compared to anywhere else in the world. The present study employs long-term, highly time-resolved chloride measurements at the IIT Delhi campus from February 2020 to April 2021. The present work sheds light on the dependence of high chloride levels in Delhi on the winds from the northwest direction. The study makes use of linear regression models and stepped linear models to quantify the role of meteorological variables in driving the seasonal variation of chloride in Delhi. The results indicate that ∼85-88% of the variation in chloride concentration observed in Delhi can be attributed to meteorological parameters, mainly temperature (T), relative humidity (RH), and percentage of wind incoming from the northwest (%NW). The results also suggest that the primary chloride emissions remain relatively consistent year-round, and are regionally transported from Delhi's northwest. The results of this study provide valuable insights in understanding the nature of the sources and the variability associated with the chloride levels in Delhi and thus provide a basis for future emission control strategies.

Changes in the concentration and composition of urban aerosols during the COVID-19 lockdown

This work investigates the impact of COVID-19 restrictive measures on the mass concentrations of PM1 and PM10, and their chemical components (water-soluble ions, organic and elemental carbon, and major and trace metals) at an urban site in the western Mediterranean. The evolution of gaseous pollutants (NOx, O3 and some volatile organic compounds) was also analyzed. The concentrations measured during the lockdown in 2020 were compared to those obtained during the same period over the preceding five years. The average decrease in the levels of NOx and traffic-related volatile organic compounds was higher than 50 %, while O3 concentrations did not exhibit significant variations during the study period. Our results show that temporal variations in PM1 and PM10 concentrations were strongly affected by the frequency of Saharan dust events. When these episodes were excluded from the analysis period, a 35 % decrease in PM1 and PM10 levels was observed. Traffic restrictions during the lockdown led to important reductions in the concentrations of elemental carbon and metals derived from road dust (e.g. Ca and Fe) and break wear (e.g. Cu). Regarding secondary inorganic aerosols, nitrate showed the largest reductions as a consequence of the drop in local emissions of NOx.

Impact of the COVID-19 lockdown on the chemical composition and sources of urban PM2.5

The lockdown measures caused by the COVID-19 pandemic substantially affected air quality in many cities through reduced emissions from a variety of sources, including traffic. The change in PM_2.5 and its chemical composition in downtown Toronto, Canada, including organic/inorganic composition and trace metals, were examined by comparing with a pre-lockdown period and respective periods in the three previous years. During the COVID-19 lockdown, the average traffic volume reduced by 58%, whereas PM_2.5 only decreased by 4% relative to the baselines. Major chemical components of PM_2.5, such as organic aerosol and ammonium nitrate, showed significant seasonal changes between pre- and lockdown periods. The changes in local and regional PM_2.5 sources were assessed using hourly chemical composition measurements of PM_2.5. Major regional and secondary PM_2.5 sources exhibited no clear reductions during the lockdown period compared to pre-lockdown and the previous years. However, cooking emissions substantially dropped by approximately 61% due to the restrictions imposed on local businesses (i.e., restaurants) during the lockdown, and then gradually increased throughout the recovery periods. The reduction in non-tailpipe emissions, characterized by road dust and brake/tire dust, ranged from 37% to 61%, consistent with the changes in traffic volume and meteorology across seasons in 2020. Tailpipe emissions dropped by approximately 54% and exhibited even larger reductions during morning rush hours. The reduction of tailpipe emissions was statistically associated with the reduced number of trucks, highlighting that a small fraction of trucks contributes disproportionally to tailpipe emissions. This study provides insight into the potential for local benefits to arise from traffic intervention in traffic-dominated urban areas and supports the development of targeted strategies and regulations to effectively reduce local air pollution.

Aerosol Loading and Radiation Budget Perturbations in Densely Populated and Highly Polluted Indo-Gangetic Plain by COVID-19: Influences on Cloud Properties and Air Temperature

Aerosols emitted in densely populated and industrialized Indo-Gangetic Plain, one of the most polluted regions in the world, modulate regional climate, monsoon, and Himalayan glacier retreat. Thus, this region is important for understanding aerosol perturbations and their resulting impacts on atmospheric changes during COVID-19 lockdown period, a natural experimental condition created by the pandemic. By analyzing 5 years (2016-2020) data of aerosols and performing a radiative transfer calculation, we found that columnar and near-surface aerosol loadings decreased, leading to reductions in radiative cooling at the surface and top of the atmosphere and atmospheric warming during lockdown period. Further, satellite data analyses showed increases in cloud optical thickness and cloud-particle effective radius and decrease in lower tropospheric air temperature during lockdown period. These results indicate critical influences of COVID-19 lockdown on regional climate and water cycle over Indo-Gangetic Plain, emphasizing need for further studies from modeling perspectives.

Influencing factors of PM2.5 and O3 from 2016 to 2020 based on DLNM and WRF-CMAQ

In this study, distributed lag nonlinear models (DLNM) were built to characterize the non-linear exposure-lag-response relationship between the concentration of PM_2.5 and O₃ and multiple influencing factors, including basic meteorological elements and precursors. Then, a stratified analysis of different years, seasons, pollution levels, and wind direction was conducted. DLNMs and coupled Weather Research and Forecasting Model-Community Multi-scale Air Quality Model (WRF-CMAQ) were used to evaluate PM_2.5 and O₃ changes attributed to meteorological conditions and anthropogenic emissions comparing 2020 with 2016. As DLNMs showed, PM_2.5 pollution was promoted by low wind speed, high temperature, low humidity, and high concentrations of SO₂, NO₂, and O₃, among which NO₂ tended to be the dominant influencing factor. O₃ pollution was promoted by low wind speed, high temperature, low humidity, high concentration of PM_2.5 and low concentration of NO₂, among which temperature tended to be the dominant influencing factor. Moreover, north-south and easterly winds showed the greatest contribution to PM_2.5 and O₃, respectively. Both DLNMs and CMAQ showed that anthropogenic factors alleviated PM_2.5 pollution but aggravated O₃ pollution in 2020 in comparison with 2016, so did meteorological factors, but with smaller impacts. And anthropogenic influences were more evident in heavily polluted seasons for both PM_2.5 and O₃. This research may help understand the influencing factors of PM_2.5 and O₃ and provide scientific guide for abatement policies. Moreover, the good consistency in the results obtained from DLNMs and CMAQ indicated the reliability of the two models.

Changes in air quality in Mexico City, London and Delhi in response to various stages and levels of lockdowns and easing of restrictions during COVID-19 pandemic

The impacts of COVID-19 lockdown restrictions have provided a valuable global experiment into the extent of improvements in air quality possible with reductions in vehicle movements. Mexico City, London and Delhi all share the problem of air quality failing WHO guideline limits, each with unique situations and influencing factors. We determine, discuss and compare the air quality changes across these cities during the COVID-19, to understand how the findings may support future improvements in their air quality and associated health of citizens. We analysed ground-level PM₁₀, PM_2.5, NO₂, O₃ and CO changes in each city for the period 1st January to August 31, 2020 under different phases of lockdown, with respect to daily average concentrations over the same period for 2017 to 2019. We found major reductions in PM₁₀, PM_2.5, NO₂ and CO across the three cities for the lockdown phases and increases in O₃ in London and Mexico City but not Delhi. The differences were due to the O₃ production criteria across the cities, for Delhi production depends on the VOC-limited photochemical regime. Levels of reductions were commensurate with the degree of lockdown. In Mexico City, the greatest reduction in measured concentration was in CO in the initial lockdown phase (40%), in London the greatest decrease was for NO₂ in the later part of the lockdown (49%), and in Delhi the greatest decrease was in PM₁₀, and PM_2.5 in the initial lockdown phase (61% and 50%, respectively). Reduction in pollutant concentrations agreed with reductions in vehicle movements. In the initial lockdown phase vehicle movements reduced by up to 59% in Mexico City and 63% in London. The cities demonstrated a range of air quality changes in their differing geographical areas and land use types. Local meteorology and pollution events, such as forest fires, also impacted the results.

Exploring short term spatio-temporal pattern of PM2.5 and PM10 and their relationship with meteorological parameters during COVID-19 in Delhi

Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM2.5 and PM10 - categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind speed, relative humidity, rainfall, pressure, sun hour and cloud cover) in Delhi. To aid the study, a comparison was made with the last two years (2018 to 2019), covering the same periods of pre-lockdown, lockdown and unlock phases of 2020. Correlation analysis, linear regression (LR) was used to examine the impact of meteorological parameters on particulate matter (PM) concentrations in Delhi, India. The findings showed that (i) substantial decline of PM concentration in Delhi during lockdown period, (ii) there were substantial seasonal variation of particulate matter concentration in city and (iii) meteorological parameters have close associations with PM concentrations. The findings will help planners and policy makers to understand the impact of air pollutants and meteorological parameters on infectious disease and to adopt effective strategies for future.