Humans spend close to 90% of their time within the indoor environment. Deteriorating indoor air quality, especially high PM10, PM2.5 and PM1 is slowly becoming a major concern. A study was carried out, for two years, to characterize the spatiotemporal variation of PM in the indoor-outdoor environment across different residential setups (R1, R2, R3, and MC) in the Delhi region. The study established correlation between monthly variations of Indoor/Outdoor (I/O) ratios and meteorological factors. The results showed Spatio-temporal variation in the average mass concentrations of PM10 recorded peak values during the winter season (avg. 514± 72.15 µg/m3) and minimum concentration was observed during monsoon (avg. 91.41± 22.64 µg/m3) months. Among all the sites, the mixed cluster (MC), a residential cum commercial zone reported the highest particulate matter concentration (avg. 308.10 ±37.23 µg/m3) and while R2 reported the least concentration (avg. 244.9± 27.65 µg/m3) within the indoor environment. The I/O ratios of particulate matter were observed to be highest in January (I/O ratio1.6) and lowest in June month (I/O ratio 0.8). PM10, PM2.5, and PM1 dynamics were found to be critically influenced by meteorological factors, regular household activities, and diverse building designs. The short- or long-term exposure of particulate pollutants (beyond the permissible limits) can increase the probability of acute health effects, so there is an utmost requirement to collect better and systematic information about actual exposure levels experienced in different urban residential environments.

Exposure to household dust is a common occurrence in all countries and causes various diseases. This study provided information on the number, shape, size distribution, and elemental composition of household dust particles collected in urban homes in Agadir city in Morocco. Moreover, a potential human health risk of exposure has been identified based on current research. Samples were analyzed using computer-controlled scanning electron microscopy and ImageJ image processing program. A total of 3296 particles were analyzed for their size, and 76 particles were classified according to their size and elemental composition. Household dust particles were classified in six types: micro-aggregates (31.6%), biogenic (5.3%), spherical (17.1%), subrounded (7.9%), subangular (11.8%), and angular (26.3%). These particles were determined to have originated from a distant source (Trask classification index between 1 and 2.5). They were large (Skewness asymmetry coefficient > 1), and ranged from 0.2 to 363 µm with an average value of 22.8 ± 0.6 µm in diameter. Dust particles with diameters of 5-10 µm and 10-20 µm were the most abundant, while dust diameters of 10-20 µm, 20-30 µm, and > 100 µm were the highest in volume. The domestic dust deposition rate was 19.8 ± 7.4 g/m2 per year. Household dust is one of the major sources of PM10 in the residential environment (44.6% of the total number of particles), and the studied properties of house dust are highly related to human health. Household dust is a critical element to be considered in the occurrence of respiratory and cardiovascular infections.

A simple and rapid method for the highly sensitive determination of polycyclic aromatic hydrocarbons (PAHs) from airborne fine particulate matter (PM2.5) in an urban environment of Delhi was developed. The target compounds were 10 of the 16 United States Environmental Protection Agency (US-EPA) priority PAHs: fluoranthene, pyrene, chrysene, benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo[a]pyrene, dibenzo(ah)anthracene, benzo(ghi)perylene, indeno(1,2,3-cd)pyrene. For collecting the samples, the following two locations in Delhi (India) were chosen: ITO and Okhla Industrial Area.  Two sets of samples at these locations of were collected for the purpose of investigation. The fine particulate matter samples were collected on glass fiber filter papers for 24h, from which the PAHs were extracted using dichloromethane (DCM) and hexane using ultrasonication method. Comparison of the characteristic emission of spectra of PAHs with standard spectra indicated the degree of condensation of aromatic compounds present in the investigated mixtures. However, this identification could be more effective with the use of the respective values of Δλ parameter for each particular component of the mixture. It has been found that the concentration of the PAHs is maximum during the winter season and minimum during the summer and monsoon seasons at both the locations.

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed. | peer reviewed

Inhalation exposure to fine particulate matter (PM₂.₅) represents a global concern due to the adverse effects in human health. In the last years, scientific community has been adopted the assessment of the PM₂.₅-bound pollutant fraction that could be released (bioaccessible fraction) in simulated lung fluids (SLFs) to achieve a better understanding of PM risk assessment and toxicological studies. Thus, bioaccessibility of 49 organic pollutants, including 18 polycyclic aromatic hydrocarbons (PAHs), 12 phthalate esters (PAEs), 11 organophosphorus flame retardants (OPFRs), 6 synthetic musk compounds (SMCs) and 2 bisphenols in PM₂.₅ samples was evaluated. The proposed method consists of a physiologically based extraction test (PBET) by using artificial lysosomal fluid (ALF) to obtain bioaccessible fractions, followed by a vortex-assisted liquid-liquid microextraction (VALLME) and a final analysis by programmed temperature vaporization-gas chromatography-tandem mass spectrometry (PTV-GC-MS/MS). The highest inhalation bioaccessibility ratio was found for bisphenol A (BPA) with an average of 83%, followed by OPFRs, PAEs and PAHs (with average bioaccessibilities of 68%, 41% and 34%, respectively). Correlations between PM₂.₅ composition (major ions, trace metals, equivalent black carbon (eBC) and UV-absorbing particulate matter (UVPM)) and bioaccessibility ratios were also assessed. Principal Component Analysis (PCA) suggested that PAHs, PAES and OPFRs bioaccessibility ratios could be positively correlated with PM₂.₅ carbonaceous content. Furthermore, both inverse and positive correlations on PAHs, PAEs and OPFRs bioaccessibilites could be accounted for some major ions and metal (oid)s associated to PM₂.₅, whereas no correlations comprising considered PM₂.₅ major ions and metal (oid)s contents and BPA bioaccessibility was observed. In addition, health risk assessment of target PM₂.₅-associated PAHs via inhalation was assessed in the study area considering both total and bioaccessible concentrations, being averaged human health risks within the safe carcinogenic and non-carcinogenic levels.

Individual-level studies with adjustment for important COVID-19 risk factors suggest positive associations of long-term air pollution exposure (particulate matter and nitrogen dioxide) with COVID-19 infection, hospitalisations and mortality. The evidence, however, remains limited and mechanisms unclear. We aimed to investigate these associations within UK Biobank, and to examine the role of underlying chronic disease as a potential mechanism. UK Biobank COVID-19 positive laboratory test results were ascertained via Public Health England and general practitioner record linkage, COVID-19 hospitalisations via Hospital Episode Statistics, and COVID-19 mortality via Office for National Statistics mortality records from March–December 2020. We used annual average outdoor air pollution modelled at 2010 residential addresses of UK Biobank participants who resided in England (n = 424,721). We obtained important COVID-19 risk factors from baseline UK Biobank questionnaire responses (2006–2010) and general practitioner record linkage. We used logistic regression models to assess associations of air pollution with COVID-19 outcomes, adjusted for relevant confounders, and conducted sensitivity analyses. We found positive associations of fine particulate matter (PM₂.₅) and nitrogen dioxide (NO₂) with COVID-19 positive test result after adjustment for confounders and COVID-19 risk factors, with odds ratios of 1.05 (95% confidence intervals (CI) = 1.02, 1.08), and 1.05 (95% CI = 1.01, 1.08), respectively. PM 2.5 and NO 2 were positively associated with COVID-19 hospitalisations and deaths in minimally adjusted models, but not in fully adjusted models. No associations for PM₁₀ were found. In analyses with additional adjustment for pre-existing chronic disease, effect estimates were not substantially attenuated, indicating that underlying chronic disease may not fully explain associations. We found some evidence that long-term exposure to PM₂.₅ and NO₂ was associated with a COVID-19 positive test result in UK Biobank, though not with COVID-19 hospitalisations or deaths.

The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NOX, NO₂, O₃, PM₁₀, PM₂.₅, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM₂.₅, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM₂.₅, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.

Numerous epidemiological studies have shown a close relationship between outdoor air pollution and increased risks for cancer, infection, and cardiopulmonary diseases. However, very few studies have investigated the potential health effects of coexposure to airborne particulate matter (PM) and bioaerosols through the transmission of infectious agents, particularly under the current circumstances of the coronavirus disease 2019 pandemic. In this study, we aimed to identify urinary metabolite biomarkers that might serve as clinically predictive or diagnostic standards for relevant diseases in a real-time manner. We performed an unbiased gas/liquid chromatography-mass spectroscopy (GC/LC-MS) approach to detect urinary metabolites in 92 samples from young healthy individuals collected at three different time points after exposure to clean air, polluted ambient, or purified air, as well as two additional time points after air repollution or repurification. Subsequently, we compared the metabolomic profiles between the two time points using an integrated analysis, along with Kyoto Encyclopedia of Genes and Genomes-enriched pathway and time-series analysis. We identified 33 and 155 differential metabolites (DMs) associated with PM and bioaerosol exposure using GC/LC-MS and follow-up analyses, respectively. Our findings suggest that 16-dehydroprogesterone and 4-hydroxyphenylethanol in urine samples may serve as potential biomarkers to predict or diagnose PM- or bioaerosol-related diseases, respectively. The results indicated apparent differences between PM- and bioaerosol-associated DMs at five different time points and revealed dynamic alterations in the urinary metabolic profiles of young healthy humans with cyclic exposure to clean and polluted air environments. Our findings will help in investigating the detrimental health effects of short-term coexposure to airborne PM and bioaerosols in a real-time manner and improve clinically predictive or diagnostic strategies for preventing air pollution-related diseases.

Little is known about the main sources of ambient particulate matter (PM) in the 22 Eastern Mediterranean Region (EMR) countries. We designed this study to systematically review all published and unpublished source apportionment (SA), identification and characterization studies as well as emission inventories in the EMR. Of 440 articles identified, 82 (11 emission inventory ones) met our inclusion criteria for final analyses. Of 22 EMR countries, Iran with 30 articles had the highest number of studies on source specific PM followed by Pakistan (n = 15 articles) and Saudi Arabia (n = 8 papers). By contrast, there were no studies in Afghanistan, Bahrain, Djibouti, Libya, Somalia, Sudan, Syria, Tunisia, United Arab Emirates and Yemen. Approximately 72% of studies (51) were published within a span of 2015–2021.48 studies identified the sources of PM₂.₅ and its constituents. Positive matrix factorization (PMF), principal component analysis (PCA) and chemical mass balance (CMB) were the most common approaches to identify the source contributions of ambient PM. Both secondary aerosols and dust, with 12–51% and 8–80% (33% and 30% for all EMR countries, on average) had the greatest contributions in ambient PM₂.₅. The remaining sources for ambient PM₂.₅, including mixed sources (traffic, industry and residential (TIR)), traffic, industries, biomass burning, and sea salt were in the range of approximately 4–69%, 4–49%, 1–53%, 7–25% and 3–29%, respectively. For PM₁₀, the most dominant source was dust with 7–95% (49% for all EMR countries, on average). The limited number of SA studies in the EMR countries (one study per approximately 9.6 million people) in comparison to Europe and North America (1 study per 4.3 and 2.1 million people respectively) can be augmented by future studies that will provide a better understanding of emission sources in the urban environment.

To investigate the chemical components, sources, and interactions of particulate matter (PM) and volatile organic compounds (VOCs), a field campaign was implemented during the spring of 2018 in nine cities in northwestern (NW) China. PM was mainly contributed by organic matter and water-soluble inorganic ions (41% for PM₁₀ and approximately 60% for PM₂.₅ and PM₁). Two typical haze patterns were observed: anthropogenic pollution type (AP-type), wherein contributions of sulfate, nitrate, and ammonium (SNA) increased, and dust pollution type (DP-type), wherein contributions of Ca²⁺ increased and SNA decreased. Source appointment suggested that regional sources contributed close to half to PM₂.₅ pollution (40% for AP-type and 50% for DP-type). Thus, sources from regional transport are also important for haze and dust pollution. The ranking of VOC concentrations was methanol > acetaldehyde > formic acid + ethanol > acetone. Compared with other cities, there are higher oxygenated VOCs (OVOCs) and lower aromatics in NW China. The relationships between VOCs and PM were discussed. The dominating secondary organic aerosols (SOA) formation potential precursors were C₁₀–aromatics, xylene, and styrene under low–nitrogen oxide (NOx) conditions, and benzene, C₁₀–aromatics, and toluene dominated under high–NOx conditions. The quadratic polynomial was the most suitable fitting model for their correlation, and the results suggested that VOC oxidations explained 6.1–10.8% and 9.9–20.7% of SOA formation under high–NOx and low–NOx conditions, respectively.