Ambient Pollution Levels Research Articles

Impact of Warehouse Expansion on Ambient PM2.5 and Elemental Carbon Levels in Southern California's Disadvantaged Communities: A Two‐Decade Analysis

AbstractOver the past two decades, the surge in warehouse construction near seaports and in economically lower‐cost land areas has intensified product transportation and e‐commerce activities, particularly affecting air quality and health in nearby socially disadvantaged communities. This study, spanning from 2000 to 2019 in Southern California, investigated the relationship between ambient concentrations of PM2.5 and elemental carbon (EC) and the proliferation of warehouses. Utilizing satellite‐driven estimates of annual mean ambient pollution levels at the ZIP code level and linear mixed effect models, positive associations were found between warehouse characteristics such as rentable building area (RBA), number of loading docks (LD), and parking spaces (PS), and increases in PM2.5 and EC concentrations. After adjusting for demographic covariates, an Interquartile Range increase of the RBA, LD, and PS were associated with a 0.16 μg/m³ (95% CI = [0.13, 0.19], p < 0.001), 0.10 μg/m³ (95% CI = [0.08, 0.12], p < 0.001), and 0.21 μg/m³ (95% CI = [0.18, 0.24], p < 0.001) increase in PM2.5, respectively. For EC concentrations, an IQR increase of RBA, LD, and PS were each associated with a 0.021 μg/m³ (95% CI = [0.019, 0.024], p < 0.001), 0.014 μg/m³ (95% CI = [0.012, 0.015], p < 0.001), and 0.021 μg/m³ (95% CI = [0.019, 0.024], p < 0.001) increase. The study also highlighted that disadvantaged populations, including racial/ethnic minorities, individuals with lower education levels, and lower‐income earners, were disproportionately affected by higher pollution levels.

Ambient air pollution decreased normal fertilization rate via the mediation of seminal prosaposin

ObjectiveThis study focuses on the association between seminal concentration of prosaposin and ambient air pollutants and whether the association affects the normal fertilization rate in vitro fertilization (IVF) treatment. MethodsThe cohort of 323 couple participants aged 22–46 was recruited from Jan. 2013 to Jun. 2018. At enrollment, resident address information was obtained and semen parameters of male counterparts were evaluated according to WHO criteria. We used inverse distance weighting interpolation to estimate the levels of ambient pollutants (SO2, O3, CO, NO2, PM2.5, and PM10) in the surrounding area. The exposure of each participant was estimated based on the data gathered from air quality monitoring stations and their home address over various periods (0–9, 10–14, and 0–90 days) before semen sampling. The generalized linear regression model (GLM) and the Bayesian kernel machine regression (BKMR) were used to analyze the associations between pollutants, semen parameters, prosaposin, and normal fertilization. Additionally, the mediating effect of prosaposin and semen parameters on the link between pollutants and normal fertilization was investigated. ResultsGLM and BKMR showed exposure to ambient air pollutants was all associated with the concentration of seminal prosaposin, among them, O3 and CO were also associated with normal fertilization (-0.10, 95 %CI: −0.13, −0.06; −26.43, 95 %CI: −33.79, −19.07). Among the semen parameters, only the concentration of prosaposin and total motile sperm count (TMC) was associated with normal fertilization (0.059, 95 %CI: 0.047, 0.071; 0.016, 95 %CI: 0.012, 0.020). Mediation analysis showed that prosaposin played a stronger mediating role than TMC in the relationship between short-term exposure to O3 and fertilization (66.83 %, P<0.001 versus 3.05 %, P>0.05). ConclusionSeminal plasma prosaposin showed a stronger meditating effect reflect the correlation between ambient air pollutants and normal fertilization rate than conventional semen parameters, which may be used as one of the indicators between pollution and fertilization in IVF.

Experimental Investigation of Parameters Influencing the Formation of Dry Bands and Related Electric Field

This paper presents an experimental investigation conducted to determine the influence of parameters such as the ambient temperature, pollution level, and substrate material on the formation of dry bands on polluted layers. To investigate these parameters, we applied a simplified insulator geometry, developed in our previous work, to experimentally control the complex process of dry band formation on a polluted surface. The simple geometry of the experimental model enabled the use of Plexiglas, RTV, and glass as construction substrate materials. RTV and glass were used to simulate a composite and ceramic insulator surface, respectively. Moreover, an electrooptic (EO) probe enabled the measurement of the axial E-field evolution at the surface of the dry band during dry band formation. The results indicated that the substrate material, ambient temperature, and pollution level substantially influence dry band formation. The effects of the first two parameters are directly associated with heat transfer phenomena in the substrate material and at the ambient air/substrate interface. The effect of the third parameter is associated with absorption and evaporation of the pollution layer. In addition, the appearance of the dry band can be clearly identified by a rapid increase in both the pollution layer resistance and the axial E-field in the dry band area. The value of the axial E-field is influenced primarily by the width of the dry band and by the pollution layer resistance, which is directly dependent on the humidification duration. Finally, because most of the results obtained herein were in accordance with those in the literature, we conclude that the proposed experimental model may provide an effective and inexpensive testing method for developing new materials and solutions for improving the dielectric performance of insulators used in polluted environments. Similarly, the simple geometry of the experimental model and the ability to easily control the experimental parameters may enable this tool to validate the results of various numerical models in studies of the thermoelectrical behavior of polluted insulators.

Effects of ambient air pollution on the risk of small- and large-for-gestational-age births: an analysis using national birth data in Japan.

Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births are major adverse birth outcomes related to newborn health. In contrast, the association between ambient air pollution levels and SGA or LGA births has not been investigated in Japan; hence, the purpose of our study is to investigate this association. We used birth data from Vital Statistics in Japan from 2017 to 2021 and municipality-level data on air pollutants, including nitrogen dioxide (NO2), sulfur dioxide (SO2), photochemical oxidants, and particulate matter 2.5 (PM2.5). Ambient air pollution levels throughout the first, second, and third trimesters, as well as the whole pregnancy, were calculated for each birth. The association between SGA/LGA and ambient levels of the air pollutants was investigated using crude and adjusted log-binomial regression models. In addition, a regression model with spline functions was also used to detect the non-linear association. We analyzed data from 2,434,217 births. Adjusted regression analyses revealed statistically significant and positive associations between SGA birth and SO2 level, regardless of the exposure period. Specifically, the risk ratio for average SO2 values throughout the whole pregnancy was 1.014 (95% confidence interval [CI] 1.009, 1.019) per 1ppb increase. In addition, regression analysis with spline functions indicated that an increase in risk ratio for SGA birth depending on SO2 level was linear. Furthermore, statistically significant and negative associations were observed between LGA birth and SO2 except for the third trimester. It was suggested that ambient level of SO2 during the pregnancy term is a risk factor for SGA birth in Japan.

Direct deposition of air pollutants in the wake of container vessels: The missing term in the environmental impact of shipping

Understanding the deposition of pollutants produced by the operation of vessels is necessary to quantify air-water pollution interactions. This work develops and presents a novel model for calculating the amount of pollutants deposited on the sea water at the wake of vessels. Deposition depends on meteorological conditions, and vessel operation and design. The work was repeated for several subcategories of vessels included within the broader category of container ships and considered the impact of scrubber operation if such a system were installed on the vessel. Computational fluid dynamics (CFD) modelling was utilized, employing the open-source code OpenFOAM, to calculate the concentration of pollutants in the wake of the vessel. The sensitivity of deposition to different parameters was studied. The key parameters, including the wind relative speed and angle, the main engine power as a proxy for vehicle size, and the exhaust gas velocity, were combined to a single equation that can be used to predict deposition from sea-going container vessels. Direct deposition of pollutants (e.g., SO2) in the wake of vessels was found to be as much as 24 % of the total pollutant quantity produced, under favourable conditions. Direct deposition is so far neglected by air quality models that only report regional level deposition, starting from background ambient levels of pollution. This creates a bias to the predicted air and water pollution impacts. The use of the model proposed to whole vessel fleets, taking stock of the local weather conditions, will enable understanding the global impacts of direct deposition.

Ambient PM2.5 temporal variation and source apportionment in Mbarara, Uganda.

Air pollution is the leading environmental cause of death globally, and most mortality occurs in resource-limited settings such as sub-Saharan Africa. The African continent experiences some of the worst ambient air pollution in the world, yet there are relatively little African data characterizing ambient pollutant levels and source admixtures. In Uganda, ambient PM2.5 levels exceed international health standards. However, most studies focus only on urban environments and do not characterize pollutant sources. We measured daily ambient PM2.5 concentrations and sources in Mbarara, Uganda from May 2018 through February 2019 using Harvard impactors fitted with size-selective inlets. We compared our estimates to publicly available levels in Kampala, and to World Health Organization (WHO) air quality guidelines. We characterized the leading PM2.5 sources in Mbarara using x-ray fluorescence and positive matrix factorization. Daily PM2.5 concentrations were 26.7 μg m-3 and 59.4 μg m-3 in Mbarara and Kampala, respectively (p<0.001). PM2.5 concentrations exceeded WHO guidelines on 58% of days in Mbarara and 99% of days in Kampala. In Mbarara, PM2.5 was higher in the dry as compared to the rainy season (30.8 vs 21.3, p<0.001), while seasonal variation was not observed in Kampala. PM2.5 concentrations did not vary on weekdays versus weekends in either city. In Mbarara, the six main ambient PM2.5 sources identified included (in order of abundance): traffic-related, biomass and secondary aerosols, industry and metallurgy, heavy oil and fuel combustion, fine soil, and salt aerosol. Our findings confirm that air quality in southwestern Uganda is unsafe and that mitigation efforts are urgently needed. Ongoing work focused on improving air quality in the region may have the greatest impact if focused on traffic and biomass-related sources.

Real-Time Measurements of Indoor-Outdoor Exchange of Gaseous and Particulate Atmospheric Pollutants in an Urban Area.

Air pollution is one of the greatest environmental risks to health, causing millions of deaths and deleterious health effects worldwide, especially in urban areas where citizens are exposed to high ambient levels of pollutants, also influencing indoor air quality (IAQ). Many sources of indoor air are fairly obvious and well known, but the contribution of outside sources to indoor air still leads to significant uncertainties, in particular the influence that environmental variables have on outdoor/indoor pollutant exchange mechanisms. This is a critical aspect to consider in IAQ studies. In this respect, an experimental study was performed at a public site such as a university classroom during a non-academic period in Madrid city. This includes two field campaigns, in summer (2021) and winter (2020), where instruments for measuring gases and particle air pollutants simultaneously measured outdoor and indoor real-time concentrations. This study aimed to investigate the dynamic variations in the indoor/outdoor (I/O) ratios in terms of ambient outdoor conditions (meteorology, turbulence and air quality) and indoor features (human presence or natural ventilation). The results show that the I/O ratio is pollutant-dependent. In this sense, the infiltration capacity is higher for gaseous compounds, and in the case of particles, it depends on the particle size, with a higher infiltration capacity for smaller particles (<PM2.5). Additionally, under specific situations of high atmospheric stability, the concentrations of gases derived from traffic tend to accumulate in the room, keeping the background concentrations. These concentrations decreased when room ventilation was produced simultaneously with well-ventilated (high wind speed) external conditions. This suggests that the meteorology and turbulence parameters played a key role in influencing indoor ambient pollution conditions by enhancing the dispersion or accumulation of pollutants. The obtained results highlight the high number of variables involved in the outdoor/indoor exchange of air pollutants and, consequently, how complex its study is. Thus, the knowledge of these factors is critical for understanding the behavior of indoor pollutants and controlling human exposure in indoor environments.

Understanding the time-activity pattern to improve the measurement of personal exposure: An exploratory and experimental research

Although ambient fine particulate matter (PM2.5) concentrations and their components are commonly used as proxies for personal exposure monitoring, developing an accurate and cost-effective method to use these proxies for personal exposure measurement continues to pose a significant challenge. Herein, we propose a scenario-based exposure model to precisely estimate personal exposure level of heavy metal(loid)s (HMs) using scenario HMs concentrations and time-activity patterns. Personal exposure levels and ambient pollution levels for PM2.5 and HMs differed significantly with corresponding personal/ambient ratios of approximately 2, and exposure scenarios could narrow the assessment error gap by 26.1–45.4%. Using a scenario-based exposure model, we assessed the associated health risks of a large sample population and identified that the carcinogenic risk of As exceeded 1 × 10−6, while we observed non-carcinogenic risks from As, Cd, Ni, and Mn in personal exposure to PM2.5. We conclude that the scenario-based exposure model is a preferential alternative for monitoring personal exposure compared to ambient concentrations. This method ensures the feasibility of personal exposure monitoring and health risk assessments in large-scale studies.

Quantification of the degradation of paintings due to the deposition of atmospheric aerosols

Soiling of cultural heritage due to air pollution is a major challenge for the conservation community and it has motivated scientists to understand the mechanisms that govern the processes of degradation and the effectiveness of potential preventative measures. The relationship between perceptible optical degradation of paintings and cumulative exposure to particulate matter has so far not been well established. This study develops a method for the quantification of optical changes resulting from particulate mass deposition on the surface of realistic paintings simulating prolonged exposure in ambient conditions. For that purpose, a painting was exposed to diesel exhaust emissions simulating exposure equivalent to approximately 5 months in polluted atmospheric conditions. The color changes, assessed by a colorimetric technique, indicated detectable color changes under close observation by the end of the exposure. Similar results were obtained following the exposure of a blank canvas acting as a reference to omit potential color sensitivity to the measured optical changes. The experiments showed that exposing the canvases to levels of moderate ambient pollution results in perceptible color difference in less than a year, through a darkening and yellowing effect indicating the vulnerability of unprotected artwork.

Independent and interactive associations between greenness and ambient pollutants on novel glycolipid metabolism biomarkers: A national repeated measurement study

This study aims to investigate the independent and interactive effects of greenness and ambient pollutants on novel glycolipid metabolism biomarkers. A repeated national cohort study was conducted among 5085 adults from 150 counties/districts across China, with levels of novel glycolipid metabolism biomarkers of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c measured. Exposure levels of greenness and ambient pollutants (including PM1, PM2.5, PM10, and NO2) for each participant were determined based on their residential location. Linear mixed-effect and interactive models were used to evaluate the independent and interactive effects between greenness and ambient pollutants on the four novel glycolipid metabolism biomarkers. In the main models, the changes [β (95% CIs)] of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c were −0.021 (−0.036, −0.007), −0.120 (−0.175, −0.066), −0.092 (−0.122, −0.062), and −0.445 (−1.370, 0.480) for every 0.1 increase in NDVI, and were 0.004 (0.003, 0.005), 0.014 (0.009, 0.019), 0.009 (0.006, 0.011), and 0.067 (−0.019, 0.154) for every 1 μg/m3 increase in PM1. Results of interactive analyses demonstrated that individuals living in low-polluted areas could get greater benefits from greenness than those living in highly-polluted areas. Additionally, the results of mediation analyses revealed that PM2.5 mediated 14.40% of the association between greenness and the TyG index. Further research is needed to validate our findings.

Linking between ambient pollution and metals concentration in blood. Nationwide study based on the national blood banking system

This study was aimed to describe the chemical traces of air pollution in blood of residents and evaluate the association between ambient pollution and its dose absorbed internally by a human body.The national Magen David Adom Blood Services blood donation collection platform and the National Public Health Laboratory's testing services were utilized to conduct a human biomonitoring study among blood donors in Israel. The donors' residential addresses and donations sites' locations were geocoded and merged with the levels of pollutants recorded by the nearby monitoring stations. Pollutants included nitrogen dioxide (NO2), sulfate dioxide (SO2), ozone (O3), carbon monoxide (CO) and particulate matter of size <10 and 2.5 μm in diameter (PM10 & PM2.5). Metal concentrations were statistically analyzed by ratio t-test and a lognormal regression, and adjusted to age, gender and smoking (defined based on Cadmium values).The findings indicate an independent positive association between pollutants and metals' concentrations in blood. Specifically, an increase in interquartile range (IQR) of NO2 was associated with 9.5 % increase in As in blood. The increase in one IQR of PM10 and SO2 was associated with an increase in Pb, of 16.6 % and 12.4 %, respectively. SO2 was also adversely associated with Cd concentrations, by increasing its levels by 5.7 %. The donors' proximity to quarries was related to the Pb blood levels higher 1.47 times compared to donors without quarries close to their residence (p-value = 0.013).To conclude, ambient pollution levels are associated with internal metals' concentrations, reaffirming the link between the two in the pathological pathway from air pollution to morbidity.

Short-term effects of ambient ozone exposure on daily hospitalizations for circulatory diseases in Ganzhou, China: A time-series study

Adverse health effects of ambient ozone are getting widespread attention, but the evidence on the relationship between ozone levels and circulatory system diseases are limited and inconsistent. Daily data for ambient ozone levels and hospitalizations for total circulatory diseases and five subtypes in Ganzhou, China from January 1, 2016 to December 31, 2020 were collected. We constructed a generalized additive model with quasi-Poisson regression accounting for lag effects to estimate the associations between ambient ozone levels and the number of hospitalized cases of total circulatory diseases and five subtypes. The differences among gender, age, and season subgroups were furtherly assessed through stratified analysis. A total of 201,799 hospitalized cases of total circulatory diseases were included in the present study, including 94,844 hypertension (HBP), 28,597 coronary heart disease (CHD), 42,120 cerebrovascular disease (CEVD), 21,636 heart failure (HF), and 14,602 arrhythmia. Significantly positive associations were observed between ambient ozone levels and daily hospitalizations for total circulatory diseases and all subtypes except arrhythmia. Each 10 μg/m3 increase in ozone concentration, the risk of hospitalizations for total circulatory diseases, HBP, CHD, CEVD, and HF increased by 0.718% (95% confidence interval, 0.156%–1.284%), 0.956% (0.346%–1.570%), 0.499% (0.057%–0.943%), 0.386% (0.025%–0.748%), and 0.907% (0.118%–1.702%), respectively. The above associations remained significant after adjusting for other air pollutants. The risk of hospitalization for circulatory diseases was higher in warm season (May to October) and varied in gender and age subgroups. This study suggested that short-term exposure to ambient ozone may increase the risk of hospitalizations for circulatory diseases. Our findings reinforce the importance of reducing ambient ozone pollution levels for protecting public health.

Characterisation of ambient air quality over two urban sites on the South African Highveld

Air pollution is an environmental-health challenge that many developing and developed countries are struggling to deal with. The purpose of our study was to characterise the ambient air quality during the year 2019–2020 over two urban sites of DiepKloof and Vanderbijilpark which are located on the South African Highveld. The study characterised PM10, PM2.5, SO2, NO2 and O3. Findings were that PM10, PM2.5, SO2 and NO2 ambient concentrations predominantly peaked during the winter season in June, July and August with mean concentrations of 48.6 µg/m3, 29.2 µg/m3, 38.6 µg/m3 and 12.6 µg/m3, respectively for the DiepKloof site while for the Vanderbijilpark site, winter mean for PM10, PM2.5 and SO2 were recorded at 124 µg/m3, 50.7 µg/m3 and 22.1 µg/m3, respectively. The average daily pollutant concentrations of the majority of pollutants were elevated above the WHO air quality guideline limits. Analysis of variance showed the seasonal variations had a significant (all p-values less than 0.01) effect on the variability of pollutant concentrations in both sites. The study attributes these elevated ambient pollutant levels to industrial, domestic and vehicular emission sources that are scattered over the South African Highveld. The study also highlighted the impact of the first lockdown period in South Africa indicating that the first three-week lockdown had a significant (p-values less than 0.001) impact on the variability of pollutant concentrations in both Diep Kloof and Vanderbijlpark. The study also established that pollutant concentrations were more significantly affected by wind direction in the more industrialized Vanderbijlpark than in Diep Kloof. The study contributes towards air quality monitoring and management policy formulation both in South Africa and other African countries. Furthermore, the study contributes towards the academic body of knowledge. To curtail pollutant emissions governments have several options including tightening the air quality regulatory frameworks as well as establishing and supporting community-based air quality advocates. Air quality advocates can act as a conduit in raising general public awareness regarding the impact of air pollution on human health.

The “Weekend Effect” in Lightning Activity during Winter Thunderstorms over the Tel-Aviv, Israel, Metropolitan Area

We report the analysis of nine winter seasons (December, January, February (DJF)) aerosol and lightning data over the Tel-Aviv metropolitan area, Israel’s largest and densest urban region. Hourly averaged aerosol concentrations (PM2.5 and PM10) were obtained from 27 automatic air quality stations operated by the Ministry for Environmental Protection. Lightning data obtained from the Israeli Lightning Detection Network (ILDN) and by the Earth Network Total Lightning Network (ENTLN) for four overlapping seasons showed an irregular pattern, with lower activity during Sunday–Tuesday, and maximum activity on Wednesday and Thursday, but also on Saturday, when less pollution was present. The accepted explanation for the weekend effect is that increased amounts of particles tend to prolong the lifetime of storms and their total lightning amounts and change their intracloud/cloud-to-ground flash ratios. However, our results suggest that lightning is not directly related to the level of ambient pollution, but likely depends on the synergistic effects of desert dust and urban pollution particles in the area that affect the electrical structure of winter thunderstorms. Since the source of desert dust is independent of any regularity that can be attributed to anthropogenic activity (e.g., increased levels of pollution due to the traffic-load in Tel-Aviv), it obscures any weekend–weekday patterns that are often detected in other large metropolitan areas.

Sensitivity of modeled residential fine particulate matter exposure to select building and source characteristics: A case study using public data in Boston, MA

Many techniques for estimating exposure to airborne contaminants do not account for building characteristics that can magnify contaminant contributions from indoor and outdoor sources. Building characteristics that influence exposure can be challenging to obtain at scale, but some may be incorporated into exposure assessments using public datasets. We present a methodology for using public datasets to generate housing models for a test cohort, and examined sensitivity of predicted fine particulate matter (PM2.5) exposures to selected building and source characteristics. We used addresses of a cohort of children with asthma and public tax assessor's data to guide selection of floorplans of US residences from a public database. This in turn guided generation of coupled multi-zone models (CONTAM and EnergyPlus) that estimated indoor PM2.5 exposure profiles. To examine sensitivity to model parameters, we varied building floors and floorplan, heating, ventilating and air-conditioning (HVAC) type, room or floor-level model resolution, and indoor source strength and schedule (for hypothesized gas stove cooking and tobacco smoking). Occupant time-activity and ambient pollutant levels were held constant. Our address matching methodology identified two multi-family house templates and one single-family house template that had similar characteristics to 60 % of test addresses. Exposure to infiltrated ambient PM2.5 was similar across selected building characteristics, HVAC types, and model resolutions (holding all else equal). By comparison, exposures to indoor-sourced PM2.5 were higher in the two multi-family residences than the single family residence (e.g., for cooking PM2.5 exposure, by 26 % and 47 % respectively) and were sensitive to HVAC type and model resolution. We derived the influence of building characteristics and HVAC type on PM2.5 exposure indoors using public data sources and coupled multi-zone models. With the important inclusion of individualized resident behavior data, similar housing modeling can be used to incorporate exposure variability in health studies of the indoor residential environment.

A real-world digital study evaluating associations between levels of allergens and air pollutants, and severity and frequency of symptoms of allergic rhinitis (The DSApp study)

Allergic rhinitis (AR), a chronic inflammatory disease, significantly impacts quality of life and socioeconomic burden. AR inflammation is driven by environmental allergens as well as indoor and outdoor pollutants, with increased prevalence and symptoms associated with increasing levels of ambient pollutants. This real-world study investigated associations between AR symptoms, patient activity, and levels of environmental allergens and pollutants.

Air quality in underground metro station commuter platforms in Singapore: A cross-sectional analysis of factors influencing commuter exposure levels

The metro is a major component of public transport systems in urbanized cities and may expose commuters to indoor air pollutants. We examined how commuter exposure to indoor air pollutant levels varied with the characteristics of underground metro stations. We carried out a national study of 41 commuter platforms from 39 randomly selected underground stations in Singapore. We used generalized linear models to assess the variability of air pollutant concentrations with station characteristics. We computed commuter-weighted pollutant-specific station rankings to inform mitigation priority. PM2.5 (mean = 24.1 μg/m3) and PM10 (mean = 26.9 μg/m3) concentrations across commuter platforms were generally lower than those found outdoors while platform CO2 levels (mean = 608.1 ppm) were 1.7 times those outdoors. More stations exceeded the WHO 24-h mean exposure guidelines values for PM2.5 (n = 30, 73%) than for PM10 (n = 4, 10%). PM2.5, PM10 and CO2 levels were lowest in stations on the Circle, North-East and Downtown lines. PM2.5 and PM10 concentrations at platforms were positively associated with their outdoor concentrations. Mean CO2 concentration levels at platforms were the highest during commuter rush hours. Longer train arrival intervals were associated with lower CO2 levels. PM2.5 and PM10 levels in stations were negatively associated with the depth of the commuter platforms. Commuter volumes influenced the priority ranking of mitigation measures. Underground metro stations exhibited high variability and dependence on station characteristics as well as outdoor ambient pollutant levels. Our study findings suggest that any required improvements in ventilation and station design should be focused on PM2.5 exposure reduction and prioritized according to both indoor air pollutant levels and commuter volumes to provide the largest extent of commuter benefits.

Impact of inhaled pollutants on response to viral infection in controlled exposures

Air pollutants are a major source of increased risk of disease, hospitalization, morbidity, and mortality worldwide. The respiratory tract is a primary target of potential concurrent exposure to both inhaled pollutants and pathogens, including viruses. Although there are various associative studies linking adverse outcomes to co- or subsequent exposures to inhaled pollutants and viruses, knowledge about causal linkages and mechanisms by which pollutant exposure may alter human respiratory responses to viral infection is more limited. In this article, we review what is known about the impact of pollutant exposure on antiviral host defense responses and describe potential mechanisms by which pollutants can alter the viral infection cycle. This review focuses on evidence from human observational and controlled exposure, ex vivo, and in vitro studies. Overall, there are a myriad of points throughout the viral infection cycle that inhaled pollutants can alter to modulate appropriate host defense responses. These alterations may contribute to observed increases in rates of viral infection and associated morbidity and mortality in areas of the world with high ambient pollution levels or in people using tobacco products. Although the understanding of mechanisms of interaction is advancing through controlled in vivo and in vitro exposure models, more studies are needed because emerging infectious pathogens, such as severe acute respiratory syndrome coronavirus 2, present a significant threat to public health.

PM2.5 as a major predictor of COVID-19 basic reproduction number in the USA

Many studies have proposed a relationship between COVID-19 transmissibility and ambient pollution levels. However, a major limitation in establishing such associations is to adequately account for complex disease dynamics, influenced by e.g. significant differences in control measures and testing policies. Another difficulty is appropriately controlling the effects of other potentially important factors, due to both their mutual correlations and a limited dataset. To overcome these difficulties, we will here use the basic reproduction number (R0) that we estimate for USA states using non-linear dynamics methods. To account for a large number of predictors (many of which are mutually strongly correlated), combined with a limited dataset, we employ machine-learning methods. Specifically, to reduce dimensionality without complicating the variable interpretation, we employ Principal Component Analysis on subsets of mutually related (and correlated) predictors. Methods that allow feature (predictor) selection, and ranking their importance, are then used, including both linear regressions with regularization and feature selection (Lasso and Elastic Net) and non-parametric methods based on ensembles of weak-learners (Random Forest and Gradient Boost). Through these substantially different approaches, we robustly obtain that PM2.5 is a major predictor of R0 in USA states, with corrections from factors such as other pollutants, prosperity measures, population density, chronic disease levels, and possibly racial composition. As a rough magnitude estimate, we obtain that a relative change in R0, with variations in pollution levels observed in the USA, is typically ~30%, which further underscores the importance of pollution in COVID-19 transmissibility.

A spatiotemporal case-crossover model of asthma exacerbation in the City of Houston.

Case‐crossover design is a popular construction for analyzing the impact of a transient effect, such as ambient pollution levels, on an acute outcome, such as an asthma exacerbation. Case‐crossover design avoids the need to model individual, time‐varying risk factors for cases by using cases as their own ‘controls’, chosen to be time periods for which individual risk factors can be assumed constant and need not be modelled. Many studies have examined the complex effects of the control period structure on model performance, but these discussions were simplified when case‐crossover design was shown to be equivalent to various specifications of Poisson regression when exposure is considered constant across study participants. While reasonable for some applications, there are cases where such an assumption does not apply due to spatial variability in exposure, which may affect parameter estimation. This work presents a spatiotemporal model, which has temporal case‐crossover and a geometrically aware spatial random effect based on the Hausdorff distance. The model construction incorporates a residual spatial structure in cases when the constant assumption exposure is not reasonable and when spatial regions are irregular.