Air quality standards for the concentration of particulate matter 2.5, global descriptive analysis

Environmental Determinants of Post-Discharge Acute Respiratory Illness among Preterm Infants with Bronchopulmonary Dysplasia

OBJECTIVE

To analyze the association of components of the Centers for Disease Control and Prevention (CDC) Environmental Justice Index (EJI) with respiratory health outcomes among infants with bronchopulmonary dysplasia (BPD) within one year after discharge from the neonatal intensive care unit.

METHODS

This was a retrospective cohort study of a cohort of preterm infants with BPD. Multivariable logistic regression models estimated associations of EJI and its components with medically attended acute respiratory illness, defined as an ED visit or inpatient readmission, within one year of discharge from the neonatal intensive care unit. A mediation analysis was conducted to evaluate how environmental injustice may contribute to racial disparities in acute respiratory illness.

RESULTS

Greater EJI was associated with an increased risk of medically attended respiratory illness (per EJI standard deviation increment, aOR 1.38, 95% CI: 1.12-1.69). Of the index's components, the Environmental Burden Module's Air pollution domain had the greatest association (aOR 1.44, 95% CI: 1.44-2.61). With respect to individual indicators within the EJI, Diesel Particulate Matter (DSLPM) and Air Toxic Cancer Risk (ATCR) demonstrated the strongest relationship (aOR 2.06, 95% CI: 1.57-2.71 and aOR 2.10, 95% CI: 1.59-2.78, respectively). Among non-Hispanic Black infants, 63% experienced a medically attended acute respiratory illness as compared to 18% of non-Hispanic White infants. DSLPM mediated 39% of the Black-White disparity in medically attended acute respiratory illness (p = 0.004).

CONCLUSIONS

Environmental exposures, particularly air pollution, are associated with post-discharge respiratory health outcomes among preterm infants with BPD after adjusting for clinical, demographic, and social vulnerability risk factors. Certain types of air pollutants, namely, DSLPM, are more greatly associated with acute respiratory illness. Environmental exposures may contribute to racial disparities in medically attended acute respiratory illness among infants with BPD.

Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.

Emissions from modern engines induce distinct effects in human olfactory mucosa cells, depending on fuel and aftertreatment

Ultrafine particles (UFP) with a diameter of ≤0.1 μm, are contributors to ambient air pollution and derived mainly from traffic emissions, yet their health effects remain poorly characterized. The olfactory mucosa (OM) is located at the rooftop of the nasal cavity and directly exposed to both the environment and the brain. Mounting evidence suggests that pollutant particles affect the brain through the olfactory tract, however, the exact cellular mechanisms of how the OM responds to air pollutants remain poorly known. Here we show that the responses of primary human OM cells are altered upon exposure to UFPs and that different fuels and engines elicit different adverse effects. We used UFPs collected from exhausts of a heavy-duty-engine run with renewable diesel (A0) and fossil diesel (A20), and from a modern diesel vehicle run with renewable diesel (Euro6) and compared their health effects on the OM cells by assessing cellular processes on the functional and transcriptomic levels. Quantification revealed all samples as UFPs with the majority of particles being ≤0.1 μm by an aerodynamic diameter. Exposure to A0 and A20 induced substantial alterations in processes associated with inflammatory response, xenobiotic metabolism, olfactory signaling, and epithelial integrity. Euro6 caused only negligible changes, demonstrating the efficacy of aftertreatment devices. Furthermore, when compared to A20, A0 elicited less pronounced effects on OM cells, suggesting renewable diesel induces less adverse effects in OM cells. Prior studies and these results suggest that PAHs may disturb the inflammatory process and xenobiotic metabolism in the OM and that UFPs might mediate harmful effects on the brain through the olfactory route. This study provides important information on the adverse effects of UFPs in a human-based in vitro model, therefore providing new insight to form the basis for mitigation and preventive actions against the possible toxicological impairments caused by UFP exposure.

Biological Impact of Organic Extracts from Urban-Air Particulate Matter: An In Vitro Study of Cytotoxic and Metabolic Effects in Lung Cells

Atmospheric particulate matter (PM) with diameters below 10 µm (PM10) may enter the lungs through inhalation and are linked to various negative health consequences. Emergent evidence emphasizes the significance of cell metabolism as a sensitive target of PM exposure. However, the current understanding of the relationship between PM composition, conventional toxicity measures, and the rewiring of intracellular metabolic processes remains limited. In this work, PM10 sampled at a residential area (urban background, UB) and a traffic-impacted location (roadside, RS) of a Portuguese city was comprehensively characterized in terms of polycyclic aromatic hydrocarbons and plasticizers. Epithelial lung cells (A549) were then exposed for 72 h to PM10 organic extracts and different biological outcomes were assessed. UB and RS PM10 extracts dose-dependently decreased cell viability, induced reactive oxygen species (ROS), decreased mitochondrial membrane potential, caused cell cycle arrest at the G0/G1 phase, and modulated the intracellular metabolic profile. Interestingly, the RS sample, richer in particularly toxic PAHs and plasticizers, had a greater metabolic impact than the UB extract. Changes comprised significant increases in glutathione, reflecting activation of antioxidant defences to counterbalance ROS production, together with increases in lactate, NAD+, and ATP, which suggest stimulation of glycolytic energy production, possibly to compensate for reduced mitochondrial activity. Furthermore, a number of other metabolic variations hinted at changes in membrane turnover and TCA cycle dynamics, which represent novel clues on potential PM10 biological effects.

The burden of ischemic heart disease attributable to ambient and household particulate matter pollution, 1990-2019: a global analysis

Elevated risk of ischemic heart disease (IHD) is associated with exposure to fine particulate matter. However, there is limited data on trends and comparisons in the global burden of IHD due to household air pollution from solid fuels (HAP) and ambient particulate matter pollution (APMP), particularly in regions of varying socio-economic levels. Based on the Global Burden of Disease Study 2019 (GBD 2019), we obtained age-standardized mortality rates (ASMR) and age-standardized disability-adjusted life years (ASDR) of IHD due to APMP and HAP from 1990 to 2019. Trends in the burden of IHD attributable to APMP and HAP during the period 1990 to 2019 were calculated by Joinpoint models. We estimated the relationship between ASMR with the socio-demographic indexes (SDI) and the health care accessibility and quality (HAQ) index by the Loess regression model. In 2019, the global burden of IHD ASMR attributed to APMP stabilized, but the most significant increases were observed in low-middle SDI regions. The global IHD ASMR attributed to APMP was 16.60 [95% Uncertainty Interval (UI), 13.61 to 19.44] per 100,000 population, with the highest APMP burden in middle SDI regions. From 1990 to 2019, the global ASMR for HAP-attributable IHD declined. The global ASMR of IHD attributable to HAP in 2019 was 6.30 (95% UI, 4.28 to 8.80) per 100,000 population, with the highest burden observed in the low SDI regions. From 1990 to 2019, the global burden of ASMR and ASDR of IHD attributable to APMP showed stabilization, whereas the HAP burden exhibited a decrease. There are a large burden of APMP particularly in middle SDI countries and a higher burden of HAP in low SDI countries. The burden of IHD due to APMP and HAP in men, the elderly, and populations in low, medium, and low SDI regions should be noticed.

The effect of social determinants of health on severity of microbial keratitis presentation at a tertiary eye care hospital in Southern India

Purpose

Understanding the association between social determinants of health (SDoHs) and microbial keratitis (MK) can inform underlying risk for patients and identify risk factors associated with worse disease, such as presenting visual acuity (VA) and time to initial presentation.

Methods

This was a cross-sectional study was conducted with patients presenting with MK to the cornea clinic at a tertiary care hospital in Madurai, India. Patient demographics, SDoH survey responses, geographic pollution, and clinical features at presentation were collected. Descriptive statistics, univariate analysis, multi-variable linear regression models, and Poisson regression models were utilized.

Results

There were 51 patients evaluated. The mean age was 51.2 years (SD = 13.3); 33.3% were female and 55% did not visit a vision center (VC) prior to presenting to the clinic. The median presenting logarithm of the minimum angle of resolution (logMAR) VA was 1.1 [Snellen 20/240, inter-quartile range (IQR) = 20/80 to 20/4000]. The median time to presentation was 7 days (IQR = 4.5 to 10). The average particulate matter 2.5 (PM2.5) concentration, a measure of air pollution, for the districts from which the patients traveled was 24.3 μg/m3 (SD = 1.6). Age- and sex-adjusted linear regression and Poisson regression results showed that higher levels of PM2.5 were associated with 0.28 worse presenting logMAR VA (Snellen 2.8 lines, P = 0.002). Patients who did not visit a VC had a 100% longer time to presentation compared to those who did (incidence rate ratio = 2.0, 95% confidence interval = 1.3-3.0, P = 0.001).

Conclusion

Patient SDoH and environmental exposures can impact MK presentation. Understanding SDoH is important for public health and policy implications to mitigate eye health disparities in India.

Estimation of exposure to particulate matter in pregnant individuals living in an area of unconventional oil and gas operations: Findings from the EXPERIVA study

Northeastern British Columbia (Canada) is an area of oil and gas exploitation, which may result in release of fine (PM_2.5) and inhalable (PM₁₀) particulate matter. The aims of this study were to: 1) apply extrapolation methods to estimate exposure to PM_2.5 and PM₁₀ concentrations among EXPERIVA (Exposures in the Peace River Valley study) participants using air quality data archives; and 2) conduct exploratory analyses to investigate correlation between PM exposure and metrics of oil and gas wells density, proximity, and activity. Gestational exposure to PM_2.5 and PM₁₀ of the EXPERIVA participants (n = 85) was estimated by averaging the concentrations measured at the closest or three closest air monitoring stations during the pregnancy period. Drilling metrics were calculated based upon the density and proximity of conventional and unconventional oil and gas wells to each participant's residence. Phase-specific metrics were determined for unconventional wells. The correlations (ρ) between exposure to PM_2.5 and PM₁₀ and metrics of well density/proximity were determined using Spearman's rank correlation test. Estimated PM ambient air concentrations ranged between 4.73 to 12.13 µg/m³ for PM_2.5 and 7.14 to 26.61 µg/m³ for PM₁₀. Conventional wells metrics were more strongly correlated with PM₁₀ estimations (ρ between 0.28 and 0.79). Unconventional wells metrics for all phases were positively correlated with PM_2.5 estimations (ρ between 0.23 and 0.55). These results provide evidence of a correlation between density and proximity of oil and gas wells and estimated PM exposure in the EXPERIVA participants.

Avoidable mortality due to long-term exposure to PM2.5 in Colombia 2014-2019

OBJECTIVE

To compare estimates of spatiotemporal variations of surface PM_2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM_2.5 annual mean at municipality level.

METHODS

We retrieved PM_2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM_2.5 concentration over the current mean annual national standard of 25 µg/m³ and projected standard of 15 µg/m³.

RESULTS

Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM_2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m³ compared to a mean bias of 4,7 µg/m³ from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM_2.5 exposure over 25 and 15 µg/m³ were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM_2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m³ were 2,381 years.

CONCLUSION

Comparison of two global air quality models for estimating surface PM_2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM_2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

Effect of PM2.5 Levels on ED Visits for Respiratory Causes in a Greek Semi-Urban Area

Fine particulate matter that have a diameter of <2.5 μm (PM2.5) are an important factor of anthropogenic pollution since they are associated with the development of acute respiratory illnesses. The aim of this prospective study is to examine the correlation between PM2.5 levels in the semi-urban city of Volos and Emergency Department (ED) visits for respiratory causes. ED visits from patients with asthma, pneumonia and upper respiratory infection (URI) were recorded during a one-year period. The 24 h PM2.5 pollution data were collected in a prospective manner by using twelve fully automated air quality monitoring stations. PM2.5 levels exceeded the daily limit during 48.6% of the study period, with the mean PM2.5 concentration being 30.03 ± 17.47 μg/m3. PM2.5 levels were significantly higher during winter. When PM2.5 levels were beyond the daily limit, there was a statistically significant increase in respiratory-related ED visits (1.77 vs. 2.22 visits per day; p: 0.018). PM2.5 levels were also statistically significantly related to the number of URI-related ED visits (0.71 vs. 0.99 visits/day; p = 0.01). The temperature was negatively correlated with ED visits (r: −0.21; p < 0.001) and age was found to be positively correlated with ED visits (r: 0.69; p < 0.001), while no statistically significant correlation was found concerning humidity (r: 0.03; p = 0.58). In conclusion, PM2.5 levels had a significant effect on ED visits for respiratory causes in the city of Volos.

Health risk assessment and source apportionment of PM2.5-bound toxic elements in the industrial city of Siheung, Korea

The emission sources and their health risks of fine particulate matter (PM_2.5) in Siheung, Republic of Korea, were investigated as a middle-sized industrial city. To identify the PM_2.5 sources with error estimation, a positive matrix factorization model was conducted using daily mean speciated data from November 16, 2019, to October 2, 2020 (95 samples, 22 chemical species). As a result, 10 sources were identified: secondary nitrate (24.3%), secondary sulfate (18.8%), traffic (18.8%), combustion for heating (12.6%), biomass burning (11.8%), coal combustion (3.6%), heavy oil industry (1.8%), smelting industry (4.0%), sea salts (2.7%), and soil (1.7%). Based on the source apportionment results, health risks by inhalation of PM_2.5 were assessed for each source using the concentration of toxic elements portioned. The estimated cumulative carcinogenic health risks from the coal combustion, heavy oil industry, and traffic sources exceeded the benchmark, 1E-06. Similarly, carcinogenic health risks from exposure to As and Cr exceeded 1E-05 and 1E-06, respectively, needing a risk reduction plan. The non-carcinogenic risk was smaller than the hazard index of one, implying low potential for adverse health effects. The probable locations of sources with relatively higher carcinogenic risks were tracked. In this study, health risk assessment was performed on the elements for which mass concentration and toxicity information were available; however, future research needs to reflect the toxicity of organic compounds, elemental carbon, and PM_2.5 itself.

Ambient concentrations and dosimetry of inhaled size-segregated particulate matter during periods of low urban mobility in Bragança, Portugal

The restrictive measures in place during the COVID-19 pandemic provided a timely scenario to investigate the effects of human activities on air quality, and the extent to which mobility reduction strategies can impact atmospheric pollutant levels. Real-time concentrations of PM₁, PM_2.5 and PM₁₀ were measured using a mobile platform in a small city of Portugal, during morning and afternoon rush hours, in two distinct phases of the pandemic: emergency phase (cold period, lockdown) and calamity phase (warm period, less restricted). The Multiple-Path Particle Dosimetry Model (MPPD) was used to calculate the PM deposition for adults. Large spatio-temporal variabilities and pronounced changes in mean PM concentrations were observed, with lower concentrations in the calamity phase: PM₁ = 2.33 ± 1.61 μg m^-3; PM_2.5 = 5.15 ± 2.77 μg m^-3; PM₁₀ = 23.30 ± 21.53 μg m^-3 than in the emergency phase: PM₁ = 16.85 ± 31.80 μg m^-3; PM_2.5 = 30.92 ± 31.93 μg m^-3; PM₁₀ = 111.27 ± 104.53 μg m^-3. These changes are explained by a combination of meteorological factors and local emissions, mainly residential firewood burning. Regarding regional deposition, PM₁ was the main contributor to deposition in the tracheobronchial (5%) and pulmonary (12%) regions, and PM₁₀ in the head region (92%). In general, total deposition doses were higher for males than for females. This work quantitatively demonstrated that even with a 38% reduction in urban mobility during the lockdown, the use of firewood for residential heating is the main contributor to the high concentrations of PM and the respective inhaled dose.

Estimation of On-Road PM2.5 Distributions by Combining Satellite Top-of-Atmosphere With Microscale Geographic Predictors for Healthy Route Planning

How to reduce the health risks for commuters, caused by air pollution such as PM_2.5 has always been an urgent issue needing to be solved. Proposed in this study, is a novel framework which enables greater avoidance of pollution and hence assists the provision of healthy travel. This framework is based on the estimation of on-road PM_2.5 throughout the whole city. First, the micro-scale PM_2.5 is predicted by land use regression (LUR) modeling enhanced by the use of the Landsat-8 top-of-atmosphere (TOA) data and microscale geographic predictors. In particular, the green view index (GVI) factor derived, the sky view factor, and the index-based built-up index, are incorporated within the TOA-LUR modeling. On-road PM_2.5 distributions are then mapped in high-spatial-resolution. The maps obtained can be used to find healthy travel routes with less PM_2.5. The proposed framework was applied in high-density Hong Kong by Landsat 8 images. External testing was based on mobile measurements. The results showed that the estimation performance of the proposed seasonal TOA-LUR Geographical and Temporal Weighted Regression models is at a high-level with an R ² of 0.70-0.90. The newly introduced GVI index played an important role in these estimations. The PM_2.5 distribution maps at high-spatial-resolution were then used to develop an application providing Hong Kong residents with healthy route planning services. The proposed framework can, likewise, be applied in other cities to better ensure people's health when traveling, especially those in high-density cities.

PM2.5 decadal data in cold vs. mild climate airports: COVID-19 era and a call for sustainable air quality policy

Airports are identified hotspots for air pollution, notably for fine particles (PM_2.5) that are pivotal in aerosol-cloud interaction processes of climate change and human health. We herein studied the field observation and statistical analysis of 10-year data of PM_2.5 and selected emitted co-pollutants (CO, NO_x, and O₃), in the vicinity of three major Canadian airports, with moderate to cold climates. The decadal data analysis indicated that in colder climate airports, pollutants like PM_2.5 and CO accumulate disproportionally to their emissions in fall and winter, in comparison to airports in milder climates. Decadal daily averages and standard errors of PM_2.5 concentrations were as follows: Vancouver, 5.31 ± 0.017; Toronto, 6.71 ± 0.199; and Montreal, 7.52 ± 0.023 μg/m³. The smallest and the coldest airport with the least flights/passengers had the highest PM_2.5 concentration. QQQ-ICP-MS/MS and HR-S/TEM analysis of aerosols near Montreal Airport indicated a wide range of emerging contaminants (Cd, Mo, Co, As, Ni, Cr, and Pb) ranging from 0.90 to 622 μg/L, which were also observed in the atmosphere. During the lockdown, a pronounced decrease in the concentrations of PM_2.5 and submicron particles, including nanoparticles_, in residential areas close to airports was observed, conforming with the recommended workplace health thresholds (~ 2 × 10⁴ cm^-3), while before the lockdown, condensable particles were up to ~ 1 × 10⁵ cm^-3. Targeted reduction of PM_2.5 emission is recommended for cold climate regions.

Fine Particulate Matter and Age-Related Eye Disease: The Canadian Longitudinal Study on Aging

Purpose

To determine the relationship between fine particulate matter (PM2.5) and ocular outcomes such as visual impairment and age-related eye disease.

Methods

Baseline data were used from the Canadian Longitudinal Study on Aging. The Comprehensive Cohort consisted of 30,097 adults ages 45 to 85 years. Annual mean PM2.5 levels (µg/m3) for each participant's postal code were estimated from satellite data. Ozone, sulfur dioxide, and nitrogen dioxide levels were also estimated. Binocular presenting visual acuity was measured using a visual acuity chart. Intraocular pressure (IOP) was measured in millimeters of mercury using the Reichart Ocular Response Analyzer. Participants were asked about a diagnosis of glaucoma, macular degeneration, or cataract. Logistic and linear regression models were used.

Results

The overall mean PM2.5 level was 6.5 µg/m3 (SD = 1.8). In the single pollutant models, increased PM2.5 levels (per interquartile range) were associated with visual impairment (odds ratio [OR] = 1.12; 95% confidence interval [CI], 1.02-1.24), glaucoma (OR = 1.14; 95% CI, 1.01-1.29), and visually impairing age-related macular degeneration (OR = 1.52; 95% CI, 1.10-2.09) after adjustment for sociodemographics and disease. PM2.5 had a borderline adjusted association with cataract (OR = 1.06; 95% CI, 0.99-1.14). In the multi-pollutant models, increased PM2.5 was associated with glaucoma and IOP only after adjustment for sociodemographics and disease (OR = 1.24; 95% CI, 1.05-1.46 and β = 0.24; 95% CI, 0.12-0.37).

Conclusions

Increased PM2.5 is associated with glaucoma and IOP. These associations should be confirmed using longitudinal data and potential mechanisms should be explored. If confirmed, this work may have relevance for revision of World Health Organization thresholds to protect human health.