Source-Apportioned PM2.5 and Cardiorespiratory Emergency Department Visits: Accounting for Source Contribution Uncertainty

Wildland Fire-Related Smoke PM 2.5 and Cardiovascular Disease ED Visits in the Western United States

Background

The impact of short-term exposure to fine particulate matter (PM 2.5 ) due to wildland fire smoke on the risk of cardiovascular disease (CVD) remains unclear. We investigated the association between short-term exposure to wildfire smoke PM 2.5 and Emergency Department (ED) visits for acute CVD in the Western United States from 2007 to 2018.

Methods

ED visits for primary or secondary diagnoses of atrial fibrillation (AF), acute myocardial infarction (AMI), heart failure (HF), stroke, and total CVD were obtained from hospital associations or state health departments in California, Arizona, Nevada, Oregon, and Utah. ED visits included those that were subsequently hospitalized. Daily smoke, non-smoke, and total PM 2.5 were estimated using a satellite-driven multi-stage model with a high resolution of 1 km. The data were aggregated to the zip code level and a case-crossover study design was employed. Temperature, relative humidity, and day of the year were included as covariates.

Results

We analyzed 49,759,958 ED visits for primary or secondary CVD diagnoses, which included 6,808,839 (13.7%) AFs, 1,222,053 (2.5%) AMIs, 7,194,474 (14.5%) HFs, and 808,396 (1.6%) strokes. Over the study period from 2007-01-01 to 2018-12-31, the mean smoke PM 2.5 was 1.27 (Q1: 0, Q3: 1.29) µg/m 3 . A 10 µg/m 3 increase in smoke PM 2.5 was associated with a minuscule decreased risk for AF (OR 0.994, 95% CI 0.991-0.997), HF (OR 0.995, 95% CI 0.992-0.998), and CVD (OR 0.9997, 95% CI 0.996-0.998), but not for AMI and stroke. Adjusting for non-smoke PM 2.5 did not alter these associations. A 10 µg/m 3 increase in total PM 2.5 was linked to a small increased risk for all outcomes except stroke (OR for CVD 1.006, 95% CI 1.006-1.007). Associations were similar across sex and age groups.

Conclusion

We identified an unexpected slight lower risk of CVD ED visits associated with short-term wildfire smoke PM 2.5 exposure. Whether these findings are due to methodological issues, behavioral changes, or other factors requires further investigation.

Decomposing PM2.5 concentrations in urban environments into meaningful factors: 1. Separating the contribution of local anthropogenic activities from background and long-range transport

Fine particulate matter (PM2.5) is a complex mixture of aerosol particles with varying properties and sources, both local and distant. In areas lacking detailed monitoring of PM2.5 speciation, the common source-apportionment analyses are not applicable. This study demonstrates an alternative framework for estimating sources and processes that affect observed PM2.5 concentrations when information on the particle composition is unavailable. Eight years (2012-2019) of half-hourly PM2.5 observations from 10 air quality monitoring (AQM) stations, clustered according to their airmass transport sector were analyzed, using Non-negative Matrix Factorization (NMF). Factors were determined based on their variation in time, space, and between airmass sectors. Employing a supervised machine-learning model provided insights into the relationships between the extracted factors, meteorological parameters and co-measured airborne pollutants. Factor interpretations were evaluated through comparisons with measurements of PM2.5 species from a nearby Surface PARTiculate mAtter Network (SPARTAN) station. The NMF successfully separated background factors from an urban anthropogenic-activity factor, with the latter accounting for approximately 60 % of the observed PM2.5 levels in Tel Aviv (∼10±6μg/m3). Positive monotonic relationships were observed between the PM2.5 urban anthropogenic-activity factor and measurements of nitrogen oxides (NOx) and absolute humidity (AH), representing the impact of traffic emissions and hygroscopic growth, respectively. The summer background factor was found to represent long-range transport (LRT) from Europe, showing a good agreement (R2 = 0.81) with ammonium sulphate concentrations. Our results demonstrate that a spatial NMF analysis can reliably estimate contributions of different sources with distinct compositions and properties to the total observed PM2.5. Using such an analysis, future environmental health studies could assess health risks associated with exposure to distinct PM2.5 fractions. This information may assist decision makers to set environmental targets for abating PM2.5 with specific compositions and properties.

Impact of Chemical Speciation Network method changes on time series ion and carbon species concentrations

Numerous studies rely on long-term PM2.5 speciation data from the EPA's Chemical Speciation Network (CSN), for example, to estimate health impacts or investigate the sources and transport of PM2.5 pollution. These studies rely on consistent, long-term time series measurements of PM2.5 species to draw conclusions about PM2.5 emissions sources and their health impacts. However, changes in contractors and associated methodological changes in 2015 and 2018 led to disruptions in the consistency of the CSN data, specifically, concentration discontinuities in the CSN time series for ions and elemental carbon (EC) from November 2015 to September 2018 and from October 2018 onward, respectively. To address the impact of these changes on downstream air quality and health analyses, this study developed correction factors by comparing collocated CSN measurements to measurements from the Interagency Monitoring of Protected Visual Environment (IMPROVE) network, which used consistent instrumentation and contractors throughout the study period. These correction factors reduced the discontinuities in the ions and EC concentration time series data, which could be critical for time series source apportionment receptor modeling, air pollution policy and accountability investigations, and health effect studies.

Sources of acellular oxidative potential of water-soluble fine ambient particulate matter in the midwestern United States

Ambient fine particulate matter (PM2.5) is associated with numerous health complications, yet the specific PM2.5 chemical components and their emission sources contributing to these health outcomes are understudied. Our study analyzes the chemical composition of PM2.5 collected from five distinct locations at urban, roadside and rural environments in midwestern region of the United States, and associates them with five acellular oxidative potential (OP) endpoints of water-soluble PM2.5. Redox-active metals (i.e., Cu, Fe, and Mn) and carbonaceous species were correlated with most OP endpoints, suggesting their significant role in OP. We conducted a source apportionment analysis using positive matrix factorization (PMF) and found a strong disparity in the contribution of various emission sources to PM2.5 mass vs. OP. Regional secondary sources and combustion-related aerosols contributed significantly (> 75 % in total) to PM2.5 mass, but showed weaker contribution (43-69 %) to OP. Local sources such as parking emissions, industrial emissions, and agricultural activities, though accounting marginally to PM2.5 mass (< 10 % for each), significantly contributed to various OP endpoints (10-50 %). Our results demonstrate that the sources contributing to PM2.5 mass and health effects are not necessarily same, emphasizing the need for an improved air quality management strategy utilizing more health-relevant PM2.5 indicators.

A case-crossover study of ST-elevation myocardial infarction and organic carbon and source-specific PM2.5 concentrations in Monroe County, New York

Background

Previous work reported increased rates of cardiovascular hospitalizations associated with increased source-specific PM2.5 concentrations in New York State, despite decreased PM2.5 concentrations. We also found increased rates of ST elevation myocardial infarction (STEMI) associated with short-term increases in concentrations of ultrafine particles and other traffic-related pollutants in the 2014-2016 period, but not during 2017-2019 in Rochester. Changes in PM2.5 composition and sources resulting from air quality policies (e.g., Tier 3 light-duty vehicles) may explain the differences. Thus, this study aimed to estimate whether rates of STEMI were associated with organic carbon and source-specific PM2.5 concentrations.

Methods

Using STEMI patients treated at the University of Rochester Medical Center, compositional and source-apportioned PM2.5 concentrations measured in Rochester, a time-stratified case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increases in mean primary organic carbon (POC), secondary organic carbon (SOC), and source-specific PM2.5 concentrations on lag days 0, 0-3, and 0-6 during 2014-2019.

Results

The associations of an increased rate of STEMI with interquartile range (IQR) increases in spark-ignition emissions (GAS) and diesel (DIE) concentrations in the previous few days were not found from 2014 to 2019. However, IQR increases in GAS concentrations were associated with an increased rate of STEMI on the same day in the 2014-2016 period (Rate ratio [RR] = 1.69; 95% CI = 0.98, 2.94; 1.73 μg/m3). In addition, each IQR increase in mean SOC concentration in the previous 6 days was associated with an increased rate of STEMI, despite imprecision (RR = 1.14; 95% CI = 0.89, 1.45; 0.42 μg/m3).

Conclusion

Increased SOC concentrations may be associated with increased rates of STEMI, while there seems to be a declining trend in adverse effects of GAS on triggering of STEMI. These changes could be attributed to changes in PM2.5 composition and sources following the Tier 3 vehicle introduction.

The impact of vegetative and solid roadway barriers on particulate matter concentration in urban settings

A potentially important approach for reducing exposure to traffic-related air pollution (TRAP) is the use of roadside barriers to reduce dispersion from highway sources to adjacent populated areas. The Trees Reducing Environmental Exposures (TREE) study investigated the effect of vegetative and solid barriers along major controlled-access highways in Atlanta, Georgia, USA by simultaneously sampling TRAP concentration at roadside locations in front of barriers and at comparison locations down-range. We measured black carbon (BC) mass concentration, particle number concentration (PNC), and the size distribution of ultrafine aerosols. Our sample sites encompassed the range of roadway barrier options in the Atlanta area: simple chain-link fences, solid barriers, and vegetative barriers. We used Generalized Linear Mixed Models (GLMMs) to estimate the effect of barrier type on the ratio of particle concentrations at the comparison site relative to the roadside site while controlling for covariates including wind direction, temperature, relative humidity, traffic volume, and distance to the roadway. Vegetative barriers exhibited the greatest TRAP reduction in terms of BC mass concentration (37% lower behind a vegetative barrier) as well as PNC (6.7% lower), and sensitivity analysis was consistent with this effect being more pronounced when the barrier was downwind of the highway. The ultrafine size distribution was comprised of modestly smaller particles on the highway side of the barrier. Non-highway particle sources were present at all sample sites, most commonly motor vehicle emissions from nearby arterials or secondary streets, which may have obscured the effect of roadside barriers.

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.

Effect of Air Pollution on Heart Failure: Systematic Review and Meta-Analysis

BACKGROUND

Heart failure (HF) poses a significant global disease burden. The current evidence on the impact of air pollution on HF remains inconsistent.

OBJECTIVES

We aimed to conduct a systematic review of the literature and meta-analysis to provide a more comprehensive and multiperspective assessment of the associations between short- and long-term air pollution exposure and HF from epidemiological evidences.

METHODS

Three databases were searched up to 31 August 2022 for studies investigating the association between air pollutants (PM 2.5 , PM 10 , NO 2 , SO 2 , CO, O 3 ) and HF hospitalization, incidence, or mortality. A random effects model was used to derive the risk estimations. Subgroup analysis was conducted by geographical location, age of participants, outcome, study design, covered area, the methods of exposure assessment, and the length of exposure window. Sensitivity analysis and adjustment for publication bias were performed to test the robustness of the results.

RESULTS

Of 100 studies covering 20 countries worldwide, 81 were for short-term and 19 were for long-term exposure. Almost all air pollutants were adversely associated with the risk of HF in both short- and long-term exposure studies. For short-term exposures, we found the risk of HF increased by 1.8% [relative risk ( RR ) = 1.018 , 95% confidence interval (CI): 1.011, 1.025] and 1.6% (RR = 1.016 , 95% CI: 1.011, 1.020) per 10 - μ g / m 3 increment of PM 2.5 and PM 10 , respectively. HF was also significantly associated with NO 2 , SO 2 , and CO, but not O 3 . Positive associations were stronger when exposure was considered over the previous 2 d (lag 0-1) rather than on the day of exposure only (lag 0). For long-term exposures, there were significant associations between several air pollutants and HF with RR (95% CI) of 1.748 (1.112, 2.747) per 10 - μ g / m 3 increment in PM 2.5 , 1.212 (1.010, 1.454) per 10 - μ g / m 3 increment in PM 10 , and 1.204 (1.069, 1.356) per 10 -ppb increment in NO 2 , respectively. The adverse associations of most pollutants with HF were greater in low- and middle-income countries than in high-income countries. Sensitivity analysis demonstrated the robustness of our results.

DISCUSSION

Available evidence highlighted adverse associations between air pollution and HF regardless of short- and long-term exposure. Air pollution is still a prevalent public health issue globally and sustained policies and actions are called for to reduce the burden of HF. https://doi.org/10.1289/EHP11506.

Effects of ambient air pollution on cause-specific hospitalizations in Wuhan during 2017-2019

BACKGROUND

Few studies have focused on the associations between air pollutants and multiple organ system diseases in the entire hospitalized population. The present study aims to explore the short-term effects of six routinely monitored air pollutants on the broad causes of hospital admissions and estimate the resulting hospital admission burdens.

METHODS

Daily hospital admission records from 2017 to 2019 were obtained from the Wuhan Information center of Health and Family Planning. Generalized additive models (GAMs) were employed to evaluate the effects of air pollutants on the percent increase in the cause-specific daily number of hospital admissions. Increased hospital admission numbers, days, and expenses were also estimated.

RESULTS

A total of 2636,026 hospital admissions were identified. We found that both PM_2.5 and PM₁₀ increased the risk of hospital admissions for most disease categories. Short-term exposure to PM_2.5 was positively associated with hospitalizations of several rarely studied disease categories, such as diseases of the eye and adnexa (2.83%, 95%CI: 0.96-4.73%, P < 0.01) and diseases of the musculoskeletal system and connective tissue (2.17%, 95% CI: 0.88-3.47%, P < 0.001). NO₂ was observed to have a robust effect on diseases of the respiratory system (1.36%, 95%CI: 0.74-1.98%, P < 0.001). CO was significantly associated with hospital admissions for six disease categories. Furthermore, each 10-μg/m³ increase in PM_2.5 was associated with an annual increase of 13,444 hospital admissions (95% CI: 6239-20,649), 124,344 admission days (95% CI: 57,705-190,983), and 166-million-yuan admission expenses (95% CI: 77-255).

CONCLUSION

Our study suggested that particulate matter (PM) had a short-term effect on hospital admissions of most major disease categories and resulted in a considerable hospital admission burden. In addition, the health effects of NO₂ and CO emissions require more attention in megacities.

Attributable risk and economic burden of pneumonia among older adults admitted to hospital due to short-term exposure to airborne particulate matter: a time-stratified case-crossover study from China

Many studies have proven the relationship between air pollutants and respiratory diseases, but few studies have assessed the impacts of air particulate matter exposure on older patients with pneumonia. This study aimed to reveal the impacts of short-term exposure to air particulate matter on the daily number of older adult patients hospitalized due to pneumonia and calculate the economic costs attributable to this exposure. We collected inpatient data from 9 city hospitals in Sichuan Province, China, from January 1, 2018, to December 31, 2019, and calculated odds ratios and 95% confidence intervals using a time-stratified case-crossover study design and an attributable risk model to calculate the economic burden due to particulate matter pollution. It was found that for every 10 μg/m³ increase in PM_2.5 and PM₁₀ concentrations, the daily number of older adult pneumonia inpatients increased by 1.5% (95% CI: 1.010-1.021) and 1.0% (95% CI: 1.006-1.014), respectively. Those 65 ~ 79 years old were more susceptible to air particulate pollutants (P < 0.05). During the study period, the total hospitalization costs and out-of-pocket expenses attributable to PM_2.5 and PM₁₀ exposure were 44.60 million CNY (6.22%) and 16.03 million CNY (6.21%), respectively, with PM_2.5 being the primary influencing factor. This study revealed the relationship between particulate matter pollution and pneumonia among older adults. The role of policies to limit particulate matter concentrations in reducing disease burden among older adults can be further explored.

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.

Long-term personal PM2.5 exposure and lung function alternation: A longitudinal study in Wuhan urban adults

BACKGROUND

The effect of long-term PM_2.5 exposure on lung function has not been well established.

OBJECTIVES

To investigate the effects of long-term personal PM_2.5 exposure on lung function decline, obstructive, and restrictive ventilatory disorders.

METHOD

Personal PM_2.5 concentrations were evaluated using an estimation model. Lung function parameters including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁) and peak expiratory flow (PEF) were measured in 3053 Wuhan participants from the Wuhan-Zhuhai cohort and were repeated every 3 years. Participants were classified into persistently high exposure group, persistently low exposure group and inconsistent exposure group according to the median of PM_2.5 concentration of each visit. Mixed linear models with subject-specific random intercept were used to assess the association of 3-year change of lung function with personal PM_2.5 exposure, and generalized linear models were used to assess the association of 6-year change of lung function with personal PM_2.5 exposure. Cox regression models were applied to assess the associations of PM_2.5 with obstructive and restrictive ventilatory disorders.

RESULTS

The medians of personal PM_2.5 concentrations at baseline and two follow-ups were 153.18, 209.57 and 83.78 μg/m³, respectively. Compared with participants in the persistently low exposure group, participants in the persistently high exposure group showed a 2.99 % (95 % CI: 0.91, 5.08), a 380.15 mL/s (95 % CI: 32.82, 727.48) and a 5.98 % (95 % CI: 0.84, 11.11) additional decline in FEV₁/FVC, PEF and PEFpred after 6 years, respectively. Stratified analyses showed that age, gender, body mass index, smoking status and drinking status had no significant modification effect on the associations. The associations of PM_2.5 exposure with obstructive and restrictive ventilatory disorders were not significant, except for a positive association between persistently high PM_2.5 exposure and restrictive ventilatory disorder among ever drinkers.

CONCLUSION

Long-term high PM_2.5 exposure was associated with FEV₁/FVC, PEF and PEFpred declines.

Ambient Air Pollution and Risk for Stroke Hospitalization: Impact on Susceptible Groups

Stroke is a leading cause of death, and air pollution is associated with stroke hospitalization. However, the susceptibility factors are unclear. Retrospective studies from 2014 to 2018 in Kaohsiung, Taiwan, were analyzed. Adult patients (>17 years) admitted to a medical center with stroke diagnosis were enrolled and patient characteristics and comorbidities were recorded. Air pollutant measurements, including those of particulate matter (PM) with aerodynamic diameters < 10 μm (PM10) and < 2.5 μm (PM2.5), nitrogen dioxide (NO2), and ozone (O3), were collected from air quality monitoring stations. During the study period, interquartile range (IQR) increments in PM2.5 on lag3 and lag4 were 12.3% (95% CI, 1.1−24.7%) and 11.5% (95% CI, 0.3−23.9%) concerning the risk of stroke hospitalization, respectively. Subgroup analysis revealed that the risk of stroke hospitalization after exposure to PM2.5 was greater for those with advanced age (≥80 years, interaction p = 0.045) and hypertension (interaction p = 0.034), after adjusting for temperature and humidity. A dose-dependent effect of PM2.5 on stroke hospitalization was evident. This is one of few studies focusing on the health effects of PM2.5 for patients with risk factors of stroke. We found that patients with risk factors, such as advanced age and hypertension, are more susceptible to PM2.5 impacts on stroke hospitalization.

Short term exposure to ambient air pollutants and cardiovascular emergency department visits in Mexico city

Available data on the acute cardiovascular effect of ambient air pollution (AAP) in Latin America is limited considering that over 80% of its 1 billion inhabitants live in urban settlements with poor air quality. The study aim was to evaluate the association between Cardiovascular Emergency Department Visits (CEDVs) and AAP in Mexico City from 2016 to 2019 using generalized additive models with distributed lags to examine the percentage change of CEDVs and a backward approach of time-series model to calculate attributable fractions. A total of 48,891 CEDVs were recorded in a period of 1019 days. We estimated a significant percentage increase for each 10 μg/m³ of PM₁₀ at Lag0-5 (2.8%, 95%CI 0.6-5.0), PM_2.5 at Lag0-6 (3.7%, 95%CI 0.1-7.6), O₃ at Lag0-5 (1.1%, 95%CI 0.2-2.0), NO₂ at Lag0-4 (2.5%, 95%CI 0.3-4.7) and for each 1 mg/m³ of CO at Lag0 (6.6%, 95%CI 0.3-13.2). Overall, 10.3% of CEDVs in Mexico City may be related to PM¹⁰ exposure, 9.5% to PM_2.5, 10.3% to O₃, 11% to NO₂ and 5.7% to CO. AAP significantly increase cardiovascular morbidity impacting on emergency medical services.

Associations between Source-Specific Fine Particulate Matter and Mortality and Hospital Admissions in Beijing, China

The health effects of PM_2.5 exposure have become a major public concern in developing countries. Identifying major PM_2.5 sources and quantifying the health effects at the population level are essential for controlling PM_2.5 pollution and formulating targeted emissions reduction policies. In the current study, we have obtained PM_2.5 mass data and used positive matrix factorization to identify the major sources of PM_2.5. We evaluated the relationship between short-term exposure to PM_2.5 sources and mortality or hospital admissions in Beijing, China, using 441 742 deaths and 9 420 305 hospital admissions from 2013 to 2018. We found positive associations for coal combustion and road dust sources with mortality. Increased hospital admission risks were significantly associated with sources of vehicle exhaust, coal combustion, secondary sulfates, and secondary nitrates. Compared to the cool season, excess mortality risk estimates of coal combustion source were significantly higher in the warm season. Our findings show that reducing more toxic sources of PM_2.5, especially coal emissions, and developing clean energy alternatives can have critical implications for improving air quality and protecting public health.

Examining fine particulate matter and cause-specific morbidity during the 2017 North San Francisco Bay wildfires

BACKGROUND

Recent increases in wildfire frequency and severity necessitate better understanding of health effects of wildfire smoke to protect affected populations.

OBJECTIVES

We examined relationships between fine particulate matter (PM_2.5) and morbidity during wildfires in California, and whether those relationships differed during the fire compared to a similar non-fire period.

METHODS

For nine San Francisco Bay Area counties, daily county-level diagnosis-specific counts of emergency department visits (EDVs) and hospitalizations were linked with county-level estimates of daily mean PM_2.5 during the October 2017 Northern California wildfires and similar October days in 2015, 2016, and 2017. Associations were estimated using Poisson regression.

RESULTS

The median difference between county PM_2.5 during the fire versus the non-fire period was 23.4 μg/m³, with days exceeding 80 μg/m³ in some counties. Over the entire study period, PM_2.5 was most consistently linked to EDVs for respiratory disease (RR_EDV(lag0) per 23.4 μg/m³ increase: 1.25, 95% CI: 1.21, 1.30), asthma, chronic lower respiratory disease (CLRD; RR_EDV(lag0): 1.18, 95% CI: 1.10, 1.27), and acute myocardial infarction (RR_EDV(lag0): 1.14, 95% CI: 1.03, 1.25). Increases in acute upper respiratory infections and decreases in mental/behavioral EDVs were observed but were sensitive to model specification, specifically the inclusion of time-related covariates. Comparing fire and non-fire period EDV associations, we observed indications that PM_2.5 during the fire was more strongly associated with asthma (RR_lag0: 1.46, 95% CI: 1.38, 1.55) compared to non-fire period PM_2.5 (RR_lag0: 0.77, 95% CI: 0.55, 1.08)_, and the opposite observed for dysrhythmia, with the asthma difference being particularly robust to model choice. For hospitalizations, the most robust PM_2.5 relationships were positive associations with respiratory, CLRD, and diabetes, and inverse associations with pneumonia. Respiratory and CLRD effect estimates were generally similar or smaller than for EDVs.

CONCLUSIONS

Elevated short-term PM_2.5 levels from wildfire smoke appears to impact respiratory and other health domains.

Short-term exposure to fine particulate air pollution and emergency department visits for kidney diseases in the Atlanta metropolitan area

Toxicological evidence has shown that fine particulate matter (PM_2.5) may affect distant organs, including kidneys, over the short term. However, epidemiological evidence is limited.

OBJECTIVES

We investigated associations between short-term exposure to PM_2.5, major PM_2.5 components [elemental carbon (EC), organic carbon (OC), sulfate, and nitrate], and gaseous co-pollutants (O₃, CO, SO₂, NO₂, and NO_x) and emergency department (ED) visits for kidney diseases during 2002-2008 in Atlanta, Georgia.

METHODS

Log-linear time-series models were fitted to estimate the acute effects of air pollution, with single-day and unconstrained distributed lags, on rates of ED visits for kidney diseases [all renal diseases and acute renal failure (ARF)], controlling for meteorology (maximum air and dew-point temperatures) and time (season, day of week, holidays, and long-term time trend).

RESULTS

For all renal diseases, we observed positive associations for most air pollutants, particularly 8-day cumulative exposure to OC [rate ratio (RR) = 1.018, (95% confidence interval [CI]: 1.003, 1.034)] and EC [1.016 (1.000, 1.031)] per interquartile range increase exposure. For ARF, we observed positive associations particularly for 8-day exposure to OC [1.034 (1.005, 1.064)], EC [1.032 (1.002, 1.063)], nitrate [1.032 (0.996, 1.069)], and PM_2.5 [1.026 (0.997, 1.057)] per interquartile range increase exposure. We also observed positive associations for most criteria gases. The RR estimates were generally higher for ARF than all renal diseases.

CONCLUSIONS

We observed positive associations between short-term exposure to fine particulate air pollution and kidney disease outcomes. This study adds to the growing epidemiological evidence that fine particles may impact distant organs (e.g., kidneys) over the short term.

Effect of PM2.5 Levels on Respiratory Pediatric ED Visits in a Semi-Urban Greek Peninsula

Ambient air pollution accounts for an estimated 4.2 million deaths worldwide. Particulate matter (PM)_2.5 particles are believed to be the most harmful, as when inhaled they can penetrate deep into the lungs. The aim of this study was to examine the relationship between PM_2.5 daily air concentrations and pediatric emergency department (ED) visits for respiratory diseases in a Greek suburban area. All pediatric ED visits for asthma-, pneumonia- and upper respiratory infection (URI)-related complaints were recorded during the one-year period. The 24-h PM_2.5 air pollution data were prospectively collected from twelve fully automated air quality monitoring stations. The mean annual concentration of PM_2.5 was 30.03 μg/m³ (World Health Organization (WHO) Air Quality Guidelines (AQG) Annual mean concentration: 10 μg/m³). PM_2.5 levels rose above the WHO Air Quality Guidelines (AQG) 24-h concentrations (25 μg/m³)), 178 times (48.6% of the study period). When PM_2.5 levels were above the daily limit, an increase of 32.44% (p < 0.001) was observed in daily pediatric ED visits for respiratory diseases and the increase was much higher during spring (21.19%, p = 0.018). A 32% (p < 0.001) increase was observed in URI-related visits, when PM_2.5 levels were ≥25 μg/m³, compared to the mean daily visits when PM_2.5 levels were <25 μg/m³. Air pollution levels were associated with increased pediatric ED visits for respiratory-related diseases.

Air Pollution Neurotoxicity in the Adult Brain: Emerging Concepts from Experimental Findings

Epidemiological studies are associating elevated exposure to air pollution with increased risk of Alzheimer's disease and other neurodegenerative disorders. In effect, air pollution accelerates many aging conditions that promote cognitive declines of aging. The underlying mechanisms and scale of effects remain largely unknown due to its chemical and physical complexity. Moreover, individual responses to air pollution are shaped by an intricate interface of pollutant mixture with the biological features of the exposed individual such as age, sex, genetic background, underlying diseases, and nutrition, but also other environmental factors including exposure to cigarette smoke. Resolving this complex manifold requires more detailed environmental and lifestyle data on diverse populations, and a systematic experimental approach. Our review aims to summarize the modest existing literature on experimental studies on air pollution neurotoxicity for adult rodents and identify key gaps and emerging challenges as we go forward. It is timely for experimental biologists to critically understand prior findings and develop innovative approaches to this urgent global problem. We hope to increase recognition of the importance of air pollution on brain aging by our colleagues in the neurosciences and in biomedical gerontology, and to support the immediate translation of the findings into public health guidelines for the regulation of remedial environmental factors that accelerate aging processes.

Short-term exposure to air pollution and hospital admission for pneumonia: a systematic review and meta-analysis

BACKGROUND

Air pollution is a major issue that poses a health threat worldwide. Although several studies investigated the adverse effects of air pollution on various diseases, few have directly demonstrated the effects on pneumonia. Therefore, we performed a systematic review and meta-analysis on the associations between short-term exposure of air pollutants and hospital admission or emergency room (ER) visit for pneumonia.

METHODS

A literature search was performed using PubMed, Embase, and Web of Science up to April 10, 2020. Pooled estimates were calculated as % increase with 95% confidence intervals using a random-effects model. A sensitivity analysis using the leave-one-out method and subgroup analysis by region were performed.

RESULTS

A total of 21 studies were included in the analysis. Every 10 μg/m3 increment in PM2.5 and PM10 resulted in a 1.0% (95% CI: 0.5-1.5) and 0.4% (95% CI: 0.2-0.6) increase in hospital admission or ER visit for pneumonia, respectively. Every 1 ppm increase of CO and 10 ppb increase of NO2, SO2, and O3 was associated with 4.2% (95% CI: 0.6-7.9), 3.2% (95% CI: 1.3-5.1), 2.4% (95% CI: - 2.0-7.1), and 0.4% (95% CI: 0-0.8) increase in pneumonia-specific hospital admission or ER visit, respectively. Except for CO, the sensitivity analyses yielded similar results, demonstrating the robustness of the results. In a subgroup analysis by region, PM2.5 increased hospital admission or ER visit for pneumonia in East Asia but not in North America.

CONCLUSION

By combining the inconsistent findings of several studies, this study revealed the associations between short-term exposure of air pollutants and pneumonia-specific hospital admission or ER visit, especially for PM and NO2. Based on the results, stricter intervention policies regarding air pollution and programs for protecting human respiratory health should be implemented.

Development of Europe-Wide Models for Particle Elemental Composition Using Supervised Linear Regression and Random Forest

We developed Europe-wide models of long-term exposure to eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in particulate matter with diameter <2.5 μm (PM_2.5) using standardized measurements for one-year periods between October 2008 and April 2011 in 19 study areas across Europe, with supervised linear regression (SLR) and random forest (RF) algorithms. Potential predictor variables were obtained from satellites, chemical transport models, land-use, traffic, and industrial point source databases to represent different sources. Overall model performance across Europe was moderate to good for all elements with hold-out-validation R-squared ranging from 0.41 to 0.90. RF consistently outperformed SLR. Models explained within-area variation much less than the overall variation, with similar performance for RF and SLR. Maps proved a useful additional model evaluation tool. Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement between the two algorithm predictions was generally high at the overall European level and varied substantially at the national level. Applying the two models in epidemiological studies could lead to different associations with health. If both between- and within-area exposure variability are exploited, RF may be preferred. If only within-area variability is used, both methods should be interpreted equally.