A Long-Term Comparison between the AethLabs MA350 and Aerosol Magee Scientific AE33 Black Carbon Monitors in the Greater Salt Lake City Metropolitan Area.

Black carbon (BC) or soot contains ultrafine combustion particles that are associated with a wide range of health impacts, leading to respiratory and cardiovascular diseases. Both long-term and short-term health impacts of BC have been documented, with even low-level exposures to BC resulting in negative health outcomes for vulnerable groups. Two aethalometers-AethLabs MA350 and Aerosol Magee Scientific AE33-were co-located at a Utah Division of Air Quality site in Bountiful, Utah for just under a year. The aethalometer comparison showed a close relationship between instruments for IR BC, Blue BC, and fossil fuel source-specific BC estimates. The biomass source-specific BC estimates were markedly different between instruments at the minute and hour scale but became more similar and perhaps less-affected by high-leverage outliers at the daily time scale. The greater inter-device difference for biomass BC may have been confounded by very low biomass-specific BC concentrations during the study period. These findings at a mountainous, high-elevation, Greater Salt Lake City Area site support previous study results and broaden the body of evidence validating the performance of the MA350.

Intra-city variability of fine particulate matter during COVID-19 lockdown: A case study from Park City, Utah.

Urban air quality is a growing concern due a range of social, economic, and health impacts. Since the SARS-CoV-19 pandemic began in 2020, governments have produced a range of non-medical interventions (NMIs) (e.g. lockdowns, stay-at-home orders, mask mandates) to prevent the spread of COVID-19. A co-benefit of NMI implementation has been the measurable improvement in air quality in cities around the world. Using the lockdown policy of the COVID-19 pandemic as a natural experiment, we traced the changing emissions patterns produced under the pandemic in a mid-sized, high-altitude city to isolate the effects of human behavior on air pollution. We tracked air pollution over time periods reflecting the Pre-Lockdown, Lockdown, and Reopening stages, using high quality, research grade sensors in both commercial and residential areas to better understand how each setting may be uniquely impacted by pollution downturn events. Based on this approach, we found the commercial area of the city showed a greater decrease in air pollution than residential areas during the lockdown period, while both areas experienced a similar rebound post lockdown. The easing period following the lockdown did not lead to an immediate rebound in human activity and the air pollution increase associated with reopening, took place nearly two months after the lockdown period ended. We hypothesize that differences in heating needs, travel demands, and commercial activity, are responsible for the corresponding observed changes in the spatial distribution of pollutants over the study period. This research has implications for climate policy, low-carbon energy transitions, and may even impact local policy due to changing patterns in human exposure that could lead to important public health outcomes, if left unaddressed.

Effects of Short-Term Air Pollution Exposure on Venous Thromboembolism: A Case-Crossover Study.

Rationale: Exposure to outdoor air pollution is associated with increased cardiovascular disease, respiratory illness, and mortality. The effect of air pollution on venous thromboembolism (VTE) is less certain. Objectives: To test for associations between short-term exposure to air pollution and VTE. Methods: This is a retrospective case-crossover study of adult patients with an objectively confirmed VTE event. Exposure to the mean and maximum particulate matter ⩽2.5 µm in aerodynamic diameter (PM2.5) and ozone were estimated with inverse distance squared weighting from multiple stationary air quality monitors. Conditional logistic regression with a 7-day individual lag model estimated the odds ratio (OR) of VTE occurrence during the case period relative to the referent period. Prespecified subgroup analysis was performed to further test associations in higher risk patients. Results: A total of 2,803 VTE events met inclusion criteria for analysis. Deep vein thrombosis was identified in 1,966 (70.1%) and pulmonary embolism in 915 (32.6%) subjects. Median age was 57 years. Small negative associations were observed for the maximum PM2.5 exposure at 1 day (OR, 0.992; 95% confidence interval [CI], 0.986-0.997) and the mean PM2.5 exposure at 1 day (OR, 0.982; 95% CI, 0.97-0.994), 5 days (OR, 0.987; 95% CI, 0.975-0.999), 6 days (OR, 0.984; 95% CI, 0.972-0.996), and 7 days (OR, 0.982; 95% CI, 0.971-0.994) before VTE diagnosis. Similar negative associations were observed for the 8-hour mean (OR, 0.989; 95% CI, 0.981-0.997) and 8-hour maximum (OR, 0.992; 95% CI, 0.985-0.999) ozone exposure 4 days before VTE diagnosis. Positive relationships (ORs of ∼1.02) between the 8-hour mean and maximum ozone exposures 6-7 days preceding VTE diagnosis were observed in a recently hospitalized subgroup. Conclusions: Short-term exposure to PM2.5 and ozone does not appear to be associated with an overall increased risk of VTE. Further well-designed studies are needed to test whether previously reported associations between VTE and air pollution exist.

Long-term analysis of the relationships between indoor and outdoor fine particulate pollution: A case study using research grade sensors.

The growing concern of air quality and its associated health-related impacts has led to increased awareness of pollutant exposure. Most human populations spend the majority of their time indoors and the COVID-19 pandemic has likely exacerbated this behavior. While significant amounts of research have focused on outdoor air quality, to date there have been no studies that examined simultaneous long-term trends on indoor and outdoor air quality on a site using research-grade sensors. We measured fine particulate matter (PM2.5) for a year using sensors located on the rooftop, air handling room, and indoor office space in a building and captured the impacts of three types of regularly occurring elevated pollution events: wintertime atmospheric inversions, wildfires, and fireworks. The events had different magnitudes and durations, and infiltration rates varied for each event leading to dissimilar indoor air pollution levels. The building's air handling unit and different environmental conditions (lower indoor humidity and temperature during the winter) combined to reduce indoor pollution from inversion events however, particulate matter from wildfires and fireworks infiltrated at higher rates. Together, this suggests possible intervention strategies, such as ventilation rates and filter upgrades, that could be used to mitigate contaminant intrusion during elevated pollution events. This year-long study illustrates an array of ways that elevated pollution events interact with the protective effects that buildings have against air pollution for its occupants. Furthermore, we show that outdoor air pollution is an important variable to consider when studying indoor air quality as contaminant infiltration is strongly dependent on the specific pollution source.

Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform.

Urban environments are characterized by pronounced spatiotemporal heterogeneity, which can present sampling challenges when utilizing conventional greenhouse gas (GHG) measurement systems. In Salt Lake City, Utah, a GHG instrument was deployed on a light rail train car that continuously traverses the Salt Lake Valley (SLV) through a range of urban typologies. CO2 measurements from a light rail train car were used within a Bayesian inverse modeling framework to constrain urban emissions across the SLV during the fall of 2015. The primary objectives of this study were to (1) evaluate whether ground-based mobile measurements could be used to constrain urban emissions using an inverse modeling framework and (2) quantify the information that mobile observations provided relative to conventional GHG monitoring networks. Preliminary results suggest that ingesting mobile measurements into an inverse modeling framework generated a posterior emission estimate that more closely aligned with observations, reduced posterior emission uncertainties, and extends the geographical extent of emission adjustments.

Air Pollution-Related Health Impacts on Individuals Experiencing Homelessness: Environmental Justice and Health Vulnerability in Salt Lake County, Utah.

Experiences of homelessness, although widely varied, are characterized by extensive time in public spaces, often outdoors. However, there has been little empirical research about the ways in which environmental factors affect individuals experiencing homelessness (IEHs). Therefore, the purpose of this study was to use an environmental justice approach to understand how cardiopulmonary health of IEHs is affected by episodic poor air quality in Salt Lake County. It was hypothesized that people who had experienced unsheltered homelessness and those who had been experiencing homelessness for longer periods of time would report greater health difficulties from poor air quality exposure. Through a combination of in-person semistructured interviews with IEHs (n = 138) and access to corresponding state-based service provider databases, researchers examined both overall descriptives of and relationships between types (sheltered and unsheltered) and duration (chronic and nonchronic) of homelessness. More than 61% of IEHs reported physical reactions to air pollution, 37% reported air pollution-related emotional stress, and more than 89% had sought medical attention for a condition related to air pollution. Findings indicate that while IEHs report a number of health effects related to poor air quality, there were no significant differences between individuals based on either sheltered status or duration of their experiences of homelessness. This study provides an initial empirical inquiry to understand how environmental disamenities negatively influence IEHs, as well as noting that sheltered status and duration of homelessness are less impactful than originally hypothesized.

Effects of PM2.5 on Third Grade Students' Proficiency in Math and English Language Arts.

Fine particulate air pollution is harmful to children in myriad ways. While evidence is mounting that chronic exposures are associated with reduced academic proficiency, no research has examined the frequency of peak exposures. It is also unknown if pollution exposures influence academic proficiency to the same degree in all schools or if the level of children's social disadvantage in schools modifies the effects, such that some schools' academic proficiency levels are more sensitive to exposures. We address these gaps by examining the percentage of third grade students who tested below the grade level in math and English language arts (ELA) in Salt Lake County, Utah primary schools (n = 156), where fine particulate pollution is a serious health threat. More frequent peak exposures were associated with reduced math and ELA proficiency, as was greater school disadvantage. High frequency peak exposures were more strongly linked to lower math proficiency in more advantaged schools. Findings highlight the need for policies to reduce the number of days with peak air pollution.

Impact of low-level fine particulate matter and ozone exposure on absences in K-12 students and economic consequences.

High air pollution levels are associated with school absences. However, low level pollution impacts on individual school absences are under-studied. Understanding the variability of pollution at individual schools within an urban region could improve school recess decisions, better identify local pollution sources, and improve local economic impact assessments by providing granular information relevant to specific schools. We modelled PM2.5 and ozone concentrations at 36 schools from July 2015 to June 2018 using data from a dense, research grade regulatory sensor network. We determined exposures and daily absences at each school. We used a generalized estimating equations model to retrospectively estimate rate ratios for association between outdoor pollutant concentrations and school absences. We estimated lost school revenue, productivity, and family economic burden. PM2.5 and ozone concentrations and absence rates vary across the School District. Pollution exposure was associated with a rate ratio as high as 1.02 absences per µg m-3 and 1.01 per ppb increase for PM2.5 and ozone, respectively. Significantly, even PM2.5 and ozone exposure below the air quality index breakpoints for good air quality (<12.1 µg m-3 and <55 ppb, respectively) was associated with positive rate ratios of absences: 1.04 per µg m-3 and 1.01 per ppb increase, respectively. Granular local measurements enabled demonstration of air pollution impacts that varied between schools and were undetectable with averaged pollution levels. Reducing pollution by 50% would save $426000 per year districtwide. Pollution reduction benefits would be greatest in schools located in socioeconomically disadvantaged areas. Heterogeneity in exposure, disproportionately affecting socioeconomically disadvantaged schools, points to the need for fine resolution exposure estimation. The economic cost of absences associated with air pollution is substantial even excluding indirect costs such as hospital visits and medication. These findings may help elucidate the differential burden on individual schools and inform local decisions about recess and regulatory considerations for localized pollution sources.

Short-Term Particulate Air Pollution Exposure is Associated with Increased Severity of Respiratory and Quality of Life Symptoms in Patients with Fibrotic Sarcoidosis.

This study aimed to determine if short-term exposure to particulate matter (PM2.5) and ozone (O3) is associated with increased symptoms or lung function decline in fibrotic sarcoidosis. Sixteen patients with fibrotic sarcoidosis complicated by frequent exacerbations completed pulmonary function testing and questionnaires every three months for one year. We compared 7-, 10-, and 14-day average levels of PM2.5 and O3 estimated at patient residences to spirometry (forced expiratory volume in 1 s (FEV1), to forced vital capacity (FVC), episodes of FEV1 decline > 10%) and questionnaire outcomes (Leicester cough questionnaire (LCQ), Saint George Respiratory Questionnaire (SGRQ), and King's Sarcoidosis Questionnaire (KSQ)) using generalized linear mixed effect models. PM2.5 level averaged over 14 days was associated with lower KSQ general health status (score change -6.60 per interquartile range (IQR) PM2.5 increase). PM2.5 level averaged over 10 and 14 days was associated with lower KSQ lung specific health status (score change -6.93 and -6.91, respectively). PM2.5 levels were not associated with FEV1, FVC, episodes of FEV1 decline > 10%, or respiratory symptoms measured by SGRQ or LCQ. Ozone exposure was not associated with any health outcomes. In this small cohort of patients with fibrotic sarcoidosis, PM2.5 exposure was associated with increased severity of respiratory and quality of life symptoms.

High resolution fossil fuel combustion CO2 emission fluxes for the United States.

Quantification of fossil fuel CO2 emissions at fine space and time resolution is emerging as a critical need in carbon cycle and climate change research. As atmospheric CO2 measurements expand with the advent of a dedicated remote sensing platform and denser in situ measurements, the ability to close the carbon budget at spatial scales of approximately 100 km2 and daily time scales requires fossil fuel CO2 inventories at commensurate resolution. Additionally, the growing interest in U.S. climate change policy measures are best served by emissions that are tied to the driving processes in space and time. Here we introduce a high resolution data product (the "Vulcan" inventory: www.purdue.edu/eas/carbon/vulcan/) that has quantified fossil fuel CO2 emissions for the contiguous U.S. at spatial scales less than 100 km2 and temporal scales as small as hours. This data product completed for the year 2002, includes detail on combustion technology and 48 fuel types through all sectors of the U.S. economy. The Vulcan inventory is built from the decades of local/regional air pollution monitoring and complements these data with census, traffic, and digital road data sets. The Vulcan inventory shows excellent agreement with national-level Department of Energy inventories, despite the different approach taken by the DOE to quantify U.S. fossil fuel CO2 emissions. Comparison to the global 1degree x 1 degree fossil fuel CO2 inventory, used widely by the carbon cycle and climate change community prior to the construction of the Vulcan inventory, highlights the space/time biases inherent in the population-based approach.