Using Gas-Phase Air Quality Sensors to Disentangle Potential Sources in a Los Angeles Neighborhood.
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ABSTRACT:
SUBMITTER: Collier-Oxandale A
PROVIDER: S-EPMC8248942 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Over the past decade, sensor networks have been proven valuable to assess air quality on highly localized scales. Here we leverage innovative sensors to characterize gaseous pollutants in a complex urban environment and evaluate differences in air quality in three different Los Angeles neighborhoods where oil and gas activity is present. We deployed monitors across urban neighborhoods in South Los Angles adjacent to oil and gas facilities with varying levels of production. Using low-cost sensors built in-house, we measured methane, total non-methane hydrocarbons (TNMHCs), carbon monoxide, and carbon dioxide during three deployment campaigns over four years. The multi-sensor linear regression calibration model developed to quantify methane and TNMHCs offers up to 16% improvement in coefficient of determination and up to a 22% reduction in root mean square error for the most recent dataset as compared to previous models. The deployment results demonstrate that airborne methane concentrations are higher within a 500 m radius of three urban oil and gas facilities, as well as near a natural gas distribution pipeline, likely a result of proximity to sources. While there are numerous additional sources of TNMHCs in complex urban environments, some sites appear to be larger emitters than others. Significant methane emissions were also measured at an idle site, suggesting that fugitive emissions may still occur even if production is ceased. Episodic spikes of both compounds suggested an association with oil and gas activities, demonstrating how sensor networks can be used to elucidate community-scale sources and differences in air quality moving forward.
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Project description:With the near-future launch of geostationary pollution monitoring satellite instruments over North America, East Asia, and Europe, the air quality community is preparing for an integrated global atmospheric composition observing system at unprecedented spatial and temporal resolutions. One of the ways that NASA has supported this community preparation is through demonstration of future space-borne capabilities using the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument. This paper integrates repeated high-resolution maps from GeoTASO, ground-based Pandora spectrometers, and low Earth orbit measurements from the Ozone Mapping and Profiler Suite (OMPS), for case studies over two metropolitan areas: Seoul, South Korea on June 9th, 2016 and Los Angeles, California on June 27th, 2017. This dataset provides a unique opportunity to illustrate how geostationary air quality monitoring platforms and ground-based remote sensing networks will close the current spatiotemporal observation gap. GeoTASO observes large differences in diurnal behavior between these urban areas, with NO2 accumulating within the Seoul Metropolitan Area through the day but NO2 peaking in the morning and decreasing throughout the afternoon in the Los Angeles Basin. In both areas, the earliest morning maps exhibit spatial patterns similar to emission source areas (e.g., urbanized valleys, roadways, major airports). These spatial patterns change later in the day due to boundary layer dynamics, horizontal transport, and chemistry. The nominal resolution of GeoTASO is finer than will be obtained from geostationary platforms, but when NO2 data over Los Angeles are up-scaled to the expected resolution of TEMPO, spatial features discussed are conserved. Pandora instruments installed in both metropolitan areas capture the diurnal patterns observed by GeoTASO, continuously and over longer time periods, and will play a critical role in validation of the next generation of satellite measurement.. These case studies demonstrate that different regions can have diverse diurnal patterns and that day-to-day variability due to meteorology or anthropogenic patterns such as weekday/weekend variations in emissions is large. Low Earth orbit measurements, despite their inability to capture the diurnal patterns at fine spatial resolution, will be essential for intercalibrating the geostationary radiances and cross-validating the geostationary retrievals in an integrated global observing system.
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Project description:We observed elevated air pollutant concentrations, especially of ultrafine particles (UFP), black carbon (BC) and NO, across the residential neighborhood of the Boyle Heights Community (BH) of Los Angeles, California. Using an electric vehicle mobile platform equipped with fast response instruments, real-time air pollutant concentrations were measured in BH in spring and summer of 2008. Pollutant concentrations varied significantly in the two seasons, on different days, and by time of day, with an overall average UFP concentration in the residential areas of ~33 000 cm-3. The averaged UFP, BC, and NO concentrations measured on Soto St, a major surface street in BH, were 57 000 cm-3, 5.1 µg m-3, and 67 ppb, respectively. Concentrations of UFP across the residential areas in BH were nearly uniform spatially, in contrast to other areas in the greater metropolitan area of Los Angeles where UFP concentrations exhibit strong gradients downwind of roadways. We attribute this "UFP cloud" to high traffic volumes, including heavy duty diesel trucks on the freeways which surround and traverse BH, and substantial numbers of high-emitting vehicles (HEVs) on the surface streets traversing BH. Additionally, the high density of stop signs and lights and short block lengths, requiring frequent accelerations of vehicles, may contribute. The data also support a role for photochemical production of UFP in the afternoon. UFP concentration peaks (5 s average) of up to 9 million particles cm-3 were also observed immediately behind HEVs when they accelerated from stop lights in the BH neighborhood and areas immediately adjacent. Although encounters with HEV during mornings accounted for only about 6% and 17% of time spent monitoring residential areas and major surface streets, HEV contributed to about 28% and 53% of total ultrafine particles measured on the route, respectively. The observation of elevated pollutant number concentrations across the Boyle Heights community highlights how multiple factors combine to create high pollutant levels, and has important human exposure assessment implications, including the potential utility of our data as inputs to epidemiological studies.
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Project description:The objective of this study was to examine the associations between alcohol availability types and community characteristics in randomly selected census tracts in Southern California and Southeastern Louisiana. Outlet shelf space and price by beverage type was collected from all off-sale alcohol outlets in 189 census tracts by trained research personnel. Three aspects of alcohol availability at the census tract level were considered--outlets per roadway mile, shelf space, and least price by beverage type. Using multivariate analyses, we examined the associations between census tract socioeconomic and demographic characteristics and alcohol availability types. Fifteen measures of alcohol availability were calculated-total shelf space and shelf space by beverage types (beer, malt liquor, and distilled spirits); outlets per roadway mile, per tract, and per capita; and least price by beverage type (including wine). In multivariate analyses controlling for state, male unemployment rate was inversely associated with total shelf space (p = 0.03) and distilled spirit shelf space (p = 0.05). Malt liquor shelf space was inversely associated with percent White (p = 0.02). Outlets per roadway mile was positively associated with household poverty (p < 0.0001), whereas percent African American was inversely associated with outlets per roadway mile (p = 0.03). Beverage-specific least prices were not associated with any socioeconomic or demographic community characteristics. Alcohol availability types, but not least price, were associated with some community characteristics. More research exploring how alcohol availability types vary by community and their relationship to alcohol-related harms should be conducted.
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Project description:BackgroundThe prevalence of autistic disorder (AD), a serious developmental condition, has risen dramatically over the past two decades, but high-quality population-based research addressing etiology is limited.ObjectivesWe studied the influence of exposures to traffic-related air pollution during pregnancy on the development of autism using data from air monitoring stations and a land use regression (LUR) model to estimate exposures.MethodsChildren of mothers who gave birth in Los Angeles, California, who were diagnosed with a primary AD diagnosis at 3-5 years of age during 1998-2009 were identified through the California Department of Developmental Services and linked to 1995-2006 California birth certificates. For 7,603 children with autism and 10 controls per case matched by sex, birth year, and minimum gestational age, birth addresses were mapped and linked to the nearest air monitoring station and a LUR model. We used conditional logistic regression, adjusting for maternal and perinatal characteristics including indicators of SES.ResultsPer interquartile range (IQR) increase, we estimated a 12-15% relative increase in odds of autism for ozone [odds ratio (OR) = 1.12, 95% CI: 1.06, 1.19; per 11.54-ppb increase] and particulate matter ≤ 2.5 µm (OR = 1.15; 95% CI: 1.06, 1.24; per 4.68-μg/m3 increase) when mutually adjusting for both pollutants. Furthermore, we estimated 3-9% relative increases in odds per IQR increase for LUR-based nitric oxide and nitrogen dioxide exposure estimates. LUR-based associations were strongest for children of mothers with less than a high school education.ConclusionMeasured and estimated exposures from ambient pollutant monitors and LUR model suggest associations between autism and prenatal air pollution exposure, mostly related to traffic sources.
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Project description:ObjectivesGrowing evidence indicates that ambient (AAP: NO2 , PM2.5 and O3 ) and traffic-related air pollutants (TRAP) contribute to metabolic disease risk in adults; however, few studies have examined these relationships in children.MethodsMetabolic profiling was performed in 429 overweight and obese African-American and Latino youth living in urban Los Angeles, California. This cross-sectional study estimated individual residential air pollution exposure and used linear regression to examine relationships between air pollution and metabolic outcomes.ResultsAAP and TRAP exposure were associated with adverse effects on glucose metabolism independent of body fat percent. PM2.5 was associated with 25.0% higher fasting insulin (p < 0.001), 8.3% lower insulin sensitivity (p < 0.001), 14.7% higher acute insulin response to glucose (p = 0.001) and 1.7% higher fasting glucose (p < 0.001). Similar associations were observed for increased NO2 exposure. TRAP from non-freeway roads was associated with 12.1% higher insulin (p < 0.001), 6.9% lower insulin sensitivity (p = 0.02), 10.8% higher acute insulin response to glucose (p = 0.003) and 0.7% higher fasting glucose (p = 0.047).ConclusionsElevated air pollution exposure was associated with a metabolic profile that is characteristic of increased risk for type 2 diabetes. These results indicate that increased prior year exposure to air pollution may adversely affect type 2 diabetes-related pathophysiology in overweight and obese minority children.
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Project description:Few previous studies examined the impact of prenatal air pollution exposures on fetal development based on ultrasound measures during pregnancy.In a prospective birth cohort of more than 500 women followed during 1993-1996 in Los Angeles, California, we examined how air pollution impacts fetal growth during pregnancy. Exposure to traffic related air pollution was estimated using CALINE4 air dispersion modeling for nitrogen oxides (NOx) and a land use regression (LUR) model for nitrogen monoxide (NO), nitrogen dioxide (NO2) and NOx. Exposures to carbon monoxide (CO), NO2, ozone (O3) and particles <10?m in aerodynamic diameter (PM10) were estimated using government monitoring data. We employed a linear mixed effects model to estimate changes in fetal size at approximately 19, 29 and 37 weeks gestation based on ultrasound.Exposure to traffic-derived air pollution during 29 to 37 weeks was negatively associated with biparietal diameter at 37 weeks gestation. For each interquartile range (IQR) increase in LUR-based estimates of NO, NO2 and NOx, or freeway CALINE4 NOx we estimated a reduction in biparietal diameter of 0.2-0.3mm. For women residing within 5km of a monitoring station, we estimated biparietal diameter reductions of 0.9-1.0mm per IQR increase in CO and NO2. Effect estimates were robust to adjustment for a number of potential confounders. We did not observe consistent patterns for other growth endpoints we examined.Prenatal exposure to traffic-derived pollution was negatively associated with fetal head size measured as biparietal diameter in late pregnancy.
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Project description:BackgroundNumerous studies have linked criteria air pollutants with adverse birth outcomes, but there is less information on the importance of specific emission sources, such as traffic, and air toxics.ObjectivesWe used three exposure data sources to examine odds of term low birth weight (LBW) in Los Angeles, California, women when exposed to high levels of traffic-related air pollutants during pregnancy.MethodsWe identified term births during 1 June 2004 to 30 March 2006 to women residing within 5 miles of a South Coast Air Quality Management District (SCAQMD) Multiple Air Toxics Exposure Study (MATES III) monitoring station. Pregnancy period average exposures were estimated for air toxics, including polycyclic aromatic hydrocarbons (PAHs), source-specific particulate matter < 2.5 μm in aerodynamic diameter (PM2.5) based on a chemical mass balance model, criteria air pollutants from government monitoring data, and land use regression (LUR) model estimates of nitric oxide (NO), nitrogen dioxide (NO2) and nitrogen oxides (NOx). Associations between these metrics and odds of term LBW (< 2,500 g) were examined using logistic regression.ResultsOdds of term LBW increased approximately 5% per interquartile range increase in entire pregnancy exposures to several correlated traffic pollutants: LUR measures of NO, NO2, and NOx, elemental carbon, and PM2.5 from diesel and gasoline combustion and paved road dust (geological PM2.5).ConclusionsThese analyses provide additional evidence of the potential impact of traffic-related air pollution on fetal growth. Particles from traffic sources should be a focus of future studies.
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Project description:The oceans are the main source of natural halogen and sulfur compounds, which have a significant influence on the oxidizing capacity of the marine atmosphere; however, their impact on the air quality of coastal cities is currently unknown. We explore the effect of marine halogens (Cl, Br and I) and dimethyl sulfide (DMS) on the air quality of a large coastal city through a set of high-resolution (4-km) air quality simulations for the urban area of Los Angeles, US, using the Community Multiscale Air Quality (CMAQ model). The results indicate that marine halogen emissions decrease ozone and nitrogen dioxide levels up to 5ppbv and 2.5ppbv, respectively, in the city of Los Angeles. Previous studies suggested that the inclusion of chlorine in air quality models leads to the generation of ozone in urban areas through photolysis of nitryl chloride (ClNO2). However, we find that when considering the chemistry of Cl, Br and I together the net effect is a reduction of surface ozone concentrations. Furthermore, combined ocean emissions of halogens and DMS cause substantial changes in the levels of key urban atmospheric oxidants such as OH, HO2 and NO3, and in the composition and mass of fine particles. Although the levels of ozone, NO3 and HOx are reduced, we find a 10% increase in secondary organic aerosol (SOA) mean concentration, attributed to the increase in aerosol acidity and sulfate aerosol formation when combining DMS and bromine. Therefore, this new pathway for enhanced SOA formation may potentially help with current model under predictions of urban SOA. Although further observations and research are needed to establish these preliminary conclusions, this first city-scale investigation suggests that the inclusion of oceanic halogens and DMS in air quality models may improve regional air quality predictions over coastal cities around the world.
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