PRETA Air: Hazardous Air Pollutants

This report shows that people living in a 10-county region of southwestern Pennsylvania have a significantly higher than acceptable risk of developing cancer due to exposure to toxic air pollution released by manufacturing processes, energy production and diesel combustionThe Pittsburgh Regional Environmental Threats Analysis Report -- funded by The Heinz Endowments -- analyzes publicly available data on hazardous air pollutants (HAPs), also known as air toxics. Air toxics include approximately 200 pollutants identified by the U.S. Environmental Protection Agency (EPA) as known or suspected to cause cancer or other serious health effects, such as respiratory, neurological and reproductive disorders. The report is the third in a series as part of a project examining major threats to human health and the environment in southwestern Pennsylvania

Hybrid Dispersion/ Land Use Regression Modeling for Improving Air Pollutant Concentration Estimates

The overall objective of this dissertation was to examine the utility of incorporating source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient NO2 and PM2.5. Ultimately, we are interested in obtaining highly resolved spatiotemporal pollutant estimates to examine the attenuation of health effect estimate bias that may result from exposure model misspecification. A multi-pollutant sampling campaign was conducted across six successive weekly sampling sessions in the summer and winter seasons of 2011-2013 in Pittsburgh, PA. As a preliminary investigation, predictions from a roadway dispersion model (Caline3) were included as an independent predictor in pre-constructed winter season LUR models for NO2. Caline3 output improved out-of-sample model fitness and added an additional portion of unexplained variation (3-10% by leave-one-out cross-validated R2) in NO2 observations compared to the standard LUR models. Correspondingly, the AERMOD dispersion model was implemented to predict PM2.5 from local and regional stationary sources in a similar hybrid framework. As per cross-validated R2 and RMSE, AERMOD predictions improved overall model fitness and explained an additional 9-13% in out-of-sample variability in summer and winter PM2.5 models. Both dispersion model output functioned similarly when incorporated into standard LUR models, effectively displacing the respective GIS-based covariates, corroborating model interpretability, and capturing the greatest degree of improvements at nearby, high-density source locations. To examine the potential for spatially-differential exposure measurement improvement in health effect estimation studies, we applied LUR and hybrid LUR/ dispersion model PM2.5 predictions to non-sampled locations and observed non-Berkson-type measurement error only when the modeling domain was restricted to a near-source (<1km) environment. By a simple stochastic simulation, we demonstrated that a well characterized dispersion-derived geographic covariate, defined by a robust variance about the monitoring locations, can theoretically result in less exposure measurement error and exposure misclassification. Therefore, highly refined spatiotemporal information can improve out-of-sample prediction accuracy; however, the statistical fidelity remains constrained by the degree of source contribution captured by monitoring locations. These findings have important public health implications for understanding air pollutant exposure measurement error derived from typical LUR studies. In the absence of a spatially dense monitoring network, we demonstrated that AERMOD can produce a spatiotemporally resolved prediction surface compared to typical GIS-based covariates across a large urban-to-suburban domain with pertinent pollutant sources and complex topography

Air pollution and health impacts of oil & gas production in the United States

Oil and gas production is one of the largest emitters of methane, a potent greenhouse gas and a significant contributor of air pollution emissions. While research on methane emissions from oil and gas production has grown rapidly, there is comparatively limited information on the distribution of impacts of this sector on air quality and associated health impacts. Understanding the contribution of air quality and health impacts of oil and gas can be useful for designing mitigation strategies. Here we assess air quality and human health impacts associated with ozone, fine particulate matter, and nitrogen dioxide from the oil and gas sector in the US in 2016, and compare this impact with that of the associated methane emissions. We find that air pollution in 2016 from the oil and gas sector in the US resulted in 410 000 asthma exacerbations, 2200 new cases of childhood asthma and 7500 excess deaths, with $77 billion in total health impacts. NO2 was the highest contributor to health impacts (37%) followed by ozone (35%), and then PM2.5 (28%). When monetized, these air quality health impacts of oil and gas production exceeded estimated climate impact costs from methane leakage by a factor of 3. These impacts add to the total life cycle impacts of oil and gas, and represent potential additional health benefits of strategies that reduce consumption of oil and gas. Policies to reduce oil and gas production emissions will lead to additional and significant health benefits from co-pollutant reductions that are not currently quantified or monetized

Population allocation at the housing unit level: estimates around underground natural gas storage wells in PA, OH, NY, WV, MI, and CA

Background Spatially accurate population data are critical for determining health impacts from many known risk factors. However, the utility of the increasing spatial resolution of disease mapping and environmental exposures is limited by the lack of receptor population data at similar sub-census block spatial scales. Methods Here we apply an innovative method (Population Allocation by Occupied Domicile Estimation – ABODE) to disaggregate U.S. Census populations by allocating an average person per household to geospatially-identified residential housing units (RHU). We considered two possible sources of RHU location data: address point locations and building footprint centroids. We compared the performance of ABODE with the common proportional population allocation (PPA) method for estimating the nighttime residential populations within 200 m radii and setback areas (100 – 300 ft) around active underground natural gas storage (UGS) wells (n = 9834) in six U.S. states. Results Address location data generally outperformed building footprint data in predicting total counts of census residential housing units, with correlations ranging from 0.67 to 0.81 at the census block level. Using residentially-sited addresses only, ABODE estimated upwards of 20,000 physical households with between 48,126 and 53,250 people living within 200 m of active UGS wells – likely encompassing the size of a proposed UGS Wellhead Safety Zone. Across the 9834 active wells assessed, ABODE estimated between 5074 and 10,198 more people living in these areas compare to PPA, and the difference was significant at the individual well level (p = < 0.0001). By either population estimation method, OH exhibits a substantial degree of hyperlocal land use conflict between populations and UGS wells – more so than other states assessed. In some rare cases, population estimates differed by more than 100 people for the small 200 m2 well-areas. ABODE’s explicit accounting of physical households confirmed over 50% of PPA predictions as false positives indicated by non-zero predictions in areas absent physical RHUs. Conclusions Compared to PPA – in allocating identical population data at sub-census block spatial scales –ABODE provides a more precise population at risk (PAR) estimate with higher confidence estimates of populations at greatest risk. 65% of UGS wells occupy residential urban and suburban areas indicating the unique land use conflicts presented by UGS systems that likely continue to experience population encroachment. Overall, ABODE confirms tens of thousands of homes and residents are likely located within the proposed UGS Wellhead Safety Zone – and in some cases within state’s oil and gas well surface setback distances – of active UGS wells

Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain

Background: Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. Methods: We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. Results: During July-August 2011 and January-March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Conclusions: Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling

Home is where the pipeline ends: characterization of volatile organic compounds present in natural gas at the point of the residential end user

The presence of volatile organic compounds (VOCs) in unprocessed natural gas (NG) is well documented; however, the degree to which VOCs are present in NG at the point of end use is largely uncharacterized. We collected 234 whole NG samples across 69 unique residential locations across the Greater Boston metropolitan area, Massachusetts. NG samples were measured for methane (CH4), ethane (C2H6), and nonmethane VOC (NMVOC) content (including tentatively identified compounds) using commercially available USEPA analytical methods. Results revealed 296 unique NMVOC constituents in end use NG, of which 21 (or approximately 7%) were designated as hazardous air pollutants. Benzene (bootstrapped mean = 164 ppbv; SD = 16; 95% CI: 134-196) was detected in 95% of samples along with hexane (98% detection), toluene (94%), heptane (94%), and cyclohexane (89%), contributing to a mean total concentration of NMVOCs in distribution-grade NG of 6.0 ppmv (95% CI: 5.5-6.6). While total VOCs exhibited significant spatial variability, over twice as much temporal variability was observed, with a wintertime NG benzene concentration nearly eight-fold greater than summertime. By using previous NG leakage data, we estimated that 120-356 kg/yr of annual NG benzene emissions throughout Greater Boston are not currently accounted for in emissions inventories, along with an unaccounted-for indoor portion. NG-odorant content (tert-butyl mercaptan and isopropyl mercaptan) was used to estimate that a mean NG-CH4 concentration of 21.3 ppmv (95% CI: 16.7-25.9) could persist undetected in ambient air given known odor detection thresholds. This implies that indoor NG leakage may be an underappreciated source of both CH4 and associated VOCs.19-07957 - Barr Foundation; Putnam FoundationPublished versio

Apecificazione, apicogenesi e procedure endodontiche rigenerative : revisione della letteratura

RiassuntoObiettivoPresentare le alternative terapeutiche per la gestione degli apici immaturi e l'evoluzione delle tecniche e dei materiali utilizzati.Materiali e metodiÈ stata effettuata una ricerca della letteratura in Medline™ limitata agli studi su esseri umani pubblicati negli ultimi 10 anni, con sequenza appropriata di parole chiave.RisultatiNelle tecniche di apicogenesi e apecificazione utilizzando idrossido di calcio o MTA si riscontra una buona percentuale di successo clinico. Le recenti procedure rigenerative pongono dei dubbi sul futuro dell'apecificazione anche in elementi non vitali.ConclusioniL'idrossido di calcio risulta il gold standard tra i materiali utilizzati in elementi immaturi. Nuove tecnologie stanno promuovendo un interesse crescente per strategie atte a mantenere o addirittura ripristinare la vitalità pulpare.SummaryObjectiveTo present the terapheutical approach to the management of the immature apex and the evolution of materials and techniques.Materials and methodsA Medline™ search was performed limited to human studies published in the last 10 years. The keywords searched were apexogenesis, apexification, pulp regeneration, revascularization.ResultsApexogenesis and apexification techniques using Calcium hydroxide or MTA give a good success rate. Recent regeneration procedures may put into discussion the opportunity of apexification in non vital elements.ConclusionsCalcium hydroxide is the gold standard material used for immature teeth. New technologies are promoting incoming interest for strategies of vitality preservation and pulp regeneration

Developing a Modular Unmanned Aerial Vehicle (UAV) Platform for Air Pollution Profiling

The unmanned aerial vehicle (UAV) offers great potential for collecting air quality data with high spatial and temporal resolutions. The objective of this study is to design and develop a modular UAV-based platform capable of real-time monitoring of multiple air pollutants. The system comprises five modules: the UAV, the ground station, the sensors, the data acquisition (DA) module, and the data fusion (DF) module. The hardware was constructed with off-the-shelf consumer parts and the open source software Ardupilot was used for flight control and data fusion. The prototype UAV system was tested in representative settings. Results show that this UAV platform can fly on pre-determined pathways with adequate flight time for various data collection missions. The system simultaneously collects air quality and high precision X-Y-Z data and integrates and visualizes them in a real-time manner. While the system can accommodate multiple gas sensors, UAV operations may electronically interfere with the performance of chemical-resistant sensors. Our prototype and experiments prove the feasibility of the system and show that it features a stable and high precision spatial-temporal platform for air sample collection. Future work should be focused on gas sensor development, plug-and-play interfaces, impacts of rotor wash, and all-weather designs