Comparing Building and Neighborhood-Scale Variability of CO₂ and O₃ to Inform Deployment Considerations for Low-Cost Sensor System Use.

The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO₂ (a primary pollutant) and O₃ (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions

Statistical considerations in a systematic review of proxy measures of clinical behaviour

Peer reviewedPublisher PD

Assessing Exposure to Chlorinated Solvents from the Subsurface to Indoor Air Pathway

The migration of chlorinated volatile organic compounds from groundwater to indoor air--known as vapor intrusion--is an important exposure pathway at sites with contaminated groundwater. However, monitoring indoor air quality in the hundreds or thousands of at-risk homes at each site is logistically and financially infeasible. Screening methods are needed to prioritize homes for monitoring and remediation. Current screening approaches do not adequately account for the substantial spatial and temporal variability in vapor intrusion risk, in part because the causes of this variability are not well understood. This work explores variability in vapor intrusion risk in a case-study community and then develops two different modeling approaches for screening at-risk homes. We employed a community-based approach to collect indoor air samples and analyze vapor intrusion risk in 20 homes at a case-study site. Results demonstrate that indoor concentrations of tetrachloroethylene from vapor intrusion vary by an order of magnitude across space and time. We show that key factors affecting this variability include barometric pressure drop, humidity, wind speed, and season. Using data collected from 370 homes in the National Database on Vapor Intrusion, we developed a multilevel regression model to predict vapor intrusion risks in unmonitored homes. The resulting predictions decrease the rate of false negatives compared with the U.S. Environmental Protection Agency's (EPA) current screening approach, which assumes that indoor air concentration will not exceed 1/1,000 times the soil gas concentration just above the groundwater. Finally, we demonstrate a second approach for improving the accuracy of screening by using Bayesian statistical techniques to integrate observational data into a mechanistic model describing the physical and chemical processes driving vapor intrusion. The resulting calibrated model also decreases the rate of false negatives in screening homes for vapor intrusion risks when compared with the current EPA approach. The results suggest current policy may underestimate vapor intrusion exposures, and we demonstrate two approaches to improve exposure assessment. Future research should evaluate the potential for community-centered and real-time monitoring devices, the integration of localized and cumulative risk information into the framework, and assessment of the risks and benefits of a precautionary approach to mitigation.Doctor of Philosoph

Probabilistic approach to residential vapor intrusion exposure screening for Chlorinated Volatile Organic Compounds: a case study in San Antonio,Texas

The potential for subsurface volatile chemicals to migrate through the soil and impact indoor air quality is an increasingly important exposure pathway at contaminated sites. The characterization of this pathway is highly uncertain and dependent upon many site and building-specific parameters. A probability house-by-house model, based on the Johnson-Ettinger algorithm, is developed based on the current and historic conditions of groundwater contamination of tricholorethylene and tetrachlorethylene from activities at the former Kelly Air Force Base in San Antonio, Texas. The analysis suggests that historically 5.5% of houses exceed PCE screening levels (0.41 ug/m3) at the mean level and 85.3% at the 95th percentile; for TCE (at 0.25 ug/m3) it is 49% and 99% respectively. The current EPA model is slightly less conservative than the new parameterization by Johnson (2005). Comparison with measured samples suggests the probabilistic model underestimates exposure. Soil properties and air exchange rates are the most input critical parameters

Genetic architecture and lifetime dynamics of inbreeding depression in a wild

Inbreeding depression is ubiquitous, but we still know little about its genetic architecture and precise effects in wild populations. Here, we combine long-term life-history data with 417 K imputed SNP genotypes for 5952 wild Soay sheep to explore inbreeding depression on a key fitness component, annual survival. Inbreeding manifests in long runs of homozygosity (ROH), which make up nearly half of the genome in the most inbred individuals. The ROH landscape varies widely across the genome, with islands where up to 87% and deserts where only 4% of individuals have ROH. The fitness consequences of inbreeding are severe; a 10% increase in individual inbreeding F(ROH) is associated with a 60% reduction in the odds of survival in lambs, though inbreeding depression decreases with age. Finally, a genome-wide association scan on ROH shows that many loci with small effects and five loci with larger effects contribute to inbreeding depression in survival

Mutation load decreases with haplotype age in wild Soay sheep

Abstract Runs of homozygosity (ROH) are pervasive in diploid genomes and expose the effects of deleterious recessive mutations, but how exactly these regions contribute to variation in fitness remains unclear. Here, we combined empirical analyses and simulations to explore the deleterious effects of ROH with varying genetic map lengths in wild Soay sheep. Using a long‐term dataset of 4879 individuals genotyped at 417K SNPs, we found that inbreeding depression increases with ROH length. A 1% genomic increase in long ROH (>12.5 cM) reduced the odds of first‐year survival by 12.4% compared to only 7.7% for medium ROH (1.56–12.5 cM), whereas short ROH (<1.56 cM) had no effect on survival. We show by forward genetic simulations that this is predicted: compared to shorter ROH, long ROH will have higher densities of deleterious alleles, with larger average effects on fitness and lower population frequencies. Taken together, our results are consistent with the idea that the mutation load decreases in older haplotypes underlying shorter ROH, where purifying selection has had more time to purge deleterious mutations. Finally, our study demonstrates that strong inbreeding depression can persist despite ongoing purging in a historically small population

Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary).

In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena

Improving professional practice in the disclosure of a diagnosis of dementia : a modeling experiment to evaluate a theory-based intervention

The original publication is available at www.springerlink.com.Peer reviewedPostprin

Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making

At hazardous waste sites, volatile chemicals can migrate through groundwater and soil into buildings, a process known as vapor intrusion. Due to increasing recognition of vapor intrusion as a potential indoor air pollution source, in 2015 the U.S. Environmental Protection Agency (EPA) released a new vapor intrusion guidance document. The guidance specifies two conditions for demonstrating that remediation is needed: (1) proof of a vapor intrusion pathway; and (2) evidence that human health risks exceed established thresholds (for example, one excess cancer among 10,000 exposed people). However, the guidance lacks details on methods for demonstrating these conditions. We review current evidence suggesting that monitoring and modeling approaches commonly employed at vapor intrusion sites do not adequately characterize long-term exposure and in many cases may underestimate risks. On the basis of this evidence, we recommend specific approaches to monitoring and modeling to account for these uncertainties. We propose a value of information approach to integrate the lines of evidence at a site and determine if more information is needed before deciding whether the two conditions specified in the vapor intrusion guidance are satisfied. To facilitate data collection and decision-making, we recommend a multi-directional community engagement strategy and consideration of environment justice concerns

Ambient Monitoring for Sinclair and Dyes Inlets, Puget Sound, Washington: Chemical Analyses for 2010 Regional Mussel Watch (AMB02)

The Puget Sound Naval Shipyard & Intermediate Maintenance Facility (PSNS&IMF) and Naval Base Kitsap-Bremerton (Shipyard) located in Bremerton, WA are committed to a culture of continuous process improvement for all aspects of Shipyard operations, including reducing the releases of hazardous materials and waste in discharges from the Shipyard. Under the Project ENVVEST Final Project Agreement, a cooperative project among PSNS&IMF, the Environmental Protection Agency (EPA), and the Washington State Department of Ecology (Ecology), and local stakeholders (US Navy, EPA and Ecology 2002) has been helping to improve the environmental quality of the Sinclair and Dyes Inlet Watershed (ENVVEST 2006). An ambient monitoring program for sediment, water, and indigenous mussels began in 2009 to assess the status and trend of ecological resources, assess the effectiveness of cleanup and pollution control measures, and determine if discharges from all sources are protective of beneficial uses including aquatic life. This document presents the 2010 chemical residue data and stable isotopes of carbon (δ13C) and nitrogen (δ15N) for the regional mussel watch stations located in Sinclair Inlet, Dyes Inlet, Port Orchard Passage, Rich Passage, Agate Passage, Liberty Bay, and Keyport Lagoon. Indigenous bivalves were collected from a small boat and/or from along the shoreline, measured, composited, and analyzed for a suite of trace metals and organic contaminants. The trace metals included silver, arsenic, cadmium, chromium, copper, mercury, nickel, lead, and zinc. The organic contaminants included the list of NOAA Status and Trends 20 polychlorinated biphenyls (PCB) congeners and suite of parent and methylated polycyclic aromatic hydrocarbons (PAHs). These chemical residue data provide the first year of the biota ambient monitoring