<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Christine C Ghetu</style></author><author><style face="normal" font="default" size="100%">Diana Rohlman</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Richard P Scott</style></author><author><style face="normal" font="default" size="100%">Kaley A Adams</style></author><author><style face="normal" font="default" size="100%">Peter D Hoffman</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wildfire Impact on Indoor and Outdoor PAH Air Quality.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022 Jul 08</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Air quality impacts from wildfires are poorly understood, particularly indoors. As frequencies increase, it is important to optimize methodologies to understand and reduce chemical exposures from wildfires. Public health recommendations use air quality estimates from outdoor stationary air monitors, discounting indoor air conditions, and do not consider chemicals in the vapor phase, known to elicit adverse effects. We investigated vapor-phase polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor air before, during, and after wildfires using a community-engaged research approach. Paired passive air samplers were deployed at 15 locations across four states. Twelve unique PAHs were detected only in outdoor air during wildfires, highlighting a PAH exposure mixture for future study. Heavy-molecular-weight (HMW) outdoor PAH concentrations and average Air Quality Index (AQI) values were positively correlated ( &amp;lt; 0.001). Indoor PAH concentrations were higher in 77% of samples across all sampling events. Even during wildfires, 58% of sampled locations still had higher indoor PAH air concentrations. When AQI values exceeded 140 (unhealthy for sensitive groups), outdoor PAH concentrations became similar to or higher than indoors. Cancer and noncancer inhalation risk estimates from vapor-phase PAHs were higher indoors than outdoors, regardless of the wildfire impact. Consideration of indoor air quality and vapor-phase PAHs could inform public health recommendations regarding wildfires.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Holly Dixon</style></author><author><style face="normal" font="default" size="100%">Armstrong, Georgina</style></author><author><style face="normal" font="default" size="100%">Michael L Barton</style></author><author><style face="normal" font="default" size="100%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Melissa Bondy</style></author><author><style face="normal" font="default" size="100%">Mary L Halbleib</style></author><author><style face="normal" font="default" size="100%">Winnifred Hamilton</style></author><author><style face="normal" font="default" size="100%">Erin N Haynes</style></author><author><style face="normal" font="default" size="100%">Julie Herbstman</style></author><author><style face="normal" font="default" size="100%">Peter D Hoffman</style></author><author><style face="normal" font="default" size="100%">Paul C Jepson</style></author><author><style face="normal" font="default" size="100%">Molly Kile</style></author><author><style face="normal" font="default" size="100%">Laurel D Kincl</style></author><author><style face="normal" font="default" size="100%">Paul J Laurienti</style></author><author><style face="normal" font="default" size="100%">Paula E North</style></author><author><style face="normal" font="default" size="100%">Paulik, L Blair</style></author><author><style face="normal" font="default" size="100%">Petrosino, Joe</style></author><author><style face="normal" font="default" size="100%">Points, Gary L</style></author><author><style face="normal" font="default" size="100%">Carolyn M Poutasse</style></author><author><style face="normal" font="default" size="100%">Diana Rohlman</style></author><author><style face="normal" font="default" size="100%">Richard P Scott</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Lane G Tidwell</style></author><author><style face="normal" font="default" size="100%">Cheryl Walker</style></author><author><style face="normal" font="default" size="100%">Katrina M Waters</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discovery of common chemical exposures across three continents using silicone wristbands.</style></title><secondary-title><style face="normal" font="default" size="100%">R Soc Open Sci</style></secondary-title><alt-title><style face="normal" font="default" size="100%">R Soc Open Sci</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">181836</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;To assess differences and trends in personal chemical exposure, volunteers from 14 communities in Africa (Senegal, South Africa), North America (United States (U.S.)) and South America (Peru) wore 262 silicone wristbands. We analysed wristband extracts for 1530 unique chemicals, resulting in 400 860 chemical data points. The number of chemical detections ranged from 4 to 43 per wristband, with 191 different chemicals detected, and 1339 chemicals were not detected in any wristband. No two wristbands had identical chemical detections. We detected 13 potential endocrine disrupting chemicals in over 50% of all wristbands and found 36 chemicals in common between chemicals detected in three geographical wristband groups (Africa, North America and South America). U.S. children (less than or equal to 11 years) had the highest percentage of flame retardant detections compared with all other participants. Wristbands worn in Texas post-Hurricane Harvey had the highest mean number of chemical detections (28) compared with other study locations (10-25). Consumer product-related chemicals and phthalates were a high percentage of chemical detections across all study locations (36-53% and 18-42%, respectively). Chemical exposures varied among individuals; however, many individuals were exposed to similar chemical mixtures. Our exploratory investigation uncovered personal chemical exposure trends that can help prioritize certain mixtures and chemical classes for future studies.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Paulik, L Blair</style></author><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Diana Rohlman</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Richard P Scott</style></author><author><style face="normal" font="default" size="100%">Laurel D Kincl</style></author><author><style face="normal" font="default" size="100%">Erin N Haynes</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Environmental and individual PAH exposures near rural natural gas extraction.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Pollut</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Pollut.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollution</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Exposure</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Linear Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Natural Gas</style></keyword><keyword><style  face="normal" font="default" size="100%">Oil and Gas Fields</style></keyword><keyword><style  face="normal" font="default" size="100%">Petroleum</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Aromatic Hydrocarbons</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyrenes</style></keyword><keyword><style  face="normal" font="default" size="100%">Silicones</style></keyword><keyword><style  face="normal" font="default" size="100%">Tandem Mass Spectrometry</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">241</style></volume><pages><style face="normal" font="default" size="100%">397-405</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Natural gas extraction (NGE) has expanded rapidly in the United States in recent years. Despite concerns, there is little information about the effects of NGE on air quality or personal exposures of people living or working nearby. Recent research suggests NGE emits polycyclic aromatic hydrocarbons (PAHs) into air. This study used low-density polyethylene passive samplers to measure concentrations of PAHs in air near active (n = 3) and proposed (n = 2) NGE sites. At each site, two concentric rings of air samplers were placed around the active or proposed well pad location. Silicone wristbands were used to assess personal PAH exposures of participants (n = 19) living or working near the sampling sites. All samples were analyzed for 62 PAHs using GC-MS/MS, and point sources were estimated using the fluoranthene/pyrene isomer ratio. ∑PAH was significantly higher in air at active NGE sites (Wilcoxon rank sum test, p &amp;lt; 0.01). PAHs in air were also more petrogenic (petroleum-derived) at active NGE sites. This suggests that PAH mixtures at active NGE sites may have been affected by direct emissions from petroleum sources at these sites. ∑PAH was also significantly higher in wristbands from participants who had active NGE wells on their properties than from participants who did not (Wilcoxon rank sum test, p &amp;lt; 0.005). There was a significant positive correlation between ∑PAH in participants&#039; wristbands and ∑PAH in air measured closest to participants&#039; homes or workplaces (simple linear regression, p &amp;lt; 0.0001). These findings suggest that living or working near an active NGE well may increase personal PAH exposure. This work also supports the utility of the silicone wristband to assess personal PAH exposure.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">LB Paulik</style></author><author><style face="normal" font="default" size="100%">Carey E Donald</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Lane G Tidwell</style></author><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Laurel D Kincl</style></author><author><style face="normal" font="default" size="100%">Erin N Haynes</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Emissions of Polycyclic Aromatic Hydrocarbons from Natural Gas Extraction into Air.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Sci. Technol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2016</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">7921-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Natural gas extraction, often referred to as &quot;fracking&quot;, has increased rapidly in the United States in recent years. To address potential health impacts, passive air samplers were deployed in a rural community heavily affected by the natural gas boom. Samplers were analyzed for 62 polycyclic aromatic hydrocarbons (PAHs). Results were grouped based on distance from each sampler to the nearest active well. Levels of benzo[a]pyrene, phenanthrene, and carcinogenic potency of PAH mixtures were highest when samplers were closest to active wells. PAH levels closest to natural gas activity were comparable to levels previously reported in rural areas in winter. Sourcing ratios indicated that PAHs were predominantly petrogenic, suggesting that PAH levels were influenced by direct releases from the earth. Quantitative human health risk assessment estimated the excess lifetime cancer risks associated with exposure to the measured PAHs. At sites closest to active wells, the risk estimated for maximum residential exposure was 0.04 in a million, which is below the U.S. Environmental Protection Agency&#039;s acceptable risk level. Overall, risk estimates decreased 30% when comparing results from samplers closest to active wells to those farthest from them. This work suggests that natural gas extraction is contributing PAHs to the air, at levels that would not be expected to increase cancer risk.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">14</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lane G Tidwell</style></author><author><style face="normal" font="default" size="100%">Sarah E Allan</style></author><author><style face="normal" font="default" size="100%">Steven G O&#039;Connell</style></author><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PAH and OPAH Flux during the Deepwater Horizon Incident.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Sci. Technol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2016</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">7489-97</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Passive sampling devices were used to measure air vapor and water dissolved phase concentrations of 33 polycyclic aromatic hydrocarbons (PAHs) and 22 oxygenated PAHs (OPAHs) at four Gulf of Mexico coastal sites prior to, during and after shoreline oiling from the Deepwater Horizon oil spill (DWH). Measurements were taken at each site over a 13 month period, and flux across the water-air boundary was determined. This is the first report of vapor phase and diffusive flux of both PAHs and OPAHs during the DWH. Vapor phase sum PAH and OPAH concentrations ranged between 6.6 and 210 ng/m(3) and 0.02 and 34 ng/m(3) respectively. PAH and OPAH concentrations in air exhibited different spatial and temporal trends than in water, and air-water flux of 13 individual PAHs was shown to be at least partially influenced by the DWH incident. The largest PAH volatilizations occurred at the sites in Alabama and Mississippi at nominal rates of 56 000 and 42 000 ng/m(2) day(-1) in the summer. Naphthalene was the PAH with the highest observed volatilization rate of 52 000 ng/m(2) day(-1) in June 2010. This work represents additional evidence of the DWH incident contributing to air contamination, and provides one of the first quantitative air-water chemical flux determinations with passive sampling technology.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">14</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">LB Paulik</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Gregory J Sower</style></author><author><style face="normal" font="default" size="100%">Norman D Forsberg</style></author><author><style face="normal" font="default" size="100%">JG Teeguarden</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Passive samplers accurately predict PAH levels in resident crayfish.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Total Environ</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci. Total Environ.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2016</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">544</style></volume><pages><style face="normal" font="default" size="100%">782-791</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4±1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests that it could be easily adapted to predict contamination in other shellfish of concern.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Carey E Donald</style></author><author><style face="normal" font="default" size="100%">Elie, Marc R</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Peter D Hoffman</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transport stability of pesticides and PAHs sequestered in polyethylene passive sampling devices.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Pollut Res Int</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ Sci Pollut Res Int</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2016</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Research using low-density polyethylene (LDPE) passive samplers has steadily increased over the past two decades. However, such research efforts remain hampered because of strict guidelines, requiring that these samplers be quickly transported in airtight metal or glass containers or foil wrapped on ice. We investigate the transport stability of model pesticides and polycyclic aromatic hydrocarbons (PAHs) with varying physicochemical properties using polytetrafluoroethylene (PTFE) bags instead. Transport scenarios were simulated with transport times up to 14&amp;nbsp;days with temperatures ranging between -20 and 35&amp;nbsp;°C. Our findings show that concentrations of all model compounds examined were stable for all transport conditions tested, with mean recoveries ranging from 88 to 113&amp;nbsp;%. Furthermore, PTFE bags proved beneficial as reusable, lightweight, low-volume, low-cost alternatives to conventional containers. This documentation of stability will allow for more flexible transportation of LDPE passive samplers in an expanding range of research applications while maintaining experimental rigor.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">LB Paulik</style></author><author><style face="normal" font="default" size="100%">Carey E Donald</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Lane G Tidwell</style></author><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Laurel D Kincl</style></author><author><style face="normal" font="default" size="100%">Erin N Haynes</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of natural gas extraction on PAH levels in ambient air.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Sci. Technol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">5203-5210</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Natural gas extraction, often referred to as &quot;fracking,&quot; has increased rapidly in the U.S. in recent years. To address potential health impacts, passive air samplers were deployed in a rural community heavily affected by the natural gas boom. Samplers were analyzed for 62 polycyclic aromatic hydrocarbons (PAHs). Results were grouped based on distance from each sampler to the nearest active well. PAH levels were highest when samplers were closest to active wells. Additionally, PAH levels closest to natural gas activity were an order of magnitude higher than levels previously reported in rural areas. Sourcing ratios indicate that PAHs were predominantly petrogenic, suggesting that elevated PAH levels were influenced by direct releases from the earth. Quantitative human health risk assessment estimated the excess lifetime cancer risks associated with exposure to the measured PAHs. Closest to active wells, the risk estimated for maximum residential exposure was 2.9 in 10,000, which is above the U.S. EPA&#039;s acceptable risk level. Overall, risk estimates decreased 30% when comparing results from samplers closest to active wells to those farthest. This work suggests that natural gas extraction may be contributing significantly to PAHs in air, at levels that are relevant to human health.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lane G Tidwell</style></author><author><style face="normal" font="default" size="100%">Sarah E Allan</style></author><author><style face="normal" font="default" size="100%">Steven G O&#039;Connell</style></author><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Polycyclic Aromatic Hydrocarbon (PAH) and Oxygenated PAH (OPAH) Air-Water Exchange during the Deepwater Horizon Oil Spill.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Sci. Technol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1/2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">141-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Passive sampling devices were used to measure air vapor and water dissolved phase concentrations of 33 polycyclic aromatic hydrocarbons (PAHs) and 22 oxygenated PAHs (OPAHs) at four Gulf of Mexico coastal sites prior to, during, and after shoreline oiling from the Deepwater Horizon oil spill (DWH). Measurements were taken at each site over a 13 month period, and flux across the water-air boundary was determined. This is the first report of vapor phase and flux of both PAHs and OPAHs during the DWH. Vapor phase sum PAH and OPAH concentrations ranged between 1 and 24 ng/m(3) and 0.3 and 27 ng/m(3), respectively. PAH and OPAH concentrations in air exhibited different spatial and temporal trends than in water, and air-water flux of 13 individual PAHs were strongly associated with the DWH incident. The largest PAH volatilizations occurred at the sites in Alabama and Mississippi in the summer, each nominally 10 000 ng/m(2)/day. Acenaphthene was the PAH with the highest observed volatilization rate of 6800 ng/m(2)/day in September 2010. This work represents additional evidence of the DWH incident contributing to air contamination, and provides one of the first quantitative air-water chemical flux determinations with passive sampling technology.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Norman D Forsberg</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Gregory J Sower</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting polycyclic aromatic hydrocarbon concentrations in resident aquatic organisms using passive samplers and partial least-squares calibration.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Sci. Technol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">6/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">6291-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The current work sought to develop predictive models between time-weighted average polycyclic aromatic hydrocarbon (PAH) concentrations in the freely dissolved phase and those present in resident aquatic organisms. We deployed semipermeable membrane passive sampling devices (SPMDs) and collected resident crayfish (Pacifastacus leniusculus) at nine locations within and outside of the Portland Harbor Superfund Mega-site in Portland, OR. Study results show that crayfish and aqueous phase samples collected within the Mega-site had PAH profiles enriched in high molecular weight PAHs and that freely dissolved PAH profiles tended to be more populated by low molecular weight PAHs compared to crayfish tissues. Results also show that of several modeling approaches, a two-factor partial least-squares (PLS) calibration model using detection limit substitution provided the best predictive power for estimating PAH concentrations in crayfish, where the model explained ≥72% of the variation in the data set and provided predictions within ∼3× of measured values. Importantly, PLS calibration provided a means to estimate PAH concentrations in tissues when concentrations were below detection in the freely dissolved phase. The impact of measurements below detection limits is discussed.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sarah E Allan</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Robyn L Tanguay</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bridging environmental mixtures and toxic effects.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Toxicol Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Toxicol. Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biological Assay</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Hydrocarbons, Aromatic</style></keyword><keyword><style  face="normal" font="default" size="100%">Rivers</style></keyword><keyword><style  face="normal" font="default" size="100%">Water Pollutants, Chemical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2012</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">2877-87</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Biological Response Indicator Devices Gauging Environmental Stressors (BRIDGES) is a bioanalytical tool that combines passive sampling with the embryonic zebrafish developmental toxicity bioassay to provide a quantitative measure of the toxicity of bioavailable complex mixtures. Passive sampling devices (PSDs), which sequester and concentrate bioavailable organic contaminants from the environment, were deployed in the Willamette and Columbia Rivers within and outside of the Portland Harbor Superfund site in Portland, OR, USA. Six sampling events were conducted in the summer and fall of 2009 and 2010. Passive sampling device extracts were analyzed for polycyclic aromatic hydrocarbon (PAH) compounds and screened for 1,201 chemicals of concern using deconvolution-reporting software. The developmental toxicity of the extracts was analyzed using the embryonic zebrafish bioassay. The BRIDGES tool provided site-specific, temporally resolved information about environmental contaminant mixtures and their toxicity. Multivariate modeling approaches were applied to paired chemical and toxic effects data sets to help unravel chemistry-toxicity associations. Modeling elucidated spatial and temporal trends in PAH concentrations and the toxicity of the samples and identified a subset of PAH analytes that were the most highly correlated with observed toxicity. Although the present study highlights the complexity of discerning specific bioactive compounds in complex mixtures, it demonstrates methods for associating toxic effects with chemical characteristics of environmental samples.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/23001962?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sarah E Allan</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of the deepwater horizon oil spill on bioavailable polycyclic aromatic hydrocarbons in Gulf of Mexico coastal waters.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Sci Technol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Sci. Technol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Gulf of Mexico</style></keyword><keyword><style  face="normal" font="default" size="100%">Petroleum Pollution</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Hydrocarbons, Aromatic</style></keyword><keyword><style  face="normal" font="default" size="100%">Water Pollutants, Chemical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2012</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">46</style></volume><pages><style face="normal" font="default" size="100%">2033-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;An estimated 4.1 million barrels of oil and 2.1 million gallons of dispersants were released into the Gulf of Mexico during the Deepwater Horizon oil spill. There is a continued need for information about the impacts and long-term effects of the disaster on the Gulf of Mexico. The objectives of this study were to assess bioavailable polycyclic aromatic hydrocarbons (PAHs) in the coastal waters of four Gulf Coast states that were impacted by the spill. For over a year, beginning in May 2010, passive sampling devices were used to monitor the bioavailable concentration of PAHs. Prior to shoreline oiling, baseline data were obtained at all the study sites, allowing for direct before and after comparisons of PAH contamination. Significant increases in bioavailable PAHs were seen following the oil spill, however, preoiling levels were observed at all sites by March 2011. A return to elevated PAH concentrations, accompanied by a chemical fingerprint similar to that observed while the site was being impacted by the spill, was observed in Alabama in summer 2011. Chemical forensic modeling demonstrated that elevated PAH concentrations are associated with distinctive chemical profiles.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/22321043?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Chemical profiling with modeling differentiates wild and farm-raised salmon.</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Agric. Food Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Fisheries</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Principal Component Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Salmon</style></keyword><keyword><style  face="normal" font="default" size="100%">Seafood</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">11768-74</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Classifications of fish production methods, wild or farm-raised salmon, by elemental profiles or C and N stable isotope ratios combined with various modeling approaches were determined. Elemental analysis (As, Ba, Be, Ca, Co, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, and Zn) of wild and farm-raised salmon samples was performed using an inductively coupled plasma atomic emission spectroscopy. Isotopic and compositional analyses of carbon and nitrogen were performed using mass spectrometry as an alternative fingerprinting technique. Each salmon (king salmon, Oncorhynchus tshawytscha ; coho salmon, Oncorhynchus kisutch ; Atlantic salmon, Salmo salar ) was analyzed from two food production practices, wild and farm raised. Principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for data exploration and visualization. Five classification modeling approaches were investigated: linear discriminate function, quadratic discriminant function, neural network, probabilistic neural network, and neural network bagging. Methods for evaluating model reliability included four strategies: resubstitution, cross-validation, and two very different test set scenarios. Generally speaking, the models performed well, with the percentage of samples classified correctly depending on the particular choice of model and evaluation method used.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">22</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/20973481?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Seasonal and Variety Effects on Stable Isotope Profiling to Determine Geographic Growing Origin of Pistachios</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Agric. Food Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Carbon Isotopes</style></keyword><keyword><style  face="normal" font="default" size="100%">Iran</style></keyword><keyword><style  face="normal" font="default" size="100%">Isotopes</style></keyword><keyword><style  face="normal" font="default" size="100%">Nitrogen Isotopes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pistacia</style></keyword><keyword><style  face="normal" font="default" size="100%">Seasons</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Turkey</style></keyword><keyword><style  face="normal" font="default" size="100%">United States</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2006</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">54</style></volume><pages><style face="normal" font="default" size="100%">1747-52</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The objectives of this study were to demonstrate if seasonal or variety differences affected the feasibility of stable isotope profiling methods to differentiate the geographical growing regions of pistachios (Pistachia vera). Bulk carbon and nitrogen isotope analyses of approximately 150 pistachios samples were performed. Isotope ratios were determined using a stable isotope mass spectrometer. The pistachio samples analyzed were from the three major pistachio-growing regions: Turkey, Iran, and the United States (California). Geographic regions were well separated on the basis of isotope ratios. Seasonal effects were found to affect some isotopes for some regions. Pistachio varieties within specified geographic regions were not found to affect the discriminating power of stable isotopes, for the varieties tested. This paper reports the development of a simple chemical profiling method using bulk stable isotope ratios that may be widely applied to the determination of the geographic origin of foods.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/16506828?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Perez, Angela L</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Stable isotope and trace element profiling combined with classification models to differentiate geographic growing origin for three fruits: effects of subregion and variety.</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Agric. Food Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Argentina</style></keyword><keyword><style  face="normal" font="default" size="100%">Blueberry Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Chile</style></keyword><keyword><style  face="normal" font="default" size="100%">Environment</style></keyword><keyword><style  face="normal" font="default" size="100%">Fragaria</style></keyword><keyword><style  face="normal" font="default" size="100%">Fruit</style></keyword><keyword><style  face="normal" font="default" size="100%">Isotopes</style></keyword><keyword><style  face="normal" font="default" size="100%">Mexico</style></keyword><keyword><style  face="normal" font="default" size="100%">Oregon</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyrus</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2006</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">54</style></volume><pages><style face="normal" font="default" size="100%">4506-16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Classifications of geographic growing origin of three fresh fruits combining elemental profiles with various modeling approaches were determined. Elemental analysis (Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, V, and Zn) of strawberry, blueberry, and pear samples was performed using inductively coupled plasma argon atomic emission spectrometer. Bulk stable carbon and nitrogen isotope analyses in pear were performed using mass spectrometry as an alternative fingerprinting technique. Each fruit, strawberry (Fragaria x ananassa), blueberry (Vaccinium caesariense/corymbosum), and pear (Pyrus communis), was analyzed from two growing regions: Oregon vs Mexico, Chile, and Argentina, respectively. Principal component analysis and canonical discriminant analysis were used for data visualization. The data were modeled using linear discriminant function, quadratic discriminant function, neural network, genetic neural network, and hierarchical tree models with successful classification ranging from 70 to 100% depending on commodity and model. Effects of Oregon subregional and variety classification were investigated with similar success rates.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">13</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/16786991?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Chemical Profiling to Differentiate Geographic Origin of Pistachios</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Agric. Food Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Analysis of Variance</style></keyword><keyword><style  face="normal" font="default" size="100%">California</style></keyword><keyword><style  face="normal" font="default" size="100%">Iran</style></keyword><keyword><style  face="normal" font="default" size="100%">Metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Pistacia</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectrophotometry, Atomic</style></keyword><keyword><style  face="normal" font="default" size="100%">Turkey</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2005</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">53</style></volume><pages><style face="normal" font="default" size="100%">410-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The objective of this study was to demonstrate the feasibility of chemical profiling methods combined with multivariate methods to differentiate the geographical growing regions of pistachios (Pistachia vera). Elemental analysis (Ba, Be, Ca, Cu, Cr, K, Mg, Mn, Na, V, Fe, Co, Ni, Cu, Zn, Sr, Ti, Cd, and P) of pistachios samples was performed using inductively coupled plasma atomic emission spectrometry. Analysis of inorganic anions and organic acids (selenite, bromate, fumarate, malate, selenate, pyruvate, acetate, phosphate, and ascorbate) of pistachio samples was performed using capillary electrophoresis. Bulk carbon and nitrogen isotope ratios were performed using stable isotope MS. There were nearly 400 pistachio samples analyzed from the three major pistachio growing regions: Turkey, Iran, and California (United States). A computational evaluation of the trace element data sets was carried out using statistical pattern recognition methods including principal component analysis, canonical discriminant analysis, discriminant analysis, and neural network modeling. Several linear discriminant function models classified the data sets with 95% or higher accuracy. We report the development of a method combining elemental analysis and classification techniques that may be widely applied to the determination of the geographical origin of foods.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15656681?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Chemical Profiling to Differentiating Geographic Growing Origin of Coffee</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Agric. Food Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Africa, Eastern</style></keyword><keyword><style  face="normal" font="default" size="100%">Central America</style></keyword><keyword><style  face="normal" font="default" size="100%">Coffee</style></keyword><keyword><style  face="normal" font="default" size="100%">Discriminant Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Indonesia</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Networks (Computer)</style></keyword><keyword><style  face="normal" font="default" size="100%">South America</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectrum Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2002</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">2068-75</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The objective of this research was to demonstrate the feasibility of this method to differentiate the geographical growing regions of coffee beans. Elemental analysis (K, Mg, Ca, Na, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, S, Cd, Pb, and P) of coffee bean samples was performed using ICPAES. There were 160 coffee samples analyzed from the three major coffee-growing regions: Indonesia, East Africa, and Central/South America. A computational evaluation of the data sets was carried out using statistical pattern recognition methods including principal component analysis, discriminant function analysis, and neural network modeling. This paper reports the development of a method combining elemental analysis and classification techniques that may be widely applied to the determination of the geographical origin of foods.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/11902958?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fingerprinting the Potato</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/1998</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">281</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">511</style></section></record></records></xml>