Rationale for assessment of risk from exposure to 2,3,7,8-TCDD

The human health risk assessment is supported by methodology for utilizing toxic effects in animals consisting of carcinogenic and noncarcinogenic responses as a result of chronic, subchronic and acute exposures. One of the initial steps in a risk assessment activity involves the estimation of exposure levels. These estimates are typically based on either direct environmental measurements or predictions obtained from fate and transport models. The decision to develop assessment of risk from chronic exposure based on a nonthreshold model is made if a chemical demonstrates carcinogenic activity in animal bioassays and/or in human epidemiological studies. In the absence of any positive human epidemiologic data, it is assumed that a substance which induces a statistically significant carcinogenic response in animals has the probability to cause cancer in humans. The carcinogenic potential of 2,3,7,8-TCDD has been established based on chronic exposure in rodents. In addition, 2,3,7,8-TCDD has also been shown to be a liver cancer promoter in rodents. In the risk assessment on dioxins based on chronic exposure in experimental animals, 2,3,7,8-TCDD is regarded as a carcinogenic substance. Carcinogenic data from animal bioassays are utilized for the assessment of risk for the purpose of estimating the likelihood of 2,3,7,8-TCDD being carcinogenic for humans and to determine the magnitude of the potential impact on public health.     

Particulate matter,nitrogen oxides,ozone, and select volatile organic compounds during a winter sampling period in Logan,Utah, USA

Particulate matter mass (PM), trace gaseous pollutants, and select volatile organic compounds (VOCs) with meteorological variables were measured in Logan, Utah (Cache Valley), for >4 weeks during winter 2017 as part of the Utah Winter Fine Particle Study (UWFPS). Higher PM levels for short time periods and lower ozone (O₃) levels were present due to meteorological and mountain valley conditions. Nitrogenous pollutants were relatively strongly correlated with PM variables. Diurnal cycles of NO_x, O₃, and fine PM(PM 2.5) (aerodynamic diameter <2.5 μm [PM_2.5]) suggested formation from NO_x. O₃ levels increased from early morning into midafternoon, and NO_x and PM_2.5 increased throughout the morning, followed by sharp decreases. Toluene/benzene and xylenes/benzene ratios and VOC correlations with nitrogenous and PM species were indicative of local traffic sources. Wind sector comparisons suggested that pollutant levels were lower when winds were from nearby mountains to the east versus winds from northerly or southerly origins.

Implications: The Cache Valley in Idaho and Utah has been designated a PM_2.5 nonattainment area that has been attributed to air pollution buildup during winter stagnation events. To inform state implementation plans for PM_2.5 in Cache Valley and other PM_2.5 nonattainment areas in Utah, a state and multiagency federal research effort known as the UWFPS was conducted in winter 2017. As part of the UWFPS, the U.S. Environmental Protection Agency (EPA) measured ground-based PM species and their precursors, VOCs, and meteorology in Logan, Utah. Results reported here from the EPA study in Logan provide additional understanding of wintertime air pollution conditions and possible sources of PM and gaseous pollutants as well as being useful for future PM control strategies in this area.     

Field method comparison between passive air samplers and continuous monitors for Vocs and NO2 in El Paso, Texas

This study evaluates the performance of Model 3300 Ogawa Passive Nitrogen Dioxide (NO2) Samplers and 3M 3520 Organic Vapor Monitors (OVMs) by comparing integrated passive sampling concentrations to averaged hourly NO2 and volatile organic compound (VOC) measurements at two sites in El Paso, TX. Sampling periods were three time intervals (3-day weekend, 4-day weekday, and 7-day weekly) for three consecutive weeks. OVM concentrations were corrected for ambient pressure to account for higher elevation. Precise results (< 5% relative standard deviation, RSD) were found for NO2 measurements from collocated Ogawa samplers. Reproducibility was lower from duplicate OVMs for BTEX (benzene, toluene, ethylbenzene, and xylene isomers) VOCs (> or = 77% RSD for 2-day samples) with better precision for longer sampling periods. Comparison of Ogawa NO2 samplers with chemiluminescence measurements averaged over the same time period suggested potential calibration problems with the chemiluminescence analyzer. For BTEX species, generally good agreement was obtained between OVMs and automated-gas chromatograph (auto-GC) measurements. The OVMs successfully tracked increasing levels of VOCs recorded by the auto-GCs. However, except for toluene, OVM BTEX measurements generally exceeded their continuous counterparts with a mean bias of 5-10%. Although interpretation of the study results was limited due to small sample sizes, diffusion barrier influences caused by shelters that housed OVMs and differences in sampling heights between OVMs and auto-GC inlet may explain the overestimation.     

South Philadelphia passive sampler and sensor study

From June 2013 to March 2015, in total 41 passive sampler deployments of 2 wk duration each were conducted at 17 sites in South Philadelphia, PA, with results for benzene discussed here. Complementary time-resolved measurements with lower cost prototype fenceline sensors and an open-path ultraviolet differential optical absorption spectrometer were also conducted. Minimum passive sampler benzene concentrations for each sampling period ranged from 0.08 ppbv to 0.65 ppbv, with a mean of 0.25 ppbv, and were negatively correlated with ambient temperature (–0.01 ppbv/°C, R² = 0.68). Co-deployed duplicate passive sampler pairs (N = 609) demonstrated good precision with an average and maximum percent difference of 1.5% and 34%, respectively. A group of passive samplers located within 50 m of a refinery fenceline had a study mean benzene concentration of 1.22 ppbv, whereas a group of samplers located in communities >1 km distant from facilities had a mean of 0.29 ppbv. The difference in the means of these groups was statistically significant at the 95% confidence level (p < 0.001). A decreasing gradient in benzene concentrations moving away from the facilities was observed, as was a significant period-to-period variation. The highest recorded 2-wk average benzene concentration for the fenceline group was 3.11 ppbv. During this period, time-resolved data from the prototype sensors and the open-path spectrometer detected a benzene signal from the west on one day in particular, with the highest 5-min path-averaged benzene concentration measured at 24 ppbv.

Implications: Using a variation of EPA’s passive sampler refinery fenceline monitoring method, coupled with time-resolved measurements, a multiyear study in South Philadelphia informed benzene concentrations near facilities and in communities. The combination of measurement strategies can assist facilities in identification and mitigation of emissions from fugitive sources and improve information on air quality complex air sheds.     

Triethylamine induced photolysis of endosulphan

Photolysis of pure isomers of endosulphan in the presence of triethylamine gives products arising by the loss of a chlorine atom from the geminal bridge. The structures of these products have been established. The α‐isomer of endosulphan isomerised to ß‐isomer on a leaf surface.     

Field Method Comparison between Passive Air Samplers and Continuous Monitors for VOCs and NO2 in El Paso,Texas

Abstract

This study evaluates the performance of Model 3300 Ogawa Passive Nitrogen Dioxide (NO₂) Samplers and 3M 3520 Organic Vapor Monitors (OVMs) by comparing integrated passive sampling concentrations to averaged hourly NO₂ and volatile organic compound (VOC) measurements at two sites in El Paso, TX. Sampling periods were three time intervals (3-day weekend, 4-day weekday, and 7-day weekly) for three consecutive weeks. OVM concentrations were corrected for ambient pressure to account for higher elevation. Precise results (<5% relative standard deviation, RSD) were found for NO₂ measurements from collocated Ogawa samplers. Reproducibility was lower from duplicate OVMs for BTEX (benzene, toluene, ethylbenzene, and xylene isomers) VOCs (≥7% RSD for 2-day samples) with better precision for longer sampling periods. Comparison of Ogawa NO₂ samplers with chemiluminescence measurements averaged over the same time period suggested potential calibration problems with the chemiluminescence analyzer. For BTEX species, generally good agreement was obtained between OVMs and automated-gas chromatograph (auto-GC) measurements. The OVMs successfully tracked increasing levels of VOCs recorded by the auto-GCs.     

Evaluation of land-use regression models used to predict air quality concentrations in an urban area

Cohort studies designed to estimate human health effects of exposures to urban pollutants require accurate determination of ambient concentrations in order to minimize exposure misclassification errors. However, it is often difficult to collect concentration information at each study subject location. In the absence of complete subject-specific measurements, land-use regression (LUR) models have frequently been used for estimating individual levels of exposures to ambient air pollution. The LUR models, however, have several limitations mainly dealing with extensive monitoring data needs and challenges involved in their broader applicability to other locations. In contrast, air quality models can provide high-resolution source–concentration linkages for multiple pollutants, but require detailed emissions and meteorological information. In this study, first we predicted air quality concentrations of PM_2.5, NO_x, and benzene in New Haven, CT using hybrid modeling techniques based on CMAQ and AERMOD model results. Next, we used these values as pseudo-observations to develop and evaluate the different LUR models built using alternative numbers of (training) sites (ranging from 25 to 285 locations out of the total 318 receptors). We then evaluated the fitted LUR models using various approaches, including: 1) internal “Leave-One-Out-Cross-Validation” (LOOCV) procedure within the “training” sites selected; and 2) “Hold-Out” evaluation procedure, where we set aside 33–293 tests sites as independent datasets for external model evaluation. LUR models appeared to perform well in the training datasets. However, when these LUR models were tested against independent hold out (test) datasets, their performance diminished considerably. Our results confirm the challenges facing the LUR community in attempting to fit empirical response surfaces to spatially- and temporally-varying pollution levels using LUR techniques that are site dependent. These results also illustrate the potential benefits of enhancing basic LUR models by utilizing air quality modeling tools or concepts in order to improve their reliability or transferability.