Modeling Evidence of Incloud Transformation Of Sulfur Dioxide to Sulfate

Methylene chloride (CH₂Cl₂) is presently under study by the U.S. EPA and other agencies to determine if the compound presents an unreasonable risk to human health and to determine if regulatory action is needed to reduce the risk. This paper describes one portion of the study which required the development and validation of a method of sampling and analysis for source emission measurements.

Prior to source sampling, laboratory experiments were conducted to determine the best sample container in which to collect an integrated sample. It was found that CH₂Cl₂ remained stable in Tedlar bags for at least four weeks. The analytical method selected was gas chromatography with flame ionization detection (GC/FID). During the field portion of the study, both manufacturer and user emission sources of CH₂Cl₂ were tested. Multiple sets of simultaneous quadruplicate bag samples were collected to determine the precision of both sampling and analysis in the field. All samples were analyzed at the test site after collection and then returned to Research Triangle Park. Samples were subsequently reanalyzed in the laboratories of Radian and the U.S. EPA using three GC/FID instruments and two types of GC columns. The range of concentrations from the sources was 100 ppm to 27,000 ppm CH₂Cl₂. A statistical analysis of samples collected simultaneously showed no difference in the samples, proving good precision In both sampling and analysis. Some of the sample bags returned from the test sites developed leaks indicating that immediate on-site analysis is best. A comparison of results obtained in the field and the two laboratories showed that interand intra-laboratory precision was within 10 percent.     

Emission Factors for High-Emitting Vehicles Based on On-Road Measurements of Individual Vehicle Exhaust with a Mobile Measurement Platform

ABSTRACT

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO_x), and particle mass with aerodynamic diameter below 2.5 μm (PM_2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO_x, black carbon (BC), PM_2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO_x and CO fleet-average emission factors and more than 60% of PM_2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM_2.5, and NO_x tended to cluster among the same vehicles.

IMPLICATIONS This study presents the characterization of on-road vehicle emissions in Wilmington, CA, by sampling individual vehicle plumes. Approximately 5% of the vehicles were high emitters, whose emissions were more than 5 times the fleet-average values. These high emitters were responsible for 30% and more than 50% of the average emission factors of LDGVs and HDDVs, respectively. It is likely that as the overall fleet becomes cleaner due to more stringent regulations, a small fraction of the fleet may contribute a growing and disproportionate share of the overall emissions. Therefore, long-term changes in on-road emissions need to be monitored.     

A Strategy and Methodology for Defensibly Correlating Spilled Oil to Source Candidates

The source of crude oils and petroleum products released into navigable waterways and shipping lanes is not always known. Thus, the defensible identification of spilled crude oils and petroleum products and their correlation to suspected sources is a critical part of many oil spill assessments. Quantitative "fingerprinting" analysis, when evaluated using straightforward statistical and numerical analyses, provides a defensible means to differentiate among qualitatively similar oils and provides the best assessment of the source(s) for spilled oils. Polycyclic aromatic hydrocarbon (PAH) and petroleum biomarker concentration data are a particularly useful quantitative measure that can benefit most oil spill investigations. In this paper the strategy and methodology for correlation analysis that relies upon quantitative gas chromatography/mass spectrometry operated in the selected ion monitoring mode (GC/MS-SIM) is demonstrated in a case study involving 66 candidate sources for a heavy fuel oil spill of unknown origin. The strategy includes identification of 19 chemical indices (out of 45 evaluated) based upon PAH's and biomarkers that were (1) independent of weathering; and (2) precisely measured, both of which are determined by statistical analysis of the data. The 19 chemical indices meeting these criteria are subsequently analysed using principal component analysis (PCA), which helps to determine defensibly the "prime suspects" for the oil spill under investigation. The strategy and methodology described, which combines statistical and numerical analysis of quantitative chemical data, can be adapted and applied to other environmental forensic investigations with the objective of correlating any form of contamination to its suspected sources.     

Nationwide risk factors for hospital readmission for subsequent injury after motor vehicle crashes

Abstract

Objective: Some drivers involved in motor vehicle crashes across the United States may be identified as at risk of subsequent injury by a similar mechanism. The purpose of this study was to perform a national review of the risk factors for hospitalization for a new injury due to a subsequent motor vehicle crash. It was hypothesized that presenting to a different hospital after subsequent injury would result in worse patient outcomes when compared to presentation at the same hospital.

Methods: The Nationwide Readmissions Database for 2010–2014 was queried for all inpatient hospitalizations with injury related to motor vehicle traffic. The primary patient outcome of interest was subsequent motor vehicle crash–related injury within 1 year. The secondary patient outcomes were different hospital subsequent injury presentation, higher Injury Severity Score (ISS), longer length of stay (LOS), and in-hospital death after subsequent injury. The analysis of secondary patient outcomes was performed only on patients who were reinjured. Univariable analysis was performed for each outcome using all variables during the index admission. Multivariable logistic regression was performed using all significant (P < .05) variables on univariate analysis. Results were weighted for national estimates.

Results: During the study period, 1,008,991 patients were admitted for motor vehicle–related injury; 12,474 patients (1.2%) suffered a subsequent injury within 1 year. From the reinjured patients, 32.9% presented to a different hospital, 48.9% had a higher ISS, and 22.1% had a longer LOS. The in-hospital mortality rate after subsequent injury was 1.1%. Presentation to a different hospital for subsequent injury was associated with a longer LOS (odds ratio [OR]?=?1.32; 95% confidence interval [CI], 1.20–1.45; P < .01) and a higher ISS (OR?=?1.38; 95% CI, 1.27–1.49; P < .01). Motorcyclists were more likely to suffer subsequent injury (OR?=?1.39; 95% CI, 1.32–1.46; P < .01) and motorcycle passengers were more likely to present to a different hospital with a subsequent injury (OR?=?2.49; 95% CI, 1.73–3.59; P < .01). Alcohol abuse was associated with subsequent injury (OR?=?1.12; 95% CI, 1.07–1.18; P < .01).

Conclusions: Nearly a third of patients suffering subsequent motor vehicle crash–related injury after an initial motor vehicle crash in the United States present to a different hospital. These patients are more likely to suffer more severe injuries and longer hospitalizations due to their subsequent injury. Future efforts to prevent these injuries must consider the impact of this fragmentation of care and the implications for quality and cost improvements.     

Natal site and offshore swimming influence fitness and long-distance ocean transport in young sea turtles

Although long-distance transport of marine organisms is constrained by numerous oceanic and biological factors, some species have evolved life-histories reliant on such movements. We examine the factors that promote long-distance transport in a transoceanic migrant, young loggerhead sea turtles (Caretta caretta), from the southeastern U.S. Empirical data from near-surface buoys and simulations in two ocean circulation models indicated that passive drifters are often retained for long periods shoreward of oceanic fronts that delineate coastal and offshore waters. Further simulations revealed that offshore swimming aided newly hatched turtles in moving past fronts and increased turtles’ probability of survival, reaching distant foraging grounds, and encountering favorable temperatures. Swimming was most beneficial in regions that were more favorable under scenarios assuming passive drift. These results have broad implications for understanding the movement processes of many marine species, highlighting likely retention of more planktonic species and potential for dispersal in more nektonic species.     

The use of polymerase chain reaction for the identification of sciaenid eggs

Traditionally, sciaenid eggs have been identified based on morphological characteristics such as size, number of oil globules and/or pigmentation patterns. Identification of sciaenid eggs by these procedures is time consuming and often inaccurate due to considerable egg size overlap among species. The utilization of molecular techniques for the identification of economically important species has become a fundamental component in ecological studies involving fish eggs and larvae. This study reports the development of a series of both multiplex and individual polymerase chain reactions to identify the eggs of 11 sciaenid species commonly found in the Gulf of Mexico and estuaries near Port Aransas and Corpus Christi, TX, USA. Following method development, the discriminatory power of the assay was first determined with samples from adult fish collected from Aransas and Corpus Christi Bays, Galveston Bay and the lower Laguna Madre in northern Mexico. Most (97%) of these fishes were correctly identified to the level of species. To demonstrate the applicability of the assay, wild fish eggs were collected and analyzed from the Aransas Pass tidal inlet from September through December 2005. During this period, the eggs of four target species were positively identified which was in keeping with current knowledge regarding the spawning areas and seasons of these sciaenids based on the presence of mature females, eggs and/or larvae. Future use of this method can provide valuable information to better discriminate spawning sites and seasons of these species.     

Modeling the role of macroalgae in a shallow sub-estuary of Narragansett Bay, RI (USA)

Proliferation of macroalgal mats is a frequent consequence of nutrient-driven eutrophication in shallow, photic coastal marine ecosystems. These macroalgae have the potential to significantly modify water quality, plankton productivity, nutrient cycling, and dissolved oxygen dynamics. We developed a model for Ulva lactuca and Gracilaria tikvahiae in Greenwich Bay, RI (USA), a shallow sub-estuary of Narragansett Bay, as part of a larger estuarine ecosystem model. The model predicts the biomass of both species in units of carbon, nitrogen, and phosphorus as a function of primary production, respiration, grazing, decay, and physical exchange, with particular attention to the effects of biomass layering on light attenuation and suppression of metabolic rates. The model successfully reproduced the magnitude and seasonal cycle of area-weighted and peak biomass in Greenwich Bay along with tissue C:N ratios, and highlighted the importance of grazing and inclusion of self-limitation primarily in the form of self-shading to overcome an order of magnitude difference in rates of production and respiration. Inclusion of luxury nutrient uptake demonstrated the importance of internal nutrient storage in fueling production when nutrients are limiting. Macroalgae were predicted to contribute a small fraction of total system primary production and their removal had little effect on predicted water quality. Despite a lack of data for calibration and a fair amount of sensitivity to individual parameter values, which highlights the need for further autecological studies to constrain formulations, the model successfully predicted macroalgal biomass dynamics and their role in ecosystem functioning. Our formulations should be exportable to other temperate systems where macroalgae occur in abundance.     

Feeding ecology and niche segregation in oceanic top predators off eastern Australia

We examined the feeding ecology and niche segregation of the ten most abundant fish species caught by longline operations off eastern Australia between 1992 and 2006. Diets of 3,562 individuals were examined. Hook timer data were collected from a further 328 fish to examine feeding behaviour in relation to depth and time of day. Prey biomass was significantly related to predator species, predator length and year and latitude of capture. Although the fish examined fed on a mix of fish, squid and crustacea, fish dominated the diet of all species except small albacore (Thunnus alalunga) which fed mainly on crustacea and large swordfish (Xiphias gladius) and albacore which fed mainly on squid. Cannibalism was observed in lancetfish (Alepisaurus spp.). Multidimensional scaling identified three species groups based on their diet composition. One group consisted of yellowfin tuna (T. albacares), striped marlin (Tetrapturus audax) and dolphinfish (Coryphaena hippurus); a second group consisted of bigeye tuna (T. obesus), swordfish and albacore; and a third consisted of southern bluefin tuna (T. maccoyii) and blue shark (Prionace glauca). Of note was the separation of mako shark (Isurus oxyrhynchus) and lancetfish from all other predators. Prey length generally increased with increasing predator length although even large predators fed on a wide range of prey lengths including very small prey. Overall, differences in prey type and size, feeding times and depths were noted across the range of species examined to the extent that predators with overlapping prey, either in type or size, fed at different times of the diel period or at different depths. Taken together these data provide evidence for feeding niche segregation across the range of oceanic top predators examined.     

Sensitivity and robustness of Lagrangian coherent structures in coastal water systems

Environmental Fluid Mechanics - In coastal water systems, horizontal chaotic dispersion plays a significant role in the distribution and fate of pollutants. Lagrangian Coherent Structures (LCSs)...