Metal concentrations in used engine oils: Relevance to site assessments of soils

Used engine oils contain metals, which upon entering soils may pose risks to human health or the environment. In this study, previously published concentrations of 23 metals in 213 used engine oil samples from the early 1970s to the mid-1990s are statistically evaluated. Neat (100%) used engine oils were found to contain relatively high concentrations of lead, calcium, and zinc, attributable to piston blow-by of leaded gasoline, calcium salt detergent additives, and zinc-bearing anti-corrosion/anti-oxidation additives, respectively. Wear metal concentrations were lower. The lead concentration in used engine oils in the U.S. declined between the 1970s and early 1990s, potentially providing a basis to constrain the “age” of used engine oil(s) in soils. The concentrations of 23 metals in used engine oils were compared to soil risk benchmarks in 15 representative jurisdictions in the U.S., Canada, Australia, and Europe. The maximum concentrations in neat (100%) used engine oil of eight metals – Be, Co, Fe, Mn, Ni, Se, Ag, and Ti – were lower than their collective minimum benchmarks in soils for the jurisdictions surveyed, indicating their concentrations in soils could not be reasonably expected to exceed any soil benchmarks. Nine metals (As, Ba, Cd, Cr, Cu, Pb, Sn, V and Zn), but particularly arsenic, cadmium, lead, tin, and zinc, were identified as potential contaminants of concern (PCOC) for soils from locations impacted with used engine oils, owing to their higher median concentrations (i.e., 2.5, 1.4, 1038, 5.0, and 922 mg/kg in oil, respectively) relative to most soil benchmarks. Site-specific benchmarks and metal concentrations at reasonable oil in soil concentrations require consideration when developing the suite of PCOC metal analytes for conducting site assessments of soils impacted by used engine oil.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

Taxing Meat: Taking Responsibility for One’s Contribution to Antibiotic Resistance

Antibiotic use in animal farming is one of the main drivers of antibiotic resistance both in animals and in humans. In this paper we propose that one feasible and fair way to address this problem is to tax animal products obtained with the use of antibiotics. We argue that such tax is supported both by (a) deontological arguments, which are based on the duty individuals have to compensate society for the antibiotic resistance to which they are contributing through consumption of animal products obtained with the use of antibiotics; and (b) a cost-benefit analysis of taxing such animal products and of using revenue from the tax to fund alternatives to use of antibiotics in animal farming. Finally, we argue that such a tax would be fair because individuals who consume animal products obtained with the use of antibiotics can be held morally responsible, i.e. blameworthy, for their contribution to antibiotic resistance, in spite of the fact that each individual contribution is imperceptible.     

Multispecies remote sensing measurements of vehicle emissions on Sherman Way in Van Nuys,California

As part of the 2010 Van Nuys tunnel study, researchers from the University of Denver measured on-road fuel-specific light-duty vehicle emissions from nearly 13,000 vehicles on Sherman Way (0.4 miles west of the tunnel) in Van Nuys, California, with its multispecies Fuel Efficiency Automobile Test (FEAT) remote sensor a week ahead of the tunnel measurements. The remote sensing mean gram per kilogram carbon monoxide (CO), hydrocarbon (HC), and oxide of nitrogen (NO_x) measurements are 8.9% lower, 41% higher, and 24% higher than the tunnel measurements, respectively. The remote sensing CO/NO_x and HC/NO_x mass ratios are 28% lower and 20% higher than the comparable tunnel ratios. Comparisons with the historical tunnel measurements show large reductions in CO, HC, and NO_x over the past 23 yr, but little change in the HC/NO_x mass ratio since 1995. The fleet CO and HC emissions are increasingly dominated by a few gross emitters, with more than a third of the total emissions being contributed by less than 1% of the fleet. An example of this is a 1995 vehicle measured three times with an average HC emission of 419 g/kg fuel (two-stroke snowmobiles average 475 g/kg fuel), responsible for 4% of the total HC emissions. The 2008 economic downturn dramatically reduced the number of new vehicles entering the fleet, leading to an age increase (>1 model year) of the Sherman Way fleet that has increased the fleet's ammonia (NH₃) emissions. The mean NH₃ levels appear little changed from previous measurements collected in the Van Nuys tunnel in 1993. Comparisons between weekday and weekend data show few fleet differences, although the fraction of light-duty diesel vehicles decreased from the weekday (1.7%) to Saturday (1.2%) and Sunday (0.6%).

Implications: On-road remote sensing emission measurements of light-duty vehicles on Sherman Way in Van Nuys, California, show large historical emission reductions for CO and HC emissions despite an older fleet arising from the 2008 economic downturn. Fleet CO and HC emissions are increasingly dominated by a few gross emitters, with a single 1995 vehicle measured being responsible for 4% of the entire fleet's HC emissions. Finding and repairing and/or scrapping as little as 2% of the fleet would reduce on-road tailpipe emissions by as much as 50%. Ammonia emissions have locally increased with the increasing fleet age.     

Black Carbon Aerosol at McMurdo Station,Antarctica

ABSTRACT

Aerosol light absorption as black carbon (BC) was measured from November 19, 1995, to February 6, 1996, at a location 0.65 km downwind of the center of McMurdo Station on the Antarctic coast. The results show a bimo-dal frequency distribution of BC concentrations. Approximately 65% of the measurements were found in a mode at a low range of concentrations centered at ~20 ng/m³. These concentrations are higher than those found at other remote Antarctic locations and probably represent contamination from the station. The remaining measurements were in a high-concentration mode (BC ~300 ng/m³), indicating direct impact of local emissions from combustion activities at the station. High values of BC were associated with winds from the direction of the station, and the BC flux showed a clear directionality. Maximum BC concentrations occurred between 7:00 and 11:00 a.m. The "polluted" mode accounted for more than 80% of the BC frequency-weighted impact at this location.     

Coastal flooding,climate change and environmental justice: identifying obstacles and incentives for adaptation in two metropolitan Boston Massachusetts communities

We explored the possible future impacts of increased coastal flooding due to sea level rise and the potential adaptation responses of two urban, environmental justice communities in the metropolitan Boston area of Massachusetts. East Boston is predominantly a residential area with some industrial and commercial activities, particularly along the coastal fringe. Everett, a city to the north of Boston, has a diversified industrial and commercial base. While these two communities have similar socioeconomic characteristics, they differ substantially in the extent to which residents would be impacted by increased coastal flooding. In East Boston, a large portion of residents would be flooded, while in Everett, it is the commercial/industrial districts that are primarily vulnerable. Through a series of workshops with residents in each community, we found that the target populations do not have an adaptation perspective or knowledge of any resources that could assist them in this challenge. Furthermore, they do not feel included in the planning processes within their communities. However, a common incentive for both communities was an intense commitment to their communities and an eagerness to learn more and become actively engaged in decisions regarding climate change adaptation. The lessons that can be applied to other studies include 1) images are powerful tools in communicating concepts, 2) understanding existing cultural knowledge and values in adaptation planning is essential to the planning process and 3) engaging local residents at the beginning of the process can create important educational opportunities and develop trust and consensus that is necessary for moving from concept to implementation.     

Exploring the role of emotional intelligence in behavior-based safety coaching

INTRODUCTION: Safety coaching is an applied behavior analysis technique that involves interpersonal interaction to understand and manipulate environmental conditions that are directing (i.e., antecedent to) and motivating (i.e., consequences of) safety-related behavior. A safety coach must be skilled in interacting with others so as to understand their perspectives, communicate a point clearly, and be persuasive with behavior-based feedback. METHOD: This article discusses the evidence-based "ability model" of emotional intelligence and its relevance to the interpersonal aspect of the safety coaching process. RESULTS: Emotional intelligence has potential for improving safety-related efforts and other aspects of individuals' work and personal lives. Safety researchers and practitioners are therefore encouraged to gain an understanding of emotional intelligence and conduct and support research applying this construct toward injury prevention.     

Light Scattering from Sea-Salt Aerosols at Interagency Monitoring of Protected Visual Environments (IMPROVE) Sites

Abstract

A method is described to estimate light scattering (Bsp) by sea-salt aerosols at coastal locations in the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. Dry mass scattering efficiencies for fine and coarse sea-salt particles were based on previously measured dry sea-salt size distributions. Enhancement of sea-salt particle scattering by hygroscopic growth was based on NaCl water activity data. Sea-salt aerosol mass at the IMPROVE site in the Virgin Islands (VIIS) was estimated from strontium (Sr) concentrations in IMPROVE aerosol samples. Estimated Bsp, including contributions from sea-salt mass based on Sr, agreed well with measured Bsp at the VIIS IMPROVE site. On average, sea salt accounted for 52% of estimated Bsp at this site. Sea-salt aerosol mass cannot be reliably estimated from Sr unless its crustal enrichment factor exceeds 10. Sodium (Na) concentrations are not accurately determined by X-ray fluorescence analysis in IMPROVE samples. It is recommended that Na be measured in the fine and coarse modes by a more appropriate method, such as atomic absorption spectroscopy or ion chromatography, to account for scattering by sea-salt particles at IMPROVE sites where such contributions may be significant.