Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

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 microm (PM2.5) 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), PM2.5, 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 PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

Two‐dimensional transport of lactate‐modified nanoscale iron particles in porous media

This study investigates the two‐dimensional transport of nanoscale iron particles (NIP) and lactate‐modified NIP (LMNIP) in homogeneous and heterogeneous porous media under typical pressurized groundwater flow conditions. A two‐dimensional bench‐scale test setup was developed and a series of experiments was conducted simulating homogeneous sand profile and two‐layer profile with two different sands. NIP and LMNIP at a concentration of 4 g/L were prepared in electrolyte simulating groundwater conditions and were injected at the inlet of the test setup under different pressure gradients (0.5. 0.8, 1, and 2 pounds per square inch). During the testing, effluent was collected and its volume and nanoiron concentrations were measured. At the end of the testing, soil cores were obtained at different distances from the inlet and were used to measure nanoiron concentrations and magnetic susceptibility values. Results showed that the transport of NIP and LMNIP was enhanced by increased pressure gradient. LMNIP transport occurred more uniformly as compared to bare NIP. The iron concentrations decreased with distance from the inlet to the outlet and increased from the top to the bottom of the test cell. The data indicate that, as the particles were transported, they underwent aggregation and sedimentation, which resulted in the observed non‐uniform spatial distribution of iron. The NIP and LMNIP transported through the high‐porosity and high‐permeability soil layer in the heterogeneous soil profile, implying that the transport occurred predominantly along the path of least resistance for the flow. Magnetic susceptibility values are found to have good correlation with the iron content in the soil and are helpful to characterize the transport of NIP and LMNIP. Overall, this study shows that the non‐uniform distribution of NIP and LMNIP occurs under two‐dimensional transport conditions and the soil heterogeneities can significantly impact the transport of NIP and LMNIP. The design of field delivery systems should consider such conditions and optimize the pressurized injection systems. © 2011 Wiley Periodicals, Inc.     

Constraining SWAT Calibration with Remotely Sensed Evapotranspiration Data

Historically, many watershed studies have been based on using the streamflow flux, typically from a single gauge at the basin's outlet, to support calibration. In this setting, there is great potential for equifinality of parameters during the optimization process, especially for parameters that are not directly related to streamflow. Therefore, some of the optimal parameter values achieved during the autocalibration process may be physically unrealistic. In recent decades a vast array of data from land surface models and remote sensing platforms can help to constrain hydrologic fluxes such as evapotranspiration (ET). While the spatial resolution of these ancillary datasets varies, the continuous spatial coverage of these gridded datasets provides flux measurements across the entire basin, in stark contrast to point‐based streamflow data. This study uses Global Land Evaporation: the Amsterdam Model data to constrain Soil and Water Assessment Tool parameter values associated with ET to a more physically realistic range. The study area is the Little Washita River Experimental Watershed, in southern Oklahoma. Traditional objective metrics such as the Nash‐Sutcliffe coefficients record no performance improvement after application of this method. However, there is a dramatic increase in the number of days with receding flow where simulations match observed streamflow.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

Demonstrating Contaminant Degradation at an MGP Site With Metabolic Gas Flux and Radio Carbon Dating

Obtaining lines of evidence indicating that contamination in sediment environments is degrading and being transformed to less toxic forms is an important component of building support for a monitored natural recovery remedy for contaminated sediments. This project was a field demonstration of manufactured gas plant contaminant degradation in river sediments using metabolic gas flux and was performed in an urban area section of a river in northeastern Indiana. CO₂ sorbent traps were deployed to measure CO₂ flux from the river sediments. Sediment samples were collected and analyzed for polycyclic aromatic hydrocarbon (PAH) concentrations and for microbial community composition using molecular techniques. The results showed that the deployment was successful, measuring CO₂ flux at all sediment locations and demonstrating that microbial contaminant degrading activity was occurring in the sediments. Radio carbon dating showed a significant portion of the CO₂ being generated (approximately 19–27 percent) was the result of fossil fuel degradation. Molecular results showed that the microbial community consisted of phylotypes known to be associated with monocyclic aromatic and PAH degradation. ©2017 Wiley Periodicals, Inc.     

Rapid measurement of emissions from military aircraft turbine engines by downstream extractive sampling of aircraft on the ground: Results for C-130 and F-15 aircraft

Aircraft emissions affect air quality on scales from local to global. More than 20% of the jet fuel used in the U.S. is consumed by military aircraft, and emissions from this source are facing increasingly stringent environmental regulations, so improved methods for quickly and accurately determining emissions from existing and new engines are needed. This paper reports results of a study to advance the methods used for detailed characterization of military aircraft emissions, and provides emission factors for two aircraft: the F-15 fighter and the C-130 cargo plane. The measurements involved outdoor ground-level sampling downstream behind operational military aircraft. This permits rapid change-out of the aircraft so that engines can be tested quickly on operational aircraft. Measurements were made at throttle settings from idle to afterburner using a simple extractive probe in the dilute exhaust. Emission factors determined using this approach agree very well with those from the traditional method of extractive sampling at the exhaust exit. Emission factors are reported for CO₂, CO, NO, NO_x, and more than 60 hazardous and/or reactive organic gases. Particle size, mass and composition also were measured and are being reported separately. Comparison of the emissions of nine hazardous air pollutants from these two engines with emissions from nine other aircraft engines is discussed.     

Atmospheric chemistry of perfluorobutenes (CF3CFCFCF3 and CF3CF2CFCF2): Kinetics and mechanisms of reactions with OH radicals and chlorine atoms,IR spectra,global warming potentials,and oxidation to perfluorocarboxylic acids

Relative rate techniques were used to determine k(Cl + CF₃CFCFCF₃) = (7.27 ± 0.88) × 10^?12, k(Cl + CF₃CF₂CFCF₂) = (1.79 ± 0.41) × 10^?11, k(OH + CF₃CFCFCF₃) = (4.82 ± 1.15) × 10^?13, and k(OH + CF₃CF₂CFCF₂) = (1.94 ± 0.27) × 10^?12 cm³ molecule^?1 s^?1 in 700 Torr of air or N₂ diluent at 296 K. The chlorine atom- and OH radical-initiated oxidation of CF₃CFCFCF₃ in 700 Torr of air gives CF₃C(O)F in molar yields of 196 ± 11 and 218 ± 20%, respectively. Chlorine atom-initiated oxidation of CF₃CF₂CFCF₂ gives molar yields of 97 ± 9% CF₃CF₂C(O)F and 97 ± 9% COF₂. OH radical-initiated oxidation of CF₃CF₂CFCF₂ gives molar yields of 110 ± 15% CF₃CF₂C(O)F and 99 ± 8% COF₂. The atmospheric fate of CF₃CF₂C(O)F and CF₃C(O)F is hydrolysis to give CF₃CF₂C(O)OH and CF₃C(O)OH. The atmospheric lifetimes of CF₃CFCFCF₃ and CF₃CF₂CFCF₂ are determined by reaction with OH radicals and are approximately 24 and 6 days, respectively. The contribution of CF₃CFCFCF₃ and CF₃CF₂CFCF₂ to radiative forcing of climate change will be negligible.     

Arctic Lake Physical Processes and Regimes with Implications for Winter Water Availability and Management in the National Petroleum Reserve Alaska

Lakes are dominant landforms in the National Petroleum Reserve Alaska (NPRA) as well as important social and ecological resources. Of recent importance is the management of these freshwater ecosystems because lakes deeper than maximum ice thickness provide an important and often sole source of liquid water for aquatic biota, villages, and industry during winter. To better understand seasonal and annual hydrodynamics in the context of lake morphometry, we analyzed lakes in two adjacent areas where winter water use is expected to increase in the near future because of industrial expansion. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery acquired between 1985 and 2007 were analyzed and compared with climate data to understand interannual variability. Measured changes in lake area extent varied by 0.6% and were significantly correlated to total precipitation in the preceding 12 months (p < 0.05). Using this relation, the modeled lake area extent from 1985 to 2007 showed no long-term trends. In addition, high-resolution aerial photography, bathymetric surveys, water-level monitoring, and lake-ice thickness measurements and growth models were used to better understand seasonal hydrodynamics, surface area-to-volume relations, winter water availability, and more permanent changes related to geomorphic change. Together, these results describe how lakes vary seasonally and annually in two critical areas of the NPRA and provide simple models to help better predict variation in lake-water supply. Our findings suggest that both overestimation and underestimation of actual available winter water volume may occur regularly, and this understanding may help better inform management strategies as future resource use expands in the NPRA.