Effect of hydrogen addition on criteria and greenhouse gas emissions for a marine diesel engine

Hydrogen remains an attractive alternative fuel to petroleum and a number of investigators claim that adding hydrogen to the air intake manifold of a diesel engine will reduce criteria emissions and diesel fuel consumption. Such claims are appealing when trying to simultaneously reduce petroleum consumption, greenhouse gases and criteria pollutants. The goal of this research was to measure the change in criteria emissions (CO, NOx, and PM 2.5) and greenhouse gases such as carbon dioxide (CO2), using standard test methods for a wide range of hydrogen addition rates. A two-stroke Detroit Diesel Corporation 12V-71TI marine diesel engine was mounted on an engine dynamometer and tested at three out of the four loads specified in the ISO 8178-4 E3 emission test cycle and at idle. The engine operated on CARB ultra-low sulfur #2 diesel with hydrogen added at flow rates of 0, 22 and 220 SLPM. As compared with the base case without hydrogen, measurements showed that hydrogen injection at 22 and 220 SLPM had negligible influence on the overall carbon dioxide specific emission, EFCO2. However, in examining data at each load the data revealed that at idle EFCO2 was reduced by 21% at 22 SLPM (6.9% of the added fuel energy was from hydrogen) and 37.3% at 220 SLPM (103.1% of the added fuel energy was from hydrogen). At all other loads, the influence of added hydrogen was insignificant. Specific emissions for nitrogen oxides, EFNOx, and fine particulate matters, EFPM 2.5, showed a trade-off relationship at idle. At idle, EFNO x was reduced by 28% and 41% with increasing hydrogen flow rates, whilst EFPM2.5 increased by 41% and 86% respectively. For other engine loads, EFNOx and EFPM2.5 did not change significantly with varying hydrogen flow rates. One of the main reasons for the greater impact of hydrogen at idle is that the contribution of hydrogen to the total fuel energy is much higher at idle as compared to the other loads. The final examination in this paper was the system energy balance when hydrogen is produced by an on-board electrolysis unit. An analysis at 75% engine load showed that hydrogen production increased the overall equivalent fuel consumption by 2.6% at 22 SLPM and 17.7% at 220 SLPM. © 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved

Plume Rise and Dispersion of Emissions from Low Level Buoyant Sources in Urban Areas

The projected increase in distributed power generation (DG) has given rise to the concerns on the air quality impact of small power plants located in urban areas. In order to estimate this impact, there is a need for a model that can treat plume rise and dispersion of a buoyant release in an inhomogeneous urban boundary layer whose structure is governed by complex surface characteristics. Such a model requires three essential ingredients: 1) a realistic treatment of the interaction between the highly turbulent urban canopy layer and the turbulent plume spread, 2) a plume rise model that can accounts for the flow modifications caused by buildings, and 3) an appropriate estimate of the height of the nocturnal urban boundary layer. Comprehensive laboratory and field studies were conducted to investigate each of these elements separately. Ground level concentrations (GLC) associated with a modeled DG were measured inside the water channel under different surrounding building geometries. Results from these measurements indicated that surrounding buildings induce vigorous vertical mixing which increase the near source GLC. Further investigations focused on the plume rise from these sources. The results from plume rise measurements suggested that plume exiting the DG stack can be significantly impacted by the flows induced by surrounding buildings. In addition to dispersion and plume rise measurements, a field study was conducted in Riverside, CA and the structure of the nocturnal urban boundary layer was investigated over three different nights. Results from these measurements helped us to develop a semi-empirical model that can predict the height of the stable boundary layer. Although we were able to reasonably understand and develop models to predict the micro-meteorology as well as plume rise and spread; we concluded that simple Gaussian dispersion models have limited performance in predicting the concentrations associated with urban sources due to the substantial complexity involved with the urban dispersion process

Development of an Air Dispersion Model to Study Near-Road Exposure

In the mid-20th century, transportation agencies began constructing sound walls around major highways as suggested by Title 23 of the U.S. Code of Federal Regulations, Part 772, "Procedures for Abatement of Highway Traffic Noise and Construction Noise”. Although the primary purpose of sound walls is to reduce the noise levels in residential areas next to highways, they can have a significant impact on the dispersion of traffic related pollutants. Therefore, since early 2000, U.S. Environmental Protection Agency (U.S. EPA) initiated several projects to address the impact of sound walls and surrounding vegetation on the dispersion of vehicular emissions. The results from these projects unanimously showed that incorporation of roadside structures can cause 50% reduction in the near road concentrations as compared to an unobstructed roadway4. Although these studies provide a thorough insight on the air quality impact of sound barriers, the question that remained unanswered is how to reflect their impact into currently available dispersion models?  Over the past 5 years, there have been some efforts to model the dispersion affected by roadway structures. Bowker et al.5 used Quick Urban and Industrial Complex model6 (QUIC) developed by Los Alamos National Laboratory to describe the results from I-440 field study. Another modeling practice was the work done by Steffens et al.7 where they introduced the Comprehensive Turbulent Aerosol dynamics and Gas chemistry model (CTAG) to estimate the concentrations in Idaho Falls field study4. Although all these studies showed some abilities in describing the impact of noise barriers, none of them provides a generic solution. Both QUIC and CTAG are numerical based models and necessitate computational resources that can become impractical for exposure analysis. This article is presenting another effort conducted by researchers at University of California Riverside (UCR) to develop a simple dispersion model that can reflect the impact of roadside structures on the near roadway concentrations, and at the same time is computationally efficient

Hummingbirds generate bilateral vortex loops during hovering: evidence from flow visualization

Visualization of the vortex wake of a flying animal provides understanding of how wingbeat kinematics are translated into the aerodynamic forces for powering and controlling flight. Two general vortex flow patterns have been proposed for the wake of hovering hummingbirds: (1) The two wings form a single, merged vortex ring during each wing stroke; and (2) the two wings form bilateral vortex loops during each wing stroke. The second pattern was proposed after a study with particle image velocimetry that demonstrated bilateral source flows in a horizontal measurement plane underneath hovering Anna’s hummingbirds (Calypte anna). Proof of this hypothesis requires a clear perspective of bilateral pairs of vortices. Here, we used high-speed image sequences (500 frames per second) ofC. anna hover feeding within a white plume to visualize the vortex wake from multiple perspectives. The films revealed two key structural features: (1) Two distinct jets of downwards airflow are present under each wing; and (2) vortex loops around each jet are shed during each upstroke and downstroke. To aid in the interpretation of the flow visualization data, we analyzed high-speed kinematic data (1,000 frames per second) of wing tips and wing roots as C. anna hovered in normal air. These data were used to refine several simplified models of vortex topology. The observed flow patterns can be explained by either a single loop model with an hourglass shape or a bilateral model, with the latter being more likely. When hovering in normal air, hummingbirds used an average stroke amplitude of 153.6° (range 148.9°–164.4°) and a wingbeat frequency of 38.5 Hz (range 38.1–39.1 Hz). When hovering in the white plume, hummingbirds used shallower stroke amplitudes ( xˉ = 129.8°, range 116.3°–154.1°) and faster wingbeat frequencies ( xˉ  = 41.1 Hz, range 38.5–44.7 Hz), although the bilateral jets and associated vortices were observed across the full kinematic range. The plume did not significantly alter the air density or constrain the sustained muscle contractile frequency. Instead, higher wingbeat frequencies likely incurred a higher metabolic cost with the possible benefit of allowing the birds to more rapidly escape from the visually disruptive plume

Hummingbirds generate bilateral vortex loops during hovering: evidence from flow visualization

Visualization of the vortex wake of a flying animal provides understanding of how wingbeat kinematics are translated into the aerodynamic forces for powering and controlling flight. Two general vortex flow patterns have been proposed for the wake of hovering hummingbirds: (1) The two wings form a single, merged vortex ring during each wing stroke; and (2) the two wings form bilateral vortex loops during each wing stroke. The second pattern was proposed after a study with particle image velocimetry that demonstrated bilateral source flows in a horizontal measurement plane underneath hovering Anna’s hummingbirds (Calypte anna). Proof of this hypothesis requires a clear perspective of bilateral pairs of vortices. Here, we used high-speed image sequences (500 frames per second) ofC. anna hover feeding within a white plume to visualize the vortex wake from multiple perspectives. The films revealed two key structural features: (1) Two distinct jets of downwards airflow are present under each wing; and (2) vortex loops around each jet are shed during each upstroke and downstroke. To aid in the interpretation of the flow visualization data, we analyzed high-speed kinematic data (1,000 frames per second) of wing tips and wing roots as C. anna hovered in normal air. These data were used to refine several simplified models of vortex topology. The observed flow patterns can be explained by either a single loop model with an hourglass shape or a bilateral model, with the latter being more likely. When hovering in normal air, hummingbirds used an average stroke amplitude of 153.6° (range 148.9°–164.4°) and a wingbeat frequency of 38.5 Hz (range 38.1–39.1 Hz). When hovering in the white plume, hummingbirds used shallower stroke amplitudes ( xˉ = 129.8°, range 116.3°–154.1°) and faster wingbeat frequencies ( xˉ  = 41.1 Hz, range 38.5–44.7 Hz), although the bilateral jets and associated vortices were observed across the full kinematic range. The plume did not significantly alter the air density or constrain the sustained muscle contractile frequency. Instead, higher wingbeat frequencies likely incurred a higher metabolic cost with the possible benefit of allowing the birds to more rapidly escape from the visually disruptive plume