Proper mixing of reagents is of paramount importance for an efficient chemical reaction. While on a large scale there are many good solutions for quantitative mixing of reagents, as of today, efficient and inexpensive fluid mixing in the nanoliter and microliter volume range is still a challenge. Complete, i.e., quantitative mixing is of special importance in any small-scale analytical application because the scarcity of analytes and the low volume of the reagents demand efficient utilization of all available reaction components. In this paper we demonstrate the design and fabrication of a novel centrifugal force-based unit for fast mixing of fluids in the nanoliter to microliter volume range. The device consists of a number of chambers (including two loading chambers, one pressure chamber, and one mixing chamber) that are connected through a network of microchannels, and is made by bonding a slab of polydimethylsiloxane (PDMS) to a glass slide. The PDMS slab was cast using a SU-8 master mold fabricated by a two-level photolithography process. This microfluidic mixer exploits centrifugal force and pneumatic pressure to reciprocate the flow of fluid samples in order to minimize the amount of sample and the time of mixing. The process of mixing was monitored by utilizing the planar laser induced fluorescence (PLIF) technique. A time series of high resolution images of the mixing chamber were analyzed for the spatial distribution of light intensities as the two fluids (suspension of red fluorescent particles and water) mixed. Histograms of the fluorescent emissions within the mixing chamber during different stages of the mixing process were created to quantify the level of mixing of the mixing fluids. The results suggest that quantitative mixing was achieved in less than 3 min. This device can be employed as a stand alone mixing unit or may be integrated into a disk-based microfluidic system where, in addition to mixing, several other sample preparation steps may be included.

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The built environment surrounding arterials affects the dispersion of vehicular emissions in urban areas, modifying the potential risks to public health. In order to study the influence of urban morphometry on flow and dispersion of vehicular fine particulate matter emissions, in the summer of 2008 field measurements were performed in major arterials located in five Southern Californian cities with different building geometries. In each city, local mean wind, turbulence, virtual temperature, roadside DustTrak Fine Particles (DTFP) concentration, and traffic flow data were collected in 2-hr measurement periods during morning and evening rush hours and lighter midday traffic, over a period of 3 days. The calculated Monin-Obukhov length, L, suggests that near-neutral and slightly unstable conditions were present at both street and roof levels. The nondimensional forms of turbulent wind and temperature fluctuations show that the data at street level within the urban canopy can be represented using the Monin-Obukhov similarity theory. Generalized additive models were applied to analyze the impact of meteorological and traffic-related variables on fine particle concentrations at street level. Compared to other variables, urban-scale background concentrations were the most important variables in all five models. The results confirmed that turbulent mixing in urban areas dominated the variation of roadside particle concentrations regardless of urban geometry. The distance from the local sites to the nearby monitoring stations affected model performance when urban-scale concentrations were used to predict middle-scale concentrations by generalized additive models (GAMs). A radius of influence for background concentrations was 6-10 km. There were also relationships between concentration and other variables affecting the local components of the concentrations, such as wind direction, sensible heat flux, and vertical wind fluctuation, although the influences were much weaker.Implications: The built environment surrounding major arterials affects the dispersion of vehicular emissions in urban areas, modifying the potential risks to public health. Dispersion of pollutants within the urban canopy is governed by flow and turbulence characteristics caused by building morphometry. Current dispersion models used for regulatory purposes have difficulties simulating the flow and dispersion for complex building cases, especially when fine resolution is needed. Urban planning strategies, such as limitation of building height, pedestrian-friendly community design, or zoning of building structures, modify concentrations of vehicular emissions in built environments surrounding major arterials, which may modify health risks for adjacent communities. IntroductionIn metropolitan cities, vehicular emissions are in close proximity to pedestrians, residences, and local businesses. Current line-source models based on the Gaussian diffusion equation are commonly applied to evaluate the air quality impact of freeways or highways passing through a...

Smoke from human-induced fires such as prescribed fires can occasionally cause significant reduction in visibility on highways in the southern United States. Visibility reduction to less than 3 m has been termed "superfog" and environmental conditions that lead to its formation have been proposed previously. Accurate characterization and prediction of precursor conditions for superfog is needed to prevent dangerous low visibility situations when planning prescribed fires. It is hypothesized that extremely hygroscopic cloud condensation nuclei from the smoldering phase of a fire can produce a large number of droplets smaller in size than in naturally occurring fog. This large number of small droplets can produce superfog conditions with relatively low liquid water content. A thermodynamics-based model for fog formation was developed. Laboratory generated superfog measured by a Phase Doppler Particle Analyzer determined that mean droplet radius was 1.5 μm and the size distribution could be modeled with a lognormal distribution. Experiments in an environmentally-conditioned wind tunnel using longleaf pine (Pinus palustris Mill.) needle fuel beds provided visibility, heat flux, temperature, humidity, and particle data for model validation. Numerical modeling was used to approximate the growth of a superfog boundary-layer with liquid water content values of 2 g m −3 or greater. The model successfully predicted previous superfog events.