Evaluation of the Relationship between Momentum Wakes behind Moving Vehicles and Dispersion of Vehicle Emissions Using Near-Roadway Measurements.

A parameterization of initial vertical dispersion coefficient (σz,init) was developed for incorporation into California line source dispersion model, version 4 (CALINE4) and AMS/EPA regulatory model (AERMOD) to better predict pollutant concentrations near roadways. The momentum wake theory of moving vehicles indicates that both vehicle-induced turbulence (VIT) and dispersion occur in the vehicle wake. Based on a literature review, it is postulated that σz,init near roadways can be estimated using a "wake area model" concept of effective wake area defined as the vehicle height times the wake length, vehicle density, and vehicle type. A total of 523 5-min near-roadway simultaneous measurements (2016-2018) of pollutant concentrations and meteorological and traffic information were used to evaluate the model. Two roadways with distinct fleet composition and simple road configurations were selected for monitoring. The near-roadway σz,init ranged from 1 to 4 m for light-duty vehicles (LDVs) and from 3 to 7 m for fleet-mix (LDVs and heavy-duty vehicles (HDVs)). The results demonstrate that the dispersion contribution from one HDV was 31 times larger than that from one LDV. Calculated pollutant dispersion using the wake area model compared favorably with measurements (R2 = 0.91, slope = 1.07). These results indicate that σz,init varies with vehicle density and HDVs. Pollutant dispersion related to the vehicle wakes can be used to correctly parameterize dispersion models and improve prediction of pollutant concentrations near roadways.

Ultrafine-Particle Emission Factors as a Function of Vehicle Mode of Operation for LDVs Based on Near-Roadway Monitoring.

This paper presents ultrafine-particle (UFP) emission factors (EFs) as a function of vehicle mode of operation (free flow and congestion) using (1) concurrent 5 min measurements of UFPs and carbon monoxide (CO) concentration, wind speed and direction, traffic volume and speed near a roadway that is restricted to light-duty vehicles (LDVs) and (2) inverse dispersion model calculations. Short-term measurements are required to characterize the highly variable and rapidly changing UFP concentration generated by vehicles. Under congestion conditions, the UFP vehicle EFs increased from 0.5 × 10(13) to 2 × 10(13) (particles km(-1) vehicle(-1)) when vehicle flow increased from 5500 to 7500 vehicles/h. For free-flow conditions, the EF is constant at 1.5 × 10(13) (particles km(-1) vehicle(-1)). The analysis is based on the assumption that air-quality models adequately describe the dilution process due to both traffic and atmospheric turbulence. The approach used to verify this assumption was to use an emission factor model to determine EFs for CO and then estimate dilution factors using measured CO concentrations. This procedure eliminates the need to rely only on air quality models to generate dilution factors. The EFs are suitable for fleet emissions under real-world traffic conditions.

Odor emission rate estimation of indoor industrial sources using a modified inverse modeling method.

Odor emission rates are commonly measured in the laboratory or occasionally estimated with inverse modeling techniques. A modified inverse modeling approach is used to estimate source emission rates inside of a postdigestion centrifuge building of a water reclamation plant. Conventionally, inverse modeling methods divide an indoor environment in zones on the basis of structural design and estimate source emission rates using models that assume homogeneous distribution of agent concentrations within a zone and experimentally determined link functions to simulate airflows among zones. The modified approach segregates zones as a function of agent distribution rather than building design and identifies near and far fields. Near-field agent concentrations do not satisfy the assumption of homogeneous odor concentrations; far-field concentrations satisfy this assumption and are the only ones used to estimate emission rates. The predictive ability of the modified inverse modeling approach was validated with measured emission rate values; the difference between corresponding estimated and measured odor emission rates is not statistically significant. Similarly, the difference between measured and estimated hydrogen sulfide emission rates is also not statistically significant. The modified inverse modeling approach is easy to perform because it uses odor and odorant field measurements instead of complex chamber emission rate measurements.

Comparison of two dynamic measurement methods of odor and odorant emission rates from freshly dewatered biosolids.

Odor and odorant emission rates from freshly dewatered biosolids in a dewatering building of a Water Reclamation Plant (WRP) are measured using the EPA flux chamber and wind tunnel methods. Experimental results are compared statistically to test whether the two methods result in similar emission rates when experiments are performed under field conditions. To the best of our knowledge the literature is void of studies comparing the two methods indoors. In this paper the two methods are compared indoors where the wind velocity and air exchange rate are pertinent field conditions and can be measured. The difference between emission rates of odor and hydrogen sulfide measured with the two methods is not statistically significant (P values: 0.505 for odor, 0.130 for H(2)S). It is concluded that both methods can be used to estimate source emissions but selection of the most effective or efficient method depends on prevailing environmental conditions. The wind tunnel is appropriate for outdoor environments where wind effects on source emissions are more pronounced than indoors. The EPA flux chamber depends on the air exchange rate of the chamber, which simulates corresponding conditions of the indoor environment under investigation and is recommended for estimation of indoor pollution sources.

Near-roadway monitoring of vehicle emissions as a function of mode of operation for light-duty vehicles.

Determination of the effect of vehicle emissions on air quality near roadways is important because vehicles are a major source of air pollution. A near-roadway monitoring program was undertaken in Chicago between August 4 and October 30, 2014, to measure ultrafine particles, carbon dioxide, carbon monoxide, traffic volume and speed, and wind direction and speed. The objective of this study was to develop a method to relate short-term changes in traffic mode of operation to air quality near roadways using data averaged over 5-min intervals to provide a better understanding of the processes controlling air pollution concentrations near roadways. Three different types of data analysis are provided to demonstrate the type of results that can be obtained from a near-roadway sampling program based on 5-min measurements: (1) development of vehicle emission factors (EFs) for ultrafine particles as a function of vehicle mode of operation, (2) comparison of measured and modeled CO2 concentrations, and (3) application of dispersion models to determine concentrations near roadways. EFs for ultrafine particles are developed that are a function of traffic volume and mode of operation (free flow and congestion) for light-duty vehicles (LDVs) under real-world conditions. Two air quality models-CALINE4 (California Line Source Dispersion Model, version 4) and AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model)-are used to predict the ultrafine particulate concentrations near roadways for comparison with measured concentrations. When using CALINE4 to predict air quality levels in the mixing cell, changes in surface roughness and stability class have no effect on the predicted concentrations. However, when using AERMOD to predict air quality in the mixing cell, changes in surface roughness have a significant impact on the predicted concentrations. IMPLICATIONS: The paper provides emission factors (EFs) that are a function of traffic volume and mode of operation (free flow and congestion) for LDVs under real-world conditions. The good agreement between monitoring and modeling results indicates that high-resolution, simultaneous measurements of air quality and meteorological and traffic conditions can be used to determine real-world, fleet-wide vehicle EFs as a function of vehicle mode of operation under actual driving conditions.

Characterization of atmospheric concentrations and partitioning of PAHs in the Chicago atmosphere.

An intensive sampling program has been undertaken in the absence of precipitation at an urban site, Chicago, to characterize the atmospheric concentration and partitioning of PAHs. Two different sampling programs have been carried out with a large number of samples. Measured ambient concentrations of PAHs were classified as Land and Lake samples based on wind direction and back trajectory calculations. Differences in ambient concentrations of PAHs were observed between Land and Lake samples. The concentrations of PAHs when air originated over the Land were approximately two-four times higher than the concentrations measured when air originated over the Lake. It has been demonstrated that partitioning of PAHs shows a consistent difference between samples taken when wind came from off the land rather than off the water. This was most evident by more shallow slopes for Lake samples compared to the slopes for Land samples, when partition coefficient (K(p)) is plotted on a log-log scale vs. the subcooled liquid vapor pressure (P(L)(0)). Experimentally, determined K(p) values were compared with the results obtained using two different models, one based on absorption into aerosol organic matter and the other adsorption onto soot carbon. Experimental K(p) values generally agreed well with the soot+octanol based model predictions.

Atmospheric PAH concentrations in fine and coarse particles.

Measurements of the urban air concentrations of PAHs associated with PM2.5-fine and PM 10-coarse particles in Chicago on the campus of IIT were achieved using a Universal Air Sampler. Short sampling time (12 hr) and high flow rates were used to measure the PAH concentrations in fine and coarse particles. Measured ambient concentrations of PAHs were classified based on wind direction and back trajectory calculations as Land and Lake samples. Differences in ambient concentrations of PAHs were observed between Land and Lake samples. Fine particle concentrations varied from 9.5 to 25.7 ng m(-3) and averaged 18.2 ng m(-3) for the Land samples, while they ranged from 4.2 to 31.5 ng m(-3) and averaged 13.4 ng m(-3) for the Lake samples. The measured PAH concentrations in coarse particles varied from 6.2 to 22.1 ng m(-3) and averaged 12.9 ng m(-3) for the Land samples, and they ranged from 2.4 to 13.0 ng m(-3) with an average value of 7.3 ng m(-3) for the Lake samples. The fine/coarse ratio of each individual PAH compound varied between 1.3 and 2.7 for the Land samples: it varied between 1.6 and 4.2 for the Lake samples. There was an increase in the fine/coarse ratio of PAH as molecular weight of the compound increases for both Land and Lake samples.