Biomedical subjects

D A Niemeier

Publications and source records attributed to D A Niemeier.

5 recordsLinked to original sources

PubMed2005

Assessing air quality progress using on-road emissions inventories updates.

This analysis demonstrates that changing the assumptions used to develop emission inventories can confound attempts to show that a region is making progress toward attainment. Ambient carbon monoxide data and four different estimates of the regional emissions in the California South Coast Air Basin from 1990 through 1995 are used to estimate rollback relationships. Mixed models are specified to the ambient concentration data and estimated emissions, allowing the calculation of the expected increase in ambient concentration per ton of carbon monoxide emitted under each emissions inventory scenario. Statistically significant differences are found between rates of expected change in carbon monoxide concentration among the four scenarios tested. Existing guidance for conformity determinations is found to be insufficient.

Air Pollutants↗

PubMed2002

Spatial applicability of emission factors for modeling mobile emissions.

Driving cycles are used to create mobile emission factors. Emission factors are, in turn, used to estimate mobile source inventories, provide standards for new vehicle emissions testing, and facilitate comparisons of laboratory experiments. This study examines the spatial representativeness of the driving cycles underlying California's CO, THC, and NOx emission rates that are applied when estimating regional mobile emissions inventories. Sixteen randomly selected vehicles were tested on a laboratory dynamometer using driving cycles representative of driving in different cities. A total of 214 tests, with repetitions, representing six driving cycles, were conducted on the 16 vehicles. We used a random effects analysis of variance to statistically examine the differences in the resulting emission rates. The study results suggest that California mobile source pollutant inventories prepared using emission rates based on the standard drive cycle may be off by as much as 30% for regions where traffic congestion and roadway networks differ significantly from those of Los Angeles.

Air Pollutants↗

PubMed2001

Observations and model simulations of carbon monoxide emission factors from a California highway.

A series of twelve intensively monitored 1-hr CO dispersion studies were conducted near Davis, CA, in winter 1996. The experimental equipment included twelve CO sampling ports at elevations up to 50 m, three sonic anemometers, a tethersonde station, aircraft measurements of wind and temperature profile aloft, and a variety of conventional meteorological equipment. The study was designed to explore the role of vehicular exhaust buoyancy during worst-case meteorological conditions, such as low winds oriented in near-parallel alignment with the road during a surface-based nocturnal inversion. From the study, field estimates of the CO emission factor (EF) from a California vehicle fleet were computed using two different methods. The analysis suggests that the CT-EMFAC/EMFAC (EMission FACtor) models currently used to conduct federal conformity modeling significantly overpredict CO emissions for high-speed, free-flowing traffic on California highways.

Air Pollutants↗

PubMed2001

Time-series analysis of above-road particulate matter at the Caldecott Tunnel exit.

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PMt) depended on the level recorded in the previous three sampling periods (i.e., PMt-1, PMt-2, and PMt-3), the number of LD vehicles in the seventh past sampling period (LDt-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HDt-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM lidar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.

Air Movements↗

PubMed2000

A new screening measure to identify potential carbon monoxide hotspots.

To demonstrate conformity of transportation projects to National Ambient Air Quality Standards in accordance with State Implementation Plans, the U.S. Environmental Protection Agency (EPA) uses intersection level of service (LOS) as one of its major criteria for screening for potential carbon monoxide (CO) hotspots. Although intersection LOS is a measure of traffic volume, signal timing, and related congestion and delay, the assigned level reflects only the computed averaged stopped delay (ASD) per vehicle at the intersection. Thus, intersections can often operate at the same LOS but produce vastly different levels of predicted CO concentrations. For example, a two-lane approach operating at LOS D will produce very different levels of CO than a five-lane approach also operating at LOS D. This study explores the effectiveness of the LOS D criterion as a screen for identifying potential CO hotspots. The study results indicate that LOS is a poor predictor of potential CO hotspots when compared to results generated with the EPA-recommended micro-scale model CAL3QHCr. To more consistently screen out those intersections that will not be identified as CO hotspots using the micro-scale models, a new criterion, equivalent red-time vehicles (ERTV), is introduced. The modeling results using ERTV suggest that it is a more robust measure for identifying potential CO hotspots, and conversely, screening out those intersections that are not likely to be identified as hotspots using micro-scale simulation results.

Air Pollutants, Occupational↗