Quantifying the Air Pollution Exposure Consequences of - Houston ...

There are four important limitations to our use of the standard Gaussian model.
First, one must assume that meteorological conditions (e.g., wind speed and direction)
remain constant within the transport time of the plume to use the Gaussian model
(Turner, 1994). Travel times for a plume released at Morro Bay or any location in the Los
Angeles area, for example, to reach the boundary of our exposed population (100 km) are
between 7 and 13 hours at annual-average wind speeds in the prevailing wind direction.
Clearly, meteorological conditions do not remain constant over intervals of order 10 h.
However, what we seek in this study is closely related to the long-term temporally and
spatially averaged ground-level concentration over the entire impact area of the plume.
As the system is linear for the pollutants considered here, the assumption of steady state
as a means to estimate an average is reasonable.
The second limitation involves the discetization of atmospheric stability into six
(Pasquill) classes. This treatment does not fully capture the continuous nature of
atmospheric conditions. However, as there are no other descriptions of atmospheric
conditions as widely used and trusted as the Pasquill system, we deem its use here
appropriate.
Third, while not strictly necessary in the use of the Gaussian model, a common
assumption is no loss of pollutant to the ground surface or through the inversion layer,
i.e., that there is perfect reflection from those boundaries. While the assumption of
perfect reflection at the ground surface may not be strictly true for PM2.5, we estimate that
this assumption introduces an error of less than 10% over the travel distance of the
plume. Thus, PM2.5 can be approximated as a conserved pollutant over the distances
within the scope of this study.
As for pollutant loss at the upper boundary, for all cases where the effective stack
height of a plant is lower than the mixing height, we assume that the bottom of the
inversion layer is perfectly reflecting. However, there are many hours of the year when
the mixing height is lower than the effective stack height (the proportion is higher for
plants with taller stacks). When considering population intake during those hours, we
made the simplifying assumption that this condition was completely protective of public
health, i.e., that the vertical plume from the stack has enough momentum to fully pass
through the inversion base and be separated from the people below. The method of partial
plume penetration (Turner, 1994) is an alternative approach that could be used in future
work to test the sensitivity of our assumption. We report the number of hours the
effective stack height of the plume is higher than the mixing height in section II.C.4.a.
Finally, there are several issues related to the estimation of exposures at the nearsource
(< 100 m) and 100 km boundaries of our modeling domain. The Gaussian model
is not accurate at predicting concentrations within 100 m of the source (Turner, 1994).
Large electricity generation units have substantial effective stack heights, leading to
sufficiently small concentrations within 100 m to make an insignificant contribution to
the population exposure. 13 The hypothetical DG units cause substantially higher
concentrations within 100 m owing to their negligible buoyancy- and momentum-induced
plume rise. Lai et al. (2000) bounded the possible error to intake fraction estimation
within the first 100 m downwind and showed that not considering the first 100 m resulted
in less than 1% error. Their result was based on an assumption of uniform population
13 Section II.C.4.b discusses the calculation of effective stack height for both existing units and hypothetical
DG cases.
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