You are here:
FORMAL UNCERTAINTY ANALYSIS OF A LAGRANGIAN PHOTOCHEMICAL AIR POLLUTION MODEL. (R824792)
Citation:
Bergin, M. S., G. S. Noblet, K. Petrini, J. R. Dhieux, J. B. Milford, AND R. A. Harley. FORMAL UNCERTAINTY ANALYSIS OF A LAGRANGIAN PHOTOCHEMICAL AIR POLLUTION MODEL. (R824792). ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 33:1116-1126, (1999).
Description:
This study applied Monte Carlo analysis with Latin
hypercube sampling to evaluate the effects of uncertainty
in air parcel trajectory paths, emissions, rate constants,
deposition affinities, mixing heights, and atmospheric stability
on predictions from a vertically resolved photochemical
trajectory model. Uncertainties in concentrations of ozone
and other secondary compounds and in predicted
changes due to 25% reductions in motor vehicle non-methane organic compound (NMOC) and nitrogen oxide
(NOx) emissions were examined. Surface wind measurements
were interpolated over the modeling domain, and
uncertainties were quantified using data withholding. The
resulting wind fields and uncertainties were used to
generate ensembles of trajectories ending at four Southern
California air quality monitoring sites. A motor vehicle
emissions inventory and associated uncertainties were
derived from remote sensing and fuel sales data. Uncertainties
in chemical rate parameters were obtained from expert
reviews. Estimated uncertainties in O3 range across the four
sites from 24% to 57% (1 standard deviation (1
) relative
to the mean). Seven variables contribute almost 80% of this
uncertainty. Reductions in motor vehicle NMOC reduce
O3 from 10 ± 10% (1) to 28 ± 10%. With reductions in motor
vehicle (NOx) emissions, the change in O3 ranges from
an increase of 14 ± 14% to a decrease of 6.6 ± 6.2%.