Environmental Engineering Reference
In-Depth Information
3.1 Implementation of Real-Time Bias-Corrected O
3
and PM
2.5
Air Quality Forecast and Their Performance
Evaluations During 2008 over the Continental
United States
Daiwen Kang
1
*
, Rohit Mathur
2
, and S. Trivikrama Rao
2
1
Computer Science Corporation, Research Triangle Park, 79 T.W. Alexander Drive,
NC 27709, USA
2
Atmospheric Modeling Division, National Exposure Research Laboratory,
U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
Abstract
Real-time bias-corrected O
3
and PM
2.5
forecast systems are implemented
using the Kalman Filter, combining observations from AIRnow and outputs from
the NOAA/EPA's NAM/CMAQ air quality forecast model. Bias-corrected O
3
and
PM
2.5
forecasts are created at locations of the AIRNow monitoring network where
report hourly concentrations of these species. Observations and model outputs
from two previous consecutive days are required to produce bias-corrected model
forecasts. The performance of these systems is examined on a daily basis using O
3
and PM
2.5
observations and the results are compared with raw model forecasts.
The overall performance of the Kalman filtering technique and its capability to
produce a real-time bias correction to improve the day-to-day forecast from the
NAM-CMAQ modeling system during 2008 is investigated. Performance evaluation
trough detailed time-series analysis and regional analysis will be presented. The
ability of the technique in improving the prediction of daily 8-hr maximum O
3
and
daily mean PM
2.5
as well as its impacts on false-alarms will be examined through
the use of statistical categorical metrics.
Keywords
Air quality forecast, Bias-adjustment, O
3
, PM
2.5
, Kalman filter
1. Introduction
Ozone (O
3
) and fine particulate matter (PM
2.5
; particles with aerodynamic diameters
less than 2.5 µm) air pollution is of concern due to their adverse effect on human
and ecosystem health. Ambient levels of O
3
and PM
2.5
are the two primary
components used in the calculation of the Air Quality Index (AQI), a standardized
*
E-mail: kang.daiwen@epa.gov; Voice (919) 541-2460, Fax (919) 541-1379
