Regional Source Identification Using Lagrangian Stochastic Particle Dispersion and HYSPLIT Backward-Trajectory Models

• Published in: Journal of the Air & Waste Management Association (1995) 2011-06, Vol.61 (6), p.660-672
• Main Authors: Koracin, Darko, Vellore, Ramesh, Lowenthal, Douglas H., Watson, John G., Koracin, Julide, McCord, Travis, DuBois, David W., Chen, L.-W. Antony, Kumar, Naresh, Knipping, Eladio M., J.M. Wheeler, Neil, Craig, Kenneth, Reid, Stephen
• Format: Article
• Language: English
• Subjects: Accuracy; Aerodynamics; Air Movements; Air Pollutants - chemistry; Air Pollution; Air quality; Air quality management; Applied sciences; Atmospheric pollution; Computer simulation; Correlation coefficient; Correlation coefficients; Data collection; Dispersions; Emission; Emissions; Environmental Monitoring - methods; Exact sciences and technology; Haze; Lagrangian functions; Mathematical models; Methods; Modelling; Models, Theoretical; National parks; Outdoor air quality; Parks; Pollutants; Pollution; Pollution dispersion; Pollution sources; Receptors; Regional analysis; Statistical analysis; Stochastic Processes; Stochasticity; Studies; Sulfates; Trajectories; Trajectory analysis; Turbulence; United States
• ISSN: 1096-2247; 2162-2906
• DOI: 10.3155/1047-3289.61.6.660

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55-0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30-0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases.