Regional source identification using Lagrangian stochastic particle dispersion and HYSPLIT backward-trajectory models.

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.

Evaluation of regional-scale receptor modeling.

The ability of receptor models to estimate regional contributions to fine particulate matter (PM2.5) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM2.5 chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM2.5 source profiles from the U.S. Environmental Protection Agency (EPA)'s SPECIATE and Desert Research Institute's source profile databases. CMAQ estimated the "true" contributions of seven regions in the eastern United States to chemical species concentrations and individual source contributions to primary PM2.5 at both sites. A seven-factor solution by the positive matrix factorization (PMF) receptor model explained approximately 99% of the variability in the data at both sites. At BRIG, PMF captured the first four major contributing sources (including a secondary sulfate factor), although diesel and gasoline vehicle contributions were not separated. However, at GRSM, the resolved factors did not correspond well to major PM2.5 sources. There were no correlations between PMF factors and regional contributions to sulfate at either site. Unmix produced five- and seven-factor solutions, including a secondary sulfate factor, at both sites. Some PMF factors were combined or missing in the Unmix factors. The trajectory mass balance regression (TMBR) model apportioned sulfate concentrations to the seven source regions using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectories based on Meteorological Model Version 5 (MM5) and Eta Data Simulation System (EDAS) meteorological input. The largest estimated sulfate contributions at both sites were from the local regions; this agreed qualitatively with the true regional apportionments. Estimated regional contributions depended on the starting elevation of the trajectories and on the meteorological input data.

Toward effective source apportionment using positive matrix factorization: experiments with simulated PM2.5 data.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM2.5 (particulate matter with aerodynamic diameter < 2.5 microm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to chi2 and R2 used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis. For the most part, factors are found to represent imperfect combinations of sources, and the optimal number of factors should be just adequate to explain the input data (e.g., R2 > 0.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.

Evaluation of Regional-Scale Receptor Modeling.

The ability of receptor models to estimate regional contributions to fine particulate matter (PM2.5) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM2.5 chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM2.5 source profiles from the U.S. Environmental Protection Agency (EPA)'s SPECIATE and Desert Research Institute's source profile databases. CMAQ estimated the "true" contributions of seven regions in the eastern United States to chemical species concentrations and individual source contributions to primary PM2.5 at both sites. A seven-factor solution by the positive matrix factorization (PMF) receptor model explained approximately 99% of the variability in the data at both sites. At BRIG, PMF captured the first four major contributing sources (including a secondary sul-fate factor), although diesel and gasoline vehicle contributions were not separated. However, at GRSM, the resolved factors did not correspond well to major PM2.5 sources. There were no correlations between PMF factors and regional contributions to sulfate at either site. Unmix produced five- and seven-factor solutions, including a secondary sulfate factor, at both sites. Some PMF factors were combined or missing in the Unmix factors. The trajectory mass balance regression (TMBR) model apportioned sulfate concentrations to the seven source regions using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectories based on Meteorological Model Version 5 (MM5) and Eta Data Simulation System (EDAS) meteorological input. The largest estimated sulfate contributions at both sites were from the local regions; this agreed qualitatively with the true regional apportionments. Estimated regional contributions depended on the starting elevation of the trajectories and on the meteorological input data.

Toward Effective Source Apportionment Using Positive Matrix Factorization: Experiments with Simulated PM2.5 Data.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM2.5 (particulate matter with aerodynamic diameter <2.5 µm) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to χ-2 and R 2 used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis. For the most part, factors are found to represent imperfect combinations of sources, and the optimal number of factors should be just adequate to explain the input data (e.g., R 2 > 0.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.

Transport and dispersion during wintertime particulate matter episodes in the San Joaquin Valley, California.

Data analysis and modeling were performed to characterize the spatial and temporal variability of wintertime transport and dispersion processes and the impact of these processes on particulate matter (PM) concentrations in the California San Joaquin Valley (SJV). Radar wind profiler (RWP) and radio acoustic sounding system (RASS) data collected from 18 sites throughout Central California were used to estimate hourly mixing heights for a 3-month period and to create case studies of high-resolution diagnostic wind fields, which were used for trajectory and dispersion analyses. Data analyses show that PM episodes were characterized by an upper-level ridge of high pressure that generally produced light winds through the entire depth of the atmospheric boundary layer and low mixing heights compared with nonepisode days. Peak daytime mixing heights during episodes were -400 m above ground level (agl) compared with -800 m agl during nonepisodes. These episode/nonepisode differences were observed throughout the SJV. Dispersion modeling indicates that the range of influence of primary PM emitted in major population centers within the SJV ranged from -15 to 50 km. Trajectory analyses revealed that little intrabasin pollutant transport occurred among major population centers in the SJV; however, interbasin transport from the northern SJV and Sacramento regions into the San Francisco Bay Area (SFBA) was often observed. In addition, this analysis demonstrates the usefulness of integrating RWP/RASS measurements into data analyses and modeling to improve the understanding of meteorological processes that impact pollution, such as aloft transport and boundary layer evolution.

The effect of reducing the fine-particle mass of salmeterol from metered-dose inhalers on bronchodilatation and bronchoprotection against methacholine challenge: a randomized, placebo-controlled, double-blind, crossover study.

OBJECTIVE: This study examined the clinical relevance of fine-particle mass (FPM) delivered from metered dose inhalers (MDIs) to bronchodilatation and bronchoprotection against methacholine challenge by comparing a marketed chlorofluorocarbon (CFC) formulation of salmeterol with an investigational hydrofluoroalkane (HFA)formulation. METHODS: This was a randomized, double-blind, placebo-controlled, 3-way crossover study in patients with mild to moderate asthma who had a forced expiratory volume in 1 second (FEV (1)) of > or =60% predicted and a base-line provocation dose of inhaled methacholine required to produce a 20% decrease in FEV(1) (PD (20) [methacholine]) of < or =3.2 mg. On separate occasions, patients received 2 inhalations of salmeterol 25 microg from either the CFC MDI (FPM 14 microg), the investigational HFA MDI (FPM 7 microg), or placebo via CFC MDI. Serial measurements of FEV(1) were made over 90 minutes after dosing, followed by methacholine challenge. Efficacy end points were PD(20) (methacholine) and FEV(1) AUC (inc) (incremental area under the FEV(1) curve) over 15 to 90 minutes. The study was designed to demonstrate non-inferiority of the investigational HFA formulation to the CFC formulation in terms of protection against methacholine-induced bronchial hyperresponsiveness; for PD(20) (methacholine), noninferiority was predefined as 1.0 doubling dose of methacholine. RESULTS: The study enrolled 40 patients (65% men; mean age, 36.9 years). Both active treatments were significantly better than placebo in terms of PD(20) (methacholine) (P < 0.001). In the per-protocol population, the mean (SE) difference in bronchoprotection between the CFC MDI and placebo was 2.7888 (0.3432) doubling doses of methacholine (n = 32), and the difference between the investigational HFA MDI and placebo was 1.8268 (0.3418) doubling doses(n = 33). The adjusted mean (SE) treatment difference between the CFC MDI and HFA MDI was 0.9621 (0.3454) doubling doses. The upperlimit of the 95% CI (0.2714-1.6527) was greater than the predefined limit for noninferiority. There was no significant difference in FEV(1) AUC(inc) between formulations (mean treatment difference, 1.895 L . min; 95% CI, -4.893 to 8.684); however, both active treatments were significantly different from placebo (P < 0.001). CONCLUSIONS: FPM from different MDI formulations may affect the bronchoprotective properties of salmeterol. In this study, the formulation with the smaller FPM was associated with less-effective bronchoprotection, although there was no difference in bronchodilatation. This study did not demonstrate noninferiority of the investigational HFA formulation to the CFC formulation in terms of protection against methacholine-induced bronchial hyperresponsiveness.

Success of non-traditional students in an undergraduate occupational therapy programme.

An exit survey designed to examine the experiences of occupational therapy undergraduates was administered to 365 students in a four-year honours programme. The survey had a response rate of 51% (186). The survey was informed and supplemented by focus groups with international students and computer-mediated conferencing with community leaders from relevant ethnic minorities. Results showed that older students and those with non-traditional entry qualifications in this sample were as successful as school-leaver entrants (those with UK A Level qualifications). There were no significant differences between the support needs of the groups and previous experience did not have a beneficial or significant effect on support needs. Having to maintain part-time employment significantly increased the likelihood that students would consider withdrawing from the programme. For those who considered withdrawing but who went on to successful completion, the desire to practise occupational therapy following their successful experiences in the programme was a powerful motivator.