Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada's Regional Air Quality Deterministic Prediction System.

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr. IMPLICATIONS: This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.

Modeling of time-resolved light extinction and its applications to visibility management in the Lower Fraser Valley of British Columbia, Canada.

UNLABELLED: Fine particulate matter (PM2.5) is the dominant cause of atmospheric visibility degradation in the Lower Fraser Valley (LFV) of British Columbia, where poor visibility due to air pollution is of concern. The spatial coverage of the current LFV visibility monitoring network is relatively low, with large parts of the airshed not being represented. Given the desire on the part of local and regional governments to manage visibility in the LFV airshed, the development of a method that allows near real-time estimation of 1-hr light extinction data from the dense network of PM measurements would be highly beneficial. This paper describes a simple linear algorithm, developed using the Hybrid method, to estimate near real-time 1-hr total light extinction at four monitoring sites in the LFV. Model inputs include ambient hourly PM2.5, NO2, relative humidity measurements, and historical monthly-averaged aerosol composition. The results indicate that the developed model can provide relatively accurate and time-resolved estimates of extinction in regions where visibility is not being monitored, thus extending the spatial coverage of the regional visibility monitoring network. The model was also applied to a number of policy-related scenarios to inform visual air quality management in the study area. Results indicated that in order to achieve a perceptible improvement (1.0 deciview) relative to baseline average visibility conditions in the LFV airshed, average ambient PM2.5 concentration would have to decrease by 17% from baseline conditions. Furthermore, to achieve a 20% increase in the number of daylight hours with "excellent" visibility, average PM2.5 would need to be reduced by 30%. Model simulations also indicated that "across-the-board" emission reduction policies would result in greater improvements for the "worst 20%" visibility conditions than for the "best 20%" conditions, suggesting that reducing the number of "poor" visibility days would be easier than improving the number of "excellent" visibility days. IMPLICATIONS: This study describes the development of a model using standard air quality monitoring data (PM2.5, NO2, relative humidity, and PM speciation profiles) to provide near real-time estimates of time-resolved extinction in regions where direct optical monitoring is not available. Applications of the model include extension of spatial coverage of a visibility network, testing various air quality scenarios to inform visibility management, and as a tool for setting visual air quality standards in impacted airsheds.

Synergistic interaction between fentanyl and bupivacaine given intrathecally for labor analgesia.

BACKGROUND: Lipophilic opioids and local anesthetics are often given intrathecally in combination for labor analgesia. However, the nature of the pharmacologic interaction between these drugs has not been clearly elucidated in humans. METHODS: Three hundred nulliparous women randomly received 1 of 30 different combinations of fentanyl and bupivacaine intrathecally using a combined spinal-epidural technique for analgesia in the first stage of labor. Visual analogue scale pain scores were recorded for 30 min. Response was defined by percentage decrease in pain score from baseline at 15 and 30 min. Dose-response curves for individual drugs were fitted to a hyperbolic dose-response model using nonlinear regression. The nature of the drug interaction was determined using dose equivalence methodology to compare observed effects of drug combinations with effects predicted by additivity. RESULTS: The derived dose-response models for individual drugs (doses in micrograms) at 15 min were: Effect = 100 × dose / (13.82 + dose) for fentanyl, and Effect = 100 × dose / (1,590 + dose) for bupivacaine. Combinations of fentanyl and bupivacaine produced greater effects than those predicted by additivity at 15 min (P < 0.001) and 30 min (P = 0.015) (mean differences, 9.1 [95% CI, 4.1-14.1] and 6.4 [95% CI, 1.2-11.5] units of the normalized response, respectively), indicating a synergistic interaction. CONCLUSIONS: The pharmacologic interaction between intrathecal fentanyl and bupivacaine is synergistic. Characterization and quantification of this interaction provide a theoretical basis and support for the clinical practice of combining intrathecal opioids and local anesthetics.