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Introduction: Refractory status asthmaticus (Rsa) is a severe, life-threatening form of asthma exacerbation that persists despite aggressive treatment with systemic corticosteroids, bronchodilators, and other supportive measures. omalizumab, a monoclonal antibody that targets Ige, has been approved for treating severe allergic asthma and is effective in reducing the frequency of exacerbations and improving asthma control. Limited evidence exists regarding the use of omalizumab in Rsa, but some studies have suggested that it may have a role in its management. Case: a 39-year-old male with a decade-long history of asthma presented to the emergency department intubated and unresponsive to pharmacological therapy. the patient's Ige levels were elevated, and omalizumab was administered after a comprehensive evaluation. the patient made a dramatic recovery and was successfully weaned off the ventilator within 24 h of receiving omalizumab. He made an uneventful recovery and was discharged home on omalizumab once every two weeks with regular follow-ups. Discussion and conclusion: per our literature search, only 3 cases have been reported where omalizumab was administered to patients with Rsa to wean them off ventilatory support successfully. this case study adds to the existing data on the potential benefits of omalizumab in managing Rsa. It suggests it may be a valuable treatment option for patients who do not respond to standard therapy. However, further research is needed to determine the efficacy and safety of omalizumab in this population. [ABSTRACT FROM AUTHOR]

ABSTRACT This study presents an assessment of the performance of the Community Multiscale Air Quality (CMAQ) photochemical model in forecasting daily [PM.sub.2.5] (particulate matter ≤2.5 μm in aerodynamic diameter) mass [...]

ABSTRACT Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components [...]

ABSTRACT Recent improvements in integrated and continuous [PM.sub.2.5] mass and chemical measurements from the Supersite program and related studies in the past decade are summarized. Analytical capabilities of the measurement [...]

ABSTRACT Source apportionment of fine particles ([PM.sub.2.5], particulate matter < 2 µm in aerodynamic diameter) is important to identify the source categories that are responsible for the concentrations observed at [...]

ABSTRACT Results from six continuous and semicontinuous black carbon (BC) and elemental carbon (EC) measurement methods are compared for ambient samples collected from December 2003 through November 2004 at the [...]

The use of low-cost sensors (LCS) in air quality monitoring has been gaining interest across all walks of society, including community and citizen scientists, academic research groups, environmental agencies, and the private sector. Traditional air monitoring, performed by regulatory agencies, involves expensive regulatory-grade equipment and requires ongoing maintenance and quality control checks. The low-price tag, minimal operating cost, ease of use, and open data access are the primary driving factors behind the popularity of LCS. This study discusses the role and associated challenges of PM2.5 sensors in monitoring air quality. We present the results of evaluations of the PurpleAir (PA.) PA-II LCS against regulatory-grade PM2.5 federal equivalent methods (FEM) and the development of sensor calibration algorithms. The LCS calibration was performed for 2 to 4 weeks during December 2019-January 2020 in Raleigh, NC, and Delhi, India, to evaluate the data quality under different aerosols loadings and environmental conditions. This exercise aims to develop a robust calibration model that uses PA measured parameters (i.e., PM2.5, temperature, relative humidity) as input and provides bias-corrected PM2.5 output at an hourly scale. Thus, the calibration model relies on simultaneous measurements of PM2.5 by FEM as target output during the calibration model development process. We applied various statistical and machine learning methods to achieve a regional calibration model. The results from our study indicate that, with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors within 12 % percentage mean absolute bias at hourly and within 6 % for a daily average. Our study also suggests that pre-deployment calibrations developed at local or regional scales should be performed for the PA sensors to correct data from the field for scientific data analysis. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology for estimating gridded fields of total and speciated fine particulate matter (PM2.5) concentrations for time periods and regions not covered by observational data. The methodology is based on performing long-term regional scale meteorological and air quality simulations and then integrating these simulations with available observational data. To illustrate this methodology, we present an application in which year-round simulations with a meteorological model (the National Center for Atmospheric Research/Penn State Mesoscale Model, hereafter referred to as MM5) and a photochemical air quality model (the Community Multiscale Air Quality Model, hereafter referred to as CMAQ) have been performed over the northeastern United States for 1988–2005. Model evaluation results for total PM2.5 mass and individual species for the time period from 2000 to 2005 show that model performance varies by species, season, and location. Therefore, an approach is developed to adjust CMAQ output with factors based on these three variables. The adjusted model values for total PM2.5 mass for 2000–2005 are compared against independent measurements not utilized for the adjustment approach. This comparison reveals that the adjusted model values have a lower root mean square error (RMSE) and higher correlation coefficients than the original model values. Furthermore, the PM2.5 estimates from these adjusted model values are compared against an alternate method for estimating historic PM2.5 values that is based on PM2.5/PM10 ratios calculated at co-located monitors. Results reveal that both methods yield estimates of historic PM2.5 mass that are broadly consistent; however, the adjusted CMAQ values provide greater spatial coverage and information for PM2.5 species in addition to total PM2.5 mass. Finally, strengths and limitations of the proposed approach are discussed in the context of potential uses of this method. [Copyright &y& Elsevier]

Results from six continuous and semicontinuous black carbon (BC) and elemental carbon (EC) measurement methods are compared for ambient samples collected from December 2003 through November 2004 at the Fresno Supersite in California. Instruments included a multi-angle absorption photometer (MAAP; λ = 670 nm); a dual-wavelength (λ = 370 and 880 nm) aethalometer; seven-color (λ = 370, 470, 520, 590, 660, 880, and 950 nm) aethalometers; the Sunset Laboratory carbon aerosol analysis field instrument; a photoacoustic light absorption analyzer (λ -= 1047 nm); and the R&P 5400 ambient carbon particulate monitor. All of these acquired BC or EC measurements over periods of 1 min to 1 hr. Twenty-four-hour integrated filter samples were also acquired and analyzed by the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical reflectance carbon analysis protocol. Site-specific mass absorption efficiencies estimated by comparing light absorption with IMPROVE EC concentrations were 5.5m²/g for the MAAP, 10 m²/g for the aethalometer at a wavelength of 880 nm, and 2.3 m²/g for the photoacoustic analyzer; these differed from the default efficiencies of 6.5, 16.6, and 5 m²/g, respectively. Scaling absorption by inverse wavelength did not provide equivalent light absorption coefficients among the instruments for the Fresno aerosol measurements. Ratios of light absorption at 370 nm to those at 880 nm from the aethalometer were nearly twice as high in winter as in summer. This is consistent with wintertime contributions from vehicle exhaust and from residential wood combustion, which is believed to absorb more shorter-wavelength light. To reconcile BC and EC measurements obtained by different methods, a better understanding is needed of the wavelength dependence of light-absorption and mass-absorption efficiencies and how they vary with different aerosol composition. [ABSTRACT FROM AUTHOR]