Sensitivity Modeling Study for an Ozone Occurrence during the 1996 Paso Del Norte Ozone Campaign

Surface ozone pollution has been a persistent environmental problem in the US and Europe as well as the developing countries. A key prerequisite to find effective alternatives to meeting an ozone air quality standard is to understand the importance of local anthropogenic emissions, the significance of biogenic emissions, and the contribution of long-range transport. In this study, an air quality modeling system that includes chemistry and transport, CMAQ, an emission processing model, SMOKE, and a mesoscale numerical meteorological model, WRF, has been applied to investigate an ozone event occurring during the period of the 1996 Paso del Norte Ozone Campaign. The results show that the modeling system exhibits the capability to simulate this high ozone occurrence by providing a comparable temporal variation of surface ozone concentration at one station and to capture the spatial evolution of the event. Several sensitivity tests were also conducted to identify the contributions to high surface ozone concentration from eight VOC subspecies, biogenic VOCs, anthropogenic VOCs and long-range transportation of ozone and its precursors. It is found that the reductions of ETH, ISOP, PAR, OLE and FORM help to mitigate the surface ozone concentration, and like anthropogenic VOCs, biogenic VOC plays a nonnegligible role in ozone formation. But for this case, long-range transport of ozone and its precursors appears to produce an insignificant contribution

Exploring methods for routine atmospheric corrections for the red, near-infrared, and thermal bands of NOAA-14 AVHRR images

Includes bibliographical references (pages [74]-77)Radiances sensed by radiometers boarded on satellites are altered by transmitting through the atmosphere. Accurate correction for atmospheric degradation is currently based on modeling the physical behavior o f radiation as it passes through the atmosphere. An important limitation for the physical model is the requirement for detailed meteorological information pertaining to atmospheric humidity and the concentrations of atmospheric particles. Such data may be difficult to obtain in the necessary detail and may apply only to a few points during intensive field experiments. Routine application o f such a model is not now practicable. The objective o f this research is to develop (1 ) a simplified approach for atmospheric corrections for reflectances by using the unique spectral signature of the clear water pixel in satellite images and (2) a simplified method for retrieving land surface temperature from satellite radiances at the thermal bands. Under various clear-sky conditions, a radiative transfer model is used to generate the functional relationships between the atmospheric radiation properties such as scattering coefficient and the radiation caused by the atmosphere above the water body. The parameters, which are used to compute surface radiances, are evaluated with water vapor density and surface air temperature by using the radiative transfer model. Satellite view and solar zenith angles are also considered in developing algorithms. The applications o f the ABSTRACT algorithms to clear days show that the algorithms provide reasonable estimations of reflectances and Normalized Difference Vegetation Index (NDVI) values compared with the physically based atmospheric radiative transfer model and a good approximation o f surface temperature compared with observation. Although the algorithms are based on the characteristics o f the spectral bands on the National Oceanographic and Atmospheric Administration (NOAA-14) Advanced Very High Resolution Radiometer (AVHRR) sensor, the approaches may by applied to other satellite data.M.S. (Master of Science

Sensitivity Modeling Study for an Ozone Occurrence during the 1996 Paso Del Norte Ozone Campaign

Surface ozone pollution has been a persistent environmental problem in the US and Europe as well as the developing countries. A key prerequisite to find effective alternatives to meeting an ozone air quality standard is to understand the importance of local anthropogenic emissions, the significance of biogenic emissions, and the contribution of long-range transport. In this study, an air quality modeling system that includes chemistry and transport, CMAQ, an emission processing model, SMOKE, and a mesoscale numerical meteorological model, WRF, has been applied to investigate an ozone event occurring during the period of the 1996 Paso del Norte Ozone Campaign. The results show that the modeling system exhibits the capability to simulate this high ozone occurrence by providing a comparable temporal variation of surface ozone concentration at one station and to capture the spatial evolution of the event. Several sensitivity tests were also conducted to identify the contributions to high surface ozone concentration from eight VOC subspecies, biogenic VOCs, anthropogenic VOCs and long-range transportation of ozone and its precursors. It is found that the reductions of ETH, ISOP, PAR, OLE and FORM help to mitigate the surface ozone concentration, and like anthropogenic VOCs, biogenic VOC plays a nonnegligible role in ozone formation. But for this case, long-range transport of ozone and its precursors appears to produce an insignificant contribution

Differences in the variability of measured and forecasted Tropospheric ozone mixing ratios over the Paso del Norte Region

The objective of this study is to present differences in the variability of observed and ozone-mixing ratios simulated by a three-dimensional atmospheric chemical model using two chemical mechanisms. In this study the Comprehensive Air Quality Model with Extensions is used to make ozone simulations with the Carbon Bond mechanism, versions 4 and 5. The Paso del Norte region is used as a test-bed for these simulations. The shared variance between the simulations and measurements is typical for air quality models ranging from 0.51 to 0.86 for both mechanisms. The smallest mean normalized gross error is about 31 % with CB4 but the normalized bias is over 30 % as well. Boundary conditions, emissions and other factors affect the levels of ozone of the simulated mixing ratios and therefore error and bias but these factors have a much less affect on the simulated ozone variability. The differences in the ozone variability of the measurements and the simulations are very large and different for the two chemical mechanisms. There are many more instances of low ozone mixing ratios in the measurements than in the simulated ozone. One possible explanation is that these differences are due to problems associated with comparing point measurements with grid averages. A more disturbing possibility is that the bias could be due to the procedures used in the development and testing of air quality modeling systems. Air quality mechanisms are evaluated against environmental chamber data where the chemistry occurs at high concentrations and this may lead to a systematic positive bias in ozone simulations

Multiseason evaluation of the MM5, COAMPS and WRF over southeast United States

Three models, MM5, COAMPS, and WRF, have been applied for the warm season in 2003 and the cool season in 2003-2004 to evaluate their performances. All models run over the same domain area covering the north Gulf Mexico and southeastern United States (US) region with the same spatial resolution of 27 km. It was found that the temporal variations of the mean error distribution and strength at 24 and 36 h were rather weak for surface temperature, sea level pressure, and surface wind speed for all models. A warm bias in surface temperature forecasts dominated over land during the warm season, whereas a cool bias existed during the cool season. The MM5 and WRF produced negative biases of sea level pressure during the warm season and positive biases during the cool season while the COAMPS yielded a similar distribution of sea level pressure biases during both seasons. During both seasons, similar surface wind speed biases produced by each model included a high wind speed forecast over most areas by MM5 while the COAMPS and WRF yielded weak surface winds over the western Plains and stronger surface winds over the eastern Plains. Root-mean-squared errors revealed that the forecast of surface temperature, sea level pressure, and surface wind speed were degraded with the increase of forecast time. For rainfall evaluation, it was found that the MM5 underpredicted seasonal precipitation while the COAMPS and WRF overpredicted. The bias scores revealed that the MM5 yielded an underprediction of the coverage of precipitation areas, especially for heavier rainfall events. The MM5 presented the lower threat score at lighter rainfall events compared to the COAMPS and WRF. For moderate and heavier thresholds, all models lacked forecast accuracy. The WRF accuracy in predicting precipitation was heavily dependent upon the performance of the selected cumulus parameterization scheme. Use of the Grell-Devenyi and Bette-Miller-Janjic schemes helps suppress precipitation overprediction. © 2011 Springer-Verlag

Paenibacillus assamensis in Joint Fluid of Man with Suspected Tularemia, China

Paenibacillus assamensis is a bacterium usually found in warm springs. We detected P. assamensis in a man with suspected tularemia. The strain isolated from the man’s knee joint fluid was identified as P. assamensis after analysis of a homologous sequence of the 16S rRNA gene

Novel fully automated and parallel gas assisted dynamic accelerated solvent extractor and parallel solvent evaporator for analysis of solid and semi-solid samples

The extraction of non-volatile and semi-volatile analytes from solid and semisolid samples has been primarily carried out via heated and/or pressurized liquid extraction mechanisms. Although analyte extraction and concentration processes have significantly evolved and currently several automated solutions are commercially available, these two steps are carried out independently. To the best of our knowledge, human intervention is always required throughout the entire process for sample extract manipulation/transportation among instruments/processes. Expectedly, excessive sample handling throughout the analytical workflow contributes to an increase in the analysis cost, the loss of analyte (s), and numerous potential analytical errors. Herein, we present the first fully automated sample-to-vial solution for analysis of non-volatile and semi-volatile compounds from solid and semisolid samples. This technological development, which is based on gas assisted dynamic accelerated solvent extraction (GA-dASE) and an integrated level-sensing system that controls the endpoint of the evaporation step, allows for fully automated analyte extraction and analyte enrichment. As a proof of concept, we applied this fully automatic extraction and enrichment system towards the quantitative determination of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs) in soil samples. Our results showed that GA-dASE not only matched the performance of the legacy accelerated solvent extraction (ASE), in terms of analyte recovery and reproducibility, but also delivered nearly 3-time reduction in labor per sample. Furthermore, our experiments demonstrated the capability of the instrument to perform fully automated extraction and evaporation steps without human intervention and with no impact on data quality (Relative Standard Deviation, RSD, ≤ 20%). In terms of interlaboratory reproducibility (n = 2), our results showed comparable results for the determination of PAHs using either 10- or 100-mL sample cells