Marwan Katurji

Direct measurement of toxicants inhaled by water pipe users in the natural environment using a real-time in situ sampling technique.

While narghile water pipe smoking has become a global phenomenon, knowledge regarding its toxicant content and delivery, addictive properties, and health consequences is sorely lagging. One challenge in measuring toxicant content of the smoke in the laboratory is the large number of simplifying assumptions that must be made to model a “typical” smoking session using a smoking machine, resulting in uncertainty over the obtained toxicant yields. In this study, we develop an alternative approach in which smoke generated by a human water pipe user is sampled directly during the smoking session. The method, dubbed real-time in situ sampling (RINS), required developing a self-powered portable instrument capable of automatically sampling a fixed fraction of the smoke generated by the user. Instrument performance was validated in the laboratory, and the instrument was deployed in a field study involving 43 ad libitum water pipe use sessions in Beirut area cafés in which we measured inhaled nicotine, carbon monoxide (CO), and water pipe ma’ssel-derived “tar.” We found that users drew a mean of 119 L of smoke containing 150 mg of CO, 4 mg of nicotine, and 602 mg of ma’ssel-derived “tar” during a single use session (mean duration = 61 min). These first direct measurements of toxicant delivery demonstrate that ordinary water pipe use involves inhaling large quantities of CO, nicotine, and dry particulate matter. Results are compared with those obtained using the Beirut method smoking machine protocol.

Mapping Daily Air Temperature for Antarctica Based on MODIS LST

Spatial predictions of near-surface air temperature ( T a i r ) in Antarctica are required as baseline information for a variety of research disciplines. Since the network of weather stations in Antarctica is sparse, remote sensing methods have large potential due to their capabilities and accessibility. Based on the MODIS land surface temperature (LST) data, T a i r at the exact time of satellite overpass was modelled at a spatial resolution of 1 km using data from 32 weather stations. The performance of a simple linear regression model to predict T a i r from LST was compared to the performance of three machine learning algorithms: Random Forest (RF), generalized boosted regression models (GBM) and Cubist. In addition to LST, auxiliary predictor variables were tested in these models. Their relevance was evaluated by a Cubist-based forward feature selection in conjunction with leave-one-station-out cross-validation to reduce the impact of spatial overfitting. GBM performed best to predict T a i r using LST and the month of the year as predictor variables. Using the trained model, T a i r could be estimated with a leave-one-station-out cross-validated R 2 of 0.71 and a RMSE of 10.51 ∘ C. However, the machine learning approaches only slightly outperformed the simple linear estimation of T a i r from LST ( R 2 of 0.64, RMSE of 11.02 ∘ C). Using the trained model allowed creating time series of T a i r over Antarctica for 2013. Extending the training data by including more years will allow developing time series of T a i r from 2000 on.

The Influence of Topography and Ambient Stability on the Characteristics of Cold-Air Pools: A Numerical Investigation

AbstractA high-resolution numerical investigation of a cold-air pooling process (under quiescent conditions) is carried out that systematically highlights the relations between the characteristics of the cold-air pools (e.g., slope winds, vertical temperature and wind structure, and cooling rate) and the characteristics of the topography (e.g., basin size and slope angle) under different ambient stabilities. The Advanced Regional Prediction System model is used to simulate 40 different scenarios at 100-m (10 m) horizontal (vertical) resolution. Results are within the range of similar observed phenomena. The main physical process governing the cooling process near the basin floor (<200 m in height) was found to be longwave radiative flux divergence, whereas vertical advection of temperature dominated the cooling process for the upper-basin areas. The maximum downslope wind speed is linearly correlated with both basin size and slope angle, with stronger wind corresponding to larger basin and lower slope ang...

Road versus roadside particle size distribution in a hot Mediterranean summer--estimation of fleet emission factors.

Particle size distribution at major on-road, roadside, and university-ground sites in Lebanon were studied in summer 2011. In a predominant old traffic fleet, it is shown that calculated PM2.5 mass emission factors (EFs) conform to those of heavy duty vehicles. When compared to roads in California, higher PM2.5 mass but similar particle number EFs are obtained for the average fleet of the on-road sites. This confirms the observed particle size distribution pattern, rich in particles in the accumulation range mainly between 0.425 and 0.675 µm with a prevalent peak at 0.475 µm. Corresponding total particle counts (TC) measured on the roadside are as high as 14,050 particles/cm3 and are up to 67% higher than particle counts measured at the university-ground site. In a hot, dry and humid summer weather with consistent temperature oscillations, particle dispersion is shown to be a function of meteorological factors, mainly the effect of the boundary-layer thickness, with particle counts measured during the morning being around 40% higher than particle counts measured during the afternoon. Implications In a hot and humid Mediterranean summer, high emission factors are associated with an old car fleet. The observed diurnal variation in the particle count is attributed to the change in the thickness boundary layer in summer. In comparison to road sites, the particle size distribution shows the prevalence of larger size particles. Particle counts measured at the roadside sites are at least 20% higher than those of the road sites. The findings call for the reinforcement of local regulations on car age. Furthermore, the high number of particles can cause or aggravate a number of health and ecosystem problems.

Characteristics of the Springtime Alpine Valley Atmospheric Boundary Layer Using Self-Organizing Maps

Vertical profiles of wind velocity and air temperature from a sound detection and ranging (sodar) radio acoustic sounding system (RASS)-derived dataset within an alpine valley of the New Zealand Southern Alps were analyzed. The data covered the month of September 2013, and self-organizing maps (SOM; a dataclustering approach that is based on an unsupervised machine-learning algorithm) are used to detect topological relationships between profiles. The results of the SOM were shown to reflect the physical processes within the valley boundarylayerby preservingvalley boundarylayerdynamicsand itsresponseto wind shear. By examining the temporal evolution of ridgetop wind speed and direction and SOM node transitions, the sensitivity of the valley boundary layer to ridgetop weather conditions was highlighted. The approach of using a composite variable (wind speed and potential temperature) with SOM was successful in revealing the coupling of dynamics and atmospheric stability. The results reveal the capabilities of SOM in analyzing large datasets of atmospheric boundary layer measurements and elucidating the connectivity of ridgetop wind speeds and valley boundary layers.

Pseudovertical Temperature Profiles Give Insight into Winter Evolution of the Atmospheric Boundary Layer over the McMurdo Dry Valleys of Antarctica

AbstractMeasuring routine vertical profiles of atmospheric temperature is critical in understanding stability and the dynamics of the boundary layer. Routine monitoring in remote areas such as the McMurdo Dry Valleys (MDV) of Antarctica is logistically difficult and expensive. Pseudovertical profiles that were derived from a network of inexpensive ground temperature sensors planted on valley sidewalls (up to 330 m above valley floor), together with data from a weather station and a numerical weather prediction model, provided a long-term climatological description of the evolution of the winter boundary layer over the MDV. In winter, persistent valley cold pools (VCPs) were common, lasting up to 2 weeks. The VCPs were eroded by warm-air advection from aloft associated with strong winds, increasing the temperature of the valley by as much as 25 K. Pseudovertical datasets as described here can be used for model validation.

Application of a statistical emulator to fire emission modeling

We have demonstrated the use of an advanced Gaussian-Process (GP) emulator to estimate wildland fire emissions over a wide range of fuel and atmospheric conditions. The Fire Emission Production Simulator, or FEPS, is used to produce an initial set of emissions data that correspond to some selected values in the domain of the input fuel and atmospheric parameters for the purpose of training the emulator. The emulated emissions are found to be within ?5% of the FEPS simulated emissions, providing confidence in the potential use of the GP-emulator for this and other similar applications. Cluster analysis for 1000 emulator-produced posterior samples spanning a wide-range of fuel and environmental conditions suggest that the emulator not only produces valid results but also preserves the physical relationships between the fire emission and the fuel and environmental conditions. Results show that the GP-emulator could be used as an alternative to the simulations from the FEPS modeling system when four or more input parameters related to fuel type, fuel moisture, and weather condition are allowed to vary. This work also provides a conceptual basis for constructing a nation-wide emissions inventory based on a trained GP-emulator representing the complex geographic distribution of fuel types and environmental conditions. We emulate a fire emission model (FEPS) with a Gaussian process emulator.Results are within ?5% of the simulated values.GP-emulator could be used as a surrogate to the fire emission model.A conceptual framework for producing nation-wide emission inventory is presented.

Forward-Looking Infrared Cameras for Micrometeorological Applications within Vineyards

We apply the principles of atmospheric surface layer dynamics within a vineyard canopy to demonstrate the use of forward-looking infrared cameras measuring surface brightness temperature (spectrum bandwidth of 7.5 to 14 μm) at a relatively high temporal rate of 10 s. The temporal surface brightness signal over a few hours of the stable nighttime boundary layer, intermittently interrupted by periods of turbulent heat flux surges, was shown to be related to the observed meteorological measurements by an in situ eddy-covariance system, and reflected the above-canopy wind variability. The infrared raster images were collected and the resultant self-organized spatial cluster provided the meteorological context when compared to in situ data. The spatial brightness temperature pattern was explained in terms of the presence or absence of nighttime cloud cover and down-welling of long-wave radiation and the canopy turbulent heat flux. Time sequential thermography as demonstrated in this research provides positive evidence behind the application of thermal infrared cameras in the domain of micrometeorology, and to enhance our spatial understanding of turbulent eddy interactions with the surface.

Antarctic Climate and Soils

Climate change is having a significant impact on the ecosystems of Antarctica and has been the focus of scientific research in the past few decades. Our understanding of how large-scale weather patterns have changed has increased, but there is still way to go before we know how the shift in climate influences temperatures at microscales. Antarctica has one of the most severe climate extremes on the planet; it is the windiest, coldest, and driest. Combined with its geographic isolation, observational studies of climate change have been hampered due to lack of sufficiently dense monitoring systems. The soil exchanges energy with the overlying atmosphere (boundary layer) which influences its temperature through sensible and latent heat fluxes, both are poorly understood in the terrestrial landscapes of Antarctica. It has been shown that at least at the height of biological activity during summer, shifts in weather patterns across the Dry Valleys can have profound impacts on temperature and availability of liquid water, with downstream consequences for the biota. Therefore the terrestrial ecosystem responds rapidly to the larger climate system on a seasonal timescale.