Pranav Kulkarni

Emissions of Organic Compounds and Trace Metals in Fine Particulate Matter from Motor Vehicles: A Tunnel Study in Houston, Texas

Abstract Fine particulate matter (PM) samples collected in a highway tunnel in Houston, TX, were analyzed to quantify the concentrations of 14 n-alkanes, 12 polycyclic aromatic hydrocarbons, and nine petroleum biomarkers, as well as 21 metals, with the ultimate aim of identifying appropriate tracers for diesel engines. First, an exploratory multivariate dimensionality reduction technique called principal component analysis (PCA) was employed to identify all potential candidates for tracers. Next, emission indices were calculated to interpret PCA results physically. Emission indices of n-heneicosane, n-docosane, n-tricosane, n-tetracosane, n-pentacosane, fluoranthene, and pyrene were correlated highly and increased strongly with percentage carbon present in the tunnel emanating from diesel vehicles. This suggests that these organic compounds are useful molecular markers to separate emissions from diesel and gasoline engines. Additionally, the results are the first quantification of the metal composition of PM with aerodynamic diameters smaller than 2.5 [H9262]m (PM2.5) emissions from mobile sources in Houston. PCA of trace metal concentrations followed by emission index calculations revealed that barium in fine airborne particles can be linked quantitatively to diesel engine emissions, demonstrating its role as an elemental tracer for heavy-duty trucks.

Disinfection by-product formation following chlorination of drinking water: Artificial neural network models and changes in speciation with treatment

Artificial neural network (ANN) models were developed to predict disinfection by-product (DBP) formation during municipal drinking water treatment using the Information Collection Rule Treatment Studies database complied by the United States Environmental Protection Agency. The formation of trihalomethanes (THMs), haloacetic acids (HAAs), and total organic halide (TOX) upon chlorination of untreated water, and after conventional treatment, granular activated carbon treatment, and nanofiltration were quantified using ANNs. Highly accurate predictions of DBP concentrations were possible using physically meaningful water quality parameters as ANN inputs including dissolved organic carbon (DOC) concentration, ultraviolet absorbance at 254nm and one cm path length (UV(254)), bromide ion concentration (Br(-)), chlorine dose, chlorination pH, contact time, and reaction temperature. This highlights the ability of ANNs to closely capture the highly complex and non-linear relationships underlying DBP formation. Accurate simulations suggest the potential use of ANNs for process control and optimization, comparison of treatment alternatives for DBP control prior to piloting, and even to reduce the number of experiments to evaluate water quality variations when operating conditions are changed. Changes in THM and HAA speciation and bromine substitution patterns following treatment are also discussed.

Source Identification and Apportionment of Fine Particulate Matter in Houston, TX, Using Positive Matrix Factorization

Samples of airborne fine particulate matter were collected at three sites in Houston, TX, and were analyzed for elemental concentrations by X-ray fluorescence and inductively coupled plasma-mass spectrometry. Positive Matrix Factorization (PMF) was applied to the elemental concentration data for source identification and apportionment. PMF resolved five physically interpretable factors at each site, of which four were found to be common at all sites: Crustal material, road dust, wood burning, and sea salt. The composition of the remaining factor was similar, but not identical, at the three sites, and had an elemental composition similar to industrial combustion. Crustal material was found to be the most important contributor at each site. All other sources contributed less to the total mass, although road dust source was the second major contributor to the total mass at one site. The sea salt factor was resolved at each site with the highest contribution at the closest site to the coast.

In Situ Generation of Hydrofluoric Acid during Microwave Digestion of Atmospheric Particulate Matter Prior to Trace Element Analysis Using Inductively Coupled Plasma Mass Spectrometry

Results from a systematic evaluation of numerous microwave-assisted digestion techniques to solubilize trace elements from ambient airborne particulate matter prior to analysis using inductively coupled-plasma mass spectroscopy (ICP-MS) are reported. Direct handling of HF was avoided by generating it in situ in closed Teflon-lined vessels during digestion by heating a mixture of NaF, HNO3, and the sample and later complexing any remaining HF using stoichiometric excess of boric acid. The effects of microwave digestion variables including dwell time (20–120 min), temperature (150–200°C), pressure (38–200 psig), acid type (HNO3 and HF), and absence or presence of peroxide on extraction efficiency were determined. Principal component analysis was conducted on the recoveries of 20 elements (Mg, Al, K, Ti, V, Cr, Mn, Fe, Ni, Co, Cu, Zn, As, Rb, Cd, Cs, Ba, La, Pb, and U) from urban particulate matter Standard Reference Material 1648, which revealed that the digestion matrix was the most important variable of a...