ABSTRACT
The objective of this study was to improve the vehicular emissions inventory for the light- and heavy-duty fleet in the metropolitan area of São Paulo (MASP), Brazil. To that end, we measured vehicle emissions in road tunnels located in the MASP. On March 22-26, 2004 and May 04-07, 2004, respectively, CO, CO2, NOx, SO2, and volatile organic compounds (VOCs) emissions were measured in two tunnels: the Janio Quadros, which carries light-dutyvehicles; and the Maria Maluf, which carries light-duty vehicles and heavy-duty diesel trucks. Pollutant concentrations were measured inside the tunnels, and background pollutant concentrations were measured outside of the tunnels. The mean CO and NOx emission factors (in g km(-1)) were, respectively, 14.6 +/- 2.3 and 1.6 +/- 0.3 for light-duty vehicles, compared with 20.6 +/- 4.7 and 22.3 +/- 9.8 for heavy-duty vehicles. The total VOCs emission factor for the Maria Maluf tunnel was 1.4 +/- 1.3 g km(-1). The main VOCs classes identified were aromatic, alkane, and aldehyde compounds. For the heavy-duty fleet, NOx emission factors were approximately 14 times higher than those found for the light-duty fleet. This was attributed to the high levels of NOx emissions from diesel vehicles.
Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Environmental Monitoring/methods , Fossil Fuels/analysis , Vehicle Emissions/analysis , Air Movements , Air Pollutants/chemistry , Brazil , Carbon Monoxide/analysis , Motor Vehicles , Nitric Oxide , Polycyclic Aromatic Hydrocarbons/analysis , TransportationABSTRACT
The cooperative oncology group for Chemotherapy of Gastrointestinal Tumors (CGT) retrospectively examined 139 patients with metastatic colorectal cancer for prognostic factors. Clinical characteristics, tumor parameters, and blood parameters were investigated for prognostic explanation of survival from the start of chemotherapy for the advanced disease. A combination of a univariate regression and a multivariate step down procedure with Cox's regression model led to the identification of performance status, sex, white blood count and, to a lesser degree, blood sedimentation rate and albumin as important prognostic factors. Based on these variables an individual risk score was calculated for each patient.