Carbon Monoxide in an Urban Environment: Application of a Receptor Model for Source Apportionment

Abstract

During the winter of 1985-86 the authors took 6-h integrated air samples and measured the concentrations of carbon monoxide and other gases at a residential site in Olympia, Washington. The 6-h average concentrations were between about 0.2 and 3.2 ppmv. For each 6-h period the observed concentration of CO was apportioned among its sources which were residential wood burning and automobiles. Small and generally insignificant amounts of CO were also observed from unidentified sources. A chemical mass balance (CMB) was formulated and applied to apportion the observed CO among its sources. Methylchloride (CH₃CI), in excess of background levels, was used as a unique tracer of wood burning and excess hydrogen (H₂) served as a tracer of CO from automobiles. The source emission factors to carry out the calculations were estimated from other experiments. The results showed that in Olympia, wood burning can often contribute as much CO as automobiles during winter. The maximum 6-h average contribution of CO from wood burning was about 2 ppmv and from automobiles it was 2.2 ppmv, and the average ambient concentration was about 1 ppmv. When pollution from wood burning was present, it contributed 0.5 ppmv on average while automobiles also contributed 0.5 ppmv. Unidentified sources contributed 0.1 ppmv and the background level was 0.15 ppmv. During the winter many times wood burning did not affect CO concentrations, while CO from automobiles was always present. On average, during the winter, automobiles contributed some 50 percent of the CO mass to the lower urban atmosphere and wood burning contributed about 30 percent. Diurnal cycles became evident in the calculated concentrations of CO from wood burning and automobiles even though the measured concentrations did not show strong diurnal variations. Wood burning contributed most during evening and nighttime and very little during the day, while automobiles contributed most during the morning and evening hours and very little at night. These patterns lend support to the accuracy of the model and source emission factors since they are as expected from the diurnal variations of the sources and atmospheric mixing.