Can positive matrix factorization help to understand patterns of organic trace gases at the continental Global Atmosphere Watch site Hohenpeissenberg?
Abstract. From the rural Global Atmosphere Watch (GAW) site Hohenpeissenberg in the pre-alpine area of southern Germany, a data set of 24 C2–C8 non-methane hydrocarbons over a period of 7 years was analyzed. Receptor modeling was performed by positive matrix factorization (PMF) and the resulting factors were interpreted with respect to source profiles and photochemical aging. Differing from other studies, no direct source attribution was intended because, due to chemistry along transport, mass conservation from source to receptor is not given. However, at remote sites such as Hohenpeissenberg, the observed patterns of non-methane hydrocarbons can be derived from combinations of factors determined by PMF. A six-factor solution showed high stability and the most plausible results. In addition to a biogenic and a background factor of very stable compounds, four additional anthropogenic factors were resolved that could be divided into two short- and two long-lived patterns from evaporative sources/natural gas leakage and incomplete combustion processes. The volume or mass contribution at the site over the entire period was, in decreasing order, from the following factor categories: background, gas leakage and long-lived evaporative, residential heating and long-lived combustion, short-lived evaporative, short-lived combustion, and biogenic. The importance with respect to reactivity contribution was generally in reverse order, with the biogenic and the short-lived combustion factors contributing most. The seasonality of the factors was analyzed and compared to results of a simple box model using constant emissions and the photochemical decay calculated from the measured annual cycles of OH radicals and ozone. Two of the factors, short-lived combustion and gas leakage/long-lived evaporative, showed winter/summer ratios of about 9 and 7, respectively, as expected from constant source estimations. Contrarily, the short-lived evaporative emissions were about 3 times higher in summer than in winter, while residential heating/long-lived combustion emissions were about 2 times higher in winter than in summer.
