Can positive matrix factorization help to understand patterns of organic trace gases at the continental Global Atmosphere Watch site Hohenpeissenberg?

Abstract

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.

Origin and variability in volatile organic compounds observed at an Eastern Mediterranean background site (Cyprus)

“…In conclusion, factor 2 is also attributed to a biogenic source (mainly driven by isoprene emissions), while factor 1 is characterized by pinenes. Small amounts of C 1 −C 6 alkanes are also found in this profile with a cumulated contribution to factor 2 of 12 % and can be attributed to a mixing with other temperature-related sources or artefacts from the PMF model (Leuchner et al, 2015). CPF analysis of factor 2 localizes the corresponding biogenic emission area in the northwest to the northeast directions from the sampling site with associated distinct land covers: "garrigues" and "other land" (Fig.…”

“…An additional minor continental contribution seems to be associated with the Peloponnese region (Greece -European air masses). As a conclusion, factor 6 can be interpreted as a regional contribution of various remote sources of the Mediterranean region, hence showing the continental regional background (Hellén et al, 2003;Leuchner et al, 2015;Sauvage et al, 2009). These sources were transported towards the receptor site by aged air masses which had not recently been in contact with additional anthropogenic sources.…”

“…The temporal variation was less pronounced on weekends than weekdays (average contribution of 0.5 and 0.7 µg m −3 , respectively) consistent with human activities. This factor was hence attributed to "a short-lived combustion source" (Leuchner et al, 2015;Michoud et al, 2017).…”

“…Over the last decade, this source receptor approach has been intensively used in urban areas (e.g., Baudic et al, 2016;Salameh et al, 2016;Yuan et al, 2012) and in remote/rural environments Leuchner et al, 2015;Michoud et al, 2017;Sauvage et al, 2009). Other receptor models such as principal component analysis/absolute principal component scores (PCA/APCSs) (Guo et al, 2007), UNMIX (Jorquera and Rappenglück, 2004) and chemical mass balance (CMB) (Badol et al, 2008) have been previously used in VOC source apportionment.…”

Organic carbon at a remote site of the western Mediterranean Basin: sources and chemistry during the ChArMEx SOP2 field experiment

“…Positive matrix factorization (PMF) models (Paatero and Tapper, 1994;Paatero, 1997) have been widely used to identify and quantify sources of VOCs, generally in urban environments (e.g., Latella et al, 2005;Leuchner and Rappenglück, 2010;Gaimoz et al, 2011;Yuan et al, 2012). This type of analysis allows for the separation of different sources (e.g., vehicular exhaust, fuel evaporation and residential heating) and the apportionment of those sources to the VOC budget.…”