Combining Positive Matrix Factorization and Radiocarbon Measurements for Source Apportionment of PM_2.5 from a National Background Site in North China.

ABSTRACT: To explore the utility of combining positive matrix factorization (PMF) with radiocarbon (¹⁴C) measurements for source apportionment, we applied PM_2.5 data collected for 14 months at a national background station in North China to PMF models. The solutions were compared to ¹⁴C results of four seasonally averaged samples and three outlier samples. Comparing the most readily interpretable PMF solutions and ¹⁴C results revealed that PMF modeling was well able to capture the source patterns of PM_2.5 with two and three irrelevant source classifications for the seasonal and outlier samples. The contribution of sources that could not be classified as either fossil or non-fossil sources in the PMF solution, and the errors between the modeled a

SUBMITTER: Wang X 

PROVIDER: S-EPMC5587569 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature