Evaluation of Bias in the Measurement of Condensable Particulate Matter with Method 202

ABSTRACT

The present study evaluated the positive and negative biases in measurements of condensable particulate matter (CPM) conducted according to U.S. EPA Method 202. To reduce the overestimation of CPM, four factors were investigated: the SO₂ absorption, condensate volume, oxygen content, and residence time. The underestimation was assessed by examining the weight loss related to the electrostatic charge of the evaporation beaker, vapor pressure of the particles, volume of the rinsing solvent, size of the evaporation beaker, and leakage between the filter paper and its holder. Additionally, we constructed a forced ventilation chamber to decrease the drying time of the sampled CPM’s organic fraction. The results revealed that our homemade condensate-diverting impinger could neither eliminate nor reduce the artifacts produced by SO₂, as the SO₂ had already oxidized by the time it passed through the Graham condenser and interacted with water. Since the residence time, condensate volume, and oxygen content can all exacerbate the overestimation of CPM, field sampling should be performed as quickly as possible. Furthermore, the evaporation beaker should be electrostatically neutralized prior to its weighing. Nitrogen purging may reduce the mass of the particle fraction possessing high vapor pressure, as these substances are highly volatile. Also, we found that when we used a smaller beaker, less residual mass remained in it after transferring the CPM sample to the weighing tin. We measured a 4% loss in particles due to the gap between the filter paper and the filter paper holder provided by the original manufacturer; therefore, a gasket to minimize leakage is recommended. Finally, the organic fraction required only 1.5–2.5 h of drying time when it was placed in the forced ventilation chamber, and a sample recovery rate of > 98.5% was subsequently achieved. Although artifacts produced by SO₂ are inevitable, the improvements we suggest can enhance the precision of PM_2.5 measurements.