Sentence examples for using a source apportionment from inspiring English sources

In the present study, we took advantage of the PM10 (≤ 10 μm in aerodynamic diameter) speciation data that have been available for over a decade to identify contributing sources to PM10 mass using a source apportionment model and then used those data to estimate the acute effects of PM10 sources on daily emergency IHD hospital admissions.

However, the magnitude of the background contribution agreed with those (50 65% at European urban background-sites) reported by Querol et al. (2004), who used a source apportionment method.

We conducted a source apportionment study using particle-phase organic molecular markers in personal and work area samples at a freight terminal in an urban area in 2003 (Sheesley et al. 2008a).

The sensitivity of a source apportionment model to mobile source profiles was examined to determine the impact of using non-local mobile source profiles in chemical mass balance (CMB) models.

A source apportionment analysis for risk of hospital admissions was conducted for Manhattan, New York (Lall et al. 2011).

The MBO-derived organosulfate has the potential to serve as an SOA tracer for a source apportionment method under further investigation.

A source apportionment study of fugitive dust from military training ranges in the western United States (Labban et al. 2004) provided many of the samples.

Predicted versus observed results for total cells and LDH, respectively, are presented in Figure 6B and C. A second analysis using the source apportionment results again indicated that two components were sufficient to explain 77% of the overall variation in the predictors and 52% of the overall variation in the responses.

As noted in Table 1, research groups from seven institutions, using various source apportionment approaches, participated in this workshop.

Using the source apportionment factors from Maciejczyk and Chen (2005), we have the following four source classes: SS, RS, RO, and MV.

This study was conducted to identify and quantify the sources of selected volatile organic compounds (VOCs) and fine particulate matter (PM2.5) by using a partially constrained source apportionment model suitable for multiple time resolution data.