A combined approach for the evaluation of a volatile organic compound emissions inventory.

Emissions inventories significantly affect photochemical air quality model performance and the development of effective control strategies. However, there have been very few studies to evaluate their accuracy. Here, to evaluate a volatile organic compound (VOC) emissions inventory, we implemented a combined approach: comparing the ratios of carbon bond (CB)-IV VOC groups to nitrogen oxides (NOx) or carbon monoxide (CO) using an emission preprocessing model, comparing the ratios of VOC source contributions from a source apportionment technique to NOx or CO, and comparing ratios of CB-IV VOC groups to NOx or CO and the absolute concentrations of CB-IV VOC groups using an air quality model, with the corresponding ratios and concentrations observed at three sites (Maryland, Washington, DC, and New Jersey). The comparisons of the ethene/NOx ratio, the xylene group (XYL)/NOx ratio, and ethene and XYL concentrations between estimates and measurements showed some differences, depending on the comparison approach, at the Maryland and Washington, DC sites. On the other hand, consistent results at the New Jersey site were observed, implying a possible overestimation of vehicle exhaust. However, in the case of the toluene group (TOL), which is emitted mainly from surface coating and printing sources in the solvent utilization category, the ratios of TOL/ NOx or CO, as well as the absolute concentrations revealed an overestimate of these solvent sources by a factor of 1.5 to 3 at all three sites. In addition, the overestimate of these solvent sources agreed with the comparisons of surface coating and printing source contributions relative to NOx from a source apportionment technique to the corresponding value of estimates at the Maryland site. Other studies have also suggested an overestimate of solvent sources, implying a possibility of inaccurate emission factors in estimating VOC emissions from surface coating and printing sources. We tested the impact of these overestimates with a chemical transport model and found little change in ozone but substantial changes in calculated secondary organic aerosol concentrations.

Assessment of surfactants for efficient droplet PCR in mineral oil using the pendant drop technique.

Amplification and detection of nucleic acid sequences within integrated microsystems is routinely conducted using the technique of droplet PCR, wherein the polymerase chain reaction (PCR) is performed in microscale water-in-oil droplets (nanoliter to picoliter volumes). During droplet PCR, interactions at the interface of the droplet tend to dominate. Specifically, adsorption of the polymerase at the droplet interface leads to inefficient amplification. To reduce polymerase adsorption, surfactants such as the silicone-based ABIL EM90 have been commonly used. However, these surfactants have been selected largely through trial and error, and have been only somewhat effective. For example, when using ABIL EM90, 8 times (8 ×) the manufacturer prescribed concentration of polymerase was necessary for amplification. In this report, we use the pendant drop technique to measure adsorption and loss of enzyme at droplet interfaces for various surfactant-oil combinations. Dynamic interfacial tension and surface pressure measurements showed that significant polymerase adsorption occurs when using ABIL EM90. In contrast, much lower polymerase adsorption is observed when using Brij L4, a nonionic surfactant with a C12 tail and an oxyethylene headgroup, which has not yet been reported for droplet PCR. These results correlate strongly with droplet PCR efficiency. Brij L4 enables highly efficient PCR at 2 × polymerase concentration, and still enables effective PCR at 1 × polymerase concentration. Overall, this work introduces a methodology for quantitatively assessing surfactants for use with droplet microreactors, and it demonstrates the practical value of this new approach by identifying a surfactant that can dramatically improve the efficiency of droplet PCR.