We optimized and conducted an experimental program for the real-time monitoring of non-methane hydrocarbon instruments using the direct method. Changing the enrichment and specially designed columns further improved the test effect. The results correct the measurement errors that have prevailed for many years and can lay a foundation for the evaluation of volatile organic compounds in the regional ambient air and provide direction for the measurement of low-concentration ambient air pollutants.

We experimentally investigated vapor wall loss of n-alkanes in a Teflon chamber across a wide temperature range. Increased wall loss was observed at lower temperatures. Further analysis suggests that lower temperature enhances partitioning of n-alkanes to surface layer of Teflon wall but slows their diffusion into inner layer. The results are important for quantitative analysis of chamber experiments conducted at low temperatures, simulating wintertime or under upper tropospheric conditions.

A network of low-cost sensors is a good alternative to improve the detection of fugitive CH₄ emissions. We present the results of four tests conducted with two types of Figaro sensors that were assembled on four chambers in a laboratory experiment: a comparison of five models to reconstruct the CH₄ signal, a strategy to reduce the training set size, a detection of age effects in the sensors and a test of the capability to transfer a model between chambers for the same type of sensor.

Water vapor absorption in the near-UV region is essential to describe the energy budget of Earth; however, there is little spectroscopic information available. And accurate near-UV water absorption is also required in both ground-based observations and satellite missions for trace gas species. Here, we provide the high-resolution spectra of water vapor around 415 nm measured with cavity ring-down spectroscopy. These absorption lines have never been experimentally verified before.

Building on the identification of hundreds of gas-phase chemicals in smoke samples from laboratory and field studies, an algorithm was developed that successfully identified chemical patterns that were consistent among types of trees and unique between types of trees that are common fuels in western coniferous forests. The algorithm is a promising approach for selecting chemical speciation profiles for air quality modeling using a highly reduced suite of measured compounds.