Continuous measurement of atmospheric reduced sulphur compounds as key tracers between odour complaints and source apportionment

Observations of volatile organic and sulfur compounds in ambient air and health risk assessment near a paper mill in rural Idaho, U. S. A

The Lewis-Clark Valley is a rural area that includes the cities of Lewiston, Idaho and Clarkston, Washington and the surrounding areas. The largest industry in the Lewis-Clark Valley is a pulp paper mill located in Lewiston which emits particulate matter and odorous sulfur air pollutants. This study analyzed the Lewis-Clark Valley air composition and seasonal, temporal and spatial variations of volatile organic compounds (VOCs) from 2017 to 2018 to determine potential health risks of the paper mill emissions to the surrounding community. Both active and passive air sampling via sorbent tubes were analyzed by thermal desorption - gas chromatography-mass spectrometry (TD-GC-MS). Fifty VOCs including benzene, toluene, chloroform, dimethyl sulfide and dimethyl disulfide were measured in the ambient air of the Lewis-Clark Valley at ten different sites, totaling over 800 samples. In addition, passive sorbent tubes were deployed in 2018 to obtain monthly averages in Lewis-Clark Valley and three urban locations in Idaho and Washington for comparison. United States Environmental Protection Agency (2001) methodology was used to assess cancer risks in the community based on the upper confidence levels of five carcinogens and nine air toxics. The Lewis-Clark Valley had similar levels of benzene to urban areas but had a strong signature of chloroform and sulfides from the paper mill. The cumulative cancer risk was 2 x 10^-6 - 11 × 10^-6 mainly due to the compounds chloroform, benzene and carbon tetrachloride. The hazard index of other air toxics was less than one. Overall, these air pollutants were considered low risk to the local population.

Insight on a comprehensive profile of volatile compounds of Chlorella vulgaris extracted by two "green" methods

Some green extraction methods were selected and tested for the extraction of volatile compounds from different samples of the microalga Chlorella vulgaris: ultrasound-assisted liquid-liquid extraction using environment-friendly solvents (LLE) and solid-phase microextraction (SPME). The obtained profiles of volatile chemical compounds were different. Only one molecule was found in common to both extractions. Using the SPME method, the main chemical classes of identified volatile compounds were sulfuric compounds, aldehydes, and alcohols. Using the LLE method, the volatile profile was more balanced with alkanes, fatty acids, terpenes, alcohols, and aldehydes. Multivariate data analyses permitted discrimination among samples. Additionally, the relationship between the physicochemical properties of identified volatile compounds and the methods of extraction was studied. The results showed that the LLE extraction allowed the extraction of volatile compounds having a high boiling point (>160°C) and a high log P (>3). The SPME method was more effective to extract volatile compounds with a low boiling point (<160°C) and a low log P (<3). It is thus necessary to combine several extraction methods to obtain a complete view of the volatile profile for microalgae samples.

The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment

The olfactory evaluation function (e.g., odor intensity rating) of e-nose is always one of the most challenging issues in researches about odor pollution monitoring. But odor is normally produced by a set of stimuli, and odor interactions among constituents significantly influenced their mixture’s odor intensity. This study investigated the odor interaction principle in odor mixtures of aldehydes and esters, respectively. Then, a modified vector model (MVM) was proposed and it successfully demonstrated the similarity of the odor interaction pattern among odorants of the same type. Based on the regular interaction pattern, unlike a determined empirical model only fit for a specific odor mixture in conventional approaches, the MVM distinctly simplified the odor intensity prediction of odor mixtures. Furthermore, the MVM also provided a way of directly converting constituents’ chemical concentrations to their mixture’s odor intensity. By combining the MVM with usual data-processing algorithm of e-nose, a new e-nose system was established for an odor intensity rating. Compared with instrumental analysis and human assessor, it exhibited accuracy well in both quantitative analysis (Pearson correlation coefficient was 0.999 for individual aldehydes (n = 12), 0.996 for their binary mixtures (n = 36) and 0.990 for their ternary mixtures (n = 60)) and odor intensity assessment (Pearson correlation coefficient was 0.980 for individual aldehydes (n = 15), 0.973 for their binary mixtures (n = 24), and 0.888 for their ternary mixtures (n = 25)). Thus, the observed regular interaction pattern is considered an important foundation for accelerating extensive application of olfactory evaluation in odor pollution monitoring.