Liquid solutions were prepared of the target analytes dissolved in methanol with 0.6 μL injected directly into the GC-MS. Pure standards were of ACS Reagent grade and obtained from Sigma-Aldrich. Components and photographs of the wearable sampler are presented . Examples of GPS, temperature and humidity data are shown . Although the GPS is programmed to acquire a signal every 10 sec, this time occasionally varies. This has a minor effect for the timing of sample collection and increases the power usage slightly. Furthermore, while the sampler is designed for use in indoor and outdoor environments, the GPS signal is too poor for indoor location updates. However, the system stores the last updated location and will record it until the GPS updates again. The system also records whether or not the sampler is receiving a GPS signal. We found that the sampler could be machined and constructed in less than 16 h with a material cost around $400 USD. Almost half of the material cost came from the pump. Per the manufacturer, the pump produces less than 40 dB of noise, meaning it could be heard in a quiet room but would not be a loud disruption. In the sampler, the pump is encased in the aluminum fixture, muffling any noise. We found that the pump was very quiet and could barely be heard in typical use. The device weighed just under 400 g and could fit comfortably attached to the belt of a user. Ways to further reduce the weight include: custom PCBs in place of the commercial microcontroller and GPS; using a custom plastic outer case. Bench marking of the micro preconcentrator chips has been previously described.The work herein focuses on performance of the wearable environmental sampler. We first present evidence that the sampler successfully and reproducibility enables the μPC chip to collect a VOC sample.
The sampler was set a sample time of 10 min and a calibration curve was produced of four chemicals ranging from 300 ppb to 5 ppm . As expected,indoor vertical farm the sampler showed a linear increase of signal with an increase in chemical concentration. R2 values ranged from 0.958–0.999. Two samples were collected per concentration and the relative standard deviation ranged from 7–11%. We continued to collect samples of increasing concentration to profile the limit of linearity for this particular sampling protocol and sorbent. This is not a limitation of the environmental sampler but instead represents saturation of the sorbent within the μPC, where an increase in sample concentration would no longer lead to an increase in signal response. We sampled up to 100 ppm . Above 10 ppm, these four chemicals showed evidence of sorbent saturation for 10 min of sample time: signal increases no longer maintained a linear relationship to increases in sampling concentration. Based on this data, 10 min of sampling time might be best used in environments where VOCs are present in less than 10 ppm. This is largely contingent on the VOCs of interest, which is further discussed below. In addition to varying concentration, we also varied sampling time . There was a steady increase of signal response with longer sampling times from 10 to 60 min for hexane, 2-pentanone and 2-hexanone, and a steady increase from 10 to 90 min for heptane. After these ranges, signals decreased in intensity, suggesting saturation of the preconcentrator sorbent trap inside the sampler. Based on this experiment, a sampling time of less than 60 min might be appropriate in an environment with VOCs around a concentration of 100 ppb. We intended to build a sampler that would be worn by a person for hours at a time and provide a snapshot that was as complete as possible of their integrated VOC exposure. A variety of factors influence such detection goals.
Within the sampler, VOC extraction is influenced by sampling time, flow rate and the preconcentrator chip 19. Furthermore, without advanced knowledge of environmental conditions, it is even more challenging to define an optimized sampling protocol for general use. For instance, the sampler could be optimized to detect VOCs in the parts-per-billion range. If it is then used in situations with high concentrations, the preconcentrator chip would quickly saturate, reducing the quality of any quantitative assessment. The reverse could also occur. Additionally, the μPC chip could be exchanged at a greater frequency which would improve the temporal and spatial resolution of exposure; however, this would put greater requirements on the user and could result in relatively clean samples in unpolluted environments. Finally, it is impossible to create a single method that is optimized to detect every known VOC, as parameter changes have varying effects on classes of compounds . The above tests helped us establish initial sampling guidelines for untargeted analyses in unpredictable environments. Furthermore, we designed the sampler so that parameters can be easily changed or tailored for specific applications. The USB port on the sampler allows users to change these settings via the Adafruit Feather micro-controller. Should a researcher seek targeted analysis, such as user’s exposure to benzene or toluene, sampler parameters such as sampling time, sampling flow rate and sorbent type can be tested, optimized and applied.The environmental sampler was tested outside the lab environment as a handheld device initially by researchers in our group. Different sampling durations, sampling locations, and preconcentrator chips were used for qualitative assessments of the performance the sampler.
Figure 5 shows three deployments of the samplers for a continuous sampling duration of one hour for each run. Samples were collected in a kitchen when the user was cooking , in an institutional hallway when the floors were being stripped and waxed , and in a room where a cat litter box was kept . Table 1 shows putative peak identities of sixteen example compounds, although more were detected. Many of the putatively identified compounds are unsurprising given the context of the samples. The sample taken while the user was cooking included detection of limonene , ocimene and cuminal . A sample taken in a hallway during a floor stripping/waxing yielded high abundances of benzyl alcohol and ethylene glycol monohexyl ether . The cat litter box emitted common fragrance VOCs, such as limonene, eucalyptol and nerol, which can help mask odor. To further test our sampler, we let a representative person of the general public use the device for a week. Under IRB approval, a 17 year old high school student volunteered to test our sampler. The student carried the sampler for 12 h during the day and the sampler automatically collected a 10 min sample every 1 h. The student repeated this for 5 d. This test aided to monitor the experimental performance and get feedback of the user friendliness of the sampler during a lengthy test. The sampler did not interrupt any daily activities of the user, noise due to the sampling pump was negligible, and the student was able to carry the sampler and exchange the preconcentrator chips easily. Raw GC-MS chromatograms of samples collected by the volunteer are shown . Table 2 summarizes the number of VOCs deconvoluted from each chromatogram and also the number of unique VOCs detected in a sample. The user did vary their location during the five days of sampler use,vertical farming equipment with some overlap in location between days, and varied the time spent in each location . It is thus expected that the number of captured VOCs reflected the similarities and differences of the user’s environment. Putative identifications of compounds were performed by comparison of obtained mass spectra to the NIST ‘14 database, providing a list of potential VOCs that the user was exposed to during their day to day activities, as collected by the environmental sampler. A number of naturally occurring VOCs were detected, such as benzeneacetaldehyde, β- myrcene and camphor. Other compounds were potentially artificial in origin, such as lilial and galaxolide, two synthetic fragrances that smell floral and musky, respectively, and likely originated from a scented cosmetic product. As captured by the sampler, the user was potentially exposed to hazardous VOCs, such as ethylbenzene, toluene, phenol and benzoyl chloride. To demonstrate the quantitative capabilities of the sampler, we chose four VOCs that were present in all five of the participant’s samples .
Limonene, menthol and decanal are all common fragrance compounds while 2- butyl-1-octanol is a known humectant. As these compounds appeared in each of this volunteer’s samples, we suspect they may have derived from a personal product that was applied daily. We did not speculate further to the origins of these VOCs as the purpose of this was only to present quantification of chemicals. A calibration curve was constructed to quantify the amount of each chemical retained onto the μPC chip during deployment . Limonene is seen as the most variable, with values ranging from 3.4 to 71.5 ng. Decanal was the most stable with a relative standard deviation of 34% across all five samples. Menthol was found in the lowest abundance . In future work, we hope to deploy these samplers in environments that potentially contain hazardous levels of certain VOCs. Locations would be areas such as California’s Central Valley, which contains multiple sources of air pollution from industry, agriculture and benzene treatment plants. Areas like Paradise, California could also benefit from VOC samplers, since the area is currently recovering from a massive wildfire that has the potential to expose residents to unsafe compounds as they rebuild their community. At these sites, samplers could be used to target dangerous compounds, such as benzene or toluene, and quantify exposure concentrations. The over consumption of nutritive sugars continues to be a major dietary problem in different parts of the world. A recent report indicates than an average American consumes about 17 teaspoons of added sugar daily, which is nearly twice the amounts of the 6 and 9 teaspoons, recommended for women and men, respectively. This dietary behavior is linked to various adverse health effects such as increased risk of diabetes, obesity, high blood pressure and cardiovascular diseases. Hence, there are worldwide efforts to reduce sugar consumption. For instance, the World Health Organization made a conditional recommendation to reduce sugar consumption to less than 5% of the total caloric intake, along with a strong recommendation to keep sugar consumption to less than 10% of the total caloric intake for both adults and children. Currently, added sugar consumption accounts for approximately 11–13% of the total energy intake of Canadian adults, is greater than 13% in the US population, and is as high as 17% in US children and adolescents, the latter principally from sugar-sweetened beverages . Consequently, taxes on SSB have been proposed as an incentive to change individuals’ behavior to reduce obesity and improve health. Notably, the city of Berkeley, CA, USA successfully accomplished a 21% decrease in SSBs consumption within a year of implementation. Therefore, it is expected that more states and cities will adopt this policy. On the regulatory level, the U.S. Food and Drug Administration updated the Nutrition Facts label requirement on packaged foods and beverages, starting 1 January 2020, to declare the amount of added sugars in grams and show a percent daily value for added sugar per serving. The expansion of these efforts to spread the awareness on sugar consumption habits and the resulting health issues has generated demand for safe, non-nutritive sugar substitutes. There are many sweeteners on the market to help consumers satisfy their desire for sweetness; however, each of the sweeteners available to consumers has specific applications and certain limitations. Artificial sweeteners have been used as sugar substitutes in numerous applications; however, their long-term effects on human health and safety aspects remain controversial. For example, ATS appear to change the host microbiome, lead to decreased satiety, alter glucose homeostasis, and are associated with increased caloric consumption and weight gain. Moreover, some health effects such as dizziness, headaches, gastrointestinal issues, and mood changes are associated with the consumption of a commonly used ATS, aspartame. Additionally, Kokotou et al. have demonstrated the impact of ATS as environmental pollutants, concluding that when artificial sweeteners are applied in food products or eventually enter the environment, their transformation and/or degradation may lead to the formation of toxic substances.