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Taisui, a special substance occasionally found in China, can now be artificially cultured. In order to evaluate the safety of an artificially cultured Taisui (acTS) and develop it into fermented, functional food or oral liquid, the macronutrients, trace elements, microbial community, and extracellular metabolites of Taisui have been investigated in this study. Results showed that the concentrations of total carbohydrates, protein, fat, total ash, and moisture of wet acTS were 2.13 g/100 g, 0.13 g/100 g, 0.07 g/100 g, 0.04 g/100 g, and 88.3%, respectively. The concentrations of top three trace elements of K, Ca, and P, are 1,424.92 mg/kg, 159.96 mg/kg, and 67.89 mg/kg, respectively. Proteobacteria, Euryarchaeota, and Ascomycota were the dominant phyla of bacteria, archaea, and fungi, respectively. Uncultured_bacterium_f_Anaerolineaceae, Alcaligenes, and Ochrobactrum were the three most abundant genera of bacteria; Methanosaeta, Methanosphaera, and Natronomonas, the most abundant genera of archaea; Zygosaccharomyces, Mortierella, and Fusarium, the most abundant genera of fungi. There were 311 metabolites increased in acTS. Most of the metabolites are beneficial to human. These metabolites can be contributed to microbes in acTS. In conclusion, acTS is not a good source of macronutrients and of trace elements, while the safeness of some microorganisms in acTS is also unknown. Nevertheless, it still provides some probiotics and beneficial metabolites for human. It is thus possible to develop acTS into foods when the safety of each microorganism is proved., Jelly‐like Taisui, a unique substance usually found in the wild in China, can be artificially cultured recently, and the chemical components, microbial structure, and metabolomics of the artificially cultured one were investigated to characterize its safety.

Indoor air pollution has significant adverse health impacts, but its spatiotemporal variations and source contributions are not well quantified. In this study, we used low-cost sensors to measure PM

Household air pollution is the dominant contributor to population air pollutant exposure, but it is often of less concern compared with ambient air pollution. One of the major knowledge gaps in this field are detailed quantitative source contributions of indoor pollutants, especially for gaseous compounds. In this study, temporally, spatially, and vertically resolved monitoring for typical indoor gases including CO

Indoor air pollution has significant adverse health impacts, but its spatiotemporal variations and source contributions are not well quantified. In this study, we used low-cost sensors to measure PM2.5 concentrations in a typical apartment in Beijing. The measurements were conducted at 15 indoor sites and one outdoor site on 1-minute temporal resolution (convert to 10-minute averages for data analysis) from March 14 to 24, 2020. Based on these highly spatially-and temporally-resolved data, we characterized spatiotemporal variations and source contributions of indoor PM2.5 in this apartment. It was found that indoor particulate matter predominantly originates from outdoor infiltration and cooking emissions with the latter contributing more fine particles. Indoor PM2.5 concentrations were found to be correlated with ambient levels but were generally lower than those outdoors with an average I/O of 0.85. The predominant indoor source was cooking, leading to occasional high spikes. The variations observed in most rooms lagged behind those measured outdoors and in the studied kitchen. Differences between rooms were found to depend on pathway distances from sources. On average, outdoor sources contributed 36% of indoor PM2.5, varying extensively over time and among rooms. From observed PM2.5 concentrations at the indoor sites, source strengths, and pathway distances, a multivariate regression model was developed to predict spatiotemporal variations of PM2.5. The model explains 79% of the observed variation and can be used to dynamically simulate PM2.5 concentrations at any site indoors. The model's simplicity suggests the potential for regional-scale application for indoor air quality modeling.

Household air pollution is the dominant contributor to population air pollutant exposure, but it is often of less concern compared with ambient air pollution. One of the major knowledge gaps in this field are detailed quantitative source contributions of indoor pollutants, especially for gaseous compounds. In this study, temporally, spatially, and vertically resolved monitoring for typical indoor gases including CO2, CO, formaldehyde, methane, and the total volatile organic compounds (VOCs) was conducted to address pollution dynamics and major sources in an urban apartment. The indoor concentrations were significantly higher than the simultaneously measured outdoor concentrations. A new statistic approach was proposed to quantitatively estimate contributions of different sources. It was estimated that outdoor CO2 contributed largely to the indoor CO2, while main indoor sources were human metabolism and cooking. Outdoor infiltration and cooking contributed almost equally to the indoor CO. The contribution of outdoor infiltration to methane was much higher than that to formaldehyde. Cooking contributed to 24%, 19%, and 25% of indoor formaldehyde, methane, and VOCs, whereas the other unresolved indoor sources contributed 61%, 19%, and 35% of these pollutants, respectively. Vertical measurements showed that the uplifting of hot air masses led to relatively high concentrations of the pollutants in the upper layer of the kitchen and in the other rooms to a lesser extent.