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As one of the major sources of volatile pollutants in indoor air, gaseous emissions from adhesives during interior decoration have attracted increasing concern. Identifying major volatile pollutants and the risk in adhesive gaseous emissions is of great significance, but remains rarely reported. In the present research, we assessed the major volatile pollutants emitted from white emulsion adhesive and silicone adhesive samples (n = 30) from three aspects: chemical composition, odor and health risk contributions. The results showed that a total of 21 volatile pollutants were detected. Significantly, xylene was the most concentrated compound from white emulsion adhesives, accounting for 45.51% of the total concentrations. Butanone oxime was the most concentrated compound in silicone adhesives, accounting for 69.86% of the total concentrations. The trends in odor concentration (evaluated by the odor activity value method) over time were well correlated with the total chemical concentrations. Xylene (58.00%) and butanone oxime (76.75%) showed the highest odor contribution, respectively. Moreover, from an integrated perspective of chemical emissions, odor and health risk contributions, xylene, ethylbenzene, ethyl acetate and benzene were identified as the key volatile pollutants emitted from the white emulsion adhesives, while butanone oxime, butanone, and ethanol were the key volatile pollutants emitted from the silicone adhesives. This study not only identified the key volatile pollutants but also provided characteristics of odor and health risks of gas emitted from adhesives.

Airborne emissions from concentrated animal feeding operations (CAFOs) have the potential to pose a risk to human health and the environment. Here, we present an assessment of the emission, dispersion, and health-related impact of ammonia and hydrogen sulfide emitted from a 300-head, full-scale dairy farm with an exercise yard in Beijing, China. By monitoring the referred gas emissions with a dynamic flux chamber for seven consecutive days, we examined their emission rates. An annual hourly emission time series was constructed on the basis of the measured emission rates and a release modification model. The health risk of ammonia and hydrogen sulfide emissions around the dairy farm was then determined using atmospheric dispersion modeling and exposure risk assessment. The body mass-related mean emission factors of ammonia and hydrogen sulfide were 2.13 kg a -1  AU -1 and 24.9 g a -1  AU -1 , respectively (one animal unit (AU) is equivalent to 500 kg body mass). A log-normal distribution fitted well to ammonia emission rates. Contour lines of predicted hourly mean concentrations of ammonia and hydrogen sulfide were mainly driven by the meteorological conditions. The concentrations of ammonia and hydrogen sulfide at the fence line were below 10 μg m -3 and 0.04 μg m -3 , respectively, and were 2-3 orders of magnitude lower than the current Chinese air quality standards for such pollutants. Moreover, the cumulative non-carcinogenic risks (HI) of ammonia and hydrogen sulfide were 4 orders of magnitudes lower than the acceptable risk levels (HI = 1). Considering a health risk criterion of 1E-4, the maximum distance from the farm fence line to meet this criterion was nearly 1000 m towards north-northeast. The encompassed area of the contour lines of the ambient concentration of ammonia is much larger than that of hydrogen sulfide. However, the contour lines of the ammonia health risk are analogous to those of hydrogen sulfide. In general, the ammonia and hydrogen sulfide emissions from the dairy farm are unlikely to cause any health risks for the population living in the neighborhood.

Gaseous emissions from municipal solid waste (MSW) have raised many concerns and complaints. Identifying the key volatile pollutants in the complex gaseous emissions from MSW is significant for the efficient mitigation of their odor nuisances and health risks. For this purpose, we present an integrated investigation of the key volatile pollutants in the gaseous emissions of MSW from the perspectives of emission patterns, odor concentrations and health risks. Air samples were collected during four different emission stages of the waste matrix for both chemical and olfactometric analyses. The total chemical concentrations of the volatile compounds in the air samples were in the range of 21.49 mg m -3 to 295.61 mg m -3 , and the odor concentrations varied from 1122 ou E m -3 to 17,782 ou E m -3 . The odor concentrations in the air samples were well correlated with the odor activity values (OAVs) of sulfur compounds, oxygenated compounds and ammonia (r = 0.922, 0.879 and 0.780, respectively, for n = 17 and p < 0.01). Moreover, from an integrated perspective involving chemical emissions, the proportions of odor concentrations and health risks, ethanol, methyl mercaptan and hydrogen sulfide were identified as the key volatile pollutants in the gaseous emissions from the waste matrix during the airtight storage stage, and dimethyl disulfide, 1,2-dichloroethane and trichloroethylene were the key volatile pollutants during the ventilation stage., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Municipal solid waste (MSW) landfills are a source of odorous and toxic compounds. In this work, we present an integrated assessment of the odor concentration and human health risks of volatile compounds to evaluate the environmental quality at a MSW landfill. Air samples were collected seasonally from six areas of the landfill with different functions. The total concentrations of the compounds ranged from 204.0 to 7426.7 μg m -3 , and the concentrations in temporarily and permanently capped areas were 50.3 and 83.4% lower than those in the tipping area, respectively. The odor concentration was greatest at the leachate collection tank (1732-6254 ou E m -3 ) and tipping area (1573-4113 ou E m -3 ) and was mainly caused by hydrogen sulfide (57.9 and 49.1%, respectively). Moreover, the odor concentration was positively correlated with the temperature (r = 0.500, p < 0.05, n = 24). Although the non-carcinogenic (HI) and carcinogenic (R) risks of most compounds were largely below the acceptable levels (HI = 1, R = 1.0E-6), HI values of hydrogen sulfide (2.3), trichloropropane (2.0), and naphthalene (1.2) as well as R values of naphthalene (1.3E-4) and trimethylbenzene (1.2E-4) in the waste areas exceeded acceptable levels. Moreover, the cumulative HI (2.5-5.7) and R (1.0E-04 to 3.4E-04) in the waste areas should receive special attention since they were above acceptable levels during all of the seasons. Aromatic and halogenated compounds dominated the cumulative R, accounting for 79 and 21% of the total, on average, while for the cumulative HI, sulfur compounds contributed the most (67%)., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.