ACS Environmental Au最新文献

Plastic waste is a critical global issue, yet current strategies to avoid committing plastic waste to landfills include incineration, gasification, or pyrolysis high carbon emitting and energy consuming approaches. However, plastic waste can become a resource instead of a problem if high value products, such as fine chemicals and liquid fuel molecules, can be liberated from controlled its decomposition. This letter presents proof of concept on a low-cost, low energy approach to controlled decomposition of plastic, photocatalytic hydrolysis. This approach integrates photolysis and hydrolysis, both slow natural decomposition processes, with a photocatalytic process. The photocatalyst, α-Fe₂O₃, is embedded into a polylactic acid (PLA) plastic matrix. The photocatalyst/plastic composite is then immersed in water and subjected to low-energy (25 W) UV light for 90 h. The monomer lactide is produced as the major product. α-Fe₂O₃ (6.9 wt %) was found to accelerate the PLA degradation pathway, achieving 32% solid transformation into liquid phase products, in comparison to PLA on its own, which was found to not decompose, using the same conditions. This highlights a low energy route toward plastic waste upgrade and valorization that is less carbon intensive than pyrolysis and faster than natural degradation. By directly comparing a 25 W (0.025 kWh) UV bulb with a 13 kWh furnace, the photocatalytic reaction would directly consume 520× less energy than a conventional thermochemical pathway. Furthermore, this technology can be extended and applied to other plastics, and other photocatalysts can be used.

It is well known that atmospheric aerosol size and composition impact air quality, climate, and health. The aerosol composition is typically a mixture and consists of a wide range of organic and inorganic particles that interact with each other. Furthermore, water vapor is ubiquitous in the atmosphere, in indoor air, and within the human body’s respiratory system, and the presence of water can alter the aerosol morphology and propensity to form droplets. Specifically, aerosol mixtures can undergo liquid–liquid phase separation (LLPS) in the presence of water vapor. However, the experimental conditions for which LLPS impacts water uptake and the subsequent prediction of aerosol mixtures are poorly understood. To improve our understanding of aerosol mixtures and droplets, this study explores two ternary systems that undergo LLPS, namely, the 2MGA system (sucrose + ammonium sulfate + 2-methylglutaric acid) and the PEG1000 system (sucrose + ammonium sulfate + polyethylene glycol 1000). In this study, the ratio of species and the O:C ratios are systematically changed, and the hygroscopic properties of the resultant aerosol were investigated. Here, we show that the droplet activation above 100% RH of the 2MGA system was influenced by LLPS, while the droplet activation of the PEG1000 system was observed to be linearly additive regardless of chemical composition, O:C ratio, and LLPS. A theoretical model that accounts for LLPS with O:C ratios was developed and predicts the water uptake of internally mixed systems of different compositions and phase states. Hence, this study provides a computationally efficient algorithm to account for the LLPS and solubility parameterized by the O:C ratio for droplet activation at supersaturated relative humidity conditions and may thus be extended to mixed inorganic–organic aerosol populations with unspeciated organic composition found in the ambient environment.

N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD)-quinone (6PPD-Q), a transformation byproduct of 6PPD used in tires as an antiozonant and antioxidant, was recently discovered as the chemical primarily responsible for the acute lethal toxicity of urban storm runoff to coho salmon. The asphalt concrete (AC) surface layer is the primary medium to contact 6PPD-Q immediately upon its release from tires, and the addition of recycled tire rubber (RTR) to the asphalt binder and mixture is a widely accepted practice in asphalt production. Therefore, it is urgent to understand the fate of 6PPD-Q at the asphalt concrete surface layer–water interface. This study analyzed the sorption and desorption of 6PPD-Q by compacted and crushed loose (loose particles, ∼5 mm) rubberized asphalt mixtures and their mobilization from compacted asphalt mixtures during simulated rainfall events. It should be noted that the crushed loose asphalt mixtures demonstrated the physicochemical properties of the asphalt materials, while the compacted asphalt mixtures represent in-service AC layers. Sorption of 6PPD-Q by crushed loose and compacted asphalt mixtures reached equilibrium within 12 days, with a sorption coefficient of 151.57–257.51 L/kg for compacted asphalt mixtures. Within 12 days, desorption of 6PPD-Q from crushed loose and compacted rubberized asphalt mixtures (20 g particles/L) to the double deionized (DDI) water and synthetic stormwater was 0.01–0.09 and 0.025–0.05 μg/L, respectively. Through the rainfall simulation experiments, 0.0015–0.0049 μg/L 6PPD-Q was detected in the runoff water, much lower than the lethal concentration (LC₅₀) of 6PPD-Q of 0.095 μg/L and 308.67 μg/L for coho salmon and zebrafish larvae. Our results indicate that, while the release of 6PPD-Q from compacted rubberized asphalt mixtures is minor, the mixtures can serve as sorbents for tire-derived 6PPD-Q and retain this emerging contaminant.

Documenting the occurrence of viruses on fomites is crucial in determining the significance of fomite-mediated transmission and the potential use of fomites for environmental disease surveillance. We conducted a systematic review and meta-analysis to compile information on the occurrence of human viruses on fomites in the environment; we identified 134 peer-reviewed papers. We compiled sampling and measurement methods, results, quality control information, and whether virus data were compared with community health data from the papers. We conducted univariate and multivariate analyses to investigate if presence of virus on fomites was associated with virus type (enveloped, nonenveloped), sampling location (healthcare setting, nonhealthcare temporary setting, nonhealthcare nontemporary setting), and area of fomite swabbed (<50, 50–100, >100 cm²). Across 275 data sets from the 134 papers, there was the most data available for Coronaviridae and from fomites at hospitals. Positivity rates, defined as the percent positive fomite samples, were low (median = 6%). Data were available on viruses from 16 different viral families, but data on viruses from 9 families had few (n < 5) data sets. Many human virus families were not identified in this review (11 families). Less than 15% of the data sets reported virus concentrations in externally valid units (viruses per area of surface), and 16% provided a quantitative comparison between virus and health data. Virus type and area swabbed were significant predictors of virus presence on fomites, and the positivity rate of data sets collected from healthcare settings and nonhealthcare nontemporary settings (e.g., individual housing) were significantly higher than those collected in nonhealthcare temporary settings (e.g., restaurants). Data from this review indicates that viruses may be present on fomites, that fomite-mediated virus transmission may occur, and that fomites may provide information on circulation of infectious diseases in the community. However, more quantitative data on diverse viruses are needed, and method reporting needs significant improvements.

In May 2021, the M/V X-Press Pearl container ship burned for 2 weeks, leading to the largest maritime spill of resin pellets (nurdles). The disaster was exacerbated by the leakage of other cargo and the ship’s underway fuel. This disaster affords the unique opportunity to study a time-stamped, geolocated release of plastic under real-world conditions. Field samples collected from beaches in Sri Lanka nearest to the ship comprised nurdles exposed to heat and combustion, burnt plastic pieces (pyroplastic), and oil-plastic agglomerates (petroplastic). An unresolved question is whether the 1600+ tons of spilled and recovered plastic should be considered hazardous waste. Due to the known formation and toxicity of combustion-derived polycyclic aromatic hydrocarbons (PAHs), we measured 20 parent and 21 alkylated PAHs associated with several types of spilled plastic. The maximum PAH content of the sampled pyroplastic had the greatest amount of PAHs recorded for marine plastic debris (199,000 ng/g). In contrast, the sampled unburnt white nurdles had two orders of magnitude less PAH content. The PAH composition varied between the types of spilled plastic and presented features typical of and conflicting with petrogenic and pyrogenic sources. Nevertheless, specific markers and compositional changes for burning plastics were identified, revealing that the fire was the main source of PAHs. Eight months after the spill, the PAH contents of sampled stray nurdles and pyroplastic were reduced by more than 50%. Due to their PAH content exceeding levels allowable for plastic consumer goods, classifying burnt plastic as hazardous waste may be warranted. Following a largely successful cleanup, we recommend that the Sri Lankans re-evaluate the identification, handling, and disposal of the plastic debris collected from beaches and the potential exposure of responders and the public to PAHs from handling it. The maritime disaster underscores pyroplastic as a type of plastic pollution that has yet to be fully explored, despite the pervasiveness of intentional and unintentional burning of plastic globally.

Developing advanced onsite wastewater treatment systems (OWTS) requires accurate and consistent water quality monitoring to evaluate treatment efficiency and ensure regulatory compliance. However, off-line parameters such as chemical oxygen demand (COD), total suspended solids (TSS), and Escherichia coli (E. coli) require sample collection and time-consuming laboratory analyses that do not provide real-time information of system performance or component failure. While real-time COD analyzers have emerged in recent years, they are not economically viable for onsite systems due to cost and chemical consumables. This study aimed to design and implement a real-time remote monitoring system for OWTS by developing several multi-input and single-output soft sensors. The soft sensor integrates data that can be obtained from well-established in-line sensors to accurately predict key water quality parameters, including COD, TSS, and E. coli concentrations. The temporal and spatial water quality data of an existing field-tested OWTS operated for almost two years (n = 56 data points) were used to evaluate the prediction performance of four machine learning algorithms. These algorithms, namely, partial least square regression (PLS), support vector regression (SVR), cubist regression (CUB), and quantile regression neural network (QRNN), were chosen as candidate algorithms for their prior application and effectiveness in wastewater treatment predictions. Water quality parameters that can be measured in-line, including turbidity, color, pH, NH₄⁺, NO₃^–, and electrical conductivity, were selected as model inputs for predicting COD, TSS, and E. coli. The results revealed that the trained SVR model provided a statistically significant prediction for COD with a mean absolute percentage error (MAPE) of 14.5% and R² of 0.96. The CUB model provided the optimal predictive performance for TSS, with a MAPE of 24.8% and R² of 0.99. None of the models were able to achieve optimal prediction results for E. coli; however, the CUB model performed the best with a MAPE of 71.4% and R² of 0.22. Given the large fluctuation in the concentrations of COD, TSS, and E. coli within the OWTS wastewater dataset, the proposed soft sensor models adequately predicted COD and TSS, while E. coli prediction was comparatively less accurate and requires further improvement. These results indicate that although water quality datasets for the OWTS are relatively small, machine learning-based soft sensors can provide useful predictive estimates of off-line parameters and provide real-time monitoring capabilities that can be used to make adjustments to OWTS operations.

Rising CO₂ emissions are responsible for increasing global temperatures causing climate change. Significant efforts are underway to develop amine-based sorbents to directly capture CO₂ from air (called direct air capture (DAC)) to combat the effects of climate change. However, the sorbents’ performances have usually been evaluated at ambient temperatures (25 °C) or higher, most often under dry conditions. A significant portion of the natural environment where DAC plants can be deployed experiences temperatures below 25 °C, and ambient air always contains some humidity. In this study, we assess the CO₂ adsorption behavior of amine (poly(ethyleneimine) (PEI) and tetraethylenepentamine (TEPA)) impregnated into porous alumina at ambient (25 °C) and cold temperatures (−20 °C) under dry and humid conditions. CO₂ adsorption capacities at 25 °C and 400 ppm CO₂ are highest for 40 wt% TEPA-incorporated γ-Al₂O₃ samples (1.8 mmol CO₂/g sorbent), while 40 wt % PEI-impregnated γ-Al₂O₃ samples exhibit moderate uptakes (0.9 mmol g^–1). CO₂ capacities for both PEI- and TEPA-incorporated γ-Al₂O₃ samples decrease with decreasing amine content and temperatures. The 40 and 20 wt % TEPA sorbents show the best performance at −20 °C under dry conditions (1.6 and 1.1 mmol g^–1, respectively). Both the TEPA samples also exhibit stable and high working capacities (0.9 and 1.2 mmol g^–1) across 10 cycles of adsorption–desorption (adsorption at −20 °C and desorption conducted at 60 °C). Introducing moisture (70% RH at −20 and 25 °C) improves the CO₂ capacity of the amine-impregnated sorbents at both temperatures. The 40 wt% PEI, 40 wt % TEPA, and 20 wt% TEPA samples show good CO₂ uptakes at both temperatures. The results presented here indicate that γ-Al₂O₃ impregnated with PEI and TEPA are potential materials for DAC at ambient and cold conditions, with further opportunities to optimize these materials for the scalable deployment of DAC plants at different environmental conditions.