Environmental Science & Technology Letters Environ.最新文献

Although physical-chemical properties are critical for understanding the behavior of per- and polyfluoroalkyl substances (PFAS) in the environment, data reported in the literature can vary by orders of magnitude. The goal of this research was to accurately determine the aqueous solubility (Saq), critical micelle concentration (CMC), and acid dissociation constant (pK_a) of perfluorooctanoic acid (HPFO) and ammonium perfluoro-n-octanoate (APFO). The aqueous solubilities of HPFO in deionized (DI) water and 100 mM NaCl were ∼4500 and ∼12,500 mg/L, respectively, while APFO yielded aqueous solubilities of ∼47,000 and ∼45,000 mg/L in DI water and 100 mM NH₄Cl, respectively. Based on surface tension measurements, no CMC value was obtained for HPFO because the solubility limit was reached before micelle formation occurred, while in 100 mM NaCl the CMC was ∼3000 mg/L. The CMCs of APFO in DI water and 100 mM NH4Cl were ∼12,700 and ∼4,900 mg/L, respectively. These findings demonstrate that PFOA (1) is unlikely to form micelles in solution at environmentally relevant concentrations, (2) reported CMC values may actually correspond to the solubility limit rather than micelle formation, and (3) aqueous solubility values can vary by orders of magnitude depending upon the counterion species and solution properties.

Highly luminescent gold nanoclusters (AuNCs) are synthesized by manipulating the surface of the gold core with layer-by-layer ligand engineering. 6-Aza-2-thiothymine (ATT) and l-arginine (Arg) are first self-assembled and then encapsulated in zeolitic imidazolate framework-8 (ZIF-8). The multiple ligands effectively suppress the kernel vibration and are involved in the nonradiative relaxation of electron dynamics. Boosted fluorescence emission can thus be observed. Based on the nanomaterials of ZIF-8-Arg-ATT AuNCs, a novel fluorescent nanosensor is fabricated for the specific detection of lead ions with excellent performances. A limit of detection as low as 10 nmol/L is estimated. This nanosensor performs satisfactorily in real water samples including tap water, pool water, river water, and various drinks, showing its promising prospect for practical identification of lead ions.

Artificial intelligence (AI) holds significant potential for advancing research and development in the field of environmental science and engineering (ESE), but the development of domain-specific large language models (LLMs) in this field has not been reported. This study addresses this gap by evaluating the performance of advanced LLMs in answering expert-level, closed-book environmental engineering questions. We assessed two generative pretrained transformer (GPT) models and five fine-tuned models (FTMs) on an expert-level question answering (QA) data set, focusing on relevance (from 0 to 1), factuality (0 to 1), format, richness, QA difficulty level, and domain topic. Results show that GPT-4 achieves a relevance score of 0.644 and a factuality score of 0.791 based on 286 questions, indicating room for improvement, particularly for more difficult questions (scores dropped to below 0.5). Notably, FTMs with larger data sets resisted factuality degradation, highlighting the need for high-quality training materials. Inaccuracies and format issues are often linked to overtraining and catastrophic interference. This first investigation leverages expert-level textbooks to enhance LLM performance, thereby providing valuable insights and setting the stage for developing more robust domain-specific LLMs for environmental applications.

Previous studies of quaternary ammonium compounds (QACs) in the indoor environment have reported widespread presence of QAC in indoor dust. However, there are limited data on the contribution of dust ingestion to the QAC body burden. In this study, 18 QACs (6 benzylalkyldimethylammonium compounds [BACs], 6 dialkyldimethylammonium compounds [DADMACs], and 6 alkyltrimethylammonium compounds [ATMACs]) were analyzed in 81 paired samples of blood serum and dust collected in Indiana, United States. QACs were detected in 51–100% of the dust samples with the total QAC concentrations (∑QAC) ranging from 0.613 to 427 μg/g (median 56.9 μg/g). In contrast to dust samples, QACs were detected less frequently in blood serum with a median ∑QAC concentration of 3.66 ng/mL. The relative source contribution (RSC) of dust ingestion to serum levels was calculated using the PROTEX (PROduction-To-EXposure) model and was estimated as less than 1%, suggesting that hand-to-mouth contact, dietary intake, or inhalation could be more important exposure routes than dust ingestion. This is the first study to simultaneously measure QAC concentrations in indoor dust and blood, providing comprehensive assessment of the role of dust ingestion in QAC human exposure.

Recovery of nitrogen from wastewater presents a unique opportunity to valorize waste and contribute to a more circular nitrogen economy. However, dilute solution separations are challenging for most state-of-the-art separations technologies. This often results in technologies having low concentration factors that result in low-value products (e.g., < 1 wt % N). Here, we demonstrate how a cascading electrodialysis system combined with a hollow fiber membrane contactor (ED+HFMC) system can achieve efficient recovery of ammonia from simulated centralized animal feeding operation (CAFO) wastewater. The integrated system achieved an overall concentration factor of ∼200× (∼40× in ED and ∼5× in HFMC). This resulted in a ∼10 wt % NH₄ ⁺-N fertilizer product. The specific energy consumption (SEC) for the three stages of the ED was 1.89-6.14 kWh/kg NH₄ ⁺-N, which is lower than that of the Haber-Bosch process (8.9-19.3 kWh/kg N). Operating costs were <$0.90/kg NH₄ ⁺-N for each of the electrodialysis stages and NH₃ stripping. This integrated ED+HFMC system holds promise for the recovery of ammonia from dilute feedstreams as the ED+HFMC achieves high concentration factors and has low energy demand.

Recovery of nitrogen from wastewater presents a unique opportunity to valorize waste and contribute to a more circular nitrogen economy. However, dilute solution separations are challenging for most state-of-the-art separations technologies. This often results in technologies having low concentration factors that result in low-value products (e.g., < 1 wt % N). Here, we demonstrate how a cascading electrodialysis system combined with a hollow fiber membrane contactor (ED+HFMC) system can achieve efficient recovery of ammonia from simulated centralized animal feeding operation (CAFO) wastewater. The integrated system achieved an overall concentration factor of ∼200× (∼40× in ED and ∼5× in HFMC). This resulted in a ∼10 wt % NH₄⁺-N fertilizer product. The specific energy consumption (SEC) for the three stages of the ED was 1.89–6.14 kWh/kg NH₄⁺-N, which is lower than that of the Haber–Bosch process (8.9–19.3 kWh/kg N). Operating costs were <$0.90/kg NH₄⁺-N for each of the electrodialysis stages and NH₃ stripping. This integrated ED+HFMC system holds promise for the recovery of ammonia from dilute feedstreams as the ED+HFMC achieves high concentration factors and has low energy demand.

Fine-mode particulate matter (PM_2.5) is a highly detrimental air pollutant, regulated without regard for chemical composition and a chief component of wildfire smoke. As wildfire activity increases with climate change, its growing continental influence necessitates multidisciplinary research to examine smoke’s evolving chemical composition far downwind and connect chemical composition-based source apportionment to potential health effects. Leveraging advanced real-time speciated PM_2.5 measurements, including an aerosol chemical speciation monitor in conjunction with source apportionment and health risk assessments, we quantified the stark pollution enhancements during peak Canadian wildfire smoke transport to New York City over June 6–9, 2023. Interestingly, we also observed lower-intensity, but frequent, multiday wildfire smoke episodes during May–June 2023, which risk exposure misclassification as generic aged organic PM_2.5 via aerosol mass spectrometry given its extensive chemical transformations during 1 to 6+ days of transport. Total smoke-related organic PM_2.5 showed significant associations with asthma exacerbations, and estimates of in-lung oxidative stress were enhanced with chemical aging, collectively demonstrating elevated health risks with increasingly frequent smoke episodes. These results show that avoiding underestimated aged biomass burning PM_2.5 contributions, especially outside of peak episodes, necessitates real-time chemically resolved PM_2.5 monitoring to enable next-generation health studies, models, and policy under far-reaching wildfire impacts in the 21st century.

Fine-mode particulate matter (PM_2.5) is a highly detrimental air pollutant, regulated without regard for chemical composition and a chief component of wildfire smoke. As wildfire activity increases with climate change, its growing continental influence necessitates multidisciplinary research to examine smoke's evolving chemical composition far downwind and connect chemical composition-based source apportionment to potential health effects. Leveraging advanced real-time speciated PM_2.5 measurements, including an aerosol chemical speciation monitor in conjunction with source apportionment and health risk assessments, we quantified the stark pollution enhancements during peak Canadian wildfire smoke transport to New York City over June 6-9, 2023. Interestingly, we also observed lower-intensity, but frequent, multiday wildfire smoke episodes during May-June 2023, which risk exposure misclassification as generic aged organic PM_2.5 via aerosol mass spectrometry given its extensive chemical transformations during 1 to 6+ days of transport. Total smoke-related organic PM_2.5 showed significant associations with asthma exacerbations, and estimates of in-lung oxidative stress were enhanced with chemical aging, collectively demonstrating elevated health risks with increasingly frequent smoke episodes. These results show that avoiding underestimated aged biomass burning PM_2.5 contributions, especially outside of peak episodes, necessitates real-time chemically resolved PM_2.5 monitoring to enable next-generation health studies, models, and policy under far-reaching wildfire impacts in the 21st century.

Biomass burning (BB) is a major source of aerosols and black carbon, thereby exerting an important impact on climate and air quality. Levoglucosan is the most well-recognized organic marker compound of BB and has been used to quantitatively assess BB's contribution to ambient aerosols. However, little is known about levoglucosan's evaporation under atmospheric conditions, primarily due to the uncertainty of its effective saturation vapor concentration (C*) and its unknown activity coefficient (γ), in the complex BB emission matrix. Here, we utilized a thermodenuder to investigate the evaporation of levoglucosan from mixtures with polyethylene glycol (PEG) or BB primary organic aerosol (BBPOA) matrices, respectively. We estimate a pure component log₁₀(C*/[μg m^-3]) of levoglucosan of 1.1 ± 0.1 at 298 K. We reveal that levoglucosan mixed with PEG or BBPOA becomes more volatile than when treated as a single component due to nonideal molecular interactions. Considering that phase separation might occur in such systems, we term γ apparent activity coefficient (γ _a ). We estimate log₁₀ C* and γ _a of levoglucosan in BBPOA of 1.8 ± 0.1 and 3.8 ± 0.3, assuming a liquid phase state. Consequently, γ _a must be considered to avoid significant underestimation of levoglucosan evaporation via gas-particle partitioning during transport.

Frequent and severe wildfires have led to increased application of fire suppression products (long-term fire retardants, water enhancers, and Class A foams) in the American West. While fire suppressing products used on wildfires must be approved by the U.S. Forest Service, portions of their formulations are trade secrets. Increased metals content in soils and surface waters at the wildland-urban interface has been observed after wildfires but has primarily been attributed to ash deposition or anthropogenic impact from nearby urban areas. In this study, metal concentrations in several fire suppression products (some approved by the U.S. Forest Service, and some marketed for consumer use) were quantified to evaluate whether these products could contribute to increased metal concentrations observed in the environment postfire. Long-term fire retardants contained concentrations of toxic metals (V, Cr, Mn, Cu, As, Cd, Sb, Ba, Tl, and Pb) 4-2,880 times greater than drinking water regulatory limits, and potentially greater than some aquatic toxicity thresholds when released into the environment. Water enhancers and Class A foams contained some metals, but at lower concentrations than fire retardants. Based on these concentrations and retardant application records, we estimate fire retardant application in the U.S. contributed approximately 380,000 kg of toxic metals to the environment between 2009 and 2021.