ACS Environmental Au最新文献

Thermal methods, especially pyrolysis with biochar production, are emerging as potential solutions for sewage sludge treatment. Life cycle assessment (LCA) is commonly used to evaluate environmental impacts, and the promising performance of pyrolysis has been demonstrated in previous LCA studies. This study goes into further detail in impact analysis by applying prospective and dynamic LCA while incorporating multiple approaches to consider biogenic carbon emissions. The results show that the system provides climate benefits over a 100 year period, with findings remaining robust despite variability in facility parameters and uncertainties in model assumptions. The prospective LCA results indicate that the climate balance of the system is expected to improve over the years. The dynamic analysis demonstrates that the system provides significant temporal carbon capture, which gradually decreases as biochar decomposes in soil. Taking two perspectives on biogenic carbon accounting reveals how the results can be affected by methodological decisions. This study offers a more detailed view of the dynamic evolution of climate impacts across the facility's entire operational lifetime.

The co-occurrence of surface ozone (O₃) and particulate matter (PM_2.5) pollution (COP) has been frequently observed in China, particularly in the North China Plain (NCP) during warmer months, posing significant threats to human health and ecosystems. However, the impact of climate factors on COP remains inadequately understood. This study identifies three major modes of interannual variability in the COP frequency in Eastern China, revealing a consistent spatial pattern, a North-south dipole, and heightened sensitivity in coastal regions. These modes are linked to preseasonal cooling sea surface temperatures (SSTs) in the Western Pacific Ocean, Arctic sea ice (SI) loss near the Barents Sea, and North Atlantic tripole SST anomalies associated with the North Atlantic Oscillation, respectively. Both observations and model simulations confirm that Western Pacific cooling suppresses the Western Pacific subtropical high, promoting pollutant accumulation in the NCP; Barents Sea SI loss triggers atmospheric wave trains, facilitating water vapor transport to southern China and air pollutants transport to Northern China, resulting in a North-south dipole in COP frequency; and North Atlantic Oscillation (NAO)-driven SST anomalies generate westerly wind anomalies, driving pollutants to coastal regions of Eastern China. A model that incorporates preseasonal SST and SI signals is demonstrated to be capable of predicting COP frequency three months in advance. Our results could allow the Chinese government to improve plans for pollution control and safeguard the health of both humans and ecosystems.

Per- and polyfluoroalkyl substances (PFAS) are widespread environmental pollutants that can bioaccumulate in biota and cause a variety of adverse effects. Seabirds are useful bioindicators of pollutants in marine food webs because they are apex predators with broadly known diets and distributions, and concentrations in their tissues therefore reflect background exposure in particular regions and ecosystems. Concentrations of PFAS are high in seabirds in the Northern Hemisphere, but there have been few studies in the Southern Hemisphere, particularly in the sub-Antarctic, and these mostly involved a limited target list of PFAS. We detected 22 PFAS, of a target list of 39 compounds, in three species of procellariform seabirds (albatrosses and petrels) with different diets and migration strategies, sampled in two areas in the southwest Atlantic Ocean in 2004-2014. PFAS concentrations are reported for the first time in common diving petrels and white-chinned petrels. Concentrations in liver tissue varied significantly among species and years, with ΣPFAS ranging over 2 orders of magnitude from 0.08 to 7.5 ng/g (ww). Despite this variation in total concentrations, chemical contamination profiles were broadly similar, comprising mainly perfluorooctanesulfonic acid (PFOS) (∼80%) and perfluoroalkyl carboxylic acids (PFCAs) (∼15%), suggesting PFAS fingerprints are much the same despite the contrasting diets, trophic levels and distributions. This signature closely reflects mixtures found in south Atlantic waters and provides evidence of long-range transport of atmospheric precursors. Emerging compounds of concern including hexafluoropropylene oxide dimer acid (HFPO-DA), dodeceafluoro-3H-,4,8-dioxanonoate (ADONA), and short-chain perfluoroalkyl acids (PFAAs) were detected in some samples. This study provides evidence of contamination in biota and highlights the value of biomonitoring of remote environments.

The Amazon rainforest is the largest tropical rainforest in the world. Amazonian Podzol soils, characteristic of this region, are known to store substantial amounts of organic carbon in both their surface and deep horizons. Despite decades of research, the molecular-level composition of these soils remains uncharacterized. This study addresses this knowledge gap by employing ultrahigh resolution mass spectrometry, namely, Fourier transform-ion cyclotron resonance-mass spectrometry (FT-ICR-MS), to determine the molecular composition of humic acid (HA) and fulvic acid (FA) fractions from two Amazonian Podzol profiles of varying levels of groundwater exposure (waterlogged vs well-drained). In the waterlogged soil compounds containing nitrogen, sulfur, or phosphorus (NSP) decreased with increasing depth while labile carboxyl-containing aliphatic molecules (CCAM) increased. CCAM were likely preserved through complexation with metals or from kinetically stalled degradation processes. In the well-drained soil compounds containing NSP increased with increasing depth likely due to elevated microbial productivity in the deeper horizons. Oxidation reactions in the well-drained soil profile also led to the production of condensed aromatic compounds (ConAC), which were responsible for the significant carbon sequestration observed in the deeper horizons. The molecular fingerprints of the samples of this study could be successfully parametrized by the nominal oxidation state of carbon (NOSC) derived from FT-ICR-MS suggesting this metric for tracing the podzolization process in future studies of podzol soils. The findings of this study demonstrate the utility of molecular fingerprinting in soil science and emphasize the critical role of hydrology on the molecular composition and carbon dynamics of Amazonian Podzol soils.

Though reverse transcription-quantitative polymerase chain reaction (RT-qPCR), RT digital PCR (RT-dPCR), and RT digital droplet PCR (RT-ddPCR) are commonly used for wastewater-based epidemiology and surveillance (WBE/WBS), differences among the platforms exist. While RT-ddPCR has been suggested as an ideal approach to use globally for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) monitoring, access to RT-qPCR instrumentation is more widely available in many regions, and it is more economical. Subsequently, a larger number of studies have used RT-qPCR for SARS-CoV-2 wastewater monitoring, along with additional pathogens that can be detected with WBS. In this study, we employed RT-qPCR and RT-dPCR platforms for the comparative detection of vaccine (A genotype Edmonston) and wild-type (D8 genotype) measles RNA from wastewater in nearby cities separated by <50 km during an ongoing measles outbreak in Texas, USA, in addition to several other locations up to 30-1400 km from the outbreak location. The limit of detection (LOD) for each methodology was evaluated using a synthetic gBlock DNA gene fragment of known concentrations, with comparable LODs identified for both the RT-dPCR (∼0.5 gc/μL) and RT-qPCR (∼0.4 gc/μL) platforms. Using composite supernatant-solid wastewater samples, RNA aliquots were analyzed on each platform in parallel. The RT-qPCR platform demonstrated a higher detection rate than RT-dPCR for the vaccine strain quantified in wastewater samples, with equivalent detections for the wild-type strain in both platforms, and notable differences in the gene copies quantified in wastewater based on the platform. Our study identifies that regardless of PCR methodology employed, WBS is a particularly valuable approach for the spatially informed differentiation of measles during rapid response to an active outbreak.

The massive usage of synthetic plastics in modern life has led to plastic waste generation, and its accumulation is a key concern for the environment and human health. Therefore, plastic is a growing environmental burden because of its small size, stability, and high recalcitrance, needing urgent advancements in plastic waste management. Plastics combined with cocontaminants, i.e., heavy metals, pharmaceutical toxicants, and other plasticizers, can cause serious environmental issues. Hence, an efficient and scalable method based on enzymes and biotechnological approaches is required for sustainable microplastic degradation. The present review focuses on the advanced and emerging biotechnological approaches for plastic and microplastic degradation, i.e., genetic engineering and genome editing tools. The review also discusses the challenges encountered in degradation viz. the depolymerization rate of microplastics and the intrinsic and extrinsic factors, such as degrees of crystallinity, chemical structure, functional group, and molecular weight. Furthermore, the insight in this study is useful to the researchers and scientific communities investigating plastic degradation. Thus, future research can be focused on microbial metabolites and improving catalytic efficiency with extrinsic conditions involved in these processes.

Natural and anthropogenic sources of lead (Pb) can adversely impact water and sediment quality within large watersheds and the ecosystems they support. This study examined the sources and distribution of Pb within the San Juan watershed located in southwestern Colorado and the Four Corners region of Colorado, New Mexico, Arizona, and Utah (western United States). Samples for this project were collected from 2018 to 2021 and included seeps and springs located within the mineralized headwaters region, surface water, and sediments along an approximately 570 km stretch of riverbed. Concentrations and isotopic compositions of Pb showed that (1) source attribution using all stable Pb isotope ratios, ²⁰⁶Pb/²⁰⁴Pb, ²⁰⁷Pb/²⁰⁴Pb, and ²⁰⁸Pb/²⁰⁴Pb, allowed for an analysis of metal dilution and changing sources of Pb; (2) in upstream reaches, Pb from landscape disturbance related to mining operations and weathering of mineralized geologic units represented the most significant Pb source, accounting for as much as 90% of the Pb within the upper Animas River sediments; and (3) Pb attributed to the mining-impacted headwaters decreased downstream through the Animas River and San Juan River and represented up to about 50% of the Pb in downstream sediments. The proportion and mass of Pb derived from the mining district were reduced in downstream areas due to increased sediment delivery to the central river channels from tributaries and weathering of Paleozoic- to Tertiary-aged sedimentary deposits. Our analysis demonstrates that Pb isotope ratios can be used to effectively trace Pb transport through watershed systems where multiple Pb sources exist and where Pb concentrations may be similar to geogenic values. The study results indicate that the spatial and temporal variation of Pb isotopic signatures is associated with multiple contributions from natural sources, which are influenced by seasonality and hydrological factors.

Global wetlands have declined by 21-35% since the 18th century, losing approximately 1.3 million square miles. Infrastructure development, specifically, river channelization via levee construction, is a driver of this decline. In response, large-scale river diversion projects have been proposed to enhance sediment deposition and stabilize coastal wetlands. However, the role of aquatic chemistry in controlling the fluvial sediment deposition remains elusive. Here, we demonstrate that land formation by fluvial sediment deposition is intrinsically linked to wetland water salinity, which influences the sediment aggregation and settling kinetics. In laboratory experiments, Mississippi River sediments were exposed to a range of salinities that mimic the conditions in Louisiana wetlands. Our results show that higher ionic strength accelerates sediment aggregation and settling due to electrical double-layer compression while also reducing the packing density of deposited sediments, potentially impacting land stability. These findings point to the importance of incorporating salinity effects to optimize sediment diversion strategies.

Sulfur (S)-containing compounds can be unambiguously identified by their distinctive isotope patterns in mass spectrometry (MS) when the instrument has a mass resolution exceeding 500,000. However, many environmental research laboratories that perform nontargeted analysis rely on high-resolution mass spectrometry (HRMS) instruments, such as quadrupole time-of-flight mass spectrometry (QTOF MS). These HRMS instruments typically operate at a mass resolution of less than 50,000. At such limited resolution, confidently recognizing sulfur isotope patterns is challenging. This work develops a machine learning (ML) strategy for recognizing and predicting the number of S present using HRMS at a mass resolution as low as 25,000. We benchmarked our ML strategy on experimental data, where 200 S-containing standard compounds were mixed into complex environmental samples. In positive electrospray ionization (ESI) mode, our ML strategy achieved accuracies ranging from 87.4 to 95.0% for S recognition and accuracies ranging from 86.3 to 96.6% for S number prediction. Notably, the ML method performed similarly well in negative ESI mode. Our ML strategy was further evaluated on an external experimental water dataset where it correctly recognized the presence of S for all 24 previously reported 2-mercaptobenzothiazole disinfection byproducts (DBPs). The developed ML strategy was implemented into SulfurFinder, an R program, to facilitate automated data cleaning, S recognition, and S number prediction in HRMS data. SulfurFinder combined with HPLC-HRMS analysis of a wastewater sample tentatively identified 169 potential S-containing features. Of these, three were confirmed as S-containing pharmaceuticals. An additional S-containing drug was also putatively annotated using molecular networking. The development of SulfurFinder significantly boosts the capability of conventional HRMS to address the challenge of S recognition in the era of exposomics, supporting a wide range of environmental applications.

Environmental sciences, including environmental chemistry and toxicology, are highly interdisciplinary fields that integrate researchers with various backgrounds and expertise. This interdisciplinary aspect is critical to addressing issues of chemical pollution, environmental sustainability, and health. However, a standardized method for reporting chemical data is needed to address these issues effectively. This becomes increasingly important as both the number of chemical structures and our reliance on and use of computational analysis and cheminformatics tools grow. This paper provides background, examples, and recommendations on how to report chemical data in a findable, accessible, interoperable, and reproducible (FAIR) manner within environmental science disciplines. Ultimately, the goal is to broaden the scope and applicability of environmental research to help the entire community tackle the issues of chemical pollution and sustainability in a comprehensive manner.