Data-Driven Insights into the Contamination of Polycyclic Aromatic Hydrocarbons in Marine Bays.

The synthesis of polycyclic aromatic hydrocarbon (PAH) data allows us to quantify and gain insights into the spatiotemporal dynamics of PAH contamination in marine bays. Here, a data synthesis framework was developed to understand data-driven insights into the spatiotemporal levels, compositional profiles, and potential sources of PAHs in water and sediment of marine bays. PAHs were detected in 69 bays worldwide, with contamination hotspots located in Asian bays. PAH concentrations in pre-2000 were significantly lower than those in the 2000s and post-2010, while the dominant species in water and sediment were 2-3 ring and 4-6 ring PAHs, respectively. The composition patterns of PAHs included 2-3 ring, 3-5 ring, and 4-5 ring dominant categories, but no significant distance decay relationship was found in the composition similarity due to international energy trade. Temporal dynamic patterns of concentrations included Descending-, Ascending-, and Inverted V-type, whereas over longer time spans, the pattern is more similar to the Inverted V-type owing to the reductions in emission intensity. PAHs were derived from both petrogenic and pyrolytic sources, with combustion from both coal and petroleum being the dominant source. These data-driven discoveries provide quantitative insights into the spatiotemporal patterns in the concentration and composition of PAHs, contributing to the mitigation of PAH contamination.

Fertilization regulates global thresholds in soil bacteria.

Global patterns in soil microbiomes are driven by non-linear environmental thresholds. Fertilization is known to shape the soil microbiome of terrestrial ecosystems worldwide. Yet, whether fertilization influences global thresholds in soil microbiomes remains virtually unknown. Here, utilizing optimized machine learning models with Shapley additive explanations on a dataset of 10,907 soil samples from 24 countries, we discovered that the microbial community response to fertilization is highly dependent on environmental contexts. Furthermore, the interactions among nitrogen (N) addition, pH, and mean annual temperature contribute to non-linear patterns in soil bacterial diversity. Specifically, we observed positive responses within a soil pH range of 5.2-6.6, with the influence of higher temperature (>15°C) on bacterial diversity being positive within this pH range but reversed in more acidic or alkaline soils. Additionally, we revealed the threshold effect of soil organic carbon and total nitrogen, demonstrating how temperature and N addition amount interacted with microbial communities within specific edaphic concentration ranges. Our findings underscore how complex environmental interactions control soil bacterial diversity under fertilization.

Wastewater Discharge Transports Riverine Microplastics over Long Distances.

Wastewater discharge from wastewater treatment plants continuously pumps microplastics into rivers, yet their transport distances within these waterways remain unknown. Herein, we developed a conceptual framework by synthesizing the microplastic data from the Yangtze River Basin to evaluate its transport distances, quantifying a significant spatial dependence between large-scale wastewater discharge and riverine microplastics (p < 0.05). The presence of microplastics at a specific sampling site could be attributed to wastewater discharge within a large-scale range spanning >1000 km upstream, encompassing a substantial portion equivalent to one-third of the Yangtze River Basin. The dominance analysis indicated that the contribution of wastewater discharge in rivers with higher discharge (>100 m3/s) to riverine microplastic pollution exceeded 65% within the Yangtze River Basin. The spatial dependence framework of riverine microplastics on wastewater discharge advances our prior understanding of the prevention and control of riverine microplastics by demonstrating that such pollution is not limited to nearby environmental factors.

Distance-decay equations of antibiotic resistance genes across freshwater reservoirs.

Distance-decay (DD) equations can discern the biogeographical pattern of organisms and genes in a better way with advanced statistical methods. Here, we developed a data Compilation, Arrangement, and Statistics framework to advance quantile regression (QR) into the generation of DD equations for antibiotic resistance genes (ARGs) across various spatial scales using freshwater reservoirs as an illustration. We found that QR is superior at explaining dissemination potential of ARGs to the traditionally used least squares regression (LSR). This is because our model is based on the 'law of limiting factors', which reduces influence of unmeasured factors that reduce the efficacy of the LSR method. DD equations generated from the 99th QR model for ARGs were 'Sall = 90.03e-0.01Dall' in water and 'Sall = 92.31e-0.011Dall' in sediment. The 99th QR model was less impacted by uneven sample sizes, resulting in a better quantification of ARGs dissemination. Within an individual reservoir, the 99th QR model demonstrated that there is no dispersal limitation of ARGs at this smaller spatial scale. The QR method not only allows for construction of robust DD equations that better display dissemination of organisms and genes across ecosystems, but also provides new insights into the biogeography exhibited by key parameters, as well as the interactions between organisms and environment.

Significant regional disparities in riverine microplastics.

Research on riverine microplastics has gradually increased, highlighting an area for further exploration: the lack of extensive, large-scale regional variations analysis due to methodological and spatiotemporal limitations. Herein, we constructed and applied a comprehensive framework for synthesizing and analyzing literature data on riverine microplastics to enable comparative research on the regional variations on a large scale. Research results showed that in 76 rivers primarily located in Asia, Europe, and North America, the microplastic abundance of surface water in Asian rivers was three times higher than that in Euro-America rivers, while sediment in Euro-American rivers was five times more microplastics than Asia rivers, indicating significant regional variations (p < 0.001). Additionally, based on the income levels of countries, rivers in lower-middle and upper-middle income countries had significantly (p < 0.001) higher abundance of microplastics in surface water compared to high-income countries, while the opposite was true for sediment. This phenomenon was preliminarily attributed to varying levels of urbanization across countries. Our proposed framework for synthesizing and analyzing microplastic literature data provides a holistic understanding of microplastic disparities in the environment, and can facilitate broader discussions on management and mitigation strategies.

Microplastic accumulation in groundwater: Data-scaled insights and future research.

Given that microplastics (MPs) in groundwater have been concerned for risks to humans and ecosystems with increased publications, a Contrasting Analysis of Scales (CAS) approach is developed by this study to synthesize all existing data into a hierarchical understanding of MP accumulation in groundwater. Within the full data of 386 compiled samples, the median abundance of MPs in Open Groundwater (OG) and Closed Groundwater (CG) were 4.4 and 2.5 items/L respectively, with OG exhibiting a greater diversity of MP colors and larger particle sizes. The different pathways of MP entry (i.e., surface runoff and rock interstices) into OG and CG led to this difference. At the regional scale, median MP abundance in nature reserves and landfills were 17.5 and 13.4 items/L, respectively, all the sampling points showed high pollution load risk. MPs in agricultural areas exhibited a high coefficient of variation (716.7%), and a median abundance of 1.0 items/L. Anthropogenic activities at the regional scale are the drivers behind the differentiation in the morphological characteristics of MPs, where groundwater in residential areas with highly toxic polymers (e.g., polyvinylchloride) deserves prolonged attention. At the local scale, the transport of MPs is controlled by groundwater flow paths, with a higher abundance of MP particles downstream than upstream, and MPs with regular surfaces and lower resistance (e.g., pellets) are more likely to be transported over long distances. From the data-scaled insight this study provides on the accumulation of MPs, future research should be directed towards network-based observation for groundwater-rich regions covered with landfills, residences, and agricultural land.

Data-driven discoveries on widespread contamination of freshwater reservoirs by dominant antibiotic resistance genes.

The propagation of antibiotic resistance genes (ARGs) in freshwater reservoirs threatens ecosystem security and human health, and has attracted increasing attention. A series of recent research articles on ARGs provides a unique opportunity for data-driven discoveries in this emerging field. Here, we mined data from a total of 290 samples from 60 reservoirs worldwide with a data-driven framework (DD) developed to discover geographical distribution, influencing factors and pollution hotspots of ARGs in freshwater reservoirs. Most data came from Asia and Europe where nine classes of ARGs were most frequently detected in reservoirs with multi-drug resistance and sulfonamide resistance genes prevailing. Factors driving distribution of reservoir ARGs differed between reservoir waters and sediments, and interactions among these factors had linear or nonlinear enhancement effects on the explanatory power of ARG distribution. During the cold season, small-sized reservoir waters rich in organic carbon, mobile genetic elements (MGEs) and antibiotics had a higher pollution potential of ARGs; during the spring drought, sediments in large reservoirs located in densely populated areas were more conducive to dissemination of ARGs due to their richness in antibiotics and MGEs. Thus, distribution pattern of ARG pollution hotspots in reservoir waters and sediments varies greatly depending on the differences of internal and external factors. From the "One Health" perspective, this widespread contamination of freshwater reservoirs by ARGs we discovered through the DD framework should be a push to promote integrated research across regions and disciplines. Especially the human - food-chain - ecosystem interface needs an improved understanding of ARG contamination mechanisms and targeted monitoring and evaluation systems should be developed to maintain all ecosystem services in freshwater reservoirs as well as to safeguard human health.

Widespread occurrence of microplastics in marine bays with diverse drivers and environmental risk.

Microplastic contamination in the sediment of marine bays has attracted widespread attention, whereas the distribution, sedimentation, morphology and risk of microplastics at regional scale remain poorly understood. By introducing a data mining framework into microplastic research, we compiled a microplastic dataset of 649 samples from 24 bays to enhance the understanding of geographical difference and drivers, transfer, composition profile and environmental risk of sedimental microplastics. Microplastic abundance varied from 0.72 to 1963.96 items/kg dry weight, with higher concentrations mainly occurring in East Asian bays. The spatial pattern in abundance was driven by the river plastic emissions, aquaculture production and hydrodynamic condition. A significantly positive correlation between microplastic abundance in water and sediment was found, and microplastic sedimentation was related to polymer density, hydrodynamic conditions and sediment properties. The dominant shape and polymer of sedimental microplastics were fiber and polypropylene, respectively, and the similarity of microplastic composition decreased with increasing geographical distance. The environmental risks of microplastics were partitioned into three classes (Rank II-Rank IV) with a two-dimensional assessment system considering the bioavailability and toxicity of microplastics, and Asian bays were identified as potential high-risk areas. To reduce the environmental risk of sedimental microplastics in bays, priority should be given to the removal of microfibers, and control measures depend on the risk classes and dominant polymers. Microplastic abundance and composition were significantly affected by methodological choices regarding sampling, pretreatment and identification, suggesting a unified methodology is essential to further enhance our knowledge on the distribution and risk of microplastics in marine bays.