A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.     

Developing “precise-acting” strategies for improving anaerobic methanogenesis of organic waste: Insights from the electron transfer system of syntrophic partners

Methanogenesis is the last step in anaerobic digestion, which is usually a rate-limiting step in the biological treatment of organic waste. The low methanogenesis efficiency (low methane production rate, low methane yield, low methane content) substantially limits the development of anaerobic digestion technology. Traditional pretreatment methods and bio-stimulation strategies have impacts on the entire anaerobic system and cannot directly enhance methanogenesis in a targeted manner, which was defined as “broad-acting” strategies in this perspective. Further, we discussed our opinion of methanogenesis process with insights from the electron transfer system of syntrophic partners and provided potential targeted enhancing strategy for high-efficiency electron transfer system. These “precise-acting” strategies are expected to achieve an efficient methanogenesis process and enhance the bio-energy recovery of organic waste.     

Product identification and toxicity change during oxidation of methotrexate by ferrate and permanganate in water

• Oxidation of methotrexate by high-valent metal-oxo species was first explored. • Fe(VI) presented a higher reactivity to MTX than Mn(VII) at pH 8.0. • Ketonization and cleavage of peptide bond were two initial reaction pathways. • Products of MTX were not genotoxic, neurotoxic, or endocrine-disrupting chemicals. • The less biodegradable products exhibited developmental and acute/chronic toxicity. Accompanying an annual increase in cancer incidence, the global use of anticancer drugs has remarkably increased with their worldwide environmental prevalence and ecological risks. In this study, the oxidation of methotrexate (MTX), a typical anticancer drug with ubiquitous occurrence and multi-endpoint toxicity, by ferrate(VI) (Fe(VI)) and permanganate (Mn(VII))) was investigated in water. Fe(VI) exhibited a higher reactivity with MTX (93.34 M⁻¹ s⁻¹) than Mn(VII) (3.01 M⁻¹ s⁻¹) at pH 8.0. The introduction of Cu(II) and Fe(III) at 1.0 mM improved the removal efficiency of 5.0 μM MTX by 100.0 μM Fe(VI) from 80% to 95% and 100% after 4 min, respectively. Seven oxidized products (OPs) were identified during oxidative treatments, while OP-191 and OP-205 were characterized as specific products for Fe(VI) oxidation. Initial ketonization of the L-glutamic acid moiety and cleavage of the peptide bond of MTX were proposed. Additionally, a multi-endpoint toxicity evaluation indicated no genotoxicity, neurotoxicity, or endocrine-disrupting effects of MTX and its OPs. Particularly, serious developmental toxicity in zebrafish larvae was observed in the treated MTX solutions. Based on the acute and chronic aquatic toxicity prediction, OP-190, OP-192, OP-206, and OP-208 were deemed toxic or very toxic compared to harmful MTX. Furthermore, the reduced biodegradability index from 0.15 (MTX) to −0.5 to −0.2 (OP-192, OP-206, and OP-468) indicated the formation of lower biodegradable OPs. Overall, this study suggests that Fe(VI) and Mn(VII) oxidation are promising treatments for remediating anticancer drug-contaminated water. However, the environmental risks associated with these treatments should be considered in the evaluation of water safety.     

Semi-closed synthesis of nitrogen and oxygen Co-doped mesoporous carbon for selective aqueous oxidation

Heteroatom-doped meso/micro-porous carbon materials are conventionally produced by harsh carbonization under an inert atmosphere involving specific precursors, hard/soft templates, and heteroatom-containing agents. Herein, we report a facile synthesis of N and O co-doped meso/micro-porous carbon (NOMC) by template-free carbonization of a small-molecule precursor in a semi-closed system. The semi-closed carbonizaiton process yields hydrophilic NOMCs with large surface area in a high yield. The porous structure as well as the elemental composition of NOMCs can be modulated by changing the holding time at a particular temperature. NOMCs as metal-free heterogeneous catalysts can selectively oxidize benzyl alcohol and its derivatives into aldehydes/ketones with>85％conversion in aqueous solution, which is much higher than that of the control sample obtained in tube furnace (21％conversion), mainly due to their high N content, high percentage of pyridinic N, and large surface area. The presence of O-containing moieties also helps to improve the hydrophilicity and dispersion ability of catalysts and thus facilitates the mass transfer process during aqueous oxidation. The NOMC catalysts also dispayed excellent activity for a wide range of substrates with a selectivity of>99％.     

Study of water quality response to water transfer patterns in the receiving basin and surrogate model

Environmental Science and Pollution Research - The spatio-temporal response of water quality in the receiving basins to water transfer remains unclear when considering more practical factors....     

Emission inventory and control policy for non-road construction machinery in Tianjin

Environmental Science and Pollution Research - The establishment of a non-road construction machinery emission inventory forms the basis for the analysis of pollutant emission characteristics and...     

Accumulation of potentially toxic trace elements (PTEs) by native plant species growing in a typical gold mining area located in the northeast of Qinghai-Tibet Plateau

Environmental Science and Pollution Research - Though gold mines provide significant economic benefits to local governments, mining causes soil pollution by potentially toxic trace elements (PTEs)...     

Degradation of the typical herbicide atrazine by UV/persulfate: kinetics and mechanisms

Environmental Science and Pollution Research - Atrazine (ATZ), a widely used herbicide, had received a significant amount of attention due to its widespread detection in aquatic environments as...     

Assessing economic sustainability and ecological efficiency with genuine progress indicator: a case study of the Yangtze River Delta from 2000 to 2018

To achieve urban sustainability, it is critical to enhance the environment, economy, and society simultaneously. This study adopted the revised genuine progress indicator (GPI) and ecological footprint (EF) to evaluate the ecological efficiency and economic sustainability of the Yangtze River Delta from 2000 to 2018. Spatial analysis was utilized to identify spatial autocorrelation. A total of 27 cities were then partitioned through k-means cluster analysis. The results showed that GPI and ecological efficiency improved rapidly, but economic sustainability showed a downward trend. GPI and GDP had a high degree of spatial correlation, especially in Suzhou-Wuxi-Changzhou Metropolitan Area. However, no spatial correlation existed between GPI and EF. The city with high GEE can reach 3000 $/gha, indicating the city consumed 1 global hectare to create $3000 of genuine economic growth. Shanghai, Hangzhou, and Taizhou were cities with the highest level of economic sustainability and ecological efficiency. The spatiotemporal characteristics of economic sustainability and ecological efficiency revealed in this study will provide theoretical guidance for alleviating ecological pressure and promoting economic sustainable development.

     

Diversity and biogenesis contribution of sulfate-reducing bacteria in arsenic-contaminated soils from realgar deposits

Environmental Science and Pollution Research - Microbial sulfate reduction, a vital mechanism for microorganisms living in anaerobic, sulfate-rich environments, is an essential aspect of the sulfur...