Environmental Science: Water Research & Technology最新文献

The objective of this study was to assess the impacts of biochar and iron-enhanced sand (IES) on the comprehensive contaminant retention performance of a field-scale stormwater filtration system. The system distributed runoff from a parking lot into three filters containing sand, sand amended with biochar (custom-produced via pyrolysis of red pine wood chips at 550 °C), or IES. Over the first two field seasons of operation flow into the testbed and out of each filter were continuously monitored, and influent and effluent samples were collected during 21 precipitation events and analyzed for various contaminants and water quality parameters. To account for variations in flow distribution between the filters, long-term filter performance was assessed based on comparison of apparent cumulative input and output contaminant loads over the study duration (i.e., apparent cumulative contaminant retention). The IES filter showed the most effective phosphorous retention performance (>90% net retention of total phosphorus, TP), reflecting results from previous studies. The biochar-amended filter showed improved retention of zinc and total inorganic nitrogen (TIN) relative to the sand filter, which may be attributed to: (i) enhanced electrostatic interactions between zinc and oxygen-containing functional groups on the biochar surface, and (ii) improved attenuation of ammonia-N due to reduced nitrification and/or enhanced adsorption of ammonium. The biochar-amended filter did not show improved retention of total organic carbon or Escherichia coli, in contrast to some previous studies, potentially due to differences in biochar material properties (e.g., reduced hydrophobic interactions due to the custom biochar's relatively polar surface chemistry) or operational conditions (e.g., differences in flow rate or biofilm development between the filters). These findings demonstrate the complexities surrounding the application of biochar as a stormwater filter material for broad contaminant removal, and warrant the development of best practice recommendations for biochar selection and performance testing.

Urban domestic wastewater is a significant source of dissolved organic matter (DOM) in aquatic environments, critically impacting urban water quality. This study integrates the optical properties and molecular features of DOM, providing a comprehensive understanding of its behavior in urban sanitary sewage. Utilizing ultraviolet-visible (UV-vis) spectroscopy, three-dimensional synchronous fluorescence spectroscopy, and ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), we establish a robust bidirectional correlation between optical properties and molecular characteristics. Our findings reveal that urban domestic wastewater is predominantly composed of protein-like substances and microbial humic components, rich in heteroatoms and homologous compounds. The established correlations between optical and molecular features validate the DOM characterization system, demonstrating consistency between photochemical properties and molecular characteristics. Molecules related to photochemical parameters align with high H/C and low O/C ratio regions. The correlation analysis indicates that the highly associated areas are the fluorescent domains of protein-like materials and microbially derived humic-like substances. This innovative approach provides actionable insights for urban water quality management, highlighting the critical role of these methods in effective environmental monitoring.

Biochemical oxygen demand (BOD) is one of the most sensitive and essential indicators of wastewater quality. However, today, BOD detection methods require considerable effort and time, resulting in management and operational errors during the wastewater-treatment process which leads to the production of poor-quality effluent that poses a threat to public health and safety. Using advanced machine learning (ML) methods, we developed generalizable BOD prediction model based on a unique, centrally integrated database from 30 wastewater-treatment plants (WWTP) across Israel. The model is based on easily retrieved water parameters measured by on-site sensors or conventional analytical devices. In this work, three different ML algorithms were examined and compared, random forest (RF), support vector machine, and gradient tree boosting. The optimized RF model reached the best results, R² of 0.91 and RMSE of 8.58 in predicting the total BOD at different stages of the treatment process. The three key features for modeling were chemical oxygen demand, total suspended solids, and total Kjeldahl nitrogen. We then present an approach to predict BOD in effluent, focusing on binary classification predictions for regulatory compliance. For a prediction threshold of BOD > 9 mg L⁻¹, a recall of 0.89 was achieved. These results demonstrate the potential of the model to be a generalized solution for BOD predictions in WWTP across Israel, and possibly worldwide. This method can be used as a part of a sensor for BOD monitoring and management in wastewater, effectively minimizing the time gaps between routine lab testing. The fundamental challenge addressed herein has important global relevance, especially in an era in which the demand for high-quality wastewater reuse is expected to increase dramatically.

The efficient management of municipal sewage sludge (MSS) daily produced worldwide by biological wastewater treatment processes is nowadays of utmost importance. Classic treatment/disposal methods are affected by efficiency and/or safety issues. Innovative thermochemical treatments are gaining momentum as promising alternatives. Pyrolysis of MSS can result in the recovery of precious resources, such as nutrients and organic matter, and their conversion into three valuable fractions, i.e. biochar, bio-oil, and pyrolysis gas. These products are employable in innovative biorefinery pathways towards a wide range of value-added materials. In this review, an integrated biorefinery platform for MSS valorization is presented. After a brief introduction on MSS properties and issues related to its management, a deep focus on the influence that the feedstock and pyrolysis conditions have on the product yields and composition was conducted. Innovative valorization routes for biochar, bio-oil and pyrolysis gas were extensively discussed by highlighting challenges, opportunities, advantages and drawbacks. The characteristics required by these products to be efficiently valorized, as well as the main solution for their enhancement, were described. Additionally, economic considerations on MSS pyrolysis derived from full-scale applications conducted at the European and global level were elaborated. Finally, future perspectives about biochar, bio-oil and pyrolysis gas employment in cutting-edge upcycling routes have been reported.

The rational design of semiconductor photocatalysts with multi-dimensional nanostructures is an effective way to solve the problem of water environmental pollution. Herein, a series of ZnIn₂S₄/MgAl-LDH (ZIS/LDH) composites with core–shell nanostructures were synthesized by in situ growth of 2D ZnIn₂S₄ nanosheets on hexagonal LDH sheets. The obtained ZIS/LDH composite exhibited enhanced photocatalytic performance with 100% degradation efficiency for methyl orange (MO) within 20 min illumination, which was mainly attributed to the heterostructure formed by the excellent interface contact of the nanostructures, thereby inhibiting the recombination of photogenerated charges. Additionally, the as-synthesized photocatalyst shows satisfactory photocatalytic activity in stability tests and removal experiments for various dye pollutants. The present work provides novel insight into the design of heterojunction photocatalysts with multidimensional nanostructures and environmentally friendly applications.