Vertical-flow constructed wetlands as a sustainable on-site greywater treatment process for the decrease of micropollutant concentration in urban wastewater and integration to households' water services.

Micropollutant removal from effluent of conventional wastewater treatment has recently become one of the most discussed topics in the design and operation of wastewater treatment plants (WWTPs). This is due to the need to add a post-treatment step to the conventional processes to comply with stricter quality standards for effluents as outlined in the revised Urban Wastewater Treatment Directive (UWWTD). The adoption of on-site or decentralized greywater (GW) treatment in sustainable buildings using vertical-flow constructed wetlands (VFCWs) is a promising direction. It represents an interesting alternative for the removal of micropollutants at the source of pollution, such as personal care products (PCPs) and some pharmaceuticals which are mainly present in this wastewater fraction. Additionally, the treated greywater could be used in households' water services which do not require potable water quality, thus saving drinking water. In this context, this work compares the results of micropollutant removal from projects using VFCWs as a polishing step of WWTPs effluent, as a centralized solution, to the results from a decentralized GW treatment. The results show that VFCWs can remove the investigated micropollutants (Diclofenac and DEET) with an efficiency of >90 %, in both centralized and decentralized treatments. The admixture biochar from plant residues and from cellulose-toilet paper proved to be a promising substitute for the mineral zeolite when mixed with sand to remove PCPs from GW and, therefore, a circular economy concept can be applied to this technology.

Biochar from recovered cellulose as new admixture in constructed wetlands for micropollutant removal: A circular approach.

This study aimed to evaluate the suitability of biochar produced by pyrolysis from recovered wastewater cellulose and activated biologically as an admixture in Constructed Wetlands (CWs) when applied as a post-treatment step to remove micropollutants (MPs) from municipal wastewater effluent. Two planted vertical flow mesocosm CWs with cellulose-based admixtures of different origins (plant residue and recovered toilet paper) were fed with a municipal wastewater effluent representative for rural catchments. The results showed an average MPs elimination of 89.1 % for the activated biochar produced from recovered cellulose when 15 relevant compounds are considered and a reduction of the risk from compounds cocktail below the maximum acceptable level having diclofenac, carbamazepine, PFOS, ciprofloxacin and clarithromycin as main risk drivers (Risk Quotient > 1). The implementation of a circular approach to reduce MPs was finally conducted for the Blies catchment (Saarland region in Germany) characterized by low population density and small, sensitive water bodies. This approach demonstrates the feasibility of combining cellulose recovery with a fine sieve in large wastewater treatment plants (WWTPs) and providing biochar produced from recovered cellulose as an admixture to small WWTP where CW is an affordable solution for MP mitigation.

Can ChatGPT outperform a neurosurgical trainee? A prospective comparative study.

PURPOSE: This study aimed to compare the performance of ChatGPT, a large language model (LLM), with human neurosurgical applicants in a neurosurgical national selection interview, to assess the potential of artificial intelligence (AI) and LLMs in healthcare and provide insights into their integration into the field. METHODS: In a prospective comparative study, a set of neurosurgical national selection-style interview questions were asked to eight human participants and ChatGPT in an online interview. All participants were doctors currently practicing in the UK who had applied for a neurosurgical National Training Number. Interviews were recorded, anonymised, and scored by three neurosurgical consultants with experience as interviewers for national selection. Answers provided by ChatGPT were used as a template for a virtual interview. Interview transcripts were subsequently scored by neurosurgical consultants using criteria utilised in real national selection interviews. Overall interview score and subdomain scores were compared between human participants and ChatGPT. RESULTS: For overall score, ChatGPT fell behind six human competitors and did not achieve a mean score higher than any individuals who achieved training positions. Several factors, including factual inaccuracies and deviations from expected structure and style may have contributed to ChatGPT's underperformance. CONCLUSIONS: LLMs such as ChatGPT have huge potential for integration in healthcare. However, this study emphasises the need for further development to address limitations and challenges. While LLMs have not surpassed human performance yet, collaboration between humans and AI systems holds promise for the future of healthcare.