In order to develop constructed wetland (CW) with high-rate N and P removal, sulfur and pyrrhotite modified foam concrete (SPFC) was prepared and used as a substrate to construct CW (SPFC-CW). At hydraulic retention time 6 h, SPFC-CW achieved effluent total nitrogen (TN) 9.96 mg/L and PO-P 0.11 mg/L as influent TN and PO-P were 24.52 and 1.04 mg/L, respectively. TN and PO-P removal rates of SPFC-CW were 21.8 and 1.4 g/md, respectively. Many precipitates with high content of Ca and P attached on SPFC. Sulfurimonas was the most dominant bacterium, and its relative abundances at upper, middle and bottom of SPFC-CW were 53.8 %, 68.4 % and 87.3 %, respectively. SPFC could slowly release S and SO, which had higher autotrophic denitrification rate than pyrrhotite and sulfur, and more Ca than foam concrete. In SPFC-CW sulfur autotrophic denitrification and Ca-P precipitation were the major N and P removal processes, respectively.
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http://dx.doi.org/10.1016/j.biortech.2024.132008 | DOI Listing |
Bioresour Technol
December 2024
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, 163# Xianlin Avenue, Nanjing 210023, PR China. Electronic address:
In order to develop constructed wetland (CW) with high-rate N and P removal, sulfur and pyrrhotite modified foam concrete (SPFC) was prepared and used as a substrate to construct CW (SPFC-CW). At hydraulic retention time 6 h, SPFC-CW achieved effluent total nitrogen (TN) 9.96 mg/L and PO-P 0.
View Article and Find Full Text PDFWater Res
December 2024
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, 163# Xianlin Ave., Nanjing 210023, China. Electronic address:
Aiming at disadvantages of conventional sulfur-limestone autotrophic denitrification system, such as producing stink (HS) and low-rate nitrogen and phosphorus removal from wastewater with low C/N, foam FeSO modified limestone sulfur concrete (FFLSC) was prepared. Experimental parameters of FFLSC biofilter, such as hydraulic retention time (HRT), influent NO-N, additional alkalinity and COD addition, were tested. For wastewater without COD, FFLSC biofilter could simultaneously remove TON (NO-N+NO-N) from 22.
View Article and Find Full Text PDFMaterials (Basel)
November 2024
Department of Construction and Geoengineering, Poznan University of Life Sciences, Piątkowska 94E, 60-649 Poznan, Poland.
This study addresses a practical and efficient approach to evaluating the load-bearing capacity of severely degraded concrete manholes. Concrete deterioration, often advanced and highly irregular, can be captured accurately through surface scanning to create a detailed model of the damaged structure and also to build a simplified modeling to enable rapid engineering-level assessment, filling a critical gap in infrastructure maintenance. The repair strategy involves applying an internal polyurea layer, a variable-thickness polyurethane foam layer depending on the degree of localized degradation, and an external polyurea layer to restore the original shape of the manhole.
View Article and Find Full Text PDFHeliyon
December 2024
School of Civil Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, 600127, India.
Engineered concrete mixes using industrial waste as a construction material are an enormous step towards sustainable development and financial benefits. The refrigeration, automobile, and construction industries mainly generate polyurethane foam waste material. Most of the polyurethane foam wastes are dumped in landfills or incineration, which creates environmental effects.
View Article and Find Full Text PDFJ Environ Manage
November 2024
Department of Civil and Environmental Engineering, College of Engineering, King Faisal University, Al-Ahsa, 31982, Saudi Arabia. Electronic address:
Foamed concrete (FC) is increasingly used in modern construction due to its lightweight nature, superior thermal insulation, and sustainable properties. However, accurately predicting its compressive strength remains a challenge due to the complex interactions of its components. This study addresses this gap by employing advanced machine learning tools, including decision tree (DT), bagging, and AdaBoost, to develop predictive models for FC strength.
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