Correlation between phosphorus removal technologies and phosphorus speciation in sewage sludge: focus on iron-based P removal technologies.

Phosphorus recovery from sewage sludge as secondary raw materials or as a direct P-rich fertiliser is one of the top frontrunner solutions to tackle Phosphorus (P) scarcity and depletion. However, the efficiency of this P recovery process greatly depends on its phosphorus dissolution potential, which in return relies on the phosphorus speciation in the sewage sludge. This article investigates the potential correlation between P speciation in sewage sludge and the iron-based P removal technologies used in sewage treatment plants (STP) through an innovative sequential extraction method based on the SEDEX method that distinguishes quantitatively between ferrous bound phosphate and ferric bound phosphate. XRD and SEM-EDX were also used to characterise P and Fe species in the studied sludge qualitatively. Principal component analysis showed that the sludge characterised by P bound to ferric iron (as the dominant P fraction) are mostly correlated with sludge produced from the CPR process (chemical phosphorus removal) and primary sludge. Moreover, sludge with a non-negligible amount of P bound to ferrous iron were correlated with sludge from the mixed EBPR-CPR process (Enhanced Biological P Removal assisted with CPR). However, Vivianite was only found in CPR sludge with Fe/P molar ratio higher than 0.6.

Emission of hydrogen sulfide (H2S) at a waterfall in a sewer: study of main factors affecting H2S emission and modeling approaches.

Hydrogen sulfide (H2S) represents one of the main odorant gases emitted from sewer networks. A mathematical model can be a fast and low-cost tool for estimating its emission. This study investigates two approaches to modeling H2S gas transfer at a waterfall in a discharge manhole. The first approach is based on an adaptation of oxygen models for H2S emission at a waterfall and the second consists of a new model. An experimental set-up and a statistical data analysis allowed the main factors affecting H2S emission to be studied. A new model of the emission kinetics was developed using linear regression and taking into account H2S liquid concentration, waterfall height and fluid velocity at the outlet pipe of a rising main. Its prediction interval was estimated by the residual standard deviation (15.6%) up to a rate of 2.3 g H2S·h-1. Finally, data coming from four sampling campaigns on sewer networks were used to perform simulations and compare predictions of all developed models.

Assessment of the aerobic preparation and bottom ash addition as pretreatment steps before landfilling: impact on methanogenesis kinetics and leachate parameters.

This work focuses on assessing the impact of two types of waste pretreatment: addition of bottom ashes and aerobic pretreatment on both the onset and kinetics of methanogenesis and the evolution of different parameters in the leachate. It also studies the correlation between methane production and the different parameters measured in the leachate produced. A total of six 68-L pilots were thus used with fresh municipal solid waste (MSW) shredded to a 40-mm size. After 14 months of landfilling, the control has produced less than 10 NLkg(-1)DM, which corresponds to around 7% of its biochemical methane potential (BMP). Nevertheless, on one hand for aerobically pretreated waste, the lag phase before the onset of methanogenesis is significantly reduced to 0.9 month compared to more than 1 year for the control. In addition to that, on average 110 NLkg(-1)DM (90% of the BMP) is produced within around 6.5 months. On the other hand, the waste with added bottom ash shows a slight improvement of the lag phase over the control for one of the duplicate: 6.1 months of lag phase. At this stage, on average of 26 NLkg(-1)DM waste are detected (22% of the BMP) no final conclusion concerning the impact of bottom ashes could be made. The data obtained for the leachate parameters agrees with the observations on methane production. Statistical correlation study shows that the two components of the corrected PCA interpret 76% of the variability of the data: SUVA (specific UV absorbance at 254 nm) and HPI(*) (% of hydrophilic compounds) are identified as interesting parameters for following up the biodegradation in landfill conditions.