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Author-produced version of the article published in Waste Management Original publication available at www.elsevier. com -doi:10.1016/j.wasman.2009.10.018 2 Abstract 1 This paper aimed to compare household waste, separated pig solids, food waste, pig slaughterhouse sludge 2 and green algae regarding processes ruling nitrogen dynamic during composting. For each waste, three 3 composting simulations were performed in parallel in three similar reactors (300L), each one under a constant 4 aeration rate. The aeration flows applied were comprised between 100 and 1100 L/h. The initial waste and the 5 compost were characterized through the measurements of their contents in dry matter, total carbon, Kjeldahl and 6 total ammoniacal nitrogen, nitrite and nitrate. Kjeldahl and total ammoniacal nitrogen and nitrite and nitrate 7were measured in leachates and in condensates too. Ammonia and nitrous oxide emissions were monitored in 8 continue. The cumulated emissions in ammonia and in nitrous oxide were given for each waste and at each 9 aeration rate. The paper focused on process of ammonification and on transformations and transfer of total 10 ammoniacal nitrogen. The parameters of nitrous oxide emissions were not investigated. The removal rate of 11 total Kjeldahl nitrogen was shown being closely tied to the ammonification rate. Ammonification was modelled 12 thanks to the calculation of the ratio of biodegradable carbon to organic nitrogen content of the biodegradable 13 fraction. The wastes were shown to differ significantly regarding their ammonification ability. Nitrogen 14 balances were calculated by subtracting nitrogen losses from nitrogen removed from material. Defaults in 15 nitrogen balances were assumed to correspond to conversion of nitrate even nitrite into molecular nitrogen and 16 then to the previous conversion by nitrification of total ammoniacal nitrogen. The pool of total ammoniacal 17 nitrogen, i.e. total ammoniacal nitrogen initially contained in waste plus total ammoniacal nitrogen released by 18 ammonification, was calculated for each experiment. Then, this pool was used as the referring amount in the 19 calculation of the rates of accumulation, stripping and nitrification of total ammoniacal nitrogen. Separated pig 20 solids were characterised by a high ability to accumulate total ammoniacal nitrogen. Whatever the waste, the 21 striping rate depended mostly on the aeration rate and on the pool concentration in biofilm. The nitrification rate 22 was observed as all the higher as the concentration in total ammoniacal nitrogen in the initial waste was low. 23Thus, household waste and green algae exhibited the highest nitrification rates. This result could mean that in 24 case of low concentrations in total ammoniacal nitrogen, a nitrifying biomass was already developed and that 25 this biomass consumed it. In contrast, in case of high concentrations, this could traduce some difficulties for 26 nitrifying microorganisms to develop. 27

This paper aims to compare household waste, separated pig solids, food waste, pig slaughterhouse sludge 2 and green algae regarding their biodegradability, their stabilization kinetics and their temperature rise during 3 composting. Three experiments in lab-scale pilots (300L) were performed for each waste, each one under a 4 constant aeration rate. The aeration rates applied were comprised between 100 and 1100 L/h. The 5 biodegradability of waste was expressed as function of dry matter, organic matter, total carbon and chemical 6 oxygen demand removed, on one hand, and of total oxygen consumption and carbon dioxide production on the 7 other. These different variables were found closely correlated. Time required for stabilization of each waste was 8 determined too. A method to calculate the duration of stabilization in case of limiting oxygen supply was 9proposed. Carbon and chemical oxygen demand mass balances were established and gaseous emissions as 10 carbon dioxide and methane were given. Finally, the temperature rise was shown to be proportional to the total 11 mass of material biodegraded during composting. 12 13

Monitoring hydrophobic contaminants in surface freshwaters requires measuring contaminant concentrations in the particulate fraction (sediment or suspended particulate matter, SPM) of the water column. Particle traps (PTs) have been recently developed to sample SPM as cost-efficient, easy to operate and time-integrative tools. But the representativeness of SPM collected with PTs is not fully understood, notably in terms of grain size distribution and particulate organic carbon (POC) content, which could both skew particulate contaminant concentrations. The aim of this study was to evaluate the representativeness of SPM characteristics (i.e. grain size distribution and POC content) and associated contaminants (i.e. polychlorinated biphenyls, PCBs; mercury, Hg) in samples collected in a large river using PTs for differing hydrological conditions. Samples collected using PTs (n = 74) were compared with samples collected during the same time period by continuous flow centrifugation (CFC). The grain size distribution of PT samples shifted with increasing water discharge: the proportion of very fine silts (2-6 μm) decreased while that of coarse silts (27-74 μm) increased. Regardless of water discharge, POC contents were different likely due to integration by PT of high POC-content phytoplankton blooms or low POC-content flood events. Differences in PCBs and Hg concentrations were usually within the range of analytical uncertainties and could not be related to grain size or POC content shifts. Occasional Hg-enriched inputs may have led to higher Hg concentrations in a few PT samples (n = 4) which highlights the time-integrative capacity of the PTs. The differences of annual Hg and PCB fluxes calculated either from PT samples or CFC samples were generally below 20%. Despite some inherent limitations (e.g. grain size distribution bias), our findings suggest that PT sampling is a valuable technique to assess reliable spatial and temporal trends of particulate contaminants such as PCBs and Hg within a river monitoring network.

Understanding and predicting the propagation, deposition and re-suspension of suspended particulate matter (SPM) in river networks is important for managing water resources, ecological habitat, pollution, navigation, hydropower generation, reservoir sedimentation, etc. Observational data are scarce and costly, and there is little feedback on the efficiency of numerical simulation tools for compensating the lack of data on a river scale of several hundreds of kilometres.