Impact environnemental des pneumatiques déchiquetés utilisés pour la construction d’ouvrages en remblai

Depuis les années 1980, les pneumatiques usagés sont employés comme matériau de construction pour des ouvrages de génie civil et de géotechnique. S’agissant de déchets, leur impact sur l’environnement doit être évalué, au regard de l’application visée et de la réglementation en vigueur. Cet article porte sur l’impact environnemental de pneumatiques usagés déchiquetés, lorsqu'ils sont utilisés en mélange avec du sable, pour la construction d’ouvrages en remblai

Prediction of unsupported excavations behaviour with machine learning techniques

Artificial intelligence and machine learning algorithms have known an increasing interest from the research community, triggering new applications and services in many domains. In geotechnical engineering, for instance, neural networks have been used to benefit from information gained at a given site in order to extract relevant constitutive soil information from field measurements [1]. The goal of this work is to use machine (supervised) learning techniques in order to predict the behaviour of a sheet pile wall excavation, minimizing a loss function that maps the input (excavation’s depth, soil’s characteristics, wall’s stiffness) to a predicted output (wall’s deflection, soil’s settlement, wall’s bending moment). Neural networks are used to do this supervised learning. A neural network is composed of neurons which apply a mathematical function on their input (see Figure 1, left) and synapses which take the output of one neuron to the input of another one. For our purpose, neural networks can be understood as a set of nonlinear functions which can be fitted to data by changing their parameters. In this work, a simple class of neural networks, called Multi-Layer Perceptron (MLP) are used. They are composed of an input layer of neurons, an output layer, and one or several middle layers (hidden layers) (see Figure 1, right). A neural network learns by adjusting the weights and biases in order to minimize a certain loss function (for instance: the mean squared error) between the desired and the predicted output. Stochastic gradient descent or one of its variations are used to adjust the parameters and the gradients are obtained through backpropagation (an efficient application of the chain rule). The interest in neural networks comes from the fact that they are universal function estimators, in the sense that they can approximate any continuous function to any precision given enough neurons. However, this can lead to over-fitting problems where the network learns the noise in the data, or worse, where they memorize by rote each sample [2]

Experimental evidence of colloids and nanoparticles presence from 25 waste leachates.

International audienceThe potential colloids release from a large panel of 25 solid industrial and municipal waste leachates, contaminated soil, contaminated sediments and landfill leachates was studied. Standardized leaching, cascade filtrations and measurement of element concentrations in the microfiltrate (MF) and ultrafiltrate (UF) fraction were used to easily detect colloids potentially released by waste. Precautions against CO(2) capture by alkaline leachates, or bacterial re-growth in leachates from wastes containing organic matter should be taken. Most of the colloidal particles were visible by transmission electron microscopy with energy dispersion spectrometry (TEM-EDS) if their elemental MF concentration is greater than 200 μgl(-1). If the samples are dried during the preparation for microscopy, neoformation of particles can occur from the soluble part of the element. Size distribution analysis measured by photon correlation spectroscopy (PCS) were frequently unvalid, particularly due to polydispersity and/or too low concentrations in the leachates. A low sensitivity device is required, and further improvement is desirable in that field. For some waste leachates, particles had a zeta potential strong enough to remain in suspension. Mn, As, Co, Pb, Sn, Zn had always a colloidal form (MF concentration/UF concentration>1.5) and total organic carbon (TOC), Fe, P, Ba, Cr, Cu, Ni are partly colloidal for more than half of the samples). Nearly all the micro-pollutants (As, Ba, Co, Cr, Cu, Mo, Ni, Pb, Sb, Sn, V and Zn) were found at least once in colloidal form greater than 100 μgl(-1). In particular, the colloidal forms of Zn were always by far more concentrated than its dissolved form. The TEM-EDS method showed various particles, including manufactured nanoparticles (organic polymer, TiO(2), particles with Sr, La, Ce, Nd). All the waste had at least one element detected as colloidal. The solid waste leachates contained significant amount of colloids different in elemental composition from natural ones. The majority of the elements were in colloidal form for wastes of packaging (3), a steel slag, a sludge from hydrometallurgy, composts (2), a dredged sediment (#18), an As contaminated soil and two active landfill leachates. These results showed that cascade filtration and ICP elemental analysis seems valid methods in this field, and that electronic microscopy with elemental detection allows to identify particles. Particles can be formed from dissolved elements during TEM sample preparation and cross-checking with MF and UF composition by ICP is useful. The colloidal fraction of leachate of waste seems to be a significant source term, and should be taken into account in studies of emission and transfer of contaminants in the environment. Standardized cross-filtration method could be amended for the presence of colloids in waste leachates

Assessment of four calculation methods proposed by the EC for waste hazardous property HP 14 ‘Ecotoxic’

International audienceLegislation published in December 2014 revised both the List of Waste (LoW) and amended Appendix III of the revised Waste Framework Directive 2008/98/EC; the latter redefined hazardous properties HP 1 to HP 13 and HP 15 but left the assessment of HP 14 unchanged to allow time for the Directorate General of the Environment of the European Commission to complete a study that is examining the impacts of four different calculation methods for the assessment of HP 14. This paper is a contribution to the assessment of the four calculation methods. It also includes the results of a fifth calculation method; referred to as " Method 2 with extended M-factors ". Two sets of data were utilised in the assessment; the first (Data Set #1) comprised analytical data for 32 different waste streams (16 hazardous (H), 9 non-hazardous (NH) and 7 mirror entries, as classified by the LoW) while the second data set (Data Set #2), supplied by the eco industries, comprised analytical data for 88 waste streams, all classified as hazardous (H) by the LoW. Two approaches were used to assess the five calculation methods. The first approach assessed the relative ranking of the five calculation methods by the frequency of their classification of waste streams as H. The relative ranking of the five methods (from most severe to less severe) is: Method 3 > Method 1 > Method 2 with extended M-factors > Method 2 > Method 4. This reflects the arithmetic ranking of the concentration limits of each method whe

An analytical protocol for the knowledge of waste by substances

International audienceThe hazardousness of waste could be soon assessed in Europe by the hazard properties of its constituents. A quasi exhaustive knowledge of its constituents will therefore be necessary. A conceptual scheme of waste composition is proposed for analysis purpose, including unresolved pools of probably higher molecular weight organic substances supposed to be less bioactive and less hazardous ('non extractible organic compounds', 'unidentified volatile compounds' and 'unidentified semi-volatile compounds'). Screening ICP methods are used for major elements, and screening GC MS methods are used for volatile and semi-volatile organics. 32 laboratory samples of different industrial wastes have been tested following (with differences) this protocol by two (routine) service laboratories, with about 7 000 parameter results. A satisfactory analytical balance of 90 % is reached for 20 samples (63 % of the samples) during this first run, with identified reasons for most of the unsatisfying results. A first exploratory classification of the wastes for their hazardousness according to the Seveso legislation was performed based on data from the (chemical) CLP regulation. Using the CLP data, out of 32 samples, 27 (84 % of the samples) were classified identically by the two laboratories (23 not hazardous and 4 hazardous). Using additional EC50 data, out of 32 samples, 27 (84 % of the samples) were classified identically by the two laboratories (13 not hazardous and 14 hazardous)

Solid/Liquid partitioning coefficient of hydrophobic persistent organic pollutants (POP) for different sediments with passive sampler

International audienceThe dredged contaminated sediment are considered as waste and landfilled. Use as public work material (filling, noise protection slope, landscape mound) is considered. The environmental impact must be assessed, and in particular the emission of persistent organic pollutants (POP) in percolating water. The assessment of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) is problematic since their concentration in water in equilibrium with the sediment is below the limit of quantification of routine water analysis. This work describes a laboratory method for evaluation of hydrophobic POPs concentration in water by passive sampling, and a non-linear partition coefficient model between the sediment solid phase and the aqueous phase

Les additifs dans les plastiques qui entravent leur recyclage

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Eu waste hazardousness assessment - proposition of methods

International audienceThe European waste hazardousness classification is currently under revision by the DG ENV of the European Commission and the Member States. This paper proposes some methods for measuring or calculating some Hazard Properties (HP). Laboratory test batteries for assessing HP 1 'Explosive', HP 2 'Oxidising', HP 3 'Flammable' and HP 14 'Ecotoxic' are proposed. For calculations of HP 3 to 8, 10, 11 and 13 to 14, a general analytical protocol for the determination of elements and substances in waste has been developed in France and is submitted to CEN TC292 'Characterisation of waste' for standardization. All the organic substances, mineral elements and main anions are identified and quantified if their concentration is greater than > 0.1% or a lower threshold. For mineral elements, a stepwise approach for the difficult speciation of elements in mineral substances in waste is proposed. In a first 'worst case' approach, for the different HPs, tables with concentration limits triggering the classification control are presented. For HP 14, two additional 'worst case' methods are proposed, as well as an approach based on leachate concentration, taking into account the aquatic bioavailability of potential pollutants of waste. Detailed proposition of methods with tables of EC50, NOEC and M factors for hundreds of organic and mineral substances for calculation of HP 14 are provided in a full technical document

THE SUBSTITUTION OF REGULATED BROMINATED FLAME RETARDANTS IN PLASTIC PRODUCTS AND WASTE AND THE DECLARED PROPERTIES OF THE SUBSTITUTES IN REACH

International audiencePlastics containing brominated flame retardants (BFR) currently contain both “legacy” regulated and non-regulated BFR (R-BFRs and NR-BFRs), as evidenced by the increasingly lower correspondence over time between total bromine and R-BFRs content. The portion of substitutive NR-BFR present in the plastics and their toxicity and ecotoxicity properties are documented. Data relating to plastics and foam present in electrical and electronic equipment (EEE), waste EEE, vehicles, textiles and upholstery, toys, leisure and sports equipment show how 88% of plastic waste contains bromine from NR-BFRs. BFR substances mentioned in the catalogs of the three main producers (Albemarle, ICL, Lanxess) and BFR on the official used list of 418 plastic additives in the EU were gathered and the toxic and ecotoxic properties of these compounds as listed in their ECHA registration dossier were compiled. Fifty-five preparations using 34 NR-BFRs substances, including polymers and blends, were found. Seventeen of these substances featured an incomplete dossier, 12 were equipped with a complete dossier, whilst 11 substances (including 2 ill-defined blends) should be reassessed. Eight substances have been notified for assessment by the ECHA as persistent, bioaccumulative and toxic, or as endocrine disruptors, including decabromodiphenylethane; 3 substances display functional concentrations (the concentration of additives that retards flame) exceeding the concentration limits classifying a waste as hazardous but are “reactive” (they bind to the polymer). The technical limit of 2 000 mg total Br/kg indicated for further recycling (EN 50625-3-1) relates to all brominated substances and is relevant in the sorting of all poorly classified new substances

The sorting of waste for a circular economy : sampling when (very) few particles have (very) high concentrations of contaminant or valuable element

The measurement of elements in numerous individual particles (≥ 1 cm²) by a portable X-ray fluorimeter is used to review a part of the sampling theory of granular solid waste for environmental studies and the circular economy. The paper addresses the case when the concentration of element or substance is not related to the grain size. The key concept (from the binomial law) is the number of particles that must be present in a portion of matter to be representative of a larger portion of matter. This number depends on the frequency of particles having the studied property, and on the desired variability of this property. In all cases, the lowest achievable variability is the analytical variability with the smallest possible test portion (results cannot be less variable). The studied property can either be the presence of an element or a substance, or the presence of an element or a substance at a given concentration. Those concepts are the basis of the existing sampling standards but are not presented as such. As a result, the equations of these standards are not easy to understand and, to our knowledge, rarely used to calculate the mass of a representative sample. When the distributions of concentrations are skewed by (very) large values, the last centiles of concentration tremendously increase the observed mean concentration of a waste heap or flow, and a representative sample must include these last centiles of particles for a proper characterizing and sorting of waste and secondary raw material for the circular economy. Data of centiles of concentrations per particle and laboratory analytical variability are presented. The resulting recommended number of particles that should be present in a sample at any scale from the waste stream (thousands of tons) to the test portion (frequently less than one gram) is estimated at 100 000. Some published sampling plans (from the waste stream to the laboratory sample) and analytical standards (from the laboratory sample to the test portion) are then reviewed for the number of particles. It is crucial to measure the mean mass of the particles to sample, from the granulometric distribution of the particles, and the bulk density, to determine the weight and volume of 100 000 particles. If there is a fine fraction (< 63 μm or even < 1 mm), the recommended mass or volume complies with the requirement of n ≥ 100 000. When there is no fine fraction, like for some WEEE plastic scraps, the volume recommended in technical specification and standard for laboratory sample can’t have enough particles for p = 0.001, but well for p = 0.1 for plastics from small household appliances or higher p for plastics from fluorescent lamps. These p values must be verified for these plastics but are probably not unrealistic for the unsorted fraction. On the other hand, using the equation of the sampling standards overestimates the mean mass of particle when fines are present. Another application is the evaluation of the number of particles to measure individually, in order to calculate the fraction of particles trespassing a given concentration of an element, and the confidence interval of that fraction