Resource Recovery Engineering DTU Environment...Utilization of construction & demolition waste (concrete): impacts DTU Environment, Technical University of Denmark range was of approximately

Quality indicators for anthropogenic resources

Thomas F. AstrupResource Recovery EngineeringDTU Environment

DTU Environment, Technical University of Denmark

Quality of recoverable resources

What do we wish to know about the quality of anthropogenic

resources?

What do we mean by “quality indicators”?

Amounts PuritySubstitutability

Impacts


Example 1

Aluminum recovery from waste incineration bottom ashes: substitutability

Example 2

Chemicals in paper and plastic for recycling: purity

Example 3

Utilization of construction & demolition waste (concrete): impacts


range was of approximately 0–2 mm, 2–8 mm, 8–16 mm and 16–50 mm, based on actual load conditions. The fine fraction wasnot treated for metal recovery, while the remaining three sizespassed through three ECSs, and the 16–50 mm was fed additionallyinto an ISS. Non-conductive material was collected together withthe fine material and residue from other sections, and then itwas utilised as aggregate, substituting for virgin gravel in roadsub-bases. Conductive material from ECS output was transportedto an NFe upgrading section. This section was an industrial facilitymanaged by the company Scanmetals Ltd., consisting of a complexsequence of screens – ECSs, ISSs, X-ray sorting systems (XSS) andsorting tables – aiming at increasing the scrap metal grade, sepa-rating light NFe metal (i.e. Al) from HNFe and separating cleanscrap in three grain sizes of appropriate quality for secondary alu-minium and copper production.

2.2. Sampling campaign

Based on historical data on ash quantities and characteristics,taken from AFATEK Ltd., a sampling and measurement campaignwas designed to fill as best as possible a number of data gaps regard-ing material flows within the recovery facility itself (i.e. the threefirst sections, excluding the NFe upgrading system). Nine measure-ment campaigns were performed over one year, each covering the

treatment of approximately 100 Mg of raw BA from various inciner-ators. During the campaigns, all relevant input and output flowswere weighed and recorded by means of front loaders. Coarse mate-rials output from the Fe recovery section were hand-sorted duringeach campaign to quantify the amount of unburned materials andmetals as well as their type. Furthermore, heavy residue from theFe upgrading system was hand-sorted to estimate the amount ofcopper coil. Numerous samples were collected during the measure-ment campaigns as well as during normal system operations fromthree main streams: (i) non-magnetic BA below 50 mm output fromthe Fe recovery section (41 samples), (ii) treated BA output from theNFe recovery section (14 samples) and (iii) fine BA below 2 mmbypassing the ECSs (23 samples). The sampling procedure followedthe principles for representative sampling as stated in Danish regu-lation N. 1662:2010. A detailed overview of the sampling procedureand the number of samples collected is provided in Supplementarymaterial (see Section A.1 in Appendix A).

2.3. Characterisation of BA samples

BA samples obtained from the sampling campaign were charac-terised for the following parameters: (i) moisture content, follow-ing the EN 1097-5:2008 standard and (ii) metal scrap content,following a procedure developed at the Swiss Institute for Environ-

Fig. 1. MFA results: values are in Mg of material (e.g. MSWI BA, scrap metals) on a wet basis, and the uncertainty values represent the relative standard uncertainty. The Ferecovery, Fe upgrading and NFe recovery processes are defined by subsystems where all machinery included in each section is considered. See Fig. A.3 in Appendix A to see thesubsystem schemes.

E. Allegrini et al. / Waste Management 34 (2014) 1627–1636 1629

Aluminum recovery from bottom ashes

Allegrini, E., Maresca, A., Olsson, M. E., Holtze, M. S., Boldrin, A., & Astrup, T. F. (2014). Quantification of the resource recovery potential of municipal solid waste incineration bottom ashes. Waste Management, 34(9), 1627-‐1636.

historical data and the measurement campaigns, as well as theanalysis of samples obtained from the facility. The data wereaggregated, elaborated and entered into the MFA software packageSTAN (Cencic and Rechberger, 2008). The analysis was carried outat two different layers: in the first layer, data about the wet mass ofmaterial circulating in the system were entered (MFA), while in thesecond one the concentration of a defined substance (Fe or NFe)was applied to each material flow (SFA). The calculation algorithmapplied to the MFA and SFA was IAL-IMPL2013 (www.industrialgo-rithms.com), implemented in STAN. Additional information oninput data and assumptions in the MFA and SFA is reported in Sec-tion A.3 of Appendix A. The functional unit used for the MFA and

SFA was 5000 Mg of raw (wet) MSWI BA (referred to hereafter asBA batch), a choice based on the fact that most of the historicaldata were reported according to this unit, as required by Danishregulation N. 1662:2010.

3. Results and discussion

3.1. Fe and NFe recovery potential and efficiencies

Figs. 1–3 report the results of the MFA/SFA according to themain processes (see scheme in Fig. A.1), while additionally Table 1summarises the main conclusions which can be drawn based onthe analysis of the MFA/SFA figures. In Supplementary material,the SFA for Al and Cu scrap also is reported in Figs. A.4 and A.5.

Potential Fe and NFe content in the raw BA was estimated to be7.2%ww and 2.2%ww, respectively, while estimated recovery effi-ciencies were 85% for Fe and 61% for NFe. More specifically, rawBA consisted of 1.4%ww and 0.24%ww Al and Cu scrap, respec-tively, and the recoveries of these two types of metals were esti-mated to be 62% and 61%, respectively. Recovery efficiencieswere estimated by considering the total amount of scrap sortedfrom the BA in various system steps and the total amount of the

Fig. 3. SFA results for the Fe scrap: values are in Mg of material on a wet basis, and the uncertainty values represent the relative standard uncertainty. The Fe recovery, Feupgrading and NFe recovery processes are defined by subsystems where all machinery included in each section is considered. See Fig. A.3 in Appendix A to see the subsystemschemes.

Table 1MSWI BA metal potential (%ww: wet weight basis) and recovery efficiency.Uncertainties are shown as relative standard uncertainty.

Scrap metal potential in raw MSWI BAFe 7.2%ww ± 18%NFe 2.2%ww ± 2% Al 1.4%ww ± 2% Cu 0.24%ww ± 6%

Scrap metal recovery efficiency: Danish state-of-the-artFe 85% ± 28%NFe 61% ± 2.8% Al 62% ± 2.4% Cu 61% ± 11%

E. Allegrini et al. / Waste Management 34 (2014) 1627–1636 1631


mental and Process Engineering, UMTEC (2012). The latter proce-dure was used to quantify the content of magnetic and non-mag-netic scrap in BA by means of crushing, screening and hand-sorting material samples with minimum grain size of 0.5 mm.The same analyses were carried out on subsamples obtained bysieving the first two types of samples (non-magnetic BA below50 mm and treated BA) in the three grain sizes 2–8 mm, 8–16 mm and 16–50 mm, in order to simulate the three individualfractions treated in the NFe recovery system. Additional detailsregarding experimental procedures are provided in Supplementarymaterial (see Section A.2.).

2.4. Analytical techniques for analysing precious and critical elements

To assess the resource potential of precious and critical ele-ments, a smaller number of samples (four samples of the treatedBA and four of BA below 2 mm) were selected for further analysisof total content of a wide range of inorganic elements. The ana-lysed elements included precious metals and elements listed bythe European commission as critical (European Commission,2010), with the exception of Y, which was used as an internal stan-dard during the analyses, and Os and Pm, which were included inthe internal standard solution used. For these analyses a 5 kg sub-sample from each sample was obtained by applying mass reduc-

tion techniques, as reported by Petersen et al. (2004). Thesamples were dried in an oven at 105 !C until a constant weightwas achieved (about 24 h), and then the grain size was reducedin a jaw crusher, and after reducing the sample mass by meansof a riffle-splitter, the material was pulverised by means of vibra-tory disc mill (Wolframe Carbide discs). Coarse metallic itemswhich could not be size-reduced were removed from the samplematerial. A 0.2 g powder sample was digested by microwave-assisted digestion (Multiwave Anton Paar 3000), and then analysedby ICP-MS (7700x, Agilent Technologies). Every sample materialwas digested and analysed in duplicate. A single digestion methodwas applied to address a wide range of elements since the achieveddetection limits for all elements of interest fitted the scope of thestudy. Samples were digested with HNO3, HCl, HF and H3BO3 fol-lowing the standard EN 13656:2003 procedure, and the resultswere validated by means of three certified reference materials:fly ash (BCR-176R); sediments (GBW-07318); soil (NCS DC78302). Additional information on analytical procedure is reportedin A.2.2 in Appendix A.

2.5. MFA and SFA methodology

Material flow analysis (MFA) and substance flow analysis (SFA)were carried out based on data obtained through the analysis of

Fig. 2. SFA results for NFe scrap: values are in Mg of material on a wet basis, and the uncertainty values represent the relative standard uncertainty. The Fe recovery, Feupgrading and NFe recovery processes are defined by subsystems where all machinery included in each section is considered. See Fig. A.3 in Appendix A to see the subsystemschemes.

1630 E. Allegrini et al. / Waste Management 34 (2014) 1627–1636

Aluminum recovery from bottom ashes

Allegrini, E., Maresca, A., Olsson, M. E., Holtze, M. S., Boldrin, A., & Astrup, T. F. (2014). Quantification of the resource recovery potential of municipal solid waste incineration bottom ashes. Waste Management, 34(9), 1627-‐1636.


Life cycle assessment of resource recovery

! The ratio between the London Metal Exchange (LME) quotationfor secondary alloys and primary aluminium (Al 99.7) followingthe EAA method. In this case, using the aluminium alloy pricefrom the LME, b was set at 0.9 (Koffler and Florin, 2013), and byapplying prices for the secondary aluminium EN AB-46000, thisratio was found to be approximately 0.05. Additionally, a dif-ferentiation between the qualities of Al scrap in different grainsize fractions was made, as quality is related to the grain size ofscrap, and different oxidation levels and alloying element con-tent were found. For example, a fine fraction (i.e. below 5 mm),even though highly oxidised, is purer in terms of aluminiumcontent. As observed in recent studies (Biganzoli et al., 2012; Huet al., 2011a), Al scrap partitioning in MSWI BA depends mainlyon feedstock going into the incineration process: aluminiumfrom foils, made of alloy with aluminium content above 98%(ASTM B479, 2006), tends to enrich in the fine fractions of MSWIBA. Thus, the fine fraction of the Al scrap could be used by re-melters for wrought alloy production instead of being used forthe production of cast alloys. For sensitivity, b ¼ 1 was assignedto the fine fraction and b ¼ 0.35 to the coarse Al scrap.

! The ratio between scrap prices (instead of secondary aluminiumprices) and primary aluminium was proposed by Koffler andFlorin (2013) in order to show the level of downcyclingreached after a product's lifecycle comes to an end. However, forthe sake of consistency within the study, the system boundarieswere here not modified according to the approach proposed byKoffler and Florin (2013), so the production of secondary

aluminiumwas always included. On the basis of the list of scrapclass reported by the same authors, possible b for post-incineration scrap was below 0.35, which is the substitutionratio found by the authors for old mixed scrap aluminium.

Additionally, two combined sensitivity analyses were performedto include the effect of the quality of the Fe and SS scrap and theenergy demand of the sorting and upgrading system for the scrap.At first the substitution ratio for SS and Fe scrap (indicated as a andg, respectively) varied between 0 and 1 at a given value of b. Sub-sequently the substitution rate for SS was set to 1 and b, g, and theimpacts of the sorting and upgrading system were varied simul-taneously, in order to locate possible environmental breakevenpoints.

2.2.7. Impact assessmentInventoried emissions were characterised in the LCIA. Both toxic

and non-toxic impact categories were included: global warmingpotential (GWP) based on IPCC 2007 over a 100-year time horizon;acidification (TA) (Posch et al., 2008; Sepp€al€a et al., 2006); mineralabiotic resource depletion (ADm) based on CML v.4.2 (Van Oerset al., 2002); carcinogenic human toxicity (HTc), non-carcinogenichuman toxicity (HTnc) and ecotoxicity to freshwater (ET) basedon the USEtox model (Rosenbaum et al., 2008). The LCIA method-ologies were selected according to the recommendations providedby Hauschild et al. (2013).

Fig. 2. LCA results of the three non-toxic impact categories global warming potential (GWP), acidification (AT) and depletion of abiotic mineral resources (ADm). Potential impactsare shown as total net characterised impact (on the left of each charts “total”) and per individual group of system activities.

E. Allegrini et al. / Journal of Environmental Management 151 (2015) 132e143 137

! The ratio between the London Metal Exchange (LME) quotationfor secondary alloys and primary aluminium (Al 99.7) followingthe EAA method. In this case, using the aluminium alloy pricefrom the LME, b was set at 0.9 (Koffler and Florin, 2013), and byapplying prices for the secondary aluminium EN AB-46000, thisratio was found to be approximately 0.05. Additionally, a dif-ferentiation between the qualities of Al scrap in different grainsize fractions was made, as quality is related to the grain size ofscrap, and different oxidation levels and alloying element con-tent were found. For example, a fine fraction (i.e. below 5 mm),even though highly oxidised, is purer in terms of aluminiumcontent. As observed in recent studies (Biganzoli et al., 2012; Huet al., 2011a), Al scrap partitioning in MSWI BA depends mainlyon feedstock going into the incineration process: aluminiumfrom foils, made of alloy with aluminium content above 98%(ASTM B479, 2006), tends to enrich in the fine fractions of MSWIBA. Thus, the fine fraction of the Al scrap could be used by re-melters for wrought alloy production instead of being used forthe production of cast alloys. For sensitivity, b ¼ 1 was assignedto the fine fraction and b ¼ 0.35 to the coarse Al scrap.

! The ratio between scrap prices (instead of secondary aluminiumprices) and primary aluminium was proposed by Koffler andFlorin (2013) in order to show the level of downcyclingreached after a product's lifecycle comes to an end. However, forthe sake of consistency within the study, the system boundarieswere here not modified according to the approach proposed byKoffler and Florin (2013), so the production of secondary

aluminiumwas always included. On the basis of the list of scrapclass reported by the same authors, possible b for post-incineration scrap was below 0.35, which is the substitutionratio found by the authors for old mixed scrap aluminium.

Additionally, two combined sensitivity analyses were performedto include the effect of the quality of the Fe and SS scrap and theenergy demand of the sorting and upgrading system for the scrap.At first the substitution ratio for SS and Fe scrap (indicated as a andg, respectively) varied between 0 and 1 at a given value of b. Sub-sequently the substitution rate for SS was set to 1 and b, g, and theimpacts of the sorting and upgrading system were varied simul-taneously, in order to locate possible environmental breakevenpoints.

2.2.7. Impact assessmentInventoried emissions were characterised in the LCIA. Both toxic

and non-toxic impact categories were included: global warmingpotential (GWP) based on IPCC 2007 over a 100-year time horizon;acidification (TA) (Posch et al., 2008; Sepp€al€a et al., 2006); mineralabiotic resource depletion (ADm) based on CML v.4.2 (Van Oerset al., 2002); carcinogenic human toxicity (HTc), non-carcinogenichuman toxicity (HTnc) and ecotoxicity to freshwater (ET) basedon the USEtox model (Rosenbaum et al., 2008). The LCIA method-ologies were selected according to the recommendations providedby Hauschild et al. (2013).

Fig. 2. LCA results of the three non-toxic impact categories global warming potential (GWP), acidification (AT) and depletion of abiotic mineral resources (ADm). Potential impactsare shown as total net characterised impact (on the left of each charts “total”) and per individual group of system activities.


Allegrini, E., Vadenbo, C., Boldrin, A., & Astrup, T. F. (2015). Life cycle assessment of resource recovery from municipal solid waste incineration bottom ash. Journal of Environmental Management, 151, 132-‐143

Scenarios A->K (recovery, %)

Al 0 - 97

H-NFe 0 - 86

SS 0 - 95

Fe 85 - 95

Mineral Landfill – Aggregate - Road


Substitutability of recovered aluminum

(e.g. Cu, Mg, Mn, Zn) are more sensitive to scrap input quality andthe selected final product. Within the list of alloying elements re-ported in the EN 1676:1996 standard, Si has the lowest character-isation factor (CF) for ADm followed by Al, Mg, Ti and Fe (i.e. CFsbelow 10!7 kg Sb-Eq/kg), while Sn, Pb, Cu, Zn, Ni, Cr and Mn, haveCFs between 10!2 and 10!6 kg Sb-Eq/kg. Thus, based on the sig-nificant differences between CFs and the high case specificity of theactual exploitation of individual alloying elements, the ADm resultsprovide important insights into the resource aspects of metalrecycling, because they relate to the quality of the scrap and thesecondary production phase which marginally substitutes the pri-mary metal. The need to dilute the aluminium melt with primaryaluminium, and the loss or accumulation of alloying elements,clearly indicates downcyclinge and hence quality and functionalitylosses of aluminium scrap in the post-consumer and recyclingphases.

Overall, non-toxic results showed that the benefits of metalrecycling can be compromised by the quality of the recycled scrapmetals. The practice of differentiating Al scrap by grain size possiblyleads to higher benefits, as fine fractions with higher Al contentcould be potentially upcycled and sold to re-melters instead ofrefiners. However, the presence of metals from various origins inthe post-incineration scrap limits the possibility to optimisealloying content for a specific secondary aluminium alloy.

Moreover, the benefits of recovering such low-quality Al scrap maydecrease in the near future. In fact, as reported by several studies,the availability of old Al scrap might exceed the demand for therelevant cast aluminium alloys over a near-to mid-term time ho-rizon. As an example, a recent study byModaresi andMüller (2012)estimated that a scrap surplus may even start to build up around2018. Thus, increasing the recovery of mixed low-quality scrapmight lead to the long-term accumulation of material that has noapplication in the market.

3.2. Toxic potential impacts

3.2.1. Metal recyclingFig. 4 reports the results for the toxic categories. For all sce-

narios, potential toxic impacts were positive for the three assessedimpact categories, with the only exception being scenario K with anegative impact on HTnc and ET due to the significant recovery ofNFe metals (Al, Cu). Fe scrap recycling showed the greatestcontribution among all three categories: the results were positivefor all scenarios and impact categories, meaning that the secondaryproduction of iron contributes more impacts than primary pro-duction from a toxic perspective. However, this result was relatedto theway secondary and primary steel productionwas inventoriedin the selected Ecoinvent process. In fact, emissions contributing

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Fig. 3. Change of substitution ratios for metal recycling: effect on GWP. a) Net GWP for scenario C given a fixed aluminium substitution rate value (b) and varying substitution ratesfor SS (a) and Fe scrap (g); b) plane of breakeven points obtained by varying b, g and the impact due to sorting and upgrading activities of the scrap metals from MSWI BA forscenarios C and K. The points represent values of GWP between !0.1 and 0.1 with varying b, g; c) same as b) but the Middle East primary production of aluminium is used asmarginal technology (i.e. with electricity production based on 100% natural gas).


Allegrini, E., Vadenbo, C., Boldrin, A., & Astrup, T. F. (2015). Life cycle assessment of resource recovery from municipal solid waste incineration bottom ash. Journal of Environmental Management, 151, 132-‐143

Substitution ratios between recovered and primary metal:

α (stainless steel), β (aluminum), γ (iron),


Chemical substances in paper for recycling

1) Potential use within paper production or manufacturing?

2) Is the substance potentially hazardous?

3) Potential affinity to paper fibers?

4) Is the substance potentially biodegradable?

In the following step (Step 4) the biodegradability of the previ-ously identified chemicals was assessed. As presented in Fig. 3c,most of the substances that showed affinity for the solid phase werecharacterised as persistent (24), while the 27 remaining chemicalscould be classified as inherently (12) and readily biodegradable (15).

While the list of potential priority chemical substances may notbe exhaustive (as the screening can only be based on availableinformation about substances), it nevertheless clearly indicatesthat concerns regarding their presence in paper and their potentialaccumulation in the paper lifecycle may be pertinent to a relativelysmall number. The list therefore forms a systematic basis for fur-ther research in relation to paper characteristics and paper recy-cling. The 157 substances identified in Step 2 are grouped in thefollowing according to their chemical structure and then discussedin more detail. Individual tables listing each chemical substanceaccording to these groups can be found in the SupplementaryMaterials (Tables S1–S6).

3.2. Mineral oils

The commonly used term ‘‘mineral oils’’ refers to a mixture ofcomponents which originate from crude oil refining processes.Mineral oils mainly contain straight and branched open-chainalkanes (paraffins), alkylated cycloalkanes (naphthenes) and aro-matic hydrocarbons (EFSA, 2012b), and their final composition willdepend largely on the initial composition of the crude oil, as well asthe refinery treatment (e.g. alkylation, hydro-treatment, cracking,extraction, etc.). Although the Joint FAO/WHO Expert Committeeon Food Additives (JECFA) recently withdrew previously estab-lished acceptable daily intakes in relation to mineral oils (JECFA,2012), the JECFA assessment refers to highly-refined mineral oilsfree from aromatic hydrocarbons. On the other hand, paper prod-ucts were shown to contain technical-grade mineral oils whichmay include aromatic hydrocarbons (Biedermann and Grob,

2010). Droz and Grob (1997) found that, at least initially, printinginks (solvents in particular) used in paper products are the mainsource of mineral oils in paper. Further studies have also positedthat mineral oils may derive from recycled waste paper(Biedermann and Grob, 2010; Biedermann et al., 2011b).

Out of the 157 chemicals included in the Step 2 list, 49 wereclassified as mineral oils (Table S1 (Supplementary Material)) andcharacterised as carcinogens, while some are also mutagenic sub-stances. The chemicals presented herein are not single substancesbut rather mixtures of substances containing various hydrocar-bons. Being mixtures rather than single substances, mineral oilscan be used in a variety of applications in the industry, i.e. fromsolvents and as the basis for polymeric resins through to lubricantsand cleaning agents for machinery (EFSA, 2012b; Miljøstyrelsen,2011a). Most of the scientific studies currently available focus onmineral oil content in paper used for food packaging (e.g.(Biedermann and Grob, 2010; Biedermann et al., 2011a; 2011b;Droz and Grob, 1997)), as migration into foodstuffs remains oneof the most important sources of consumer exposure (EFSA,2012b). As they are hydrophobic substances, mineral oils maynot be removed in water-based processes of paper recycling (i.e.pulping, deinking, washing), remain in the solid matrix and havea high chance of persisting in the recycling process and being rein-troduced into newly manufactured products (BMELV, 2012). Such ascenario is unlikely for some of the lighter mineral oils, which areexpected to escape due to volatilisation in e.g. paper drying step. Arecent study (BMELV, 2012) showed that the deinking processreduces insignificantly the concentration of mineral oils, whilepaper drying is the main process for their removal (around 30%(Biedermann et al., 2011b)) – still resulting on average in340 mg/kg (<C24) in unprinted food-packaging board produced(Biedermann and Grob, 2012). One study showed that even thepresence of a barrier (e.g. plastic foil) may not always preventthe migration of mineral oils from packaging into a food product

a b c

Fig. 3. Distribution of the use of chemicals from Step 2 list (3a); phase distribution of chemicals, i.e. Step 3 list (3b); biodegradability of chemicals associated with the solidphase, i.e. Step 4 list (3c).

K. Pivnenko et al. / Waste Management xxx (2015) xxx–xxx 5

Please cite this article in press as: Pivnenko, K., et al. Waste paper for recycling: Overview and identification of potentially critical substances. Waste Man-agement (2015), http://dx.doi.org/10.1016/j.wasman.2015.02.028

Pivnenko, K., Eriksson, E., & Astrup, T. F. (2015). Waste paper for recycling: Overview and identification of potentially critical substances. Waste Management, in press.

(157) (51) (24)


Chemical substances in paper for recycling

In Step (4) of the screening process, chemicals were assessed inaccordance with their biodegradability and then classified into per-sistent, inherently and readily biodegradable. Classification wasbased either on the Biowin models 3 and 5, included in EpiSuite4.1 (U.S. EPA, 2013) with cut-off values as presented by Baunet al. (2006), or on scientific literature providing experimentalbiodegradation results. Relevance of biodegradability of chemicalsto particular processes in paper recycling was not established, asthe variations associated with different steps of the paper lifecycle(i.e. paper production, manufacturing, use, waste paper collection,re-processing, etc.) are potentially large.

3. Results and discussion

3.1. Overview of substances

Fig. 2 presents material flows of European paper recycling, indi-cating points where chemicals are introduced into the loop. Mostnon-fibrous materials are introduced in the paper production step,but they are almost entirely represented by non-hazardousnaturally occurring substances such as clay, CaCO3 and starch.No quantitative data were available regarding chemicals addednon-intentionally into the loop (i.e. Non-Intentionally AddedSubstances, NIAS). An overview of each of the sources contributingto the final list in Step 1 is presented in Table 1. Although the paperindustry uses high volumes of chemical substances (Fig. 2), it isevident that a much higher variety of chemicals associated withpaper products derives from printing (Table 1).

Due to the large number of chemicals identified in Step 1,attributing to each of them a potential use by industry is practically

impossible. Nevertheless, most of the substances used in paperproduction can be attributed to fillers, binders, retention aids,wet/dry-strength agents, coaters, biocides, dispersers, etc.(ZELLCHEMING, 2008). In the printing industry the vast majorityof chemicals are used as solvents, dyes, inks, pigments, binders,curing agents and photo-initiators, plasticisers, surfactants, etc.(Miljøstyrelsen, 2011a) Only a small fraction (157) of the almost10,000 substances could be identified in Step 2. Fig. 3a presentsthe distribution of substances on Step 2 list in accordance withtheir use by industries throughout the lifecycle of paper. Only 10of the chemicals are used exclusively in paper production (mainlybiocides). Conversely, 133 chemicals were attributed to the print-ing industry, most of which are solvents and polymeric resinsemployed in inks, pigments and dyes. Chemicals which could notbe attributed either to paper production or to the printing sector(14) could potentially be by-products or contaminants introducedinto the production cycle through recycled paper.

Chemicals on the Step 2 list were assessed in relation to theirpotential partitioning between the air, aqueous and solid phases.It is evident from Fig. 3b that most of the chemicals either have ahigher affinity for a solid matrix (51) or remain dissolved in thewater phase (51). Sixteen of the chemicals on the list are relativelyvolatile and could potentially escape through volatilisation in theproduction process, while an additional 22 substances on the listare inorganic, and although two of them (i.e. mercury and carbondisulphide) may partially volatilise, the distribution of the rest willdepend very much on specific conditions in the paper processingstages (e.g. pH, redox conditions, presence of organic matter, etc.)and are difficult to predict. Chemicals remaining in the solid matrixare of particular interest in terms of paper recycling.

Fig. 2. Material flow of the European paper recycling loop. Dotted lines indicate points where chemicals are introduced (based on (CEPI, 2013a, 2013b; EUPIA, 2013; FEICA,2008; ITC, 2014) and personal communication with the Confederation of European Paper Industries (CEPI)).

4 K. Pivnenko et al. / Waste Management xxx (2015) xxx–xxx

Please cite this article in press as: Pivnenko, K., et al. Waste paper for recycling: Overview and identification of potentially critical substances. Waste Man-agement (2015), http://dx.doi.org/10.1016/j.wasman.2015.02.028

Pivnenko, K., Eriksson, E., & Astrup, T. F. (2015). Waste paper for recycling: Overview and identification of potentially critical substances. Waste Management, in press.


Phthalates (DiBP) in paper and board for recycling

• Phthalates, e.g. used in paper manufacturing as plasticizers in inks and glue

• Example with DiBP (diisobutylphthalate)

• Source segregated paper and board in household waste

Pivnenko, K., Eriksson, E., & Astrup, T. F. (2015). Chemicals in material cycles, conference proceedings, Sardinia 2015.


Phthalates (DiBP) in paper and board for recycling

Pivnenko, K., Eriksson, E., & Astrup, T. F. (2015). Chemicals in material cycles, conference proceedings, Sardinia 2015.

Fraction Weight [%]Paper 87.3Flyers 56.1Newspapers & Magazines 26.7Office & Administrative paper 4.1Paper packaging 0.3Miscellaneous paper 0.1Board 12.7Corrugated board 8.3Paperboard 2.9Other board packaging 0.9Paper tableware <0.1Miscellaneous board 0.6Total 100


Cr in plastic: virgin, waste, and recycledTable 1. Overview of the plastic samples used in the present study.

Origin Form Polymer types Number of samples Virgin China and other Granulate PET, HDPE, LDPE, LLDPE, PP, PS 8

Waste plastics

Denmark Plastic items PET, HDPE, LDPE; PP, PS, exp.

PS, ABS, and other 20

Recycled (HHW*)

Denmark, Germany, the Netherlands, and

other

Flakes, pellets, granules,

plastic items PET, HDPE, LDPE, PP, PO 10

Recycled (IW*)

China and Denmark Flakes, pellets,

granules PET, HDPE, LDPE, PP, PS 10

* HHW: Household Waste; IW: Industrial Waste.

Pivnenko, K., Jakobsen, L. G., Eriksen, M. K., Damgaard, A. & Astrup, T. F. (2015). Quality aspects in plastic recycling. Conference proceeding, Sardinia 2015.


Composition and leaching from C&D waste

Butera, S., Christensen, T. H., & Astrup, T. F. (2014). Composition and leaching of construction and demolition waste: Inorganic elements and organic compounds. Journal of Hazardous Materials, 276, 302-‐311.

306 S. Butera et al. / Journal of Hazardous Materials 276 (2014) 302–311

Fig. 2. Content of PCBTOTAL and PAHs (sum 16 EPA PAHs) in the 33 samples.

The measured values for anionic chromium were close to the mea-sured values for total chromium (in average almost 80% of Cr wasfound in anionic form). Speciation calculations (PHREEQC) con-firmed that Cr could be present as chromate in all samples, as alsosupported by Guyonnet et al. and Astrup et al. [49–51]. Generallycopper was released in amounts ranging from 30 to 200 !g kg−1

Table 3Summary of the leaching behaviour of major and minor elements, DOC and traceelements after batch L/S 2 test (EN 12457-1, [42]) of the 33 samples; including pHvalues and conductivity (TS: total solid).

Mean Inter-samplevariation

LOD

pH 11.92 ±6.4% –Conductivity (mS cm−1) 4.68 ±63% –Aluminium (mg kg−1 TS) 3.2 ±77% 0.07Calcium (mg kg−1 TS) 790 ±63% 0.07Iron (mg kg−1 TS) 0.17 ±86% 0.07Potassium (mg kg−1 TS) 250 ±53% 0.3Sodium (mg kg−1 TS) 180 ±35% 0.07Silicon (mg kg−1 TS) 12 ±149% 0.1Magnesium (mg kg−1 TS) 0.097 ±155% 0.007S as sulphate (mg kg−1 TS) 150 ±229% 0.05DOC (mg kg−1 TS) 35 ±50% 2.0Arsenic (!g kg−1 TS) 32 ±71% 6.9Barium (!g kg−1 TS) 1600 ±119% 6.9Cadmium (!g kg−1 TS) 2.0 ±37% 1.0Chloride (!g kg−1 TS) 110,000 ±69% 2000Cobalt (!g kg−1 TS) 19 ±42% 6.9Chromium (!g kg−1 TS) 110 ±68% 1.0Anionic chromium (!g kg−1 TS) 88 ±75% 1.0Copper (!g kg−1 TS) 100 ±71% 13.8Lithium (!g kg−1 TS) 380 ±120% 3.0Manganese (!g kg−1 TS) 12 ±106% 6.9Molybdenum (!g kg−1 TS) 30 ±49% 6.9Nickel (!g kg−1 TS) 71 ±314% 3.0Phosphorous (!g kg−1 TS) 120 ±66% 13.8Lead (!g kg−1 TS) 19 ±67% 7.6Antimony (!g kg−1 TS) 72 ±42% 6.9Selenium (!g kg−1 TS) 64 ±67% 13.8Strontium (!g kg−1 TS) 15,000 ±90% 3Vanadium (!g kg−1 TS) 37 ±84% 3.0Zinc (!g kg−1 TS) 260 ±459% 13.8

Fig. 3. pH and conductivity of the leachates of the 33 samples after batch 12457-1L/S 2 test [42].

TS, with C25 being higher (400 !g kg−1 TS). Zinc leached between<15 and 160 !g kg−1 TS, mostly below 50 !g kg−1 TS, while sam-ples C24 and C25 leached respectively 7000 and 660 !g kg−1 TS.Nickel leached in concentrations between 3 and 80 !g kg−1 TS, withlow values for samples C13, C29 and a high value for sample C25.As the high values for Ni, Cu and Zn were identified in the samereplicate of sample C25 and this sample also showed elevated RSD(over 90% for Ni and Zn and over 50% for Cu), these values wereconsidered outliers. Vanadium and selenium were measured inconcentrations lower than 150 !g kg−1 TS. Antimony and arsenicleached in concentrations below 100 !g kg−1 TS, often with val-ues below LOD. Manganese only leached in concentrations of few!g kg−1 TS, while lead was in most cases below either quantifica-tion or detection limit, and overall did not exceed 50 !g kg−1 TS.Most often no concentration could be detected for cadmium.

4. Discussion

4.1. Elemental composition

Compared to literature values, major elements were present inconcentrations comparable (within a factor 2) to those reported byEngelsen et al. [23], in most cases in the lower end of the range,except for silicon. Data reported by Schiopu et al. [52], varied insome cases by a factor 10 compared to current measurements;however, they referred to only one dataset. Magnesium was ingood agreement with published data [20,23,52], while few mea-surements for sulphate appeared low (by a factor 10). TC and TOCwere in good agreement (within a factor 2) with data from [23,53].Although high values were reported by van der Sloot et al. [17]for special cements, trace elements concentrations were in generalin fair agreement (within a factor 3) from previous literature (seeAppendix F and G supplementary data). In particular, nickel seemedto be in the lower end of the literature ranges, while lead appearedto be enriched.

S. Butera et al. / Journal of Hazardous Materials 276 (2014) 302–311 307

Fig. 4. Leaching behaviour of the 33 samples for selected elements after batch 12457-1 L/S 2 test [42]. Each bar represents the average of at least two replicate measurements.

4.2. Content of organic compounds

Previous PCBs measurements in C&DW [37,54] most often didnot find detectable levels of PCBs (few detected concentrations

around 230–650 !g kg−1 TS); however the reported studies hadhigher LOD than the present study. Measured PCBs contents werewell below the limit set for inert landfills by the EU LandfillDirective [55] and the compositional requirement stated by the

S. Butera et al. / Journal of Hazardous Materials 276 (2014) 302–311 307

Fig. 4. Leaching behaviour of the 33 samples for selected elements after batch 12457-1 L/S 2 test [42]. Each bar represents the average of at least two replicate measurements.

4.2. Content of organic compounds

Previous PCBs measurements in C&DW [37,54] most often didnot find detectable levels of PCBs (few detected concentrations

around 230–650 !g kg−1 TS); however the reported studies hadhigher LOD than the present study. Measured PCBs contents werewell below the limit set for inert landfills by the EU LandfillDirective [55] and the compositional requirement stated by the

Contents of PCBs and PAHs Leaching of S and Cr


Life cycle assessment of C&D waste utilization

contaminant (HTNC would not be affected as Cr(VI) has little effectthere).

Leaching of P heavily affects the FEP impacts. However, phos-phate precipitation and adsorption on soil may significantly reduceP migration (Tunesi et al., 1999). Nevertheless, P-retention in sub-soil has not yet been incorporated into fate modelling in the con-text of LCA; thus, it is likely that the results for FEP aresignificantly overestimated. Immobilisation of 90 per cent of PO4

(comparable to the retention calculated for other elementsreported in Table 2) would result in significantly reduced FEPimpacts, especially in scenario (a), where P leaching was very

important. As a consequence, the two scenarios would haveimpacts within the same order of magnitude.

3.4.2. TransportationDifferently from what demonstrated for the waste management

of other waste streams (e.g. Merrild et al., 2012; Gentil et al., 2009;Smith et al., 2001; Beigl and Salhofer, 2004; Salhofer et al., 2007),transportation of both C&DW and virgin gravel plays a large rolein the results for most non-toxic categories. However, modelledtransportation distances are relatively uncertain, because theyare based on assumed values. As shown in Fig. 2, for most impact

Table 3Characterised and normalised impacts for the analysed impact categories, for both scenarios (the 5th and 95th percentiles are shown for the categories affected by leaching data;that is, FEP, HTC, HTNC and ETFW). The values with ‘‘%’’ represent the per cent variation in total impacts by using 5th and 95th percentile leaching data compared to the scenariowith average leaching data. Values in bold indicate the scenario with the largest environmental impacts.

Scenario (a): C&DW in road Scenario (b): C&DW to landfill

Global Warming (GWP100) kg CO2-eq 8.73E+00 1.79E+01mPE 1.08 2.8

Photochemical Ozone Formation (POF) kg NMVOC-eq 1.32E!02 1.19E!01mPE 0.23 2.2

Particulate Matter (PM) kg PM2.5 1.21E!03 5.94E!03mPE 4.4E!01 2.4

Terrestrial Acidification (AP) AE 2.37E!02 1.02E!01mPE 0.48 2.3

Freshwater Eutrophication (FEP) kg P-eq !31% 8.84E!03 30% !22% 4.42E!04 47%mPE 14.3 1.0

Marine Eutrophication (MEP) kg N-eq 4.31E!03 4.00E!02mPE 0.46 4.4

Terrestrial Eutrophication (TEP) AE 4.90E!02 4.41E!01mPE 0.43 4.0

Depletion of Abiotic Resources-Fossil (ADPF) MJ 1.45E+02 2.58E+03mPE 2.32 43

Depletion of Abiotic Resources-Elements (ADPE) kg Sb-eq 7.91E!05 3.64E!04mPE 2.3 11

Human Toxicity, Cancer Effect (HTC) CTUh !45% 1.33E!07 63% !2% 1.61E!07 2%mPE 2.5 3.1

Human Toxicity, non-Cancer Effect (HTNC) CTUh !40% 5.88E!06 37% !2% 1.12E!06 4%mPE 5.3 1.3

Freshwater Ecotoxicity (ETFW) CTUe !49% 9.90E+01 73% !24% 1.09E+01 40%mPE 149 17

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%GWP100 POF PM AP FEP MEP TEP ADPF ADPE HTC HTNC ETFW

Proc

ess

cont

ribu

tion

Transport Crushing C&DW Capital goods Extraction gravelTransport gravel Leaching gravel Leaching C&DW Net value

Fig. 2. Utilisation of C&DW in road construction (scenario (a)): environmental impact contribution of the different processes related to C&DW utilisation (in percentages ofthe total impact). Only average leaching values are included. The net value represents the total impact, expressed as a percentage of the sum of absolute values of the singleprocess contributions. Abbreviations: Global Warming Potential (GWP); Photochemical Ozone Formation (POF); Particulate Matter (PM); Acidification Potential (AP);Freshwater Eutrophication Potential (FEP); Marine Eutrophication Potential (MEP); Terrestrial Eutrophication Potential (TEP); Abiotic Resource Depletion Potential for Fossil(ADPF); Abiotic Resource Depletion Potential for Elements (ADPE); Human Toxicity, Carcinogenic (HTC); Human Toxicity, Non-Carcinogenic (HTNC); Ecotoxicity to Freshwater(ETFW).

6 S. Butera et al. / Waste Management xxx (2015) xxx–xxx

Please cite this article in press as: Butera, S., et al. Life cycle assessment of construction and demolition waste management. Waste Management (2015),http://dx.doi.org/10.1016/j.wasman.2015.07.011

Butera, S., Christensen, T. H., & Astrup, T. F. (2015). Life cycle assessment of construction and demolition waste management. Waste Management, in press.


Quality indicators for anthropogenic resources

No single indicator consistently describes quality of recoverable resources in waste

Clear definitions of resource potentials and recoverable amounts are needed

Purity and substitutability of recovered resources are essential

Environmental impacts from recovery and utilization of the anthropogenic resources are required

Thanks for the attention!

Documents

Resource Recovery Engineering DTU Environment...Utilization of construction & demolition waste (concrete): impacts DTU Environment, Technical University of Denmark range was of approximately