In quest of environmental hotspots of sewage sludge treatment combining anaerobic digestion and mechanical dewatering: A life cycle assessment approach

Journal of Cleaner Production xxx (2016) 1e14

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In quest of environmental hotspots of sewage sludge treatment combining anaerobic digestion and mechanical dewatering: A life cycle assessment approach Claire Gourdet a, Romain Girault b, c, Sarah Berthault a, Marion Richard a, Julian Tosoni a, Marilys Pradel a, * a b c

Irstea, UR TSCF, Domaine des Palaquins, 40 route de Chazeuil, 03150, Montoldre, France Irstea, UR OPAALE, 17 avenue de Cucill
e, CS 64427, 35044, Rennes Cedex, France Universit
e Bretagne Loire, France

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 February 2016 Received in revised form 1 December 2016 Accepted 2 December 2016 Available online xxx

Life cycle assessment was used to assess environmental impacts and a sensitivity analysis of 17 key technological parameters to identify the main environmental hotspots associated with the performance of a sewage sludge treatment. The scenario takes into account primary and secondary sludge and includes gravity and centrifugal thickening, anaerobic digestion with cogeneration of heat and electricity from biogas, mechanical dewatering and spreading on agricultural fields. All the relevant inputs (electricity, heat, reagents, infrastructure, fuel, transport) and outputs (emissions to air, water and soil) are accounted for in the assessment, including the sludge return liquors from thickening and dewatering processes. This study focuses on climate change, terrestrial acidification, freshwater eutrophication, human toxicity and ionizing radiation impact categories assessed using the ReCiPe E v1.08/Europe baseline method. The results showed that the most sensitive parameters are the biodegradation rate of volatile solids and the nitrogen mineralization rate during anaerobic digestion, phosphorus and nitrogen capture rates during the thickening and dewatering processes, and the consumption of FeCl3 for the treatment of sludge before dewatering. The results suggest that the environmental performances of the sewage sludge treatment line could be enhanced by increasing the production of biogas (by increasing the biodegradation rate of volatile solids), by decreasing the consumption of FeCl3 used for sludge treatment, and by finding alternative treatments for sludge return liquors. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Sewage sludge Anaerobic digestion Dewatering Life cycle assessment Sensitivity analysis

1. Introduction Significant amounts of sludge are produced by wastewater treatment plants (WWTP) worldwide. In the European Union, the production of sewage sludge has increased thanks to more effective WWTP built in compliance with the Directive 91/271/EEC (European Commission, 1991) and the Water Framework Directive (European Commission, 2000). However, sewage sludge treatment can be a source of considerable pollutant emissions, including greenhouse gases (GHGs), and organic and inorganic pollutants (Brown et al., 2010; Hospido et al., 2010; Yoshida et al., 2015),

* Corresponding author. E-mail addresses: [email protected] (R. Girault), [email protected] (M. Pradel).

thereby reducing the benefits of sludge treatment for the environment. Sewage sludge treatment optimization is a therefore major challenge for both WWTP and policy makers. Anaerobic digestion (AD) of sewage sludge may be an interesting alternative. AD is commonly used in WWTP to stabilize and reduce the volume of sewage sludge. In addition, this process converts part of the sludge organic matter into biogas, which is a renewable source of electricity and heat (Brisolara and Qi, 2015). AD also modifies dewatering properties, which affects the whole sludge treatment line (Tiehm et al., 1997; Tosoni, 2015). Life Cycle Assessment (LCA) is a widely used tool to assess the environmental impacts of the whole life cycle of a product, a process or a service (ISO14040, 2010; ISO14044, 2010). LCA is commonly used in the field of wastewater treatment to compare and assess different technological systems of water and sewage sludge treatment and disposal (Corominas et al., 2013; Pradel et al.,

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C. Gourdet et al. / Journal of Cleaner Production xxx (2016) 1e14

2016; Yoshida et al., 2013). ISO standards advise the use of sensitivity analysis (SA) to identify the effect of different systems, technologies or data choices on LCA results. SA is therefore a way to confirm the robustness of LCA results and can be used to identify parameters that need to be known precisely before drawing conclusions or identifying more sensitive parameters (Groen et al., 2014). Unfortunately, sensitivity analysis is not systematically conducted in LCA applied to sewage sludge treatment, including treatments using AD and agricultural spreading as a disposal route. However, several authors applied LCA combined with SA to study the impact of parameters on sewage sludge treatment and disposal routes. For example, Liu et al. (2013) applied a comparative LCA of six scenarios combining two different sludge treatment technologies (press filtering and centrifugal dewatering) and disposal routes (agricultural spreading, incineration) to assess GHG emissions and their contribution to global warming potential (GWP). The authors then applied SA to the results of the LCA to determine the effect of sludge water content on GWP, and concluded that disposal of sludge with lower water content would make it possible to reduce the impact of the treatment scenarios on GWP (Liu et al., 2013). The aim of an LCA conducted by Houillon and Jolliet (2005) was to identify the best system to treat sewage sludge in terms of energy consumption and GWP, and to identify the key parameters that influence the environmental impact of the system. They analyzed six wastewater sludge treatment scenarios (spreading on agricultural fields, specific incineration, wet oxidation, pyrolysis, incineration in cement kilns, and landfilling), and then conducted a SA to study the impact of four parameters (residue stabilization, transport distance, WWTP size and technology) on the environmental balance. They concluded that none of the four parameters really influence the environmental balance, even if supplementary analyses could be performed, for example, on the size of the WWTP and the technology used, since their conclusions cannot be generalized (Houillon and Jolliet, 2005). However, these studies did not consider AD as a sludge treatment, as only mechanical dewatering was assessed. Hospido et al. (2005) used LCA to compare anaerobic digestion with pyrolysis and incineration as sludge treatment processes. They conducted a sensitivity analysis of different concentrations of Pb in the spread digested sludge, i.e. the real concentration in the sludge (334 mg Pb/kg of dry matter) compared with the average and upper value of the EU range of Pb concentrations (respectively 117 and 221 mg Pb/kg of dry matter). Their results showed that the concentration of Pb did not modify terrestrial toxicity potential, but that Pb was strongly affected human toxicity potential (Hospido et al., 2005). To our knowledge, only two recent studies combined LCA and SA for LCA scenarios including AD, mechanical dewatering and land application. Alvarez-Gaitan et al. (2016) focused their study on the GHG Life Cycle Inventory (LCI) of five different WWTP train configurations and analyzed the sensitivity of three key biogas production parameters to LCI data (digester sludge retention time (SRT), the age of the activated sludge and the ratio of primary to waste activated sludge (WAS) entering into the digester). SA results showed that when a higher ratio of WAS was fed into the digester, the production of biogas decreased (for the same SRT). When the digester SRT was longer, more biogas was produced, whereas a short SRT may lead to digester failure due to acidosis (Alvarez€ m et al. (2015) focused their study on Gaitan et al., 2016). Svanstro the flows and on the importance of N, P and C fates throughout the course of wastewater and sludge management including AD, mechanical dewatering and land application. They illustrated this with a sensitivity analysis of the water treatment (alternating P and N removal compared to a baseline scenario) and a selection of high

and low values from the literature regarding the fate of the elements (N2O and CH4 emissions to the air from WWTP, N2O and NH3 emissions to the air from the soil, NO
3 emissions to water from the soil, N and P availability for plants compared to that of mineral fertilizer, and C sequestration in soil). Their results showed that an increase in N removal from water treatment led to less N and C in the sludge thereby reducing the possibility of energy recovery through biogas production and nutrient recovery through land application of sludge. Changing nitrogen emissions was shown to lead to marked changes in some impacts (GWP, acidification potential and terrestrial eutrophication potential) while other impacts € m et al., were only slightly affected or remain unchanged (Svanstro 2015). All these authors, including Hong et al., 2009 and Pasqualino et al., 2009, highlighted the fact that AD has a major impact on climate change, eutrophication, acidification and human toxicity, but that this impact can be reduced if biogas is used by cogeneration units to produce heat and electricity that will be reused to heat the digester, and if AD significantly reduces the volume of sewage sludge treated. However, it is not clear from these studies how technological sludge treatment processes are involved and which key operational parameters are important when assessing the environmental impact of a sludge treatment line combining AD and mechanical dewatering using LCA. The aim of this study was thus to identify the stages of a wastewater sludge treatment line combining AD and mechanical dewatering that could be optimized. To this end, a set of 17 key technological performance parameters were identified and associated with primary and secondary sludge thickening, anaerobic digestion and dewatering. A sensitivity analysis of LCA results was conducted for each of the 17 key parameters and their influence on climate change, acidification, eutrophication, human toxicity and ionizing radiation results was assessed to distinguish which parameter in which treatment step is worth optimizing in the whole wastewater sludge treatment line. 2. Material and methods 2.1. Life Cycle Assessment (LCA) LCA is a four-step procedure based on international standards. The first step is to define the goal and scope of the study, i.e., the system to be studied, its boundaries, functions, and the related functional unit (the reference to which all the inventory data are related), the allocation methods used and the assumptions made in the study. The second step is the life cycle inventory (LCI) during which all the inputs (raw material, energy) and outputs (emissions) related to each process in the system are taken into account. The third step is the life cycle impact assessment (LCIA) which links the inputs and outputs of the system with an environmental impact. In the final step, the results are interpreted according to the system boundaries and the assumptions that were chosen. In our case, LCA was used to assess the environmental impact of the sewage sludge treatment line combining anaerobic digestion and mechanical dewatering. 2.1.1. Definition of the goal and scope 2.1.1.1. System boundaries. The system includes all the processes involved in the sewage sludge treatment line and its disposal. The treatment line includes thickening, anaerobic digestion, dewatering, transport, and storage before the sludge is spread on agricultural land. The water treatment line is not included in the system boundaries. System boundaries are presented in Fig. 1. For each process, the inflows and outflows of the sewage sludge mass were quantified, as well as the system's inputs (consumption

Please cite this article in press as: Gourdet, C., et al., In quest of environmental hotspots of sewage sludge treatment combining anaerobic digestion and mechanical dewatering: A life cycle assessment approach, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/ j.jclepro.2016.12.007

C. Gourdet et al. / Journal of Cleaner Production xxx (2016) 1e14

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System boundary of LCA Avoided products

Heat and electricity

Fertilizers Sub. 7

INPUTS Consumables Energy Infrastructures Transport

Agricultural spreading

Heat and power plant

Sub. 6

HEAT & ELECTRICITY

Sub. 1 Primary sludge

EMISSIONS

Storage

BIOGAS

Gravity thickening Sub. 3

0.65tTS

Anaerobic digestion

LIQUOR

Sub. 4

Sub. 5

Press filter dewatering

Transport

Sub. 2 Secondary sludge 0.35tTS

Centrifugal thickening

RETURN LIQUORS

RETURN LIQUORS

0.03tTS

0.04tTS

0.02tTS Treatment of sludge return liquor

Fig. 1. System boundaries and scenario flowchart of the LCA study.

of energy, reagents, fuel) and outputs (emissions to air, water and soil). Infrastructure resources and transport were also taken into account. Infrastructure resources refer to the construction of buildings and equipment used for each process unit. Dismantlement was not included. The treatment of sludge return liquors from thickening and dewatering processes was also accounted for in the study. Sludge return liquors are rich in nitrogen, carbon and phosphorus that have to be treated. To this end, liquors return to the head of the water treatment line thereby increasing nitrogen and carbon content and hence additional consumption of electricity for aeration of the aerobic reactor. In the same way, the treatment of phosphorus in return liquors leads to overconsumption of iron (III) chloride (FeCl3), which is used to precipitate orthophosphates (Kim et al., 2014). The FeCl3 and electricity overconsumption were taken into account in this study, but the infrastructure resources related to the return liquors treatment were not, as they were considered to be negligible.

2.1.1.2. System function and functional unit. The primary function of the system is the treatment of wastewater sludge. However, the system has additional functions in the form of energy or nutrient recovery. The first additional function is the production of heat and electricity through biogas recovery. Anaerobic digestion produces biogas, which is mainly composed of methane and carbon dioxide, and can be cogenerated to produce heat and electricity. The resulting energy is usually used to power the digester (heat the reactor, use as part of the energy mix, etc.) or is sent to the national electricity grid. The second additional function is the production of organic fertilizers, as once treated, sludge contains significant amounts of nitrogen, phosphorus and potassium, which are valuable fertilizers for agriculture (Alvarenga et al., 2015) and can be used instead of mineral fertilizers. As the aim of the study was to identify stages in sludge treatment to optimize the environmental balance of the treatment line,

we chose to expand the system by subtracting the abovementioned additional functions, which led us to include avoided products (Fig. 1). The functional unit (FU) of the system is used to quantify the function of the system. In the case of waste management, the FU is defined precisely according to the quantity of waste treated (McDouglas et al., 2001). In this case study, the FU was defined as one ton of total solids (tTS) of sludge entering the sewage sludge treatment line. 2.1.1.3. Description of the scenario. The scenario corresponds to a sewage sludge treatment line in France with a 100,000 population equivalent WWTP. This is representative of the sewage sludge treatment line in a WWTP with a similar capacity elsewhere in Europe (Hospido et al., 2008; Hwang and Hanaki, 2000). The sewage sludge treatment line treats primary and secondary sludge at a ratio of 65:35 (in % TS). Primary sludge is thickened using a gravity thickener (subsystem 1) while secondary sludge is thickened by centrifugation (subsystem 2). The primary and secondary sludge are then mixed before entering the anaerobic digester (subsystem 3). Digested sludge is dewatered with a press filter (subsystem 4) and transported to the storage area (subsystem 5), stored for six months (subsystem 6), after which the sludge is spread on an agricultural field (subsystem 7) (Fig. 1). Each subsystem is described in the following section. 2.1.2. Life cycle inventory Life cycle inventory data were taken from the literature or based on our own calculations. When data were not available in the literature, we used expert opinion. Calculations of infrastructure resources, sludge return liquors and agricultural spreading are described in detail in Supporting Information. Life cycle inventory data are reported in Table 1. 2.1.2.1. Subsystem 1: gravity thickening. Primary sludge remains in

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Table 1 Life Cycle Inventory data (inputs, outputs, avoided products) in the scenario according to each subsystem. Sub. 01 Inputs Sludge (tTS) 0.65 2.54E
05a Infrastructure resources
1 (p. tTS ) Energy (kWh. tTS
1): Electricity 5b,c Heat nc Transport (t.km) nc Consumables Polymers (kg AM. tTS
1) nc nc FeCl3 (kg AM. tTS
1) Fuel (l. tTS
1) nc Agricultural machinery (kg. tTS
1) Tractor nc Spreader nc Return liquors treatment Electricity (kWh. tTS
1) 18.1a FeCl3 (kg. tTS
1) 27.3a Avoided products Energy (kWh. tTS
1) Electricity nc Heat nc Fertilizers (kg. tTS
1) Ammonium nitrate nc Triple superphosphate nc Potassium chloride nc Outputs Sludge (tTS) 0.61 Sludge return liquors (tTS) 0.03 Emissions

Emissions to air (kg.tTS
1) CO2i 9.6g CH4 3.5g N2O 1.4g N2 nc H2S nc NOx nc SOx nc CO nc NMVOC nc NH3 nc Hydrocarbons (HC) nc SO2 nc C6H6 nc Benzo(a)pyrene nc Cd nc Cr nc Cu nc Ni nc Zn nc Se nc
1 Emissions to water (kg.tTS ) NO3 nc P2O5 nc Emissions to soil (kg.tTS
1) Zn nc Pb nc Cd nc

Sub. 02

Sub. 03

Sub. 04

Sub. Sub. 07 05 þ Sub. 06

0.35 0.94 4.87E
04a 4.96E
06a

0.67 0.63 1.13E
04a 0.19a

0.57 nc

170b,d nc nc

180e 750f nc

35b,c nc nc

nc nc 68a

nc nc nc

3b nc nc

nc nc nc

6b,d 80b nc

nc nc nc

nc nc 4.57a

nc nc

nc nc

nc nc

nc nc

0.332a 0.918a

22.9a 23.7a

nc nc

28.3a nca

nc nc

nc nc

nc nc

582a 832a

nc nc

nc nc

nc nc

nc nc nc

nc nc nc

nc nc nc

nc nc nc

27.55a 32.63a 5.55a

0.33 0.02

0.67 nc From Biogas leakage From Flared biogas From (2.5%) (10%) Cogeneration (87.5%)

0.63 0.04

0.57 nc

0.57 nc From Sludge spreading

nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc

0.631a,j 0.436a,j nc 0.007a,j 0.006a,j nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc

1.813a,j nc nc nc nc 0.0002k,j 0.0005k,j nc nc nc nc nc nc nc nc nc nc nc nc nc

1.813a,j nc nc nc nc 3.42E
03k,j 5.81E
04k,j 7.88E
03k,j 3.23E
04k,j nc nc nc nc nc nc nc nc nc nc nc

nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc nc

71.8h 26.1h 0.47h nc nc nc nc nc nc 0.08h nc nc nc nc nc nc nc nc nc nc

nc nc 2.45l nc nc nc nc nc nc 11.3l nc nc nc nc nc nc nc nc nc nc

0.07m 8.95m 3.86m 0.03m 1.23E
04m 3.51E
05m 1.93E
04m 6.49E
03m 2.63E
04m 3.51E
03m 3.51E
05m

nc nc

nc nc

nc nc

nc nc

nc nc

nc nc

61.83l 0.15l

nc nc

nc nc nc

nc nc nc

nc nc nc

nc nc nc

nc nc nc

nc nc nc

0.57m 0.09m 0.02m

nc nc nc

From Fuel combustion

1.19E04m 0.49m 0.46m

156.98m 13.63m

nc: not concerned. a based on calculations. b
mont, 2001. Degre c European Commission, 2001. d OTV, 1997. e Mean from Gori et al., 2011; Hong et al., 2009; Hospido et al., 2005; Soda et al., 2010. f Mean from Soda et al., 2010. g Pradel et al., 2013a,b. h Adapted from Amon et al., 2006. i Only fossil CO2 emissions are considered, biogenic CO2 produced during the sludge treatment is not included as it is assumed neutral for climate change. j Data for subsystem 3 are provided in kg/Nm.3. k RDC Environnement, 2007. l IPCC, 2006. m €gi, 2007. Nemecek and Ka

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mont, 2001). During this the gravity thickener for 24e48 h (Degre period, organic matter is anaerobically biodegraded resulting in an up to 1% and 1.6% reduction in total solids (TS) and volatile solids (VS), respectively. In addition, the process emits methane, carbon dioxide and dinitrogen monoxide: 0.8% of organic carbon in the sludge is emitted as C-CH4, 0.8% of organic carbon in the sludge is emitted as biogenic C-CO2 and 1.6% of total nitrogen in the sludge is emitted as N-N2O. Gravity thickening requires an electric supply of 5 kWh.t
1 DM (European Commission, 2001; OTV, 1997). The electricity used in the scenario is produced with the French energy mix, based on, in decreasing order, nuclear and hydraulic energy, and from coal, natural gas, and finally, oil resources (Ecoinvent Professional database, 2007). At the end of the treatment, primary sludge is thickened up to 7% of dryness and 3% of TS is transferred to sludge return liquors. 2.1.2.2. Subsystem 2: centrifugal thickening. Secondary sludge is thickened by centrifugation using polymers comprising 50% nitric acid and 50% acrylonitrile as reagents. Secondary sludge is thickened to 5.6% of dryness and 2% of the TS is transferred to sludge return liquors. Treatment of sludge return liquors produced during gravity and centrifugal thickening requires FeCl3 and electricity. 2.1.2.3. Subsystem 3: anaerobic digestion. The form of anaerobic digestion considered here is mesophilic digestion (37  C). This
mont, process produces up to 1000 m3biogas.ton
1 degraded VS (Degre 2001). The biogas is composed of 65% methane, 34% carbon dioxide, 0.6% nitrogen and 0.4% hydrogen sulfide (Nedergaard and Ortenblad, 1997; Poulleau, 2002). Of the total biogas produced, 2.5% is assumed to be lost due to leakage (Jungbluth et al., 2007), 10% is burned using a biogas flare and 87.5% is converted into electricity and heat by a cogeneration system whose respective thermal and electric efficiency represents up to 50% and 35% of the primary energy contained in the biogas. All the methane contained in the biogas is transformed into CO2, and then emitted into the air along with nitrogen oxides and sulfur oxides created by biogas combustion (RDC Environnement, 2007). This process is characterized by different additional emissions including NOx, SOx, CO and non-methane volatile organic compounds (NMVOC). The produced heat and electricity can replace fossil energy from external sources, which will be considered as avoided products. In the scenario, energy produced by anaerobic digestion supplies the digester and the surplus is exported to the national power grid. The digested sludge obtained after anaerobic digestion has a TS content of 4.5%, calculated according to the biodegradation rate of the TS and the initial composition of both the primary and secondary sludge. 2.1.2.4. Subsystem 4: press filter dewatering. Digested sludge is then dewatered using a press filter after being treated with polymers and iron (III) chloride. Once dewatered, the sludge reaches a TS content of 32%. Sludge return liquors from dewatering are treated as described in 2.1.1.1. but because its phosphorus content is not sufficiently high, additional use of FeCl3 is not included. 2.1.2.5. Subsystem 5 and 6: transport and storage. After dewatering, the sludge is stored for six months in a concreted area located 35 km from the wastewater treatment plant, next to the spreading area. The sludge is transported from the WWTP to the storage area in a 16 t truck. Sludge storage is characterized by emissions of NH3, N2O, CH4 and CO2: 0.3% of total nitrogen in the stored sludge is emitted as N-NH3, 0.6% of total nitrogen in the stored sludge is emitted as N-N2O, 10.7% and 10.7% of the organic carbon in the stored sludge are emitted as C-CH4 and biogenic C-CO2 respectively (calculated from Amon et al., 2006).

5

2.1.2.6. Subsystem 7: agricultural spreading. The dewatered digested sludge is then spread on a sandy loam soil in a rape/wheat/ winter barley rotation. The sludge is spread during the intercrop period before barley is sown. The amount of sludge spread is calculated based on crop needs and nutrient availability in the sludge, estimated respectively as 115.4 kg N.ha
1, 57.4 kg P.ha
1 and 83.22 kg k.ha
1 and as 35% for N, 100% for P and 100% for K (Bengtsson et al., 1997; Bernstad et al., 2011; Foley et al., 2010). The concentrations of heavy metals and organic contaminants in the sludge were not taken into account in this study for two reasons: (1) losses of elements and the effectiveness of degradation are too uncertain (Yoshida et al., 2015) to be accounted for in our study based on literature data, (2) the way the parameters used in the sensitivity analysis affect the flow of heavy metal and organic contaminants throughout the sewage sludge treatment is not well understand and thus hard to account for. The field where the sludge is spread is located at a distance of 2 km from the storage area and the sludge is transported to it with a tractor and a spreader. Transport requires equipment (here a tractor and spreader) and fuel. The amount of equipment used for spreading is calculated according to the time they are used for spreading and the mass: lifespan ratio. The amount of fuel consumed is evaluated by the time tractor is used and the average fuel consumption per time unit. Sludge spreading emissions include nitrogen and phosphorus emissions after spreading as well as emissions to the air from fuel combustion and to soil from abrasion of the tires. These emissions are calculated according to the method recommended in the Ecoinvent report (Nemecek and €gi, 2007). Ka The amounts of avoided mineral fertilizers are taken into account based on the amount of available N, P and K in the sludge that is spread. The avoided mineral fertilizers are ammonium nitrate (33.5% of N), potassium chloride (60% of K2O) and triple superphosphate (45% of P2O5). 2.1.3. Life cycle impact assessment Once the LCI was completed, the scenario was modeled with GaBi® v6 LCA software, which enables calculation of the mass balance all along the treatment line based on the model parameters (such as sludge composition). This makes it possible to analyze the consequences of variations in the parameters for the environmental impact of the whole treatment line. The potential environmental impacts of the treatment scenario are identified and classified according to the characterization method selected. In this case study, ReCiPe mid-point (E) V1.08/ Europe was used. ReCiPe is the most recent approach available in life cycle impact assessment. This method is the result of mid-point and end-point harmonization of indicators with respect to modelling principles and choices. From a methodological point of view, this was a major improvement as it enables the LCA-approach to be both flexible and at the same time more uniform (Goedkoop et al., 2013). The characterization factors used in ReCiPe are based on consistent and sound environmental cause-effect chains for nearly all impact categories. In addition, the method enables evaluation of a wide range of environmental impacts as it includes 18 different categories (European Commission, 2010). Among all possible indicators, in the present study, we focused on only five: -

Climate change (CC) expressed in kgeqCO2. Terrestrial acidification (TA) expressed in kgSO2. Freshwater eutrophication (FE) expressed in kgP. Human toxicity (HT) expressed in kg1.4DB (Dichlorobenzene), including all emissions of trace elements and heavy metals that are dangerous for human health.

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- Ionizing radiation (IR) expressed in kg235U, which represents the impact of anthropogenic emissions on the presence of ionizing radiation, due to the presence of radioactive components. Actually, as mentioned in the LCA inventory step, the system is mainly characterized by greenhouse gas emissions (CH4, CO2, N2O), acidifying substances (NH3, NOx, SO2), phosphorus (P2O5) and heavy metals (manganese, arsenic, selenium), which justify the selection of the first four midpoint indicators. In addition, in this scenario, large quantities of electricity are produced (cogeneration of heat and electricity from biogas) and consumed. Because the electricity mix in France is mainly produced by nuclear power plants, the interest of including the ionizing radiation indicator is clear.

2.2. Sensitivity analysis (SA) The results of the LCA were then used to perform a sensitivity analysis to identify the main points with an environmental impact among the efficiency parameters associated with primary and secondary sludge thickening, anaerobic digestion, and dewatering. To this end, we selected parameters related to the efficiency of the process that could influence the environmental impacts. Table 2 summarizes these parameters and their range of variation. To be sure of studying real parameter sensitivity, the ranges of variation came from realistic data in the literature or, when no data were available in the literature, from expert opinion. The experts we consulted were managers of French wastewater treatment plants that use the sludge treatment described here. Once these parameters were identified, several scenarios were created and modeled with GaBi® v6: the reference scenario described in Section 2.1.1.3 (Table 2). and, for each parameter

Table 2 Parameters included in the sensitivity analysis. Parameter

Unit

Gravity thickening for primary sludge TS contentc P1b % N capture ratea P2c % P capture ratea P3c % K capture ratea P4c % Centrifugal thickening for secondary sludge TS contentc P5b % N capture ratea P6c % a c P capture rate P7 % a c K capture rate P8 % Polymer consumptionc P9b kg AM.t TS
1 Anaerobic digestion VS biodegradation ratec P10c % N mineralization ratec P11c % c c Solubilization rate of P P12 % Press filter dewatering c c TS content P13 % N capture ratea P14c % P capture ratea P15c % K capture ratea P16c % FeCl3 consumptionc P17c kg AM.t TS
1 c b Polymer consumption P18 kg AM.t TS
1

Reference scenario

Range of variation Min

Max

7 95 70 60

3 75 65 55

10 100 100 95

5,6 95 70 60 3

3 75 65 55 2.5

6 100 100 95 3.5

44 44 10

30 30 0

65 65 35

32 98 98 60 80 6

15 75 75 55 60 4

35 100 100 95 200 14

Bold numbers refer to values used to assess the environmental impacts of the reference scenario. a Capture rates represent the percentage of a given element trapped in the sludge, the remainder is transferred to sludge return liquors or is lost through emissions. b
mont, 2001. Degre c Expert opinion.

studied, two scenarios with, respectively, a minimum and a maximum value (all the other parameter values were the same as in the reference scenario). Using the LCA results, sensitivity indices (Sij) were calculated for each parameter according to Equation (1) (Dochain and Van Rolleghem, 2001).

Sij ¼

pi OFjðpi þ DpiÞ
OFjðpiÞ   100 OFjðpiÞ Dpi

(1)

where. - Sij is the sensitivity index for the parameter pi and the objective function OFj. - pi is the value of the parameter i used in the reference scenario - OFj(pi) represents the objective function affected by parameter p, i.e. the environmental impact j obtained for parameter pi - Dpi is the absolute variation from the minimum or maximum parameter pi compared to the pi reference value. The sensitivity index quantifies the impact of each parameter on each environmental impact, according to their direction and magnitude. A positive index implies that increasing the parameter will lead to a positive variation in the environmental impact. A negative index implies that increasing the parameter will lead to a negative variation in the environmental impact.

3. Results and discussion 3.1. Interpretation of LCA results for the reference scenario Fig. 2 shows the relative contribution of each process in the treatment to the five mid-point indicators used in the reference scenario. The results are described in detail below.

3.1.1. Climate change The whole sludge treatment line contributed up to 649 kgeqCO2 (57% of total impact) mainly due to storage (21%), spreading (17%) and gravity thickening (9%). N2O emissions had the biggest impact on this environmental category. N2O is mainly emitted during nitrification and denitrification and accounted for 91% of the contribution to CC during spreading. In addition, gravity thickening and storage N2O emissions, which are linked to the breathing of denitrification microorganisms in the sludge, accounted for respectively up to 68% and 15% impact on each process. CH4 emissions had the second biggest impact on the climate change indicator. CH4 is only produced during storage and gravity thickening, whose respective contribution to climate change was 27% and 2%. Avoided impacts were
491 kgeqCO2 (43% of total impact) mainly linked to spreading (38%). Fifty-six percent of these avoided impacts were due to post-spreading N2O emissions and 19% to the avoided production of the avoided mineral fertilizer (respectively 12% and 9% of ammonium nitrate and triple superphosphate).

3.1.2. Terrestrial acidification The contribution to terrestrial acidification was 11.9 kgSO2 (59% of total impact) mainly due to spreading (52%) as it results in NH3 emissions (98%). Avoided impacts were
8.3 kgSO2, 97% of which were linked to spreading, more specially to avoided nitrogen emissions related to ammonium nitrate substitution (88%), mainly in the form of NH3 and NOx emissions (respectively 79% and 9%).

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Fig. 2. LCA results obtained with the reference scenario.

3.1.3. Freshwater eutrophication The sludge treatment line contributed up to 0.112 kgP (50% of the total impact) on freshwater eutrophication originating from dewatering (21%) and spreading (15%), which emit phosphate and P2O5. The contribution of dewatering was mainly related to the impact of the production of FeCl3 which is consumed during the treatment of sludge and of sludge return liquors (phosphate precipitation). Phosphate emissions occur during the production of FeCl3, which is used in large quantities in the treatment of sludge return liquors originating from the thickening and the dewatering processes and in the treatment of sludge prior to its dewatering. P2O5 is emitted after the sludge is spread. Avoided impacts were
0.113 kgP (50% of total impact) due to avoided production of triple superphosphate and avoided P2O5 emissions due to the substitution of mineral fertilizer, respectively 38% and 45%.

impact), mainly due to the centrifugal thickening (13%) and dewatering (12%) processes. The origin of the impact of ionizing radiation is the electricity consumed during the two processes (respectively 83% and 34%) and the electricity required for the production of FeCl3 used in dewatering (37% of the impact). Biogas was recovered from anaerobic digestion and cogenerated to produce heat and electricity to replace electricity from the national grid. This substitution represented 96% of the avoided impact which reached
441.5 kg235U (70% of total impact). 3.2. Sensitivity analysis

3.1.4. Human toxicity The impact on human toxicity was 3386.34 kg1.4DB (53% of total impact) mainly due to the consumption of FeCl3 during the treatment of the sludge and of sludge return liquors originating from centrifugal and gravity thickening. These processes accounted for respectively 30%, 7% and 10% of the total impact. In both cases, the production of FeCl3 was the main process involved in this impact (98%) since several heavy metals, including manganese and barium, are emitted. On the other hand, polymer consumption only contributed 1% to this impact. A total of
3055.41 kg1.4DB was avoided thanks to the use of electricity produced from the biogas instead of electricity from the national grid and to the use of sludge instead of triple superphosphate fertilizer (47% of total impact). Indeed, the production of electricity is a source of emissions of heavy metals such as selenium, manganese and arsenic, which are mainly emitted during oil and coal combustion. The production of phosphate fertilizer also results in arsenic and manganese emissions. Avoided emissions linked to the production of triple superphosphate represented 35% of the total avoided impact, while avoided emissions linked to the production of electricity represented 33%.

Two different series of sensitivity indexes (SI) were obtained from the sensitivity analysis: one for the minimum value and one for the maximum value for each parameter and each impact studied (see Supporting Information). Average SI values (represented as bars) as well as minimum and maximum SI values (represented as error bars) are shown in Fig. 3. These SI values represent the impact sensitivity for a 100% increase in a given parameter. When the indices are positive (light grey bars), there is an increase in the environmental impact with an increase in the value of the parameter, whereas when the indices are negative (dark grey bars), there is a decrease in the impact with an increase in the parameter. Parameters with an absolute SI value < 20% are considered insensitive. To make the results easier to understand, for each process, only the results obtained for the most sensitive parameters are discussed. Regarding the environmental impact of freshwater eutrophication, the SI values are extremely high (more than 2000%). This can be explained by the value of freshwater eutrophication, which was equally distributed between generated and avoided impacts and was very close to zero (Section 3.1.3.). In this case, a minute variation can have a major effect on the resulting SI value. Similar results were found by Niero et al. (2014), who particularly underlined that for WWTP which spread anaerobically digested sludge, uncertainty on freshwater eutrophication is greater than uncertainty on climate change (Niero et al., 2014).

3.1.5. Ionizing radiation The mid-point indicator value was 192.1 kg

3.2.1. Sensitivity of thickening parameters The results obtained for the gravity and centrifugal thickening

235

U (30% of total

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Fig. 3. Results of sensitivity analysis: the percentage represents the average absolute sensitivity index of each environmental impact and each parameter according to their direction and magnitude. Light grey bars represent positive indices (i.e. increasing the parameter leads to a positive variation in the environmental impact). Dark grey bars represent negative indices (i.e. increasing the parameter leads to a negative variation in the environmental impact). Error bars show the variation of sensitivity index values for pi(min) and pi(max).

processes were very similar and phosphorus and nitrogen capture rates and TS content were the only sensitive parameters. Table 3 lists the origin of the sensitivity of thickening parameters according to each environmental category. 3.2.1.1. Phosphorus capture rate (P3 e P7). The phosphorus capture rate was a sensitive parameter for climate change, freshwater eutrophication and human toxicity (Fig. 3a, c, d). The related SI values were all negative, meaning the impact decreases with an increase in the phosphorus capture rate. The climate change impact was strongly affected by the P capture rate. Actually, when this parameter increases, sludge phosphorus content also increases, thereby reducing the amount of sludge that is spread on the land (P is the limiting factor that determines the quantity of sludge to be spread). This reduction also lowers emissions during the transport and the spreading of the sludge (N2O emissions due to fuel consumption and N denitrification in the soil) as well as reducing the amount of avoided mineral fertilizer (ammonium nitrate and potassium chloride).

The increase in the phosphorus content of the sludge had direct consequences for emissions during spreading as it increased P2O5 emissions, thereby increasing the impact of freshwater eutrophication. The avoided use of triple superphosphate led both to avoided emissions of P2O5 and to avoided phosphate emissions during its production. As a consequence, the freshwater eutrophication impact was reduced. Regarding human toxicity, the explanation is the same as for climate change if the phosphorus capture rate increases. Reducing the amount of agricultural machinery and fuel used for spreading the sludge reduces the quantity of heavy metals emitted during their production (barium (Ba), manganese (Mn), zinc (Zn), arsenic (As)), which improves the global impact of human toxicity. In the same way, thanks to the use of sludge instead of mineral fertilizer, emissions of heavy metals into the air, soil and water are also avoided. 3.2.1.2. Nitrogen capture rate (P2 e P6). The nitrogen capture rate was also a sensitive parameter for human toxicity and, according to

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Table 3 Origin of the variability of each sensitive parameter in thickening processes according to each environmental category considered in this study (þrefers to a positive contribution,
refers to avoided emissions). Parameters

Impact category

Origins of variability (% contribution)

P capture rate

Climate change

þ þ þ

þ

þ þ
þ
þ

þ
þ


Freshwater eutrophication

Human toxicity

N capture rate

Human toxicity Terrestrial acidification

TS content

Freshwater eutrophication Human toxicity

the SI, an increase in this parameter led to a decrease in the impact value (Fig. 3d). Two explanations are possible: - An increase in the nitrogen capture rate increases the concentration of nitrogen in the thickened sludge and, as a consequence, decreases the concentration of nitrogen in the sludge return liquors resulting from that process. Then, the consumption of electricity results in the emission of heavy metals, such as selenium (Se), manganese and arsenic during electricity production. However, this phenomenon is counterbalanced by an increase in the amount of N mineralized during AD, leading to an increase in the N load in return liquors from dewatering. - An increase in N content in the sludge increases avoided ammonium nitrate production, during which heavy metals are emitted. The nitrogen capture rate was also the most sensitive parameter in the terrestrial acidification and climate change impact categories (Fig. 3b and a). An increase in the nitrogen capture rate increased nitrogenous emissions (NH3, N2O) during storage and spreading by modifying the composition of the sludge. Avoided nitrogenous emissions linked to the avoided use of mineral fertilizers were also significant (N2O, NH3 emitted after application of ammonium nitrate and N2O, NH3, NOx and SO2 emissions generated during the production of ammonium nitrate). Nevertheless, avoided impacts were lower than emissions during sludge storage and spreading. Hence, for that parameter, the SI is positive: an increase in the nitrogen capture rate increased terrestrial acidification and impacts on climate change. 3.2.1.3. TS content (P1 e P5). Increasing the TS content of the two thickened sludges led to an increase in freshwater eutrophication and human toxicity impacts. This can be explained by two phenomena. On one hand, increasing TS increases the amount of sludge return liquors and as a consequence, increases their N-NHþ 4 and PPO34 content. Thus, more electricity and FeCl3 will be needed for their treatment and the FeCl3 production process is a source of phosphates and heavy metals such as manganese and barium which are involved in freshwater eutrophication and human toxicity phenomena. On the other hand, the reduction in the nitrogen content in the final sludge due to an increase in nitrogen content in the sludge return liquors reduces the amount of avoided

CO2, N2O, CH4 from fuel combustion (67%) CO2 from the production of agricultural machinery (23%) CO2 from fuel production (10%) N2O from spreading mineral fertilizer (88%) CO2 from the production of triple superphosphate (12%) P2O5 from spreading sludge (99%) P2O5 from spreading mineral fertilizer (55%) Phosphate from the production of triple superphosphate (45%) Ba, Mn, Zn, As from the production of agricultural machinery (69%) Ba from fuel production (31%) As, Mn from the production of triple superphosphate (100%) Se, Mn, As from the treatment of dewatering liquors (87%) As, Mn, Se from the production of ammonium nitrate (100%) NH3 from the storage and spreading of sludge (100%) NH3 from spreading mineral fertilizer (95%) NH3, NOx, SO2 from the production of ammonium nitrate (5%) Phosphate from the production of FeCl3 (100%) Phosphate from the production of ammonium nitrate (100%) Mn, Ba from FeCl3 production (100%) Mn, AS, Se from ammonium nitrate production (100%)

ammonium nitrate and hence reduces avoided emissions linked to its production and application (phosphate, arsenic, selenium, manganese). 3.2.2. Sensitivity of anaerobic digestion parameters The results for anaerobic digestion can be explained by two parameters: the VS biodegradation rate and the nitrogen mineralization rate. Table 4 lists the origin of the sensitivity of anaerobic digestion parameters in each environmental category studied. 3.2.2.1. VS biodegradation rate (P10). An increase in the VS biodegradation rate reduced the impact on climate change of the treatment line (Fig. 3a). An increase in the VS biodegradation rate increased biogas production. This led to additional CH4 emissions, which were counterbalanced by a reduction in CO2 emissions: - CH4 emissions: An increase in the volume of biogas produced increased the CH4 from biogas leakage. - CO2 emissions: Depending on the scenario, an increase in biogas production reduced the need for an external source of natural gas to heat the reactor, or increased the avoided consumption of natural gas (scenario with excess biogas production). An increase in the VS biodegradation rate led to a very considerably reduction in the impacts of freshwater eutrophication, human toxicity and ionizing radiation (Fig. 3c, d, e). Respectively, avoided emissions of phosphates, heavy metals and radioisotopes generated by the reused electricity and heat produced from the biogas in order to either supply the digester or be exported to the national grid explain these results. 3.2.2.2. Nitrogen mineralization rate (P11). This parameter was mainly sensitive for climate change and terrestrial acidification impacts. An increase in the nitrogen mineralization rate reduced these impacts. Increasing N mineralization increased the amount of NHþ 4 contained in digested sludge, and consequently, rendered this element more leachable during dewatering. Hence, increasing this parameter reduced nitrogen content in the dewatered sludge, and consequently N2O and NH3 emissions during storage and spreading. With the decrease in nitrogen content in the sludge, the amount of avoided ammonium nitrate also decreased, as did related avoided emissions including N2O, CO2, NH3, NOx and SO2

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Table 4 Origin of variability of each sensitive parameter for anaerobic digestion according to each environmental category considered in this study (þrefers to a positive contribution,
refers to avoided emissions). Parameters

Impact category

Origin of variability (% contribution)

VS biodegradation rate

Climate change

þ þ
þ þ
þ þ
þ þ
þ

þ



Freshwater eutrophication

Human toxicity

Ionizing radiations

N mineralization rate

Climate change

Terrestrial acidification

linked to fertilizer production, and N2O and NH3 emissions due to spreading of the sludge.

3.2.3. Sensitivity of dewatering parameters Results of the dewatering parameters sensitivity analysis enabled identification of the four most sensitive parameters: phosphorus and nitrogen capture rates, FeCl3 consumption and TS content. Table 5 lists the origin of the sensitivity of dewatering parameters for each environmental category studied.

CO2 from external heat source used for the digester (84%) CH4 from the AD and storage stages (14%) CO2 from self-consumption of heat and electricity (100%) Phosphate from external heat used for the digester (96%) Phosphate from the treatment of liquors (4%) Phosphate from self-consumption of heat/electricity (100%) Mn from external heat source used for the digester (90%) Se, Mn, As from the treatment of dewatering liquors (10%) Se, Mn, As from self-consumption of heat/electricity (100%) 222 Rn, 14C from the treatment of dewatering liquors (59%) 222 Rn, 14C from external heat used for the digester (41%) 222 Rn, 14C from self-consumption of heat/electricity (100%) N2O from storage and spreading (99%) N2O, CO2 from ammonium nitrate production (62%) N2O from spreading mineral fertilizer (38%) NH3 from storage and spreading of sludge (100%) NH3 from spreading mineral fertilizer (95%) NH3, NOx, SO2 from ammonium nitrate production (5%)

3.2.3.1. Phosphorus capture rate (P15). The increase in the P capture rate had a favorable impact on climate change and human toxicity. The two explanations given in Section 3.2.1.1 for the P capture rate during sludge thickening are also valid here. An increase in the P capture rate led to a decrease in the impact of freshwater eutrophication. As an increase in the P capture rate increased the concentration of P in the sludge, the result was an increase in P2O5 emissions linked to sludge spreading. However, these emissions were counterbalanced by the increase in the amount of avoided products, which globally improved the impact of this midpoint

Table 5 Origin of variability of each sensitive parameter for dewatering according to each environmental category considered in this study (þrefers to a positive contribution,
refers to avoided emissions). Parameters

Impact category

Origins of variability (% of contribution)

Phosphorus capture rate

Climate change

þ þ þ

þ

þ þ
þ

þ

þ
þ
þ
þ þ þ

þ þ þ



Freshwater eutrophication

Human toxicity

Nitrogen capture rate

Climate change

Terrestrial acidification

Ionizing radiation FeCl3 consumption

Freshwater eutrophication Human toxicity

TS content

Climate change

Terrestrial acidification

CO2, N2O, CH4 from fuel (67%) CO2 from the production of agricultural machinery (23%) CO2 from fuel production (10%) N2O from spreading ammonium nitrate (88%) CO2 from triple superphosphate production (12%) P2O5 from spreading sludge (99%) P2O5 of from spreading triple superphosphate (55%) Phosphate from the production of triple superphosphate (45%) Ba, Mn, Zn, As from the production of agricultural machinery (69%) Ba from fuel production (31%) As, Mn from the production of triple superphosphate (100%) N2O from storage and spreading (99%) CO2, N2O from the production of ammonium nitrate (62%) N2O from spreading ammonium nitrate (38%) NH3 from storage and spreading (100%) NH3 from spreading ammonium nitrate (95%) NH3, NOx, SO2 from the production of ammonium nitrate (5%) 222 Rn, 14C from the treatment of dewatering liquors (100%) 222 Rn, 14C from the production of ammonium nitrate (100%) Phosphate from FeCl3 production (100%) Phosphate from the production of ammonium nitrate (100%) Mn, Ba from the production of FeCl3 (100%) AS, Mn, Se from the production of ammonium nitrate (100%) CO2, N2O, SF6, CH4 from sludge transport (51%) N2O from spreading sludge (39%) N2O from sludge storage (8%) N2O, CO2 from the production of ammonium nitrate (62%) N2O from spreading ammonium nitrate (38%) NH3 from spreading sludge (85%) NOx, SO2 from sludge transport (13%) NH3 from sludge storage (2%) NH3 from spreading ammonium nitrate (95%) NH3, NOx, SO2 from the production of ammonium nitrate (5%)

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indicator. 3.2.3.2. Nitrogen capture rate (P14). The nitrogen capture rate had a significant impact on climate change and terrestrial acidification. When this parameter increased, nitrogen sludge content, and consequently, nitrogenous emissions during storage and spreading also increased. In compensation, the avoided amount of ammonium nitrate increased along with the capture rate, as did CO2, N2O, NH3, NOx and SO2 emissions due to the production and application of ammonium nitrate. The nitrogen capture rate was also the most influential parameter in the impact of ionizing radiation even if its sensitivity was not high (SI of about 20%). Increasing the capture rate led to a decrease in the concentration of nitrogen in sludge return liquors. This decrease reduced 14C and 222Rn emissions due to the production of electricity used for the treatment of return liquors. However, this was partially offset by a decrease in avoided emissions due to avoided consumption of ammonium nitrate. 3.2.3.3. FeCl3 consumption (P17). FeCl3 consumption had a marked unfavorable impact on freshwater eutrophication and human toxicity. This was mainly because increasing FeCl3 led to an increase in emissions of phosphate and heavy metals linked to its production. 3.2.3.4. TS content (P13). This parameter was not the most sensitive but an increase in TS content led to a decrease in climate change and terrestrial acidification impacts. Increasing the TS content of the sludge reduced the amount of sludge to be managed and transported, thereby reducing CO2, N2O, SF6, CH4, NOx and SO2 emissions linked to fuel combustion. Increasing the TS content also reduced the nitrogen content of the sludge, as described in Section 3.2.1.3 and hence reduced N2O and NH3 emissions during storage and spreading. However, this benefit was partially counterbalanced because the increase in TS content reduced the nitrogen content of the sludge, which reduced the avoided amount of ammonium nitrate, and related avoided emissions from the production and application of ammonium nitrate. 3.3. Identification of potentially improvable stages in the sludge treatment line and discussion 3.3.1. Hierarchy of the sensitive performance parameters Among the climate change parameters studied, the two most sensitive parameters identified were the P capture rate during dewatering (P15) and the VS biodegradation rate during AD (P10). These were followed by the rates of P capture during gravity thickening (P3), N capture during dewatering (P14), P capture during centrifugal thickening (P7), N mineralization (P11) and N capture during centrifugal thickening (P6). Concerning terrestrial acidification, the sensitivity analysis enabled the identification of four sensitive parameters which are, in decreasing order, the rate of N capture during dewatering (P14), the rate of N mineralization during AD (P11) and the rate of N capture during both types of thickening (P6 and P2). All of these parameters have an impact on the N content of the resulting sludge. According to the results of SA, freshwater eutrophication is mainly affected by five parameters: the rate of P capture during dewatering (P15), FeCl3 consumption during dewatering (P17), the rate of P capture during gravity thickening (P3), the rate of VS biodegradation during AD (P10) and finally, the rate of P capture during centrifugal thickening (P7). Nevertheless, the impact of the sludge treatment line on freshwater eutrophication was moderate and its optimization is not the main challenge. Nearly the same parameters were identified as the most

11

sensitive ones for human toxicity. The most sensitive parameter was FeCl3 consumption during dewatering (P17), followed by the rate of VS biodegradation during AD (P10), the rate of P capture during dewatering (P15) and gravity thickening (P3). Finally, ionizing radiation was only, but nevertheless significantly, affected by the variation in the rate of biodegradation during AD (P10). Generally speaking, the sensitivity of the parameters almost always depended on the same variables:  Direct emissions from AD, and more particularly from biogas leakage (CH4), like for the sensitivity of VS biodegradation rate during AD (P10).  Direct emissions during sludge storage (N2O, NH3 and CH4) and spreading (N2O, NH3 and P2O5) influenced by modifications in sludge contents, like the sensitivity of N and P capture rates during thickening and dewatering processes (P2 and P3 for primary sludge thickening, P6 and P7 for secondary sludge thickening, P14 and P15 for digested sludge dewatering) or for the sensitivity of N mineralization rate during AD (P11).  Indirect emissions during treatment of the sludge return liquors, like for the sensitivity of VS biodegradation rate during AD (P10).  Indirect emissions due to the production and combustion of fuel, like for the sensitivity of P capture rates during sludge thickening and dewatering (P3, P7 and P15).  Indirect emissions linked to the production of FeCl3 like for the sensitivity of P capture rates during sludge thickening and dewatering (P3, P7 and P15) or the sensitivity of FeCl3 consumption for sludge conditioning (P17). Avoided impacts offset the total environmental consequences of the sludge treatment line, especially those due to: - electricity and heat self-consumed by the WWTP thanks to the recovery of biogas, like for the sensitivity of VS biodegradation rate during AD (P10); - avoided triple superphosphate or ammonium nitrate production and their related post-application emissions, like for the sensitivity of N and P capture rates during sludge thickening (P2, P3, P6, P7) and dewatering (P14 and P15) or the sensitivity of N mineralization rate during AD (P11).

3.3.2. Impact of the assumptions on the results It is surprising that the results were more affected by phosphorus parameters than nitrogen parameters. The explanation is that, in each variation in each scenario, P was the limiting factor that determined the amount of sludge to be spread on the land. This variation consequently also affected the amount of agricultural machinery and fuel used for sludge spreading and all related emissions. Variations in nitrogen content had less impact than variations in phosphorus content. However, these results are entirely dependent on all the assumptions and methodological choices made concerning LCA and SA. Indeed, determining the limiting factor, which appears regularly in SA results, is completely dependent on the assumptions chosen for concerning crop rotation, the crop, and the soil that receives the sludge (see Supporting Information). These three assumptions affect the amounts of N, P and K available for crops, and consequently the amount of sludge that needs to be spread. It is likely that the results (and maybe the limiting factor) would be different if we changed these assumptions. Other important assumptions concern substitution since, as shown by the results, avoided impacts often had a significant effect. Different choices concerning avoided fertilizer or the origin of electricity would have produced different results. Indeed, calcium

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ammonium nitrate has higher impacts whatever the environmental impact compared to the ammonium nitrate (used in this study and used as reference) for 1 kg of N produced, while the other mineral fertilizers have lower impacts except for the ionizing radiation impact of urea (Fig. 4a). The same is true for the electricity mix used, as the European electricity mix has a higher impact than the French electricity mix except for ionizing radiation as 75% of French electricity is produced by nuclear power (Fig. 4b). Other assumptions used to model the treatment scenario itself need to be kept in mind when interpreting the results. Among the most important are:  Transport of the sludge from the WWTP to the storage area rarely appeared in the results, which may be linked to the assumptions concerning distances and means of transport (we used transport over a distance of 35 km with a 16 t truck).  FeCl3 was chosen as reagent for the treatment of sludge before dewatering. The results of sensitivity analysis would have been different if another reagent had been chosen.  We chose not to consider interactions between parameters whereas in reality they exist, which would certainly influence the final results (for example, the impact of VS biodegradation in the digester on dewatering efficiency, as identified by Girault et al. (2015)).  We chose not to consider concentrations of heavy metals and organic contaminants in the sludge although it is known that they may affect human toxicity. Indeed, heavy metals can contribute up to 10% of the human toxicity impact in similar system (anaerobic digestion, press filter dewatering with lime conditioning, agricultural spreading) (Pradel et al., 2013a,b) and up to 96% when human toxicity is assessed with USES model for a system where only sludge spreading is considered (Sablayrolles et al., 2010). The choice of the method of characterization also has an impact on the LCA results as there is no consensus on characterization factors for some impacts especially those of toxicity. This was confirmed by Lederer and Rechberger (2010), who compared the relative impact of heavy metal emission in different sewage sludge treatment options and different methods of characterization and highlighted great variability in the results. More recently, Niero et al. (2014) come to the same conclusion and pointed out that

1.2 1 1.1 1 1 0.9 0 0.8 0 0.7 0 0 0.6 0 0.5 0.4 0 0.3 0 0.2 0 0.1 0 0 Climate change (kg CO2 eq)

Freshwater Human eutrophication toxicity (kg (kg P eq) 1,4-DB eq)

Ammonium nitrate (reference) Calcium ammonium nitrate Urea

Ionising radiation (kg U235 eq)

Terrestrial acidification (kg SO2 eq)

Ammonium sulphate Diammonium phosphate

a) Environmental impacts for 1 kg of N at regional storage for several N mineral fertilizers (data come from Ecoinvent V2)

the results obtained for toxicity-related impacts are sensitive to the choice of the method of characterization. As indicated by Lundin et al. (2000), the choices of the boundaries for the system under study are important and the system boundaries should be chosen according to the purpose of the study. Whatever the environmental categories, an LCA focused on sludge agricultural spreading (Sablayrolles et al., 2010) will not have the same impact as an LCA focused on the whole wastewater treatment plant or on the whole water system (Lundie et al., 2004). However, different LCA studies can be compared providing they have the same objectives, the same or related functional units (i.e. one functional unit can be deduced from the other), and the results are assessed using the same method of characterization. This kind of comparison can be used to better understand the LCA results and which technological parameters or processes are important. As an illustration, for the same study environmental impact categories in this study and the study of Niero et al. (2014), we can highlight that:  Contributors to climate change are not the same in the two studies (electricity consumption in the Niero et al. study, agricultural spreading in this study) as no direct GHG emissions are considered to be emitted from the WWTP in the study by Niero et al. Except for possible emissions from N2O and CH4 during biological treatment of wastewater, the main GHG emissions occur in the sewage sludge treatment line during anaerobic digestion (CH4 leakage), sludge storage and agricultural spreading (mainly as CH4, N2O).  Contributors to human toxicity are the same in the two studies (electricity and FeCl3 consumption in the paper by Niero et al. only FeCl3 consumption in our study). As iron(III) chloride is mainly used in the sludge treatment line, reducing its consumption may reduce the human toxicity impact.  Contributors to freshwater eutrophication are mainly due to the WWTP effluent in the study by Niero et al. and to return liquor treatment in our study. As nitrate and phosphate release in WWTP effluent have a greater impact than in the sludge treatment line, the main improvement for freshwater eutrophication can be made by increasing the efficiency of water treatment. To sum up, this study highlights the fact that absolute values from sensitivity indexes depend to a great extent on the system

Normalized impact value

12

11 10 9 8 7 6 5 4 3 2 1 0 Climate Freshwater Human change (kg eutrophication toxicity (kg CO2 eq) (kg P eq) 1,4-DB eq) French electricity mix (reference)

Ionising Terrestrial radiation (kg acidification U235 eq) (kg SO2 eq) European electricity mix

b) Environmental impacts for 1 kWh of electricity produced from French or European energetic mix (data come from Ecoinvent V2)

Fig. 4. Comparison of the impact of several N mineral fertilizers and production of the electricity mix using ReCipE v1.08 (E) method (impact data are expressed according to the impact of 1 kg of N as ammonium nitrate and the impact of 1 kWh of electricity from the French energetic mix, respectively).

Please cite this article in press as: Gourdet, C., et al., In quest of environmental hotspots of sewage sludge treatment combining anaerobic digestion and mechanical dewatering: A life cycle assessment approach, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/ j.jclepro.2016.12.007

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boundaries used, whereas the parameter hierarchy remains valid whatever the system boundaries used. 4. Conclusion LCA results show that sludge spreading and dewatering, and, to a lesser extent, storage and thickening contribute the most to the environmental impacts climate change, terrestrial acidification, freshwater eutrophication, human toxicity and ionizing radiation. In addition, SA results allowed the identification of the most sensitive parameters involved in these operations. Combining LCA with SA of the key technological parameters proved to be a reliable way of estimating the environmental impacts of existing processes of sewage sludge treatment and of identifying possible areas for optimization. Indeed, this study allowed the identification of the following targets in the sludge treatment line: - nitrogen and phosphorus capture rates during thickening and dewatering, - rate of VS biodegradation and of nitrogen mineralization during anaerobic digestion, - FeCl3 consumption related to treatment of sludge return liquors (orthophosphates). The results show that the environmental performances of the sludge treatment line need to be improved by increasing the efficiency of anaerobic digestion (rate of biodegradation of volatile solids), by reducing the consumption of FeCl3 in the treatment of sludge, and by developing alternative treatments for sludge return liquors. This study highlights the advantages of using LCA and SA as tools for the optimization of these processes, the target being the ecodesign of the entire sludge management line. Acknowledgements This research was funded by the “Office National des Eaux et des Milieux Aquatiques” (ONEMA) and by the Premex 2015 from the management strategy, research and evaluation department of Irstea. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.jclepro.2016.12.007. References Alvarenga, P., Mourinha, C., Farto, M., Santos, T., Palma, P., Sengo, J., Morais, M.C., Cunha-Queda, C., 2015. Sewage sludge, compost and other representative organic wastes as agricultural soil amendments: benefits versus limiting factors. Waste Manag. 40, 44e52. Alvarez-Gaitan, J.P., Short, M.D., Lundie, S., Stuetz, R., 2016. Towards a comprehensive greenhouse gas emissions inventory for biosolids. Water Res. 96, 299e307. Amon, B., Kryvoruchko, V., Amon, T., Zechmeister-Boltenstern, S., 2006. Methane, nitrous oxide and ammonia emissions during storage and after application of dairy cattle slurry and influence of slurry treatment. Agric. Ecosyst. Environ. 112, 153e162. Bengtsson, M., Lundin, M., Molander, S., 1997. Life Cycle Assessment of Wastewater Systems: Case Studies of Conventional Treatment, Urine Sorting and Liquid Composting in Three Swedish Municipalities. Chalmers University of Technology, Gothenburg, Sweden. Bernstad, A., La Cour Jansen, J., Aspegren, H., 2011. Life cycle assessment of a household solid waste source separation programme: a Swedish case study. Waste manage. Res. 29, 1027e1042. Brisolara, K.F., Qi, Y., 2015. Biosolids and sludge management. Water Environ. Res. 87, 1147e1166. Brown, S., Beecher, N., Carpenter, A., 2010. Calculator tool for determining greenhouse gas emissions for biosolids processing and end use. Environ. Sci. Technol.

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Please cite this article in press as: Gourdet, C., et al., In quest of environmental hotspots of sewage sludge treatment combining anaerobic digestion and mechanical dewatering: A life cycle assessment approach, Journal of Cleaner Production (2016), http://dx.doi.org/10.1016/ j.jclepro.2016.12.007