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A life cycle assessment of conventional technologies for landfill leachate treatment
Accepted Manuscript A life cycle assessment of conventional technologies for landfill leachate treatment Francesco Di Maria, Federico Sisani
PII: DOI: Reference:
S2352-1864(17)30015-9 https://doi.org/10.1016/j.eti.2017.09.002 ETI 153
To appear in:
Environmental Technology & Innovation
Received date : 11 January 2017 Revised date : 18 August 2017 Accepted date : 12 September 2017 Please cite this article as: Di Maria F., Sisani F., A life cycle assessment of conventional technologies for landfill leachate treatment. Environmental Technology & Innovation (2017), https://doi.org/10.1016/j.eti.2017.09.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A life cycle assessment of conventional technologies for landfill leachate treatment *
Francesco Di Maria1,*,**, Federico Sisani* LAR Laboratory – Dipartimento di Ingegneria, University of Perugia Via G. Duranti 93, 06125 Perugia, Italy ** CIMIS – via G. Duranti 67, 06125 Perugia, Italy
Abstract Landfilling of municipal solid waste is still one of the most diffused practices worldwide, generating long-term heavily polluted gaseous and liquid (i.e. leachate) emissions, causing environmental and especially human health concerns. Improvement of the methods for treating these emissions, particularly the leachate, is mandatory for increasing the sustainability of the entire waste management system. For this aim the environmental impact of conventional off-site technologies, based on co-treatment of leachate with civil sewage in wastewater treatment plants, was compared with advanced on-site technologies based on reverse osmosis and evaporation in a life cycle perspective. The model was built using mainly experimental and technical data from fullscale facilities. Human toxicity and freshwater ecotoxicity were the impacts most affected by the scenarios analysed. Average impacts were higher for the conventional off-site co-treatment in wastewater treatment plants, whereas impacts were lower for the advanced on-site treatment based on reverse osmosis. This result was largely influenced by the high incidence due to leachate transport for the off-site management scheme. Due to the high consumption of energy (i.e. 40kWh/m3 electricity and 18.5 kWh/m3 thermal heat) and chemicals (mainly HCl) the impact for the on-site evaporation system was always higher than for reverse osmosis and in some cases also for the conventional co-treatment with civil sewage sludge. The uncertainty analysis showed that pollutant emissions to water and emissions due to transport were affected by the highest errors, influencing in a major way the uncertainty of the impacts considered. Keywords: Evaporation, leachate, life cycle analysis, reverse osmosis, wastewater treatment plant. 1. Introduction Landfill disposal is still one of the most diffused options worldwide for the management of municipal solid waste (MSW) (Camba et a., 2014). As an example, at the EU28 level, 31% of the whole MSW (i.e. about 74 Mtonnes/year) is directly landfilled (ISPRA, 2015). Degradation of MSW is a long-term event, generating heavily polluted gases (i.e. landfill gas) (Barlaz et al., 2009; Chen and Lo, 2016; Di Maria et al., 2013a) and liquids (i.e. leachate) (Camba et al., 2014; Di Maria et al. 2013b), which are the main source of the environmental impact associated with this practice. Therefore it is of prime importance to identify more sustainable technologies for their treatment in order to reduce the environmental concerns of the entire MSW management system. In particular leachate can be considered a triphasic system with the characteristics of a heavily polluted wastewater (Schiopu and Graviliescu, 2010; Slack et al., 2005), entailing an important threat to human health, soil, and surface and ground water. The most widespread options for leachate treatment can be classified as off-site and on-site treatments, which can also be referred to as conventional and advanced treatments, respectively (Renou et al., 2008). Among the conventional ones, leachate transfer for combined treatment with civil sewage in wastewater treatment plants (WWTP) is the most diffused (Wernet et al., 2016). However, due to the continuously more rigorous discharge standards and the ageing of landfill sites with more and more stabilized leachates, the capability of WWTP to remove some trace pollutants is limited (Papa et al., 2016). Furthermore off-site treatment costs are affected by both transport and 1
Corresponding author email: [email protected]
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disposal fees that can be influenced by market fluctuations, which are also an important key factor in the economic risk for the landfill manager. For these reasons advanced technologies, such as reverse osmosis (RO) and evaporation systems, have been developed and adapted for leachate treatment. They are based on chemical and physical processes and are characterized by a high treatment capacity per unit of surface (m3/m2/h), compared to other conventional solutions, making them particularly suitable for use in existing landfill sites. Both of these advanced technologies return two main liquid fractions: 1) A permeate (for RO) or a distillate (for evaporation) in compliance with water quality standards; 2) A liquid fraction, named concentrate, in which the pollutants that need further treatment before disposal are concentrated. Depending on the leachate quality, on the technology adopted and on their operating parameters, the rate of concentrate can vary from about 1.5% up to 30% of the inlet leachate rate, hence reducing the dependency from off-site treatment (e.g. WWTP) and transport. Ushikoshi et al. (2002) showed that RO was able to remove pollutants from leachate with an efficiency up to > 99%. Similar performances have also been achieved by the evaporation system (Di Palma et al., 2002). Generally improving the removal/reduction of pollutants from wastewater by advanced technologies also leads to an increase in direct and indirect emissions due to higher energy and materials consumption. This generates a conflict of interest between two contradictory goals, indicating that more research is necessary for assessing the global benefits achievable from these technical solutions (Papa et al., 2016). The current literature shows that studies using both conventional and advanced technologies have focused mainly on the efficiency of contaminant removal without accounting for their global sustainability, also based on energy, materials and chemicals consumption. The aim of the present study was to use life cycle assessment (LCA) to compare different leachate treatment schemes based on conventional and advanced technologies for an existing landfill in order to identify the method with the lowest impact. In particular on-site treatment based mainly on RO and evaporation were compared with the most diffused off-site ones based on conventional WWTP. 2. Materials and methods The existing landfill considered in the present study is a sanitary landfill for non-hazardous waste (i.e. MSW and similar waste) located in central Italy and operating since 1995. The authorized disposal volume is 1,500,000 m3 with a global amount of 1,200,000 Mg of waste disposed of at the end of 2014. The landfill is equipped with landfill gas and leachate collections and treatment systems. Nowadays the landfill gas, about 4,000,000 Stm3/year with a methane content of about 5054%v/v, is exploited as fuel in a power plant consisting of 6 internal combustion engines with a total power output of 2,000 kVA. Due to economic incentives, the total amount of electricity produced is sold. This means that all the electrical consumption of the landfill area is purchased from the national grid. Two of the six engines operate in co-generation mode with heat recovery from the cooling jackets. This heat is delivered to the existing on-site leachate treatment system, based on evaporation facility, for feeding the second stage evaporator (see section 2.1). Starting from this base scenario (BS) currently used for treating the leachate, three other modified scenarios were set up and compared by a LCA approach. 2.1 BS The BS consisted of a mixed on-site and off-site leachate treatment scheme. On-site treatment was able to process 33% of the leachate generated (i.e. 45 m3/day). The other 67% was co-treated offsite together with civil sewage in an existing WWTP 170 km away. The on-site treatment consisted of an evaporation system (Fig. 1). The leachate underwent an initial stage of evaporation TC60000 (max 60 m3/day) in which a thermal resistance and a volumetric pump maintained temperature and pressure at 90°C and 70kPa, respectively. The concentrate was further processed in the second 2
evaporator RW3000 (max 3m3/day). From the heat supplied by the co-generators and by an ejector, temperature and pressure in the RW3000 were 70°C and 10kPa, respectively. The treatment capacity of the RW3000 does not allow exploitation of the full treatment capacity of the 1st evaporation stage TC60000. Both evaporated fractions were condensed and processed in a RO unit for final removal of possible trace pollutants. This RO unit consists of two stages of 5 modules each of polyamide membranes with a specific surface of 18 m2/m3/h and a maximum pressure of 41 bars. The permeate from this unit is further processed by activated carbon, ion exchange resins and pH adjustment before being discharged. The concentrate is then returned back to the leachate storage tank. The concentrate was then treated off-site in the WWTP. Electrical and thermal energy needs were: 70kWh/m3; 46kWh/m3 (co-generated). Chemicals and materials consumptions are reported in Table 1. 2.2 Modified scenarios MS1, MS2 and WWTP As a consequence of the continuous increase in the amount of leachate produced in the last years and of the need to reduce dependency on off-site treatment, the landfill manager decided to evaluate the possibility of expanding the current on-site treatment capacity. The lack of adequate space in the area of the landfill for implementing conventional solutions and the necessity of high pollutant removal efficiency led the manager to evaluate technical solutions based on advanced technologies such as RO and evaporation. Consequently different companies were asked for detailed technical solutions able to process on-site the whole amount of leachate generated (i.e. about 125 m3/day). The proposed solutions chosen were: 1) 1st modified scenario (MS1) (see section 2.2.1): Improvement of the existing on-site evaporation system treatment capacity by adding a new RO unit and a new RW3000; 2) 2nd modified scenario (MS2) (see section 2.2.2): Replacement of the existing on-site system with a new RO unit. Furthermore the possibility of co-processing off-site the whole amount of leachate with civil sewage in a WWTP was also analysed. 2.2.1 MS1 Considering that the existing co-generation plant had a surplus of thermal energy, in modified scenario 1 (MS1) (Fig. 1), the evaporation facility was improved by adding a second evaporator stage RW3000 working in parallel with the existing one. A new RO unit was also introduced before the TC60000 to maintain the inlet rate (i.e. concentrate from RO) ≤ 60 m3/day. The RO proposed is a commercial type made of one-stage polyamide/polysulphone with 36 spiral wound membranes, a specific surface area of 41 m2/m3/h and a maximum inlet pressure of 80 bars. The permeate and concentrate from the RO were 60% and 40% of the inlet volume of the leachate, respectively. The permeate was discharged, whereas the concentrate was processed in the improved evaporation plant. MS1 required 40 kWh/m3 of electricity, 18.5 kWh/m3 of heat and chemicals (Table 1). 2.2.2 MS2 In the second modified scenario (MS2) a new three-stage RO unit was installed (Fig. 1). The first stage consisted of 54 modules, a specific surface area of 97 m2/m3/h operating at a maximum pressure of 65 bars. The second stage consisted of 12 modules, a specific surface area of 39 m2/m3/h and the third stage consisted of 10 modules, and a specific surface area of 30 m2/m3/h, both operating at a maximum pressure of 60 bars. The concentrate was processed off-site in the same WWTP. This option required 8.5 kWh/ m3 of electricity and chemicals (Table 1). 2.2.3 WWTP The third modified scenario was the off-site co-treatment of the whole leachate with civil sewage in the WWTP. 2.3 LCA The LCA was performed according to the ILCD Handbook (EC, 2010), ISO 14040 (2006) and ISO 14044 (2006). Calculations were made using SimaPro 8.2 (Goedkoop et al., 2016). 2.3.1 Goal, scope and context situation 3
The aim of the present study was to compare different technologies for treating the leachate in a LCA perspective also accounting for the contribution of the main activities involved such as transport and off-site and on-site treatments. Capital goods were not accounted in the present study for lack of data. By the way life span of different technologies investigated can be considered the same making the error arising from this assumption quite negligible. This study was carried out at the request of the company managing the landfill and the results will consequently be useful in their decision-making process. In any case the final decision will also be based on economic, operating and maintenance aspects. The backgrounds were: leachate; energy; fuel and materials. Due to the presence of economic revenues for the electricity generated by the landfill gas recovery, the amount of electricity necessary for feeding the leachate treatment systems was completely purchased from the national grid. The Italian energetic mix was considered: 37% natural gas; 15% coal; 5.4% oil; 13% hydro; 5.5% photovoltaic; 4% wind; 4.5% bioenergy; 1.6% geothermal; 14% imports. The foregrounds were energy and emissions. The backgrounds were not influenced by the foregrounds. The boundaries of the system were expanded to take into account the multi-functionality of the processes. The context situation resulted A “general rule, average data” (EC, 2010). 2.3.2 Functional unit and life cycle inventory framework The functional unit was the treatment of 1 m3 of leachate also assumed as reference flow for the study. The life cycle inventory (LCI) framework was attributional. Due to the absence of direct experimental data, the quality of the water discharged was assumed to be the same as WWTP for all the scenarios (SM 1). 2.3.3 LCI of BS, MS1, MS2 and WWTP The inventory for the BS (Table 1) was built on the basis of the actual consumption of energy and materials. For MS1 and MS2, the materials and energy consumption were evaluated on the basis of the data reported by the plant builders, resulting in line with those for the BS and with those reported in the literature. Average market data available in Ecoinvent 3.0 (Wernet et al., 2016) were used for the LCI of the chemicals supplied. LCI of the WWTP was retrieved from Ecoinvent 3.0 (Wernet et al., 2016) for a Swiss facility of 71,100 population equivalent (SM 1). Both the technology adopted and the quality standards for pollutant removal were in accordance with those of the area considered in this study (Di Maria et al., 2016). Adjustment concerning energy and materials consumption for the WWTP was introduced on the basis of the CODin/CODdes ratio, where: CODin was the one for leachate and/or concentrate (Table 1); CODdes = 600 mg/L was the design one at the WWTP inlet (Wernet et al., 2016). 2.3.4 Selection of impact categories The ILCD 2011+ midpoint impact assessment method was used (EC, 2012). Impact categories were (SM 2): Global Warming Potential at 100 years (GWP); Ozone Depletion Potential (ODP); Human toxicity, non-cancer effects (HTnc); Human toxicity, cancer effects (HTc); Particulate matter (PM); Photochemical Ozone Formation (POF); Acidification (A); Eutrophication Terrestrial (ET); Fresh Water Eutrophication (FWE); Fresh water ecotoxicity (FWec); Water resource depletion (WRD); Mineral, fossil and renewable Resource Depletion (RD). Normalization factors of the EU 27 domestic extraction of resources and emissions per person with respect to the year 2010 were used to give an impression of which impact categories were most affected by the scenarios considered. 2.3.5 Uncertainty analysis All the values of the emissions considered in the inventories for the LCA study were affected by errors determined by several factors such as (Bjorklund, 2002): data inaccuracy and gaps; unrepresentative data; model uncertainty; uncertainty due to choices; spatial and temporal variability; variability between sources and objects; epistemological uncertainty; mistakes; estimation of uncertainty. These errors propagate through the model generating composite uncertainty that cannot be disregarded for assessing the reliability of the LCA outcomes (Lloyd and Ries, 2007). For this reason, the margin of error associated with the main impacts detected during the present study was assessed under the conditions specified in this paragraph. 4
Due to the independence assumed for the background from the foreground of the systems, only direct and indirect emissions generated by the different processes and activities were considered. In particular they were: indirect emissions due to electricity production; indirect emissions due to chemicals production; direct emissions to water; indirect emissions due to transport. A lognormal distribution was assumed for these data (Frischknecht et al., 2007). The associated variance was evaluated by the procedure of the pedigree matrix (Table 2) (Weidema and Wasnaes, 1996; Weidema, 1998) and by the basic uncertainty factor (b) based on expert judgments (SM 3) (Frischknecht et al., 2007). The confidence interval was 95%. Depending on the quality of the data available, a given score, from 1 to 5, was assigned to each indicator in the pedigree matrix of the process considered. On the basis of the score assigned, each indicator corresponded to a given uncertainty factor (i.e. 1=reliability uncertainty, 2=completeness uncertainty, 3=temporal correlation uncertainty, 4=geographical correlation uncertainty, 5=further technological correlation uncertainty). Once all these values had been determined, the variance ( 2 ) of each process was evaluated using Eq. (2). 6
2 e
ln( n )
n 1
2
(2)
3. Results and discussion 3.1 LCA Normalization showed that the impact categories most affected by the scenarios were HTnc, HTc, FWE, FWec and RD (Fig. 2a), whereas the other impact categories had significantly lower values (Fig. 2b). The incidence of leachate treatment on ecotoxicity and human toxicity was also reported by Damgaard et al. (2011) in an LCA and economic analysis of landfill leachate and gas technologies. Similarly Abduli et al. (2011) found that landfill emissions affected human health to a greater degree with respect to other impacts even when gaseous and leachate treatments were used. With the exception of RD and ODP, there were higher impacts for the WWTP and for the BS in which the off-site co-treatment with civil sewage in the wastewater treatment plant was largely exploited. The large amount of energy and chemicals required by the evaporation system caused the higher value for RD for MS1 and BS (Fig. 2a), respectively. In any case there were lower impacts for POF and TE for MS2 even if they were very similar to those of MS1 (Fig. 2b). The impact characterization reported in Fig. 3 shows the incidence of the main activities (i.e. transport, on-site treatment, off-site treatment of leachate and concentrate in WWTP) involved in the four scenarios in determining the values of the impact categories. For BS, the values of HTnc, HTc and FWE were largely due to the off-site co-treatment of both the leachate and concentrate with civil sewage in the wastewater treatment plant, whereas emission from transport played a minor role with the exception of HTc for the WWTP scenario. On the other hand the contribution due to transport was more relevant for all the other impact categories except for the MS1 scenario. The values of the impact categories of MS1 were practically due to the direct and indirect emissions generated by the on-site treatment and by the off-site co-treatment of the concentrate in the wastewater treatment plant. In this case the contribution due to transport was always negligible. Differently, as a consequence of the larger amount of concentrate discharged by the RO (Table 1), the incidence of transport for the MS2 scenario played a more relevant role in determining the values of almost all the impact categories. Finally, for the WWTP scenario, with the exception of HTnc, HTc and FWE, the contribution due to transport in determining the values of the other impact categories was from 30% up to 80%. The incidence of emissions from transport was the reason for the higher values for RD, GWP, ODP, PM, POF, A and ET for the WWTP scenario compared to that of MS2. Higher values assumed by HTnc, HTc and FWE for the WWTP scenario compared to MS2 were mainly a consequence of the 5
higher direct and indirect emissions resulting from co-treatment of leachate with civil sewage in the wastewater treatment plant. Likewise the higher direct and indirect emissions for the evaporation system caused higher impact for MS1 with respect to MS2. The combined effect of the evaporation process and of the off-site cotreatment with civil sewage in the wastewater treatment plant and the respective transport caused the high impact for almost all the impact categories for the BS. In general these findings demonstrate that transport influences to a large extent the emissions associated with the WWTP scenario, even if direct and indirect emissions from MS2 were in any case lower. The positive effect of advanced wastewater treatments, in particular on human health, was also reported by Papa et al. (2016), who reported that the impact on human health can be decreased up to >25% if the conventional activated sludge process, typical of WWTP, is integrated with advanced treatments such as ozonation and powder activated carbon. Similarly, in comparing different options for managing black water source-separation sanitation systems, Thibodeau et al. (2014) reported that RO was able to reduce the impact on human health up to 3 times compared to other conventional and non-conventional solutions even if the costs were higher. RO was also reported by Renou et al. (2008) as the most promising technology for leachate treatment. On the other hand different results were reported by Menard et al. (2004) in comparing an engineered landfill with an aerated pond for leachate treatment, with a bioreactor landfill with leachate recirculation in the disposed waste body. Their main findings showed that leachate treatment affected only ozone depletion and eutrophication potentials with an incidence of 16% and 9%, respectively, on the whole impact associated with these landfills. A negligible contribution of leachate emissions was also reported by Kirkeby et al. (2004) in a LCA modelling of the impact of solid waste landfilling. Considering that human health and fresh water quality were among the categories most affected and are of particular concern, in order to better interpret the results reported above, an uncertainty analysis was performed for assessing the error associated with the values of these impact categories. 3.2 Uncertainty The emissions from transport influencing to a large extent the impact categories most affected (HTc, HTnc and Fwec) were mainly by the heavy metals such as CrVI and Zn. According to Frischknecht et al. (2007) they were characterized by the highest basic uncertainty values of 5.00 SM 3), influencing the final values of the uncertainty reported in SM 4. This showed that the process and activities characterized by the lowest uncertainty values of the respective emissions were electricity and chemicals production. Higher uncertainty values of 1.52 and 5.00 were associated with pollutant emissions to water and with emissions due to transport, respectively. These values were used determine the composite uncertainty associated with the impact categories most affected for each scenario. For doing this the share of the contribution of the emissions of the processes and activities considered in determining HTc, HTnc, FWE and FWec were determined (Table 3). According to Eq. (2) these shares were used for combining the uncertainties reported in SM 4. The main results showed that higher uncertainties were associated with the impact categories of the scenarios in which the shares due to transport and emissions to water were higher, that is, in decreasing order WWTP, BS and MS2. In particular pollutants emitted to water played a prominent role in determining the uncertainties of HTnc, HTc and FWE, whereas transport was prevalent in determining FWec. There were lower uncertainty values for HTnc, HTc, FWE and Fwec, ranging from 1.05 to 1.19, for MS1. In this case the higher share was associated with the emissions due to HCl production, from 35.4% up to 64.0% affecting to a large extent the on-site emissions (Fig. 3). 4. Conclusions More effective treatment of the leachate is a key factor for improving the environmental sustainability of landfills and consequently of the entire waste management system. Efficient processing of leachate requires appropriate technologies able to satisfy different aspects, such as the continuous change in its composition caused by chemicals and physical changes occurring inside 6
the disposed waste during the years. Consistent with the aim of sanitation, the life cycle study confirmed that leachate treatment is an activity that affects mainly human health and freshwater quality. The study revealed that the activities and processes affecting these impact categories to a larger extent were by both indirect and direct emissions due to electricity consumption, chemicals consumption, emissions to water and transport. Those related to on-site reverse osmosis treatment and conventional off-site co-treatment with civil sewage in the wastewater treatment plant were largely affected by the emissions due to transport. On the other hand the impacts associated to evaporation treatment resulted significantly influenced by the chemicals and energy consumption. The uncertainty analysis revealed that both reverse osmosis and off-site co-treatment in wastewater treatment plants had the highest values of the composite uncertainties able to modify significantly the results based on the average values of the impact categories. The high level of uncertainty for this last technology was highly influenced by that related to the pollutants emitted to water and the emissions from transport.
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Fig. 1. Scheme of thhe on-site trreatment syystem for thee Base Scen nario (BS), ffor the 1st Modified M nd S Scenario (M MS1) and forr the 2 Mo odified Scen nario (MS 22).
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0,006 BS MS1 MS2 WWTP
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Fig. 2. Normalized impacts most affected (a) and less affected (b) by the different scenarios per m3 of leachate. 3,5x10-6
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0,20 0,18 0,16 POF (kg NMVOC eq)
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Fig. 33. Impact chharacterizattion and conntribution of o the main activities a peer m3 of leacchate.
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Table 1 Main input parameters for the life cycle inventory of the on-site treatment systems for 1 m3 of leachate. Parameter Unit Base Modified Modified Scenario Scenario 1 Scenario 2 Outlet 0.755 0.9 0.66 Permeate m3 3 0.015 0.03 0.30 Concentrate m 232 232 23.4 COD Conc. g/l + 3.00 3.00 9.00 NH4 Conc. g/kg Inputs from technosphere (materials/energy) 18.4 Heat kWht/m3 46 3 40.0 8.50 Electricity kWhe/m 70.0 14 10.2 HCl kg/m3 0.13 0.11 5.88 H2SO4 kg/m3 0.17/2.23 0.084/1.116 Antifoam (Si/H2O) kg/m3 Acid product for R.O. 1E-3/1E-3 0.045/0.045 0.025/0.025 kg/m3 (HNO3/H2O) 0.08 0.067 NaOH kg/m3 3 0.04/0.23 0.036/0.204 Antibacterial (CH2NS2 /H2O) kg/m Alkaline for R.O. 4.8E-3/1.6E0.053/0.0177/ 0.0372/0.0124/ kg/m3 3/8E-4/8.8E-3 8.85E-3/0.0974 6.2E-3/0.0682 (KOH/NaOH/C28H22/H2O) Table 2 Pedigree matrix with five data quality indicators and associated uncertainty factors. 1 Verified data based on measurements 1=1.00
2 Verified data partly based on assumptions or non-verified data based on measurements 1=1.05
Score 3 Non-verified data partly based on quantified estimates 1=1.10
4 Qualified estimate (e.g. by industrial experts) 1=1.20
5 Non-qualified estimate 1=1.50
Completeness
Representative data from all sites relevant for the market considered, over an adequate period to even out normal fluctuations 2=1.00
Representative data from >50% of the sites relevant for the market considered, over an adequate period to even out normal fluctuations 2=1.02
Representative data from only some sites (<<50%) relevant for the market considered or > 50% of sites but from shorter periods 2=1.05
Representative data from only one site relevant for the market considered or some sites but from shorter periods 2=1.10
Representativeness unknown or data from a small number of sites and from shorter periods 2=1.20
Temporal correlation
Less than 3 years of difference to the time period of the dataset 3=1.00
Less than 6 years difference to the time period of the dataset 3=1.03
Less than 10 years difference to the time period of the dataset 3=1.10
Less than 15 years difference to the time period of the dataset 3=1.20
Age of data unknown or more than 15 years of difference to the period of the dataset 3=1.50
Geographical correlation
Data from area under study 4=1.00
Average data from larger area in which the area under study is included 4=1.01
Data from area with similar production conditions 4=1.02
Data from area with slightly similar production conditions 4=1.03
Data from unknown area of or distinctly different area 4=1.10
Further technological correlation
Data from enterprises, processes and materials under study 5=1.00
Data from process and materials under study but from different enterprises 5=1.02
Data from processes and materials under study but from different technology 5=1.05
Data on related processes or materials 5=1.10
Data on related processes on laboratory scale or from different technologies 5=1.20
Quality indicator Reliability
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Table 3 Contribution of the main processes and emissions to the determination of the values of HTcn, HTc, FWE and FWec and resulting composite uncertainty. Process and activities Scenario Impact cat. Electricity HCl Pollutants H2SO4 Transport Other (%) (%) emitted (%) (%) (%) to water (%) 12.3 8.60 HTnc 3.30 10.0 65.7 20.1 1.18 HTc 10.9 15.3 52.5 BS 6.74 0.61 FWE 11.3 15.3 66.1 40.4 2.26 FWec 9.31 20.0 28.1 20.3 35.4 40.3 1.52 2.5 HTnc 32.4 59.3 4.47 1.50 2.36 HTc MS1 33.8 54.8 7.05 0.51 3.87 FWE 23.4 64.0 1.41 2.57 8.57 FWec 9.86 67.7 12.9 8.63 9.86 HTnc 21.4 45.7 15.2 16.1 21.4 HTc MS2 33.2 47.2 12.9 5.11 33.2 FWE 12.8 30.3 17.8 37.7 12.8 FWec 0.08 85.4 14.3 0.08 HTnc 0.29 72.3 27.4 0.29 HTc WWTP 0.3 90.5 9.18 0.30 FWE 0.12 41.4 58.5 0.12 FWec
12
2 1.40 1.48 1.35 1.94 1.19 1.05 1.05 1.06 1.37 1.38 1.24 1.86 1.53 1.71 1.50 2.60
References Abduli, M.A., Naghib, A., Yonesi, M., Akbari, A. 2011. Life cycle assessment (LCA) of solid waste management strategies in Tehran: landfill and composting plus landfill. Environ. Monit. Assess. 178,487-498. Barlaz, M.A., Chanton, J.P., Green, R.B., 2009. Controls on landfill gas collection efficiency: instantaneous and lifetime performances. J. Air Waste Manag. Assoc. 59, 1399–1404. Beylot, A., Villeneuve, J., Bellenfant, G., 2013. Life cycle assessment of landfill biogas management: sensitivity to diffuse and combustion air emissions. Waste Manage. 33, 401– 411. Bjorklund, A,E, 2002, Survey of Approaches to Improve Reliability in LCA. Int. J. LCA 7, 64-72. Camba, A., Gonzalez-Garcia, S., Bala, A., Fullana-i-Palmer, P., Moreira, M.T., Feijoo, G. 2014. Modelling the leachate flow and aggregated emissions from municipal waste landfills under life cycle thinking in the Oceanic regions of the Iberian Peninsula. J. Clean Prod. 67,98-106. Chen, Y.C., Lo, S.L. 2016. Evaluation of greenhouse gas emissions for several municipal solid waste management strategies. J. Clean Prod. 113,606-612. Damgaad, A., Manfredi, S., Merrid, H., Stensoe, S., Christensen, T. 2011. LCA and economic evaluation of landfill leachate and gas technologies. Waste Manage. 31,1532-1541. Di Maria, F, Sordi, A., Micale, C. 2013a. Experimental and life cycle assessment analysis of gas emission from mechanically biologically treated waste in a landfill with energy recovery. Waste Manage. 33, 2557-2567. Di Maria, F., Micale, C., Sordi, A., Cirulli, G., 2013b. Leachate purification of mechanically sorted organic fraction waste in a simulated bioreactor landfill. Waste Manage. Res. 31, 1070– 1074. Di Maria, F., Micale, C. 2014. A holistic life cycle analysis of waste management scenarios at increasing source segregation intensities. Waste Manage. 34, 2382-2392. Di Maria, F., Micale, C., Contini, S., Morettini, E. 2016. Impact of biological treatment of biowaste for nutrients, energy and bio-methane recovery in a life cycle perspective. Waste Manage. 52, 86-95. Di Palma L, Ferrantelli P, Merli C, Petrucci E. 2002. Treatment of industrial landfill leachate by means of evaporation and reverse osmosis. Waste Manage. 22,951-955. EC, 2010. European Commission – Joint Research Centre – Institute for Environment and Sustainability. 2010. International Reference Life Cycle Data System (ILCD) Handbook – General guide for Life Cycle Assessment – Detailed guidance. First edition March 2010. EUR 24708 EN. Publications Office of the European Union. Luxembourg, LU. EC- European Commission. 2012. Characterization factors of the ILCD Recommended Life Cycle Impact Assessment methods, Database and Supporting Information, First edition, Joint Research Centre, Institute for Environment and Sustainability, Publications Office of the European Union, Luxembourg. Frischknecht, R., Jungbluth, N., Althaus, H.J., Doka, G., Heck, T., Hellweg, S., Hischier, R., Nemecek, T., Rebitzer, G., Spielmann, M., Wernet, G. 2007. Overview and Methodology. ecoinvent report No. 1. Swiss Centre for Life Cycle Inventories, Dübendorf, 2007. Goedkoop, M., Oele, M., Leijting, J., Ponsioen, T., Meijer, E. 2016. Introduction to LCA with SimaPro. Report version 5.2. Available in: http://www.presustainability.com/download/SimaPro8IntroductionToLCA.pdf. ISO 14040, 2006. Environmental Management: Life Cycle Assessment, Principles and Guidelines. International Organization of Standardization, Geneva 2006. ISO 14040, 2006. Environmental Management: Life Cycle Assessment – Requirements and guidelines. International Organization of Standardization, Geneva 2006. ISPRA. 2015. Rapporto Rifiuti urbani. Edizione 2015. Rapporto 230/2015. ISBN: 978-88-4480740-5. 13
Kirkeby, J.T., Birigisdottir, H., Bhander, G.S., Hauschild, M., Christensen T.H. 2007. Modelling of environmental impacts of solid waste landfilling within the life-cycle analysis program EASEWASTE. Waste Manage. 27,961-870. Lloyd, M.S., Ries, R. 2007. Characterizing, Propagating, and Analyzing Uncertainty in Life Cycle Assessment. J. Ind. Ecol. 11, 161-179. Menard, J.F., Lesage, P., Deschenes, L., Samson, R. 2004. Comparative Life Cycle Assessment of Two Landfill Technologies for the Treatment of Municipal Solid Waste. Int. J. LCA 9,371378. Papa, M., Alfonsin, C., Moreira, M.T., Bertanza, G. 2016. Ranking wastewater treatment trains based on their impacts and benefits on human health: a “Biological Assay and Disease” approach. J. Clean Prod. 113,311-317. Renou, S, Givaudan JG, Paoulain S, Dirassouyan F, Moulin P. 2008. Landfill Leachate treatment. Review and Opportunity. J. Hazard. Mate. 150,468-493. Slack, RJ, Gronow, JR, Voulvoulis, N. 2005. Household Hazardous Waste in Municipal landfills contaminants in leachate. Sci. Total Environ. 337, 119-137. Schiopu, AM, Gravilescu, M. 2010. Options for the treatment and Management of Municipal landfill Leachate: Common and Specific Issues. Clean - Soil Air Water 38,1101-1110. Thibodeau, C., Frederic, M., Glaus, M. 2014. Comparison of development scenarios of black water source-separation sanitation systems using life cycle assessment and environmental life cycle costing. Resour. Conserv. Recy. 92,38-54. Ushikoshi K, Kobayashi T, Uematsu K, Toji A, Kojima D, Matsumoto K. 2002. Leachate treatment by the reverse osmosis system. Desalination 150,121-190. Weidema, B.P., Wesnaes, M.S. 1996. Data quality management for life cycle inventories – an example of using data quality indicators. J. Clea. Prod. 4, 167-174. Weidema, B.P. 1998. Multi-User Test of the Data Quality Matrix for Product Life Cycle Inventory. Int. J.LCA 3, 259-265. Wernet, G., Bauer, C., Steubing, B., Reinhard, J., Moreno-Ruiz, E., and Weidema, B. 2016. The ecoinvent database version 3 (part I): overview and methodology. The International Journal of Life Cycle Assessment, [online] 21(9), pp.1218–1230. Available in: http://link.springer.com/10.1007/s11367-016-1087-8.
14
Supporting material (SM) SM 1 Main input parameters for the life the wastewater treatment plant. Parameter Value Energy Heat other NG 0.1087 Elec. low Volt. 0.2057 Emissions to air NOX 6.9E-4 Lead 1.75E-10 CO2, biogenic 0.19 NMVOC 2.28E-6 SO2 8.86E-4 1.03E-4 N2O Emissions to water COD 0.03 Nitrite 6.44E-4 Lead 9.49E-7 Lead, long 3.36E-7 Sulphate, long 2.37E-3 Chloride 0.04 Phosphate, river 2.7E-3 8.56E-5 BOD5, long Ammonium, ion 0.011 Nitrogen, river 4.9E-4 Emissions to soil Sulphur 5.95E-4 Aluminium 5.7E-4 Carbon 6.7E-3
cycle inventory for the treatment of 1 m3 of domestic sewage in Unit
Parameter
Value
Unit
MJ kWh
Heat NG Elec. High Volt.
0.00630 0.01864
MJ kWh
kg kg kg kg kg kg
CH4, biogenic Aluminium Phosphorus CO, biogenic Chromium Ammonia
5.02E-4 1.41E-6 1.33E-6 1.7E-4 2.73E-13 3.56E-4
kg kg kg kg kg kg
kg kg kg kg kg kg kg kg kg kg
Phosphate TOC TOC, river Phosphate, long Sulphate COD, long BOD5, river Nitrate, long Nitrate, river
1.46E-5 1.03E-4 7.3E-3 1.56E-4 0.1449 2.6E-4 9.82E-3 5.13E-5 0.048
kg kg kg kg kg kg kg kg kg
kg kg kg
Chromium Lead
2.33E-6 2.97E-6
kg kg
SM 2 Impact categories and normalization factors. Impact category
Unit
Global warming potential – GWP Ozone depletion layer – ODP Human toxicity, non-cancer effects – HTnc Human toxicity, cancer effects – HTc Particulate matter – PM Photochemical ozone formation – POF Acidification – A Eutrophication terrestrial – ET Fresh water eutrophication – FWE Fresh water ecotoxicity – FWec Water resource depletion – WRD Min., foss. & ren. Res. Depletion - RD
kgCO2 eq. kgCFC-11 eq. CTUh CTUh kgPM2.5 eq. kgNMVOC eq. molc H+ eq. molc N eq. kg P eq. CTUe m3 water eq. kg Sb eq.
Normaliz ation factors 1.10E- 04 46.3 1876 27100 2.63E -01 3.15E -02 2.11E -02 5.68E -03 6.76E -01 1.14E -04 1.23E -02 9.9
Unit kgCO2 eq./a. kgCFC-11 eq./a. CTUh CTUh kgPM2.5 eq./a. kgNMVOC eq./a. molc H+ eq./a. molc N eq./a. kg P eq./a. CTUe/a. m3 water eq./a. kg Sb eq./a. 15
SM 3 Basic uncertainty factor used for variance evaluation. Process and activities Electricity production Chemicals production Pollutants emitted to water Transport emissions
b 1.05 1.05 1.50 5.00
SM 4 Values assigned to uncertainty factors and resulting variance for the main process and activities emissions. Process and activities
21
22
23
24
25
2
Electricity production Chemicals production Pollutants emitted to water Transport emissions
1.00 1.00 1.00 1.00
1.00 1.00 1.10 1.00
1.00 1.00 1.00 1.00
1.01 1.01 1.02 1.00
1.00 1.02 1.02 1.02
1.05 1.06 1.52 5.00
16
ENER RGY
C CHEMICALS
EVAPORA ATION
R REVERSE OS SMOSIS TREATE ED WASTEW WATER
LEACHATE E EMISSIO ONS W.W.T.P.
>sustainability of conventional and advanced treatment of leachate was assessed by LCA >most affected impacts were human health and water ecotoxicity >Reverse osmosis and evaporation as to be preferred to conventional WWTP >Evaporation system impact was affected largely by energy consumption
1
PII: DOI: Reference:
S2352-1864(17)30015-9 https://doi.org/10.1016/j.eti.2017.09.002 ETI 153
To appear in:
Environmental Technology & Innovation
Received date : 11 January 2017 Revised date : 18 August 2017 Accepted date : 12 September 2017 Please cite this article as: Di Maria F., Sisani F., A life cycle assessment of conventional technologies for landfill leachate treatment. Environmental Technology & Innovation (2017), https://doi.org/10.1016/j.eti.2017.09.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A life cycle assessment of conventional technologies for landfill leachate treatment *
Francesco Di Maria1,*,**, Federico Sisani* LAR Laboratory – Dipartimento di Ingegneria, University of Perugia Via G. Duranti 93, 06125 Perugia, Italy ** CIMIS – via G. Duranti 67, 06125 Perugia, Italy
Abstract Landfilling of municipal solid waste is still one of the most diffused practices worldwide, generating long-term heavily polluted gaseous and liquid (i.e. leachate) emissions, causing environmental and especially human health concerns. Improvement of the methods for treating these emissions, particularly the leachate, is mandatory for increasing the sustainability of the entire waste management system. For this aim the environmental impact of conventional off-site technologies, based on co-treatment of leachate with civil sewage in wastewater treatment plants, was compared with advanced on-site technologies based on reverse osmosis and evaporation in a life cycle perspective. The model was built using mainly experimental and technical data from fullscale facilities. Human toxicity and freshwater ecotoxicity were the impacts most affected by the scenarios analysed. Average impacts were higher for the conventional off-site co-treatment in wastewater treatment plants, whereas impacts were lower for the advanced on-site treatment based on reverse osmosis. This result was largely influenced by the high incidence due to leachate transport for the off-site management scheme. Due to the high consumption of energy (i.e. 40kWh/m3 electricity and 18.5 kWh/m3 thermal heat) and chemicals (mainly HCl) the impact for the on-site evaporation system was always higher than for reverse osmosis and in some cases also for the conventional co-treatment with civil sewage sludge. The uncertainty analysis showed that pollutant emissions to water and emissions due to transport were affected by the highest errors, influencing in a major way the uncertainty of the impacts considered. Keywords: Evaporation, leachate, life cycle analysis, reverse osmosis, wastewater treatment plant. 1. Introduction Landfill disposal is still one of the most diffused options worldwide for the management of municipal solid waste (MSW) (Camba et a., 2014). As an example, at the EU28 level, 31% of the whole MSW (i.e. about 74 Mtonnes/year) is directly landfilled (ISPRA, 2015). Degradation of MSW is a long-term event, generating heavily polluted gases (i.e. landfill gas) (Barlaz et al., 2009; Chen and Lo, 2016; Di Maria et al., 2013a) and liquids (i.e. leachate) (Camba et al., 2014; Di Maria et al. 2013b), which are the main source of the environmental impact associated with this practice. Therefore it is of prime importance to identify more sustainable technologies for their treatment in order to reduce the environmental concerns of the entire MSW management system. In particular leachate can be considered a triphasic system with the characteristics of a heavily polluted wastewater (Schiopu and Graviliescu, 2010; Slack et al., 2005), entailing an important threat to human health, soil, and surface and ground water. The most widespread options for leachate treatment can be classified as off-site and on-site treatments, which can also be referred to as conventional and advanced treatments, respectively (Renou et al., 2008). Among the conventional ones, leachate transfer for combined treatment with civil sewage in wastewater treatment plants (WWTP) is the most diffused (Wernet et al., 2016). However, due to the continuously more rigorous discharge standards and the ageing of landfill sites with more and more stabilized leachates, the capability of WWTP to remove some trace pollutants is limited (Papa et al., 2016). Furthermore off-site treatment costs are affected by both transport and 1
Corresponding author email: [email protected]
1
disposal fees that can be influenced by market fluctuations, which are also an important key factor in the economic risk for the landfill manager. For these reasons advanced technologies, such as reverse osmosis (RO) and evaporation systems, have been developed and adapted for leachate treatment. They are based on chemical and physical processes and are characterized by a high treatment capacity per unit of surface (m3/m2/h), compared to other conventional solutions, making them particularly suitable for use in existing landfill sites. Both of these advanced technologies return two main liquid fractions: 1) A permeate (for RO) or a distillate (for evaporation) in compliance with water quality standards; 2) A liquid fraction, named concentrate, in which the pollutants that need further treatment before disposal are concentrated. Depending on the leachate quality, on the technology adopted and on their operating parameters, the rate of concentrate can vary from about 1.5% up to 30% of the inlet leachate rate, hence reducing the dependency from off-site treatment (e.g. WWTP) and transport. Ushikoshi et al. (2002) showed that RO was able to remove pollutants from leachate with an efficiency up to > 99%. Similar performances have also been achieved by the evaporation system (Di Palma et al., 2002). Generally improving the removal/reduction of pollutants from wastewater by advanced technologies also leads to an increase in direct and indirect emissions due to higher energy and materials consumption. This generates a conflict of interest between two contradictory goals, indicating that more research is necessary for assessing the global benefits achievable from these technical solutions (Papa et al., 2016). The current literature shows that studies using both conventional and advanced technologies have focused mainly on the efficiency of contaminant removal without accounting for their global sustainability, also based on energy, materials and chemicals consumption. The aim of the present study was to use life cycle assessment (LCA) to compare different leachate treatment schemes based on conventional and advanced technologies for an existing landfill in order to identify the method with the lowest impact. In particular on-site treatment based mainly on RO and evaporation were compared with the most diffused off-site ones based on conventional WWTP. 2. Materials and methods The existing landfill considered in the present study is a sanitary landfill for non-hazardous waste (i.e. MSW and similar waste) located in central Italy and operating since 1995. The authorized disposal volume is 1,500,000 m3 with a global amount of 1,200,000 Mg of waste disposed of at the end of 2014. The landfill is equipped with landfill gas and leachate collections and treatment systems. Nowadays the landfill gas, about 4,000,000 Stm3/year with a methane content of about 5054%v/v, is exploited as fuel in a power plant consisting of 6 internal combustion engines with a total power output of 2,000 kVA. Due to economic incentives, the total amount of electricity produced is sold. This means that all the electrical consumption of the landfill area is purchased from the national grid. Two of the six engines operate in co-generation mode with heat recovery from the cooling jackets. This heat is delivered to the existing on-site leachate treatment system, based on evaporation facility, for feeding the second stage evaporator (see section 2.1). Starting from this base scenario (BS) currently used for treating the leachate, three other modified scenarios were set up and compared by a LCA approach. 2.1 BS The BS consisted of a mixed on-site and off-site leachate treatment scheme. On-site treatment was able to process 33% of the leachate generated (i.e. 45 m3/day). The other 67% was co-treated offsite together with civil sewage in an existing WWTP 170 km away. The on-site treatment consisted of an evaporation system (Fig. 1). The leachate underwent an initial stage of evaporation TC60000 (max 60 m3/day) in which a thermal resistance and a volumetric pump maintained temperature and pressure at 90°C and 70kPa, respectively. The concentrate was further processed in the second 2
evaporator RW3000 (max 3m3/day). From the heat supplied by the co-generators and by an ejector, temperature and pressure in the RW3000 were 70°C and 10kPa, respectively. The treatment capacity of the RW3000 does not allow exploitation of the full treatment capacity of the 1st evaporation stage TC60000. Both evaporated fractions were condensed and processed in a RO unit for final removal of possible trace pollutants. This RO unit consists of two stages of 5 modules each of polyamide membranes with a specific surface of 18 m2/m3/h and a maximum pressure of 41 bars. The permeate from this unit is further processed by activated carbon, ion exchange resins and pH adjustment before being discharged. The concentrate is then returned back to the leachate storage tank. The concentrate was then treated off-site in the WWTP. Electrical and thermal energy needs were: 70kWh/m3; 46kWh/m3 (co-generated). Chemicals and materials consumptions are reported in Table 1. 2.2 Modified scenarios MS1, MS2 and WWTP As a consequence of the continuous increase in the amount of leachate produced in the last years and of the need to reduce dependency on off-site treatment, the landfill manager decided to evaluate the possibility of expanding the current on-site treatment capacity. The lack of adequate space in the area of the landfill for implementing conventional solutions and the necessity of high pollutant removal efficiency led the manager to evaluate technical solutions based on advanced technologies such as RO and evaporation. Consequently different companies were asked for detailed technical solutions able to process on-site the whole amount of leachate generated (i.e. about 125 m3/day). The proposed solutions chosen were: 1) 1st modified scenario (MS1) (see section 2.2.1): Improvement of the existing on-site evaporation system treatment capacity by adding a new RO unit and a new RW3000; 2) 2nd modified scenario (MS2) (see section 2.2.2): Replacement of the existing on-site system with a new RO unit. Furthermore the possibility of co-processing off-site the whole amount of leachate with civil sewage in a WWTP was also analysed. 2.2.1 MS1 Considering that the existing co-generation plant had a surplus of thermal energy, in modified scenario 1 (MS1) (Fig. 1), the evaporation facility was improved by adding a second evaporator stage RW3000 working in parallel with the existing one. A new RO unit was also introduced before the TC60000 to maintain the inlet rate (i.e. concentrate from RO) ≤ 60 m3/day. The RO proposed is a commercial type made of one-stage polyamide/polysulphone with 36 spiral wound membranes, a specific surface area of 41 m2/m3/h and a maximum inlet pressure of 80 bars. The permeate and concentrate from the RO were 60% and 40% of the inlet volume of the leachate, respectively. The permeate was discharged, whereas the concentrate was processed in the improved evaporation plant. MS1 required 40 kWh/m3 of electricity, 18.5 kWh/m3 of heat and chemicals (Table 1). 2.2.2 MS2 In the second modified scenario (MS2) a new three-stage RO unit was installed (Fig. 1). The first stage consisted of 54 modules, a specific surface area of 97 m2/m3/h operating at a maximum pressure of 65 bars. The second stage consisted of 12 modules, a specific surface area of 39 m2/m3/h and the third stage consisted of 10 modules, and a specific surface area of 30 m2/m3/h, both operating at a maximum pressure of 60 bars. The concentrate was processed off-site in the same WWTP. This option required 8.5 kWh/ m3 of electricity and chemicals (Table 1). 2.2.3 WWTP The third modified scenario was the off-site co-treatment of the whole leachate with civil sewage in the WWTP. 2.3 LCA The LCA was performed according to the ILCD Handbook (EC, 2010), ISO 14040 (2006) and ISO 14044 (2006). Calculations were made using SimaPro 8.2 (Goedkoop et al., 2016). 2.3.1 Goal, scope and context situation 3
The aim of the present study was to compare different technologies for treating the leachate in a LCA perspective also accounting for the contribution of the main activities involved such as transport and off-site and on-site treatments. Capital goods were not accounted in the present study for lack of data. By the way life span of different technologies investigated can be considered the same making the error arising from this assumption quite negligible. This study was carried out at the request of the company managing the landfill and the results will consequently be useful in their decision-making process. In any case the final decision will also be based on economic, operating and maintenance aspects. The backgrounds were: leachate; energy; fuel and materials. Due to the presence of economic revenues for the electricity generated by the landfill gas recovery, the amount of electricity necessary for feeding the leachate treatment systems was completely purchased from the national grid. The Italian energetic mix was considered: 37% natural gas; 15% coal; 5.4% oil; 13% hydro; 5.5% photovoltaic; 4% wind; 4.5% bioenergy; 1.6% geothermal; 14% imports. The foregrounds were energy and emissions. The backgrounds were not influenced by the foregrounds. The boundaries of the system were expanded to take into account the multi-functionality of the processes. The context situation resulted A “general rule, average data” (EC, 2010). 2.3.2 Functional unit and life cycle inventory framework The functional unit was the treatment of 1 m3 of leachate also assumed as reference flow for the study. The life cycle inventory (LCI) framework was attributional. Due to the absence of direct experimental data, the quality of the water discharged was assumed to be the same as WWTP for all the scenarios (SM 1). 2.3.3 LCI of BS, MS1, MS2 and WWTP The inventory for the BS (Table 1) was built on the basis of the actual consumption of energy and materials. For MS1 and MS2, the materials and energy consumption were evaluated on the basis of the data reported by the plant builders, resulting in line with those for the BS and with those reported in the literature. Average market data available in Ecoinvent 3.0 (Wernet et al., 2016) were used for the LCI of the chemicals supplied. LCI of the WWTP was retrieved from Ecoinvent 3.0 (Wernet et al., 2016) for a Swiss facility of 71,100 population equivalent (SM 1). Both the technology adopted and the quality standards for pollutant removal were in accordance with those of the area considered in this study (Di Maria et al., 2016). Adjustment concerning energy and materials consumption for the WWTP was introduced on the basis of the CODin/CODdes ratio, where: CODin was the one for leachate and/or concentrate (Table 1); CODdes = 600 mg/L was the design one at the WWTP inlet (Wernet et al., 2016). 2.3.4 Selection of impact categories The ILCD 2011+ midpoint impact assessment method was used (EC, 2012). Impact categories were (SM 2): Global Warming Potential at 100 years (GWP); Ozone Depletion Potential (ODP); Human toxicity, non-cancer effects (HTnc); Human toxicity, cancer effects (HTc); Particulate matter (PM); Photochemical Ozone Formation (POF); Acidification (A); Eutrophication Terrestrial (ET); Fresh Water Eutrophication (FWE); Fresh water ecotoxicity (FWec); Water resource depletion (WRD); Mineral, fossil and renewable Resource Depletion (RD). Normalization factors of the EU 27 domestic extraction of resources and emissions per person with respect to the year 2010 were used to give an impression of which impact categories were most affected by the scenarios considered. 2.3.5 Uncertainty analysis All the values of the emissions considered in the inventories for the LCA study were affected by errors determined by several factors such as (Bjorklund, 2002): data inaccuracy and gaps; unrepresentative data; model uncertainty; uncertainty due to choices; spatial and temporal variability; variability between sources and objects; epistemological uncertainty; mistakes; estimation of uncertainty. These errors propagate through the model generating composite uncertainty that cannot be disregarded for assessing the reliability of the LCA outcomes (Lloyd and Ries, 2007). For this reason, the margin of error associated with the main impacts detected during the present study was assessed under the conditions specified in this paragraph. 4
Due to the independence assumed for the background from the foreground of the systems, only direct and indirect emissions generated by the different processes and activities were considered. In particular they were: indirect emissions due to electricity production; indirect emissions due to chemicals production; direct emissions to water; indirect emissions due to transport. A lognormal distribution was assumed for these data (Frischknecht et al., 2007). The associated variance was evaluated by the procedure of the pedigree matrix (Table 2) (Weidema and Wasnaes, 1996; Weidema, 1998) and by the basic uncertainty factor (b) based on expert judgments (SM 3) (Frischknecht et al., 2007). The confidence interval was 95%. Depending on the quality of the data available, a given score, from 1 to 5, was assigned to each indicator in the pedigree matrix of the process considered. On the basis of the score assigned, each indicator corresponded to a given uncertainty factor (i.e. 1=reliability uncertainty, 2=completeness uncertainty, 3=temporal correlation uncertainty, 4=geographical correlation uncertainty, 5=further technological correlation uncertainty). Once all these values had been determined, the variance ( 2 ) of each process was evaluated using Eq. (2). 6
2 e
ln( n )
n 1
2
(2)
3. Results and discussion 3.1 LCA Normalization showed that the impact categories most affected by the scenarios were HTnc, HTc, FWE, FWec and RD (Fig. 2a), whereas the other impact categories had significantly lower values (Fig. 2b). The incidence of leachate treatment on ecotoxicity and human toxicity was also reported by Damgaard et al. (2011) in an LCA and economic analysis of landfill leachate and gas technologies. Similarly Abduli et al. (2011) found that landfill emissions affected human health to a greater degree with respect to other impacts even when gaseous and leachate treatments were used. With the exception of RD and ODP, there were higher impacts for the WWTP and for the BS in which the off-site co-treatment with civil sewage in the wastewater treatment plant was largely exploited. The large amount of energy and chemicals required by the evaporation system caused the higher value for RD for MS1 and BS (Fig. 2a), respectively. In any case there were lower impacts for POF and TE for MS2 even if they were very similar to those of MS1 (Fig. 2b). The impact characterization reported in Fig. 3 shows the incidence of the main activities (i.e. transport, on-site treatment, off-site treatment of leachate and concentrate in WWTP) involved in the four scenarios in determining the values of the impact categories. For BS, the values of HTnc, HTc and FWE were largely due to the off-site co-treatment of both the leachate and concentrate with civil sewage in the wastewater treatment plant, whereas emission from transport played a minor role with the exception of HTc for the WWTP scenario. On the other hand the contribution due to transport was more relevant for all the other impact categories except for the MS1 scenario. The values of the impact categories of MS1 were practically due to the direct and indirect emissions generated by the on-site treatment and by the off-site co-treatment of the concentrate in the wastewater treatment plant. In this case the contribution due to transport was always negligible. Differently, as a consequence of the larger amount of concentrate discharged by the RO (Table 1), the incidence of transport for the MS2 scenario played a more relevant role in determining the values of almost all the impact categories. Finally, for the WWTP scenario, with the exception of HTnc, HTc and FWE, the contribution due to transport in determining the values of the other impact categories was from 30% up to 80%. The incidence of emissions from transport was the reason for the higher values for RD, GWP, ODP, PM, POF, A and ET for the WWTP scenario compared to that of MS2. Higher values assumed by HTnc, HTc and FWE for the WWTP scenario compared to MS2 were mainly a consequence of the 5
higher direct and indirect emissions resulting from co-treatment of leachate with civil sewage in the wastewater treatment plant. Likewise the higher direct and indirect emissions for the evaporation system caused higher impact for MS1 with respect to MS2. The combined effect of the evaporation process and of the off-site cotreatment with civil sewage in the wastewater treatment plant and the respective transport caused the high impact for almost all the impact categories for the BS. In general these findings demonstrate that transport influences to a large extent the emissions associated with the WWTP scenario, even if direct and indirect emissions from MS2 were in any case lower. The positive effect of advanced wastewater treatments, in particular on human health, was also reported by Papa et al. (2016), who reported that the impact on human health can be decreased up to >25% if the conventional activated sludge process, typical of WWTP, is integrated with advanced treatments such as ozonation and powder activated carbon. Similarly, in comparing different options for managing black water source-separation sanitation systems, Thibodeau et al. (2014) reported that RO was able to reduce the impact on human health up to 3 times compared to other conventional and non-conventional solutions even if the costs were higher. RO was also reported by Renou et al. (2008) as the most promising technology for leachate treatment. On the other hand different results were reported by Menard et al. (2004) in comparing an engineered landfill with an aerated pond for leachate treatment, with a bioreactor landfill with leachate recirculation in the disposed waste body. Their main findings showed that leachate treatment affected only ozone depletion and eutrophication potentials with an incidence of 16% and 9%, respectively, on the whole impact associated with these landfills. A negligible contribution of leachate emissions was also reported by Kirkeby et al. (2004) in a LCA modelling of the impact of solid waste landfilling. Considering that human health and fresh water quality were among the categories most affected and are of particular concern, in order to better interpret the results reported above, an uncertainty analysis was performed for assessing the error associated with the values of these impact categories. 3.2 Uncertainty The emissions from transport influencing to a large extent the impact categories most affected (HTc, HTnc and Fwec) were mainly by the heavy metals such as CrVI and Zn. According to Frischknecht et al. (2007) they were characterized by the highest basic uncertainty values of 5.00 SM 3), influencing the final values of the uncertainty reported in SM 4. This showed that the process and activities characterized by the lowest uncertainty values of the respective emissions were electricity and chemicals production. Higher uncertainty values of 1.52 and 5.00 were associated with pollutant emissions to water and with emissions due to transport, respectively. These values were used determine the composite uncertainty associated with the impact categories most affected for each scenario. For doing this the share of the contribution of the emissions of the processes and activities considered in determining HTc, HTnc, FWE and FWec were determined (Table 3). According to Eq. (2) these shares were used for combining the uncertainties reported in SM 4. The main results showed that higher uncertainties were associated with the impact categories of the scenarios in which the shares due to transport and emissions to water were higher, that is, in decreasing order WWTP, BS and MS2. In particular pollutants emitted to water played a prominent role in determining the uncertainties of HTnc, HTc and FWE, whereas transport was prevalent in determining FWec. There were lower uncertainty values for HTnc, HTc, FWE and Fwec, ranging from 1.05 to 1.19, for MS1. In this case the higher share was associated with the emissions due to HCl production, from 35.4% up to 64.0% affecting to a large extent the on-site emissions (Fig. 3). 4. Conclusions More effective treatment of the leachate is a key factor for improving the environmental sustainability of landfills and consequently of the entire waste management system. Efficient processing of leachate requires appropriate technologies able to satisfy different aspects, such as the continuous change in its composition caused by chemicals and physical changes occurring inside 6
the disposed waste during the years. Consistent with the aim of sanitation, the life cycle study confirmed that leachate treatment is an activity that affects mainly human health and freshwater quality. The study revealed that the activities and processes affecting these impact categories to a larger extent were by both indirect and direct emissions due to electricity consumption, chemicals consumption, emissions to water and transport. Those related to on-site reverse osmosis treatment and conventional off-site co-treatment with civil sewage in the wastewater treatment plant were largely affected by the emissions due to transport. On the other hand the impacts associated to evaporation treatment resulted significantly influenced by the chemicals and energy consumption. The uncertainty analysis revealed that both reverse osmosis and off-site co-treatment in wastewater treatment plants had the highest values of the composite uncertainties able to modify significantly the results based on the average values of the impact categories. The high level of uncertainty for this last technology was highly influenced by that related to the pollutants emitted to water and the emissions from transport.
7
Fig. 1. Scheme of thhe on-site trreatment syystem for thee Base Scen nario (BS), ffor the 1st Modified M nd S Scenario (M MS1) and forr the 2 Mo odified Scen nario (MS 22).
8
0,006 BS MS1 MS2 WWTP
0,06
(a)
0,004 Normalize impacts
Normalized Impacts
0,08
0,04
0,02
0,002 0,000 -0,002
(b) BS MS1 MS2 WWTP
-0,004 -0,006 -0,008 -0,010
0,00 HTnc
HTc
FWE
FWec
GWP
RD
ODP
WRD
PM
POF
A
TE
Fig. 2. Normalized impacts most affected (a) and less affected (b) by the different scenarios per m3 of leachate. 3,5x10-6
4,0x10-5
3,0x10-6
3,5x10-5
2,5x10-6
-5
HT c (CTUh)
3,0x10
2,5x10-5 2,0x10-5 -5
1,5x10
1,0x10-5
2,0x10-6 1,5x10-6 1,0x10-6 5,0x10-7
5,0x10-6 0,0
0,0 BS
MS1
MS2
WWTP
BS
MS1
MS2
WWTP
500
0,030
450 400
0,025 0,020
FWec (CTUe)
FWE (kg P eq)
350
0,015 0,010
300 250 200 150 100
0,005
50 0,000
0 BS
MS1
MS2
WWTP
0,1
0,0045
0,0
0,0040
-0,1
0,0035
-0,2
0,0030
RD (kg Sb eq)
WRD (m3 water eq)
HT nc (CTUh)
4,5x10-5
-0,3 -0,4 -0,5
MS1
MS2
WWTP
BS
MS1
MS2
WWTP
0,0025 0,0020 0,0015
-0,6
0,0010
-0,7
0,0005
-0,8
BS
0,0000 BS
MS1
MS2
WWTP
9
0,20 0,18 0,16 POF (kg NMVOC eq)
PM (kg PM 2.5 eq)
0,024 0,022 0,020 0,018 0,016 0,014 0,012 0,010 0,008 0,006 0,004 0,002 0,000
0,14 0,12 0,10 0,08 0,06 0,04 0,02 0,00
BS
MS1
MS2
WWTP
BS
MS1
MS2
WWTP
Fig. 33. Impact chharacterizattion and conntribution of o the main activities a peer m3 of leacchate.
100
Table 1 Main input parameters for the life cycle inventory of the on-site treatment systems for 1 m3 of leachate. Parameter Unit Base Modified Modified Scenario Scenario 1 Scenario 2 Outlet 0.755 0.9 0.66 Permeate m3 3 0.015 0.03 0.30 Concentrate m 232 232 23.4 COD Conc. g/l + 3.00 3.00 9.00 NH4 Conc. g/kg Inputs from technosphere (materials/energy) 18.4 Heat kWht/m3 46 3 40.0 8.50 Electricity kWhe/m 70.0 14 10.2 HCl kg/m3 0.13 0.11 5.88 H2SO4 kg/m3 0.17/2.23 0.084/1.116 Antifoam (Si/H2O) kg/m3 Acid product for R.O. 1E-3/1E-3 0.045/0.045 0.025/0.025 kg/m3 (HNO3/H2O) 0.08 0.067 NaOH kg/m3 3 0.04/0.23 0.036/0.204 Antibacterial (CH2NS2 /H2O) kg/m Alkaline for R.O. 4.8E-3/1.6E0.053/0.0177/ 0.0372/0.0124/ kg/m3 3/8E-4/8.8E-3 8.85E-3/0.0974 6.2E-3/0.0682 (KOH/NaOH/C28H22/H2O) Table 2 Pedigree matrix with five data quality indicators and associated uncertainty factors. 1 Verified data based on measurements 1=1.00
2 Verified data partly based on assumptions or non-verified data based on measurements 1=1.05
Score 3 Non-verified data partly based on quantified estimates 1=1.10
4 Qualified estimate (e.g. by industrial experts) 1=1.20
5 Non-qualified estimate 1=1.50
Completeness
Representative data from all sites relevant for the market considered, over an adequate period to even out normal fluctuations 2=1.00
Representative data from >50% of the sites relevant for the market considered, over an adequate period to even out normal fluctuations 2=1.02
Representative data from only some sites (<<50%) relevant for the market considered or > 50% of sites but from shorter periods 2=1.05
Representative data from only one site relevant for the market considered or some sites but from shorter periods 2=1.10
Representativeness unknown or data from a small number of sites and from shorter periods 2=1.20
Temporal correlation
Less than 3 years of difference to the time period of the dataset 3=1.00
Less than 6 years difference to the time period of the dataset 3=1.03
Less than 10 years difference to the time period of the dataset 3=1.10
Less than 15 years difference to the time period of the dataset 3=1.20
Age of data unknown or more than 15 years of difference to the period of the dataset 3=1.50
Geographical correlation
Data from area under study 4=1.00
Average data from larger area in which the area under study is included 4=1.01
Data from area with similar production conditions 4=1.02
Data from area with slightly similar production conditions 4=1.03
Data from unknown area of or distinctly different area 4=1.10
Further technological correlation
Data from enterprises, processes and materials under study 5=1.00
Data from process and materials under study but from different enterprises 5=1.02
Data from processes and materials under study but from different technology 5=1.05
Data on related processes or materials 5=1.10
Data on related processes on laboratory scale or from different technologies 5=1.20
Quality indicator Reliability
11
Table 3 Contribution of the main processes and emissions to the determination of the values of HTcn, HTc, FWE and FWec and resulting composite uncertainty. Process and activities Scenario Impact cat. Electricity HCl Pollutants H2SO4 Transport Other (%) (%) emitted (%) (%) (%) to water (%) 12.3 8.60 HTnc 3.30 10.0 65.7 20.1 1.18 HTc 10.9 15.3 52.5 BS 6.74 0.61 FWE 11.3 15.3 66.1 40.4 2.26 FWec 9.31 20.0 28.1 20.3 35.4 40.3 1.52 2.5 HTnc 32.4 59.3 4.47 1.50 2.36 HTc MS1 33.8 54.8 7.05 0.51 3.87 FWE 23.4 64.0 1.41 2.57 8.57 FWec 9.86 67.7 12.9 8.63 9.86 HTnc 21.4 45.7 15.2 16.1 21.4 HTc MS2 33.2 47.2 12.9 5.11 33.2 FWE 12.8 30.3 17.8 37.7 12.8 FWec 0.08 85.4 14.3 0.08 HTnc 0.29 72.3 27.4 0.29 HTc WWTP 0.3 90.5 9.18 0.30 FWE 0.12 41.4 58.5 0.12 FWec
12
2 1.40 1.48 1.35 1.94 1.19 1.05 1.05 1.06 1.37 1.38 1.24 1.86 1.53 1.71 1.50 2.60
References Abduli, M.A., Naghib, A., Yonesi, M., Akbari, A. 2011. Life cycle assessment (LCA) of solid waste management strategies in Tehran: landfill and composting plus landfill. Environ. Monit. Assess. 178,487-498. Barlaz, M.A., Chanton, J.P., Green, R.B., 2009. Controls on landfill gas collection efficiency: instantaneous and lifetime performances. J. Air Waste Manag. Assoc. 59, 1399–1404. Beylot, A., Villeneuve, J., Bellenfant, G., 2013. Life cycle assessment of landfill biogas management: sensitivity to diffuse and combustion air emissions. Waste Manage. 33, 401– 411. Bjorklund, A,E, 2002, Survey of Approaches to Improve Reliability in LCA. Int. J. LCA 7, 64-72. Camba, A., Gonzalez-Garcia, S., Bala, A., Fullana-i-Palmer, P., Moreira, M.T., Feijoo, G. 2014. Modelling the leachate flow and aggregated emissions from municipal waste landfills under life cycle thinking in the Oceanic regions of the Iberian Peninsula. J. Clean Prod. 67,98-106. Chen, Y.C., Lo, S.L. 2016. Evaluation of greenhouse gas emissions for several municipal solid waste management strategies. J. Clean Prod. 113,606-612. Damgaad, A., Manfredi, S., Merrid, H., Stensoe, S., Christensen, T. 2011. LCA and economic evaluation of landfill leachate and gas technologies. Waste Manage. 31,1532-1541. Di Maria, F, Sordi, A., Micale, C. 2013a. Experimental and life cycle assessment analysis of gas emission from mechanically biologically treated waste in a landfill with energy recovery. Waste Manage. 33, 2557-2567. Di Maria, F., Micale, C., Sordi, A., Cirulli, G., 2013b. Leachate purification of mechanically sorted organic fraction waste in a simulated bioreactor landfill. Waste Manage. Res. 31, 1070– 1074. Di Maria, F., Micale, C. 2014. A holistic life cycle analysis of waste management scenarios at increasing source segregation intensities. Waste Manage. 34, 2382-2392. Di Maria, F., Micale, C., Contini, S., Morettini, E. 2016. Impact of biological treatment of biowaste for nutrients, energy and bio-methane recovery in a life cycle perspective. Waste Manage. 52, 86-95. Di Palma L, Ferrantelli P, Merli C, Petrucci E. 2002. Treatment of industrial landfill leachate by means of evaporation and reverse osmosis. Waste Manage. 22,951-955. EC, 2010. European Commission – Joint Research Centre – Institute for Environment and Sustainability. 2010. International Reference Life Cycle Data System (ILCD) Handbook – General guide for Life Cycle Assessment – Detailed guidance. First edition March 2010. EUR 24708 EN. Publications Office of the European Union. Luxembourg, LU. EC- European Commission. 2012. Characterization factors of the ILCD Recommended Life Cycle Impact Assessment methods, Database and Supporting Information, First edition, Joint Research Centre, Institute for Environment and Sustainability, Publications Office of the European Union, Luxembourg. Frischknecht, R., Jungbluth, N., Althaus, H.J., Doka, G., Heck, T., Hellweg, S., Hischier, R., Nemecek, T., Rebitzer, G., Spielmann, M., Wernet, G. 2007. Overview and Methodology. ecoinvent report No. 1. Swiss Centre for Life Cycle Inventories, Dübendorf, 2007. Goedkoop, M., Oele, M., Leijting, J., Ponsioen, T., Meijer, E. 2016. Introduction to LCA with SimaPro. Report version 5.2. Available in: http://www.presustainability.com/download/SimaPro8IntroductionToLCA.pdf. ISO 14040, 2006. Environmental Management: Life Cycle Assessment, Principles and Guidelines. International Organization of Standardization, Geneva 2006. ISO 14040, 2006. Environmental Management: Life Cycle Assessment – Requirements and guidelines. International Organization of Standardization, Geneva 2006. ISPRA. 2015. Rapporto Rifiuti urbani. Edizione 2015. Rapporto 230/2015. ISBN: 978-88-4480740-5. 13
Kirkeby, J.T., Birigisdottir, H., Bhander, G.S., Hauschild, M., Christensen T.H. 2007. Modelling of environmental impacts of solid waste landfilling within the life-cycle analysis program EASEWASTE. Waste Manage. 27,961-870. Lloyd, M.S., Ries, R. 2007. Characterizing, Propagating, and Analyzing Uncertainty in Life Cycle Assessment. J. Ind. Ecol. 11, 161-179. Menard, J.F., Lesage, P., Deschenes, L., Samson, R. 2004. Comparative Life Cycle Assessment of Two Landfill Technologies for the Treatment of Municipal Solid Waste. Int. J. LCA 9,371378. Papa, M., Alfonsin, C., Moreira, M.T., Bertanza, G. 2016. Ranking wastewater treatment trains based on their impacts and benefits on human health: a “Biological Assay and Disease” approach. J. Clean Prod. 113,311-317. Renou, S, Givaudan JG, Paoulain S, Dirassouyan F, Moulin P. 2008. Landfill Leachate treatment. Review and Opportunity. J. Hazard. Mate. 150,468-493. Slack, RJ, Gronow, JR, Voulvoulis, N. 2005. Household Hazardous Waste in Municipal landfills contaminants in leachate. Sci. Total Environ. 337, 119-137. Schiopu, AM, Gravilescu, M. 2010. Options for the treatment and Management of Municipal landfill Leachate: Common and Specific Issues. Clean - Soil Air Water 38,1101-1110. Thibodeau, C., Frederic, M., Glaus, M. 2014. Comparison of development scenarios of black water source-separation sanitation systems using life cycle assessment and environmental life cycle costing. Resour. Conserv. Recy. 92,38-54. Ushikoshi K, Kobayashi T, Uematsu K, Toji A, Kojima D, Matsumoto K. 2002. Leachate treatment by the reverse osmosis system. Desalination 150,121-190. Weidema, B.P., Wesnaes, M.S. 1996. Data quality management for life cycle inventories – an example of using data quality indicators. J. Clea. Prod. 4, 167-174. Weidema, B.P. 1998. Multi-User Test of the Data Quality Matrix for Product Life Cycle Inventory. Int. J.LCA 3, 259-265. Wernet, G., Bauer, C., Steubing, B., Reinhard, J., Moreno-Ruiz, E., and Weidema, B. 2016. The ecoinvent database version 3 (part I): overview and methodology. The International Journal of Life Cycle Assessment, [online] 21(9), pp.1218–1230. Available in: http://link.springer.com/10.1007/s11367-016-1087-8.
14
Supporting material (SM) SM 1 Main input parameters for the life the wastewater treatment plant. Parameter Value Energy Heat other NG 0.1087 Elec. low Volt. 0.2057 Emissions to air NOX 6.9E-4 Lead 1.75E-10 CO2, biogenic 0.19 NMVOC 2.28E-6 SO2 8.86E-4 1.03E-4 N2O Emissions to water COD 0.03 Nitrite 6.44E-4 Lead 9.49E-7 Lead, long 3.36E-7 Sulphate, long 2.37E-3 Chloride 0.04 Phosphate, river 2.7E-3 8.56E-5 BOD5, long Ammonium, ion 0.011 Nitrogen, river 4.9E-4 Emissions to soil Sulphur 5.95E-4 Aluminium 5.7E-4 Carbon 6.7E-3
cycle inventory for the treatment of 1 m3 of domestic sewage in Unit
Parameter
Value
Unit
MJ kWh
Heat NG Elec. High Volt.
0.00630 0.01864
MJ kWh
kg kg kg kg kg kg
CH4, biogenic Aluminium Phosphorus CO, biogenic Chromium Ammonia
5.02E-4 1.41E-6 1.33E-6 1.7E-4 2.73E-13 3.56E-4
kg kg kg kg kg kg
kg kg kg kg kg kg kg kg kg kg
Phosphate TOC TOC, river Phosphate, long Sulphate COD, long BOD5, river Nitrate, long Nitrate, river
1.46E-5 1.03E-4 7.3E-3 1.56E-4 0.1449 2.6E-4 9.82E-3 5.13E-5 0.048
kg kg kg kg kg kg kg kg kg
kg kg kg
Chromium Lead
2.33E-6 2.97E-6
kg kg
SM 2 Impact categories and normalization factors. Impact category
Unit
Global warming potential – GWP Ozone depletion layer – ODP Human toxicity, non-cancer effects – HTnc Human toxicity, cancer effects – HTc Particulate matter – PM Photochemical ozone formation – POF Acidification – A Eutrophication terrestrial – ET Fresh water eutrophication – FWE Fresh water ecotoxicity – FWec Water resource depletion – WRD Min., foss. & ren. Res. Depletion - RD
kgCO2 eq. kgCFC-11 eq. CTUh CTUh kgPM2.5 eq. kgNMVOC eq. molc H+ eq. molc N eq. kg P eq. CTUe m3 water eq. kg Sb eq.
Normaliz ation factors 1.10E- 04 46.3 1876 27100 2.63E -01 3.15E -02 2.11E -02 5.68E -03 6.76E -01 1.14E -04 1.23E -02 9.9
Unit kgCO2 eq./a. kgCFC-11 eq./a. CTUh CTUh kgPM2.5 eq./a. kgNMVOC eq./a. molc H+ eq./a. molc N eq./a. kg P eq./a. CTUe/a. m3 water eq./a. kg Sb eq./a. 15
SM 3 Basic uncertainty factor used for variance evaluation. Process and activities Electricity production Chemicals production Pollutants emitted to water Transport emissions
b 1.05 1.05 1.50 5.00
SM 4 Values assigned to uncertainty factors and resulting variance for the main process and activities emissions. Process and activities
21
22
23
24
25
2
Electricity production Chemicals production Pollutants emitted to water Transport emissions
1.00 1.00 1.00 1.00
1.00 1.00 1.10 1.00
1.00 1.00 1.00 1.00
1.01 1.01 1.02 1.00
1.00 1.02 1.02 1.02
1.05 1.06 1.52 5.00
16
ENER RGY
C CHEMICALS
EVAPORA ATION
R REVERSE OS SMOSIS TREATE ED WASTEW WATER
LEACHATE E EMISSIO ONS W.W.T.P.
>sustainability of conventional and advanced treatment of leachate was assessed by LCA >most affected impacts were human health and water ecotoxicity >Reverse osmosis and evaporation as to be preferred to conventional WWTP >Evaporation system impact was affected largely by energy consumption
1