Anaerobic digestion (AD) is being established as a standard technology to recover some of the energy contained in the sludge in wastewater treatment plants (WWTPs) as biogas, allowing an economy in electricity and heating and a decrease in climate gas emission. The purpose of this study was to quantify the contributions to the total environmental impact of the plant using life cycle assessment methodology. In this work, data from real operation during 2012 of a municipal WWTP were utilized as the basis to determine the impact of including AD in the process. The climate change human health was the most important impact category when AD was included in the treatment (Scenario 1), especially due to fossil carbon dioxide emissions. Without AD (Scenario 2), increased emissions of greenhouse gases, mostly derived from the use of electricity, provoked a rise in the climate change categories. Biogas utilization was able to provide 47% of the energy required in the WWTP in Scenario 1. Results obtained make Scenario 1 the better environmental choice by far, mainly due to the use of the digested sludge as fertilizer.

INTRODUCTION

Wastewater treatment plants (WWTPs) play an important environmental role minimizing the impact of discharges in river ecosystems. Simultaneously, their operation involves a series of activities that provoke an impact on the environment (use of energy, emissions, waste generation, etc.). A correct evaluation of design and operation of the plant, as well as improvements in the process, is critical in reducing these impacts. Owing to this, some studies have been developed in order to achieve energy self-sufficiency in WWTPs (Nowak et al. 2011; Svardal & Kroiss 2011; Balmer & Hellström 2012; Jenicek et al. 2012, 2013).

Another key factor is the management of the sewage sludge, not only from the economic point of view, but also from the environmental one (Iranpour et al. 2004). Nutrient contained in the sewage sludge make its use interesting as a fertilizer (Singh & Agrawal 2008). Nevertheless, the possibilities for disposal of sewage from municipal wastewater treatment are being increasingly restricted and its application as a fertilizer remains controversial (Busetti et al. 2005). Stabilization processes aim to destroy pathogens, eliminate offensive odors and improve esthetics and transportability (Yoshida et al. 2013). The current importance of anaerobic digestion (AD) in wastewater treatment is based on in its efficiency for sludge transformation into biogas which can be used as an alternative energy source (Carlos-Hernandez et al. 2009). The price and demand of electricity has increased in recent years, encouraging the use of energy sources less dependent on fossil fuels (Manzoor & Haqiqi 2012). Unfortunately, implementation of AD has some potential negative impacts that need to be minimized.

Aiming to study the environmental behavior of WWTPs, life cycle assessment (LCA) has been widely used (Corominas et al. 2013a). Recently, this methodology has exhibited significant performance as a tool to support investment decisions taken on the basis of environmental information (Rodriguez-Garcia et al. 2011; Antonopoulos et al. 2013; Remy et al. 2013). During the last decades, many studies have been developed in several countries focusing on different key aspects of WWTPs, such as greenhouse gas emissions (Bani Shahabadi et al. 2009; Flores-Alsina et al. 2011), nutrient removal or recovery (Nakakubo et al. 2012; Corominas et al. 2013b), and sewage sludge treatments (Lundin et al. 2004; Johansson et al. 2008; Murray et al. 2008; Manfredi & Christensen 2009; Remy et al. 2013; Bertanza et al. 2015). Ecotoxicity impacts caused mostly by sewage sludge disposal were present in all plants (Lassaux et al. 2007; Gallego et al. 2008), whereas global warming impact was especially important in WWTPs with advanced treatments (Muñoz et al. 2009; Rodriguez-Garcia et al. 2011; Amores et al. 2013).

To our knowledge, although many studies have been developed treating different aspects of AD on a WWTP, no studies have focused on checking the environmental effect of introducing this treatment in a real plant. Therefore, the main goal pursued in this work was to conduct an LCA in order to compare the environmental behavior of a WWTP with and without AD, creating a good reference for researchers and LCA practitioners in the field of wastewater.

MATERIAL AND METHODS

Goal and scope definition

The present study closely follows the guidelines of ISO 14040 to ISO 14044, describing the principles and framework for LCA. The goal of the study was to compare the environmental behavior of a real WWTP and the same one without the anaerobic step. The two scenarios considered are defined below.

Scenario 1 is a municipal WWTP located in central Spain. It has a wastewater treatment capacity of 76,000 m3/day, and produces 37 tons/day of dewatered sludge with a yearly average of 441,141 person equivalents (PE). The system consists of the following treatment stages: pretreatment (screening, grit, and grease removal), primary treatment (pre-aeration and sedimentation), secondary treatment (biological process and sedimentation), and sludge treatment. The biological treatment consists of a conventional activated sludge plug flow reactor with nitrification–denitrification and a system configuration for biological phosphorus removal (UCT (University of Cape Town) or Bardenpho, as needed). The primary and secondary sludges are mixed and treated by thickening, AD, and centrifugation. The stabilized sludge is deposited on agricultural land (despite the controversy existing in Europe about using WWTP sludge in agriculture). The only chemicals employed are FeCl3 and polyelectrolyte, added in the sludge line. The biogas produced is used in a cogeneration system. The average composition of this biogas is: CH4 70%, CO2 29.65%, SH2 0.001%.

Scenario 2 is the same WWTP without AD. Basically, the consequences of removing the AD were incorporated, i.e., an increase of the volume of sludge generated (with the resulting changes in transport), the change in the electricity needs of the plant (as a result of the absence of cogeneration, requirements of AD unit and more sludge to dewater), and the elimination of the emissions from the biogas burning. The disposal of the sludge on agricultural land was not considered in this scenario. According to Spanish regulations, sludge not going through an appropriate treatment to reduce its fermentability and health risks cannot be used in agriculture (RD 1310/1990). Landfill disposal was considered in this case. Figure 1 shows a block diagram for both scenarios.
Figure 1

Block diagram for Scenarios 1 and 2 (gray blocks are removed in Scenario 2 whereas the spotted one is removed in Scenario 1).

Figure 1

Block diagram for Scenarios 1 and 2 (gray blocks are removed in Scenario 2 whereas the spotted one is removed in Scenario 1).

Different LCA studies have considered different functions for a WWTP, leading to variability among the works developed in this field in the definition of the functional unit (FU) and the system boundaries, the selection of the methodology, and the procedure followed for interpreting results (Finnveden et al. 2009; Corominas et al. 2013a; Yoshida et al. 2013). According to regulations, the main function of the studied system considered is the treatment of an influent in order to discharge a suitable effluent to the environment. The FU selected was a PE, defined as the biodegradable organic load with 60 g of 5-day biochemical oxygen demand per day. This FU allowed taking into account both the volume of the influent and its associated load, unlike other FUs based only on volume (m3). This is consistent with other published works in this field (Lundin et al. 2000; Gallego et al. 2008).

Inventory analysis

After goal and scope have been determined, SimaPro v.7.3 was used in order to make an inventory analysis (Spriesma 2004). Most of the data used to perform this stage were supplied by Acciona Agua from the operation of a real WWTP during 2012. The subsystems considered to carry out the LCA are shown and described in Table 1. In addition, there have been some approaches and simplifications based on bibliographic references on similar processes considered for this stage:

  • Direct emissions of CO2, N2O, CH4, SO2, NH3 (operation and disposal) have been calculated following the recommendations of the Intergovernmental Panel on Climate Change (Houghton et al. 2001; Doorn et al. 2006). Emissions from biogas combustion were calculated from actual data of the biogas collected, mainly CO2 and SO2 due to the presence of H2S. The emissions from the sludge during storage transport and degradation in the soil were not taken into account.

  • The database used for electricity production was Ecoinvent Unit Processes V.2.2, using the units Electricity, medium voltage, at grid [ES] (Hischier et al. 2010).

  • For the bioavailability of metals contained in the sludge, data regarding the percentage of metal extracted with EDTA (ethylenediaminetetraacetic acid) were considered. The corresponding values are 58.5% for Cu, 7.8% for Pb, 4.1% for Cr, 7.5% for Ni, and 18.0% for Zn. Due to the absence of data for other metals (Hg, Cd), the worst-case scenario was considered, with 100% bioavailability (Gallego et al. 2008).

  • In Scenario 1, the application of digested sewage sludge (N and P content) in agricultural soils provides an environmental benefit by avoiding the production of synthetic fertilizers. To calculate the amount of avoided fertilizer, it has been assumed that 1 kg of dry sludge is equivalent to 0.3 kg of a chemical fertilizer, based on the composition of the sludge (Bengtsson et al. 1997).

  • The only chemicals considered were ferric chloride and polyelectrolyte, added to the sludge after AD. The amount of chemicals needed was considered proportional to the amount of sludge centrifugated. Acrylonitrile and iron(III) chloride 40% units available at Ecoinvent V.2.2 were used to approach these chemicals (Hischier et al. 2010).

  • The odor issue was not considered in this work due to the impossibility of having accurate data to estimate its impact.

  • The impact of plant construction was not taken into account (Lassaux et al. 2007). It was considered negligible in other similar cases and even studies that have included this phase showed that sewer net and plant construction contribute less than 10% to the total environmental impact (Del Borghi et al. 2008).

  • The real distances between the WWTP and the areas of chemical production (polyelectrolyte 1,800 km, ferric chloride 400 km), waste management (32 km), and application of sludge (40 km) were considered for the transport of chemicals, solid waste, and sludge. The Ecoinvent Unit Processes v.2.2 (Hischier et al. 2010) data were used to evaluate the transport impact since it was the best suited to the characteristics of the trucks used (transport, lorry >32t).

Table 1

Description of subsystems

Subsystems Description 
Influent Wastewater treated (BOD5, COD, NT, P, SS), considered as avoided emissions 
Effluent Wastewater discharged (BOD5, COD, NT, P, SS) 
Air emissions Gas emissions due to plant operation: (CO2, N2O, CH4, NH3) and burning biogas (CO2, SO2)a 
Soil emissions Heavy metals contained in the sludge (Cu, Cd, Cr, Hg, Ni, Zn, Pb) deposited on land 
Chemicals production Production of chemicals required in the sewage sludge treatment (polyelectrolyte and ferric chloride) 
Electricity Power consumed by plant operation 
Transport Sludge From the plant to the agricultural landa or to the landfill 
Chemicals From the site of manufacture to the plant 
Solid wastes From the plant to the landfill 
Biogas* Impacts derived from managing the biogas produced during sludge digestion 
Chemical fertilizer avoided Result of the use of sludge as farm fertilizer, avoiding the production and use of chemical fertilizers (N, P) 
Subsystems Description 
Influent Wastewater treated (BOD5, COD, NT, P, SS), considered as avoided emissions 
Effluent Wastewater discharged (BOD5, COD, NT, P, SS) 
Air emissions Gas emissions due to plant operation: (CO2, N2O, CH4, NH3) and burning biogas (CO2, SO2)a 
Soil emissions Heavy metals contained in the sludge (Cu, Cd, Cr, Hg, Ni, Zn, Pb) deposited on land 
Chemicals production Production of chemicals required in the sewage sludge treatment (polyelectrolyte and ferric chloride) 
Electricity Power consumed by plant operation 
Transport Sludge From the plant to the agricultural landa or to the landfill 
Chemicals From the site of manufacture to the plant 
Solid wastes From the plant to the landfill 
Biogas* Impacts derived from managing the biogas produced during sludge digestion 
Chemical fertilizer avoided Result of the use of sludge as farm fertilizer, avoiding the production and use of chemical fertilizers (N, P) 

aOnly for Scenario 1. BOD5: biochemical oxygen demand; COD: chemical oxygen demand; NT: total nitrogen; SS: suspended solids.

The yearly average of the inventory data for the two scenarios during 2012 is shown in Table 2, adding the standard deviation calculated considering monthly data.

Table 2

Inventory data in 2012 given per month (inputs and outputs)

  Scenario 1
 
Scenario 2
 
Average SD Average SD 
PE 441,141 185,120 441,141 185,120 
Inputs 
 COD (kg/PE) 3.42 0.37 3.42 0.37 
 BOD5 (kg/PE) 1.82 0.05 1.82 0.05 
 NT (kg/PE) 0.34 0.04 0.34 0.04 
 P (kg/PE) 0.05 0.005 0.05 0.005 
 SS (kg/PE) 1.63 0.27 1.63 0.27 
Electricity (kWh/PE)a 1.29 0.46 2.01 0.23 
Chemicals transport ((t·km)/PE) 0.15 0.06 0.26 0.10 
Sludge transport ((t·km)/PE) 0.12 0.05 0.16 0.07 
 Waste transport ((t·km)/PE) 0.002 0.003 0.002 0.003 
Chemicals (kg/PE) 0.35 0.14 0.59 0.23 
Outputs 
 COD (kg/PE) 0.16 0.03 0.16 0.03 
 BOD5 (kg/PE) 0.04 0.009 0.04 0.009 
 NT (kg/PE) 0.08 0.009 0.08 0.009 
 P (kg/PE) 0.003 0.0006 0.003 0.0006 
 SS (kg/PE) 0.03 0.02 0.03 0.02 
 N2O (kg/PE) 0.0006 7 × 10−5 0.0006 7 × 10−5 
CH4 (kg/PE) 0.0007 0.0003 0.001 0.0005 
Biogas (m3/PE) 0.487 0.182   
CO2 fossil (kg/PE) 0.59 0.20 0.76 0.20 
CO2 bio (kg/PE) 2.06 0.75 1.11 0.56 
NH3 (kg/PE) 0.00006 2 × 10−5 0.00008 3 × 10−5 
SO2 (kg/PE) 0.00001 5 × 10−6   
Dried sewage sludge (kg/PE) 0.75 0.32 1.25 0.53 
 Cd (kg/PE) 4.93 × 10−6 1.88 × 10−6 4.93 × 10−6 1.88 × 10−6 
 Cu (kg/PE) 6.56 × 10−4 2.5 × 10−4 6.56 × 10−4 2.5 × 10−4 
 Cr (kg/PE) 1.61 × 10−4 6.15 × 10−5 1.61 × 10−4 6.15 × 10−5 
 Hg (kg/PE) 2.38 × 10−6 0.91 × 10−6 2.38 × 10−6 0.91 × 10−6 
 Ni (kg/PE) 5.77 × 10−5 2.20 × 10−5 5.77 × 10−5 2.20 × 10−5 
 Pb (kg/PE) 1.16 × 10−4 4.43 × 10−5 1.16 × 10−4 4.43 × 10−5 
 Zn (kg/PE) 1.58 × 10−3 6 × 10−4 1.58 × 10−3 6 × 10−4 
  Scenario 1
 
Scenario 2
 
Average SD Average SD 
PE 441,141 185,120 441,141 185,120 
Inputs 
 COD (kg/PE) 3.42 0.37 3.42 0.37 
 BOD5 (kg/PE) 1.82 0.05 1.82 0.05 
 NT (kg/PE) 0.34 0.04 0.34 0.04 
 P (kg/PE) 0.05 0.005 0.05 0.005 
 SS (kg/PE) 1.63 0.27 1.63 0.27 
Electricity (kWh/PE)a 1.29 0.46 2.01 0.23 
Chemicals transport ((t·km)/PE) 0.15 0.06 0.26 0.10 
Sludge transport ((t·km)/PE) 0.12 0.05 0.16 0.07 
 Waste transport ((t·km)/PE) 0.002 0.003 0.002 0.003 
Chemicals (kg/PE) 0.35 0.14 0.59 0.23 
Outputs 
 COD (kg/PE) 0.16 0.03 0.16 0.03 
 BOD5 (kg/PE) 0.04 0.009 0.04 0.009 
 NT (kg/PE) 0.08 0.009 0.08 0.009 
 P (kg/PE) 0.003 0.0006 0.003 0.0006 
 SS (kg/PE) 0.03 0.02 0.03 0.02 
 N2O (kg/PE) 0.0006 7 × 10−5 0.0006 7 × 10−5 
CH4 (kg/PE) 0.0007 0.0003 0.001 0.0005 
Biogas (m3/PE) 0.487 0.182   
CO2 fossil (kg/PE) 0.59 0.20 0.76 0.20 
CO2 bio (kg/PE) 2.06 0.75 1.11 0.56 
NH3 (kg/PE) 0.00006 2 × 10−5 0.00008 3 × 10−5 
SO2 (kg/PE) 0.00001 5 × 10−6   
Dried sewage sludge (kg/PE) 0.75 0.32 1.25 0.53 
 Cd (kg/PE) 4.93 × 10−6 1.88 × 10−6 4.93 × 10−6 1.88 × 10−6 
 Cu (kg/PE) 6.56 × 10−4 2.5 × 10−4 6.56 × 10−4 2.5 × 10−4 
 Cr (kg/PE) 1.61 × 10−4 6.15 × 10−5 1.61 × 10−4 6.15 × 10−5 
 Hg (kg/PE) 2.38 × 10−6 0.91 × 10−6 2.38 × 10−6 0.91 × 10−6 
 Ni (kg/PE) 5.77 × 10−5 2.20 × 10−5 5.77 × 10−5 2.20 × 10−5 
 Pb (kg/PE) 1.16 × 10−4 4.43 × 10−5 1.16 × 10−4 4.43 × 10−5 
 Zn (kg/PE) 1.58 × 10−3 6 × 10−4 1.58 × 10−3 6 × 10−4 

aBold type: inputs and outputs significantly changing between scenarios.

Impact assessment

Inventory results are usually a very long list of emissions, consumed resources, and sometimes other items with difficult interpretation. A life cycle impact assessment procedure, such as the ReCiPe v.1.08 method included in SimaPro software, is designed to manage this issue, helping in the development of this work.

The primary objective of this method is to transform the list of life cycle inventory results into a limited number of indicator scores, showing the relative severity on an environmental impact category. Impact characterization allows comparison of the inventory results within each impact category. Normalization applies a selected reference value, obtaining dimensionless data and allowing the comparison between categories. The unit ‘Pt’ (point) is just a reference unit and must only be used for comparison between data obtained with the same calculation method. The absolute value of the points is not very relevant as the main purpose is to compare (Goedkoop et al. 2009). Average data of year 2012 sorted by month were supplied for characterization and normalization steps, in order to obtain the mean behavior of the year.

RESULTS AND DISCUSSION

Comparison between scenarios with and without AD

In order to know the relative importance of the impact categories on the overall system, Figure 2 (gray bars) presents normalization results of Scenario 1 using Pt as a measure of impact. At first glance, it is clearly noticeable that the main impacts were due to climate change categories, with a contribution slightly greater for human health than for ecosystems. The air emissions subsystem was mostly responsible for this impact followed closely by electricity, mainly due to the fossil carbon dioxide emissions in both cases. Beneficial contributions derived from the use of sludge as agricultural fertilizer appeared especially in three impact categories: climate change human health, climate change ecosystems, and fossil depletion. The positive impact to prevent spillage of raw water entering the treatment plant affected the freshwater eutrophication category.
Figure 2

Comparison between normalization impacts of both scenarios in 2012 (ReCiPe method).

Figure 2

Comparison between normalization impacts of both scenarios in 2012 (ReCiPe method).

The environmental analysis of Scenario 2 (black bars) was qualitatively similar to Scenario 1, with the contributions to impact categories climate change human health, climate change ecosystems, and particulate matter formation being substantially greater in this case. As well, the absence of AD affected especially the fossil depletion category, with no beneficial impact in this scenario due to the consideration of not using the undigested sludge for agricultural purposes. On the other hand, AD causes harmful emissions caused by the generation of SOx from biogas burning, practically negligible due to the low amount of H2S in the biogas composition.

The main results of both scenarios (with and without AD) are summarized in Table 3, taking into account only the most important categories of impact (fossil depletion, climate change human health, particulate matter formation, and climate change ecosystems) and the main subsystems.

Table 3

Most relevant categories of impact and subsystems (>5 mPt) in both scenarios for 2012

ReCiPe Endpoint (H) V1.08
 
  Air emissions (mPt) Chemicals production (mPt) Electricity (mPt) Biogas (mPt) Avoided fertilizer (mPt) Totala (mPt) 
Scenario 1 
 Fossil depletion – 0.1 0.2 – −24.1 −23.8 
 Climate change human health 29.6 9.3 18.7 5.2 −39.7 24.6 
 Particulate matter formation 0.2 3.0 8.5 0.3 −10.2 2.3 
 Climate change ecosystem 18.7 5.9 11.8 3.3 −25.1 15.6 
 Totala (mPt) 49.8 23.5 41.1 9.1 −99.2 23.2 
Scenario 2 
 Fossil depletion – 0.1 0.3 – – 0.4 
 Climate change human health 29.9 15.5 31.9 – – 79.6 
 Particulate matter formation 0.1 5.0 14.5 – – 20.4 
 Climate change ecosystem 18.9 9.8 20.1 – – 50.2 
 Totala (mPt) 49.0 39.2 69.8 – – 158.4 
ReCiPe Endpoint (H) V1.08
 
  Air emissions (mPt) Chemicals production (mPt) Electricity (mPt) Biogas (mPt) Avoided fertilizer (mPt) Totala (mPt) 
Scenario 1 
 Fossil depletion – 0.1 0.2 – −24.1 −23.8 
 Climate change human health 29.6 9.3 18.7 5.2 −39.7 24.6 
 Particulate matter formation 0.2 3.0 8.5 0.3 −10.2 2.3 
 Climate change ecosystem 18.7 5.9 11.8 3.3 −25.1 15.6 
 Totala (mPt) 49.8 23.5 41.1 9.1 −99.2 23.2 
Scenario 2 
 Fossil depletion – 0.1 0.3 – – 0.4 
 Climate change human health 29.9 15.5 31.9 – – 79.6 
 Particulate matter formation 0.1 5.0 14.5 – – 20.4 
 Climate change ecosystem 18.9 9.8 20.1 – – 50.2 
 Totala (mPt) 49.0 39.2 69.8 – – 158.4 

aTotal values considering all the impact categories and subsystems.

Analyzing the results obtained from the subsystems point of view, most of the impact comes from air emissions in Scenario 1 (49.8 mPt) and from electricity in Scenario 2 (69.8 mPt). Air emissions contribution was almost the same for both scenarios. On the other hand, electricity grew without the AD (41.1 to 69.8 mPt) and chemicals production almost doubled its impact in the absence of AD. This is due to the increase in the volume of sludge to manage and the absence of cogeneration, slightly affecting all impact categories. Additionally, the beneficial impact of agricultural use of sludge made a difference between scenarios due to the avoided fertilizer. Transport contributions were very low for both scenarios (not shown in Table 3). Finally, the overall impact analysis (Pt) revealed huge environmental damage if the AD was removed from the system, mainly due to the inability to use the sludge for agricultural purposes.

CONCLUSIONS

The most important impact category in Scenario 1 (with AD) was climate change human health, mainly due to fossil carbon dioxide emissions. The use of digested sewage sludge in agriculture positively affected the fossil depletion category. In Scenario 2 (without AD), the weight of climate change categories and particulate matter formation increased significantly.

In terms of subsystems, when the AD is included, air emissions were the most harmful followed by electricity. In the absence of AD, the importance of electricity increased due to the absence of cogeneration. The main credits only from Scenario 1 came from fertilizer avoided due to sewage sludge utilization.

Considering the total impact, results of the LCA analysis clearly showed that the introduction of AD in WWTPs greatly improves the system from the environmental point of view, especially if the digested sludge is used as fertilizer. The quantification analysis carried out with the ReCiPe method indicated a remarkable impact reduction of about 85% with the introduction of AD, confirming that Scenario 1 is the best choice in this study.

ACKNOWLEDGEMENTS

The content of this document summarizes the results of a research project developed during the year 2013. The authors would like to thank the company ACCIONA Agua SA for providing real operation data from an actual WWTP and for the economic support.

REFERENCES

REFERENCES
Amores
M. J.
Meneses
M.
Pasqualino
J.
Antón
A.
Castells
F.
2013
Environmental assessment of urban water cycle on Mediterranean conditions by LCA approach
.
J. Cleaner Prod.
43
,
84
92
.
Antonopoulos
I. S.
Karagiannidis
A.
Tsatsarelis
T.
Perkoulidis
G.
2013
Applying waste management scenarios in the Peloponnese region in Greece: a critical analysis in the frame of life cycle assessment
.
Environ. Sci. Pollut. Res.
20
,
2499
2511
.
Balmer
P.
Hellström
D.
2012
Performance indicators for wastewater treatment plants
.
Water Sci. Technol.
65
(
7
),
1304
1310
.
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
,
Goteborg
,
Sweden
.
Bertanza
G.
Canato
M.
Heimersson
S.
Laera
G.
Salvetti
R.
Slavik
E.
Svanström
M.
2015
Techno-economic and environmental assessment of sewage sludge wet oxidation
.
Environ. Sci. Pollut. Res.
22
,
7327
7338
.
Carlos-Hernandez
S.
Sanchez
E. N.
Béteau
J. F.
2009
Fuzzy observers for anaerobic WWTP: development and implementation
.
Control Eng. Pract.
17
,
690
702
.
Corominas
L.
Foley
J.
Guest
J. S.
Hospido
A.
Larsen
H. F.
Morera
S.
Shaw
A.
2013a
Life cycle assessment applied to wastewater treatment: state of the art
.
Water Res.
47
,
5480
5492
.
Corominas
L.
Larsen
H. F.
Flores-Alsina
X.
Vanrolleghem
P. A.
2013b
Including Life Cycle Assessment for decision-making in controlling wastewater nutrient removal systems
.
J. Environ. Manage.
128
,
759
767
.
Del Borghi
A.
Gaggero
P. L.
Gallo
M.
Strazza
C.
2008
Development of PCR for WWTP based on a case study
.
Int. J. Life Cycle Assess.
13
,
512
521
.
Doorn
M. R. J.
Manso
S. M.
Irving
W.
Palmer
C.
Pipatti
R.
Wang
C.
2006
IPCC Guidelines for National Greenhouse Gas Inventories Intergovernmental Panel on Climate Change 5
.
Finnveden
G.
Hauschild
M. Z.
Ekvall
T.
Guinée
J.
Heijungs
R.
Hellweg
S.
Koehler
A.
Pennington
D.
Suh
S.
2009
Recent developments in Life Cycle Assessment
.
J. Environ. Manage.
91
,
1
21
.
Gallego
A.
Hospido
A.
Moreira
M. T.
Feijoo
G.
2008
Environmental performance of wastewater treatment plants for small populations
.
Resour. Conserv. Recycling
52
,
931
940
.
Goedkoop
M. J.
Heijungs
R.
Huijbregts
M.
De Schryver
A.
Struijs
J.
Van Zelm
R.
2009
ReCiPe 2008: A Life Cycle Impact Assessment Method which Comprises Harmonised Category Indicators at the Midpoint and the Endpoint Level, 1st edn
.
ReCiPe Report I: Characterisation. Ministerie van VROM, The Hague, The Netherlands
.
Hischier
R.
Weidema
B.
Althaus
H. J.
Bauer
C.
Doka
G.
Dones
R.
Frischknecht
R.
Hellweg
S.
Humbert
S.
Jungbluth
N.
Köllner
T.
Loerincik
Y.
Margni
M.
Nemecek
T.
2010
Implementation of Life Cycle Impact Assessment Methods Data v2.2. Ecoinvent Report No. 3. Swiss Centre for Life Cycle Inventories, Zurich, Switzerland
.
Houghton
J. T.
Ding
Y.
Griggs
D. J.
Noguer
M.
van der Linden
P. J.
Dai
X.
Maskell
K.
Johnson
C. A.
2001
Climate Change 2001: The Scientific Basis.
Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK.
Iranpour
R.
Cox
H. H. J.
Kearney
R. J.
Clark
J. H.
Pincince
A. B.
Daigger
G. T.
2004
Regulation for biosolids land application in U.S. and European Union
.
J. Residuals Sci. Tech.
1
,
209
222
.
Jenicek
P.
Kutil
J.
Benes
O.
Todt
V.
Zabranska
J.
Dohanyos
M.
2013
Energy self-sufficient sewage wastewater treatment plants: is optimized anaerobic sludge digestion the key?
Water Sci. Technol.
68
(
8
),
1739
1743
.
Johansson
K.
Perzon
M.
Fröling
M.
Mossakowska
A.
Svanström
M.
2008
Sewage sludge handling with phosphorus utilization – life cycle assessment of four alternatives
.
J. Cleaner Prod.
16
,
135
151
.
Lassaux
S.
Renzoni
R.
Germain
A.
2007
Life cycle assessment of water from the pumping station to the wastewater treatment plant
.
Int. J. Life Cycle Assess.
12
,
118
126
.
Lundin
M.
Olofsson
M.
Pettersson
G. J.
Zetterlund
H.
2004
Environmental and economic assessment of sewage sludge handling options
.
Resour. Conserv. Recycling
41
,
255
278
.
Manzoor
D.
Haqiqi
I.
2012
Impact of energy price reform on environmental emissions; a computable general equilibrium approach
.
J. Environ. Stud.
37
,
1
12
.
Rodriguez-Garcia
G.
Molinos-Senante
M.
Hospido
A.
Hernandez-Sancho
F.
Moreira
M. T.
Feijoo
G.
2011
Environmental and economic profile of six typologies of wastewater treatment plants
.
Water Res.
45
,
5997
6010
.
Spriesma
R.
2004
SimaPRO Tutorial and Database Manuals
.
Pré Consultants, Amersfoort, The Netherlands
.
Svardal
K.
Kroiss
H.
2011
Energy requirements for waste water treatment
.
Water Sci. Technol.
64
(
6
),
1355
1361
.
Yoshida
H.
Christensen
T. H.
Scheutz
C.
2013
Life cycle assessment of sewage sludge management: a review
.
Waste Manage. Res.
31
,
1083
1101
.