Low complexity wastewater treatment process in developing countries: A LCA approach to evaluate environmental gains

Science of the Total Environment 720 (2020) 137593

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Low complexity wastewater treatment process in developing countries: A LCA approach to evaluate environmental gains Thaís A.S. Lopes b, Luciano M. Queiroz a,b,⁎, Ednildo A. Torres b,c, Asher Kiperstok b a b c

Department of Environmental Engineering, Federal University of Bahia (UFBA), Aristides Novis Street 2, 4° floor, Federação, 40210-630, Salvador, Bahia, Brazil Energy and Environment Interdisciplinary Center (CIENAM), Federal University of Bahia (UFBA), Barão de Jeremoabo Street n/a, Ondina, 40170-115, Salvador, Bahia, Brazil Department of Chemical Engineering, Federal University of Bahia (UFBA), Aristides Novis Street 2, 3° floor, Federação, 40210-630 Salvador, Bahia, Brazil

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The construction phase should not be excluded in LCA of low complexity technologies • There is a correlation between nutrients removal efficiency and Global Warming Potential • There is a trade-off between low operation consumption and air emissions

a r t i c l e

i n f o

Article history: Received 28 December 2019 Received in revised form 10 February 2020 Accepted 25 February 2020 Available online 26 February 2020 Editor: Konstantinos G Moustakas Keywords: Life cycle assessment Constructed wetlands UASB reactor Emissions Environmental impact

a b s t r a c t Reliable Life Cycle Assessment (LCA) indicators for wastewater treatment plants (WWTP) construction and operation phases are still a demand mainly in developing countries. Thus, the purpose of this paper was to present and discuss the environmental performance of a full-scale WWTP installed in a Brazilian city using LCA approach. The treatment process consists of a UASB reactor followed by constructed wetlands, which makes it particularly attractive to developing countries due to its operational simplicity. The Life Cycle Inventory (LCI) was developed from a WWTP design and operation data including those of untreated wastewater and effluent quality. The results show that the environmental impacts from construction phase should not be neglected in LCA studies of low complexity treatment technologies (e.g. UASB reactor, constructed wetlands and pond systems). There is a trade-off between the use of materials and energy for construction and the low energy and materials consumption during the operation phase in these systems. The majority share of hydroelectric generation in the energy matrix and the combination of anaerobic and natural processes for wastewater treatment have contributed to a smaller impact potential for the operation phase. The LCA approach should be associated with plans and actions

Abbreviations: AC, Acidification; AD, Abiotic depletion; BOD5, Biological oxygen demand; CED, Cumulative energy demand; COD, Chemical oxygen demand; CW, Constructed wetlands; eq, Equivalent; EU, Eutrophication; FEW, Fresh water ecotoxicity; FU, Functional unit; GW, Global warming; GWP, Global warming potential; HSF, CW Horizontal subsurface flow constructed wetlands; HT, Human toxicity; IPCC, Intergovernmental Panel Climate Change; ISO, International Organization for Standardization; kg, Kilogram; kWh, Kilowatt hour; L, Liter; LCA, Life cycle assessment; LCI, Life cycle inventory; LCIA, Life cycle impact assessment; MAE, Marine aquatic ecotoxicity; OLD, Ozone layer depletion; PE, Equivalent population; PO, Photochemical oxidation; SDG, Sustainable Development Goals; TE, Terrestrial ecotoxicity; tkm, Ton per kilometer; TKN, Total Kjeldahl nitrogen; TSS, total suspended solids; UASB, Upflow anaerobic sludge blanket reactor; UNEP, United Nations; WWTP, Wastewater treatment plants. ⁎ Corresponding author at: Department of Environmental Engineering, Federal University of Bahia (UFBA), Aristides Novis Street 2, 4° floor, Federação, 40210-630 Salvador, Bahia, Brazil. E-mail addresses: [email protected] (L.M. Queiroz), [email protected] (E.A. Torres).

https://doi.org/10.1016/j.scitotenv.2020.137593 0048-9697/© 2020 Elsevier B.V. All rights reserved.

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T.A.S. Lopes et al. / Science of the Total Environment 720 (2020) 137593

to face the challenges of providing wastewater treatment in developing countries. Only in this way, compliance with the eco-efficiency targets and protect public health will be guaranteed. © 2020 Elsevier B.V. All rights reserved.

1. Introduction Developing countries face major challenges when trying to meet requirements, regarding the availability and sustainable management of water and sanitation services. Recent data show that b50% of the sanitation services are safely managed in these regions (UN, 2018). Therefore, evaluating and improving the environmental performance of a small WWTP is a challenge to developing countries that want to meet the United Nations Sustainable Development goals (SDG) number 6. The main objective of a WWTP is to improve the effluent quality. According to Noyola et al. (2012), in Latin America, 67% of the wastewater treatment plants are small (influent flow b25 L.s−1) and very small (influent flow b5 L.s−1). However, the potential environmental impacts associated with the construction and operation phases of these facilities often are not taken into account. The Life Cycle Assessment (LCA) is the most used methodology to evaluate the environmental impacts of a WWTP (Morera et al., 2017). The LCA stands out for being able to evaluate a WWTP beyond the trade-off between process efficiency and final effluent quality because it takes into consideration resource and energy consumption, air emissions and waste generation (Foley et al., 2010). The LCA could help in the selection of wastewater treatment processes, and support the decision-making regarding environmental impacts, assessing the entire life cycle of a WWTP and not just the effect of effluent discharge on water bodies. For practical purposes, a careful study of LCA can help to estimate the environmental gains from the use of thermal or electrical energy in anaerobic reactors, or the recovery of nutrients such as struvite, or the environmental impacts of energy consumption in activated sludge processes, for example. According to Gallego-Schmid and Tarpani (2019), who analyzed 43 studies of LCA applied to wastewater treatment in developing countries, the majority of the papers only evaluated conventional technologies and did not include the construction phase; about 20% included network collection; 53% included direct greenhouse gas emissions and only three studies were from Brazil. The lack of specific databases, the non-transparency of data, the absence of knowledge and interest of the authorities when considering the LCA as a tool, and the nonimprovement of public policies in the sanitation sector contribute to the low representativeness of WWT-related LCA studies in developing countries. In most LCA studies, the sewage collection and pumping system, sludge management and direct greenhouse gas emissions were neglected. Few papers include the construction phase and the ones that evaluated both construction and operation phases showed that the operation phase presented a greater impact potential. Furthermore, about 50% of the papers do not include inventory data at all (Sabeen et al., 2018; Gallego-Schmid and Tarpani, 2019). One of the limitations on LCA applied to WWTP is the lack of a detailed Life Cycle Inventory (LCI), which does not allow verifying the correlation of all input and output flows with a functional unit (FU) and the Life Cycle Impact Assessment (LCIA) results. Data collection and the LCI elaboration are the most laborious and limiting stages of LCA studies. The availability of reliable and representative data is not always possible, creating the need to make assumptions and look for literature data, which increases the uncertainty of the final data and results. There is also a lack of certainty in the analysis of the inventory data in the LCA studies applied to WWTP in developing countries (Gallego-Schmid and Tarpani, 2019).

In the context of developing countries, it is necessary to incorporate reliable LCA indicators and review previous studies to recognize key lessons and gaps. The LCA applied to WWTP needs to improve regarding the description of sources, the technical parameters, and the elaboration of local databases to be added to wider ones. Thus, there is a demand for WWT-related LCA in developing countries, in special for a WWTP construction and operation phases, due to the geographical diversity and specific characteristics of these regions (Guérin-Schneider et al., 2018). The UASB reactors followed by a post-treatment play a crucial role in developing countries, due to their low operational cost and easy maintenance (Noyola et al., 2012). Therefore, the aim of this paper was apply LCA to evaluate the environmental performance for construction and operation phases of a full-scale WWTP composed of a UASB reactor followed by constructed wetlands. The study included the sewage collection and pumping system, pretreatment stage, biological sludge disposal and effluent discharge. 2. Material and methods The object was a full-scale WWTP (maximum flow rate equal to 3.3 L·s−1), located in a small community, in Bahia State, Brazil, which has been operating since 2008 and treating domestic wastewater. The wastewater treatment process is divided into four main steps: preliminary treatment (grit removal and sand traps), removal of soluble organic matter in the UASB reactors, nutrients removal in the constructed wetlands and a disinfection step for pathogens removal. The UASB reactor (3.8 × 3.8 m × 5.1 m) works as a primary settling and a secondary treatment corresponds to a cross-section of 14.4 m2, which has an effective volume of 73.6 m3 and a hydraulic retention time of 8.5 h. The horizontal subsurface flow constructed wetlands (HSF CW) consist of four parallel beds, each 7 m × 18 m, depth of 0.8 m and hydraulic retention time of 46.7 h. The support material used for the CW beds is crushed gravel. Two cells were planted with Typha sp. and other two were planted with Cyperus alternifolius sp. The design flow rate is equal to 96 m3 per day. A low-power electrical pump adds sodium hypochlorite solution (NaClO) for additional pathogens removal. 2.1. Goal and scope The LCA according to the ISO 14040 (2006) was used to perform this WWTP environmental analysis. The goal of the LCA was to perform an environmental analysis of a full-scale WWTP, considering the construction and operation phases. The function of the system is to treat raw wastewater in order to reduce pollutants and therefore meet the required standards of the Brazilian environmental legislation. The functional unit was defined as the volume of 1.0 m3 of treated wastewater, considering that the total volume of wastewater treated in the WWTP was 700.800 m3 during a lifetime of 20 years. The cubic meter, as a functional unit, was used because it comes from real data and agrees with several papers that have applied LCA in WWTP (Hernández-Padilla et al., 2017; Lorenzo-Toja et al., 2016; Arashiro et al., 2018). The downstream system boundary included the following units: collection and pumping of raw wastewater, pretreatment stage, a WWTP with a disinfection step, sludge disposal and treated effluent discharge for construction and operation phases, as shown in Fig. 1. The background system boundary included data from materials, chemical and energy production from the Ecoinvent® version 3.1 datasets, system model ‘allocation, default’ as a unit process, available in SimaPro 8.1®.

T.A.S. Lopes et al. / Science of the Total Environment 720 (2020) 137593

Dismantling has been excluded of the analysis due to the lack of data and because the WWTP is still in operation. Some authors assumed that the dismantling impact would be small when compared to the construction and operation phases (Foley et al., 2010; Garfí et al., 2017; LarreyLassalle et al., 2017). The allocation has not been used since the studied WWTP does not have co-functions. 2.2. Data quality requirements According to the ISO 14040 (2006), data quality requirements are necessary to demonstrate the reliability of the study results, and to allow LCA interpretation to be performed properly. The data represents the actual scale of the system construction and operation, collected from the WWTP project. The laboratory analyses of the raw wastewater and effluent contributed to the representativeness, consistency and completeness of the study. The Standard Deviation values for the downstream system flows were taken under basic uncertainty and pedigree matrix with the available uncertainty factors in Simapro® 8.1, which considers the lognormal probability distribution function by default. 2.3. Life cycle inventory The LCI included the following treatment steps: the analysis of the construction's material, the construction and operation of the pretreatment stage, WWTP with a disinfection step (e.g. building materials, air emissions, chemicals and energy use), the biological sludge disposal and the treated effluent discharge. The LCI of the construction phase used data collected from the WWTP project, websites of manufacturers and construction materials. The LCI operation phase used: the flow rate, physicochemical characteristics of the effluent, chemical and, energy consumed and air emissions. The physicochemical parameters were biological oxygen demand (BOD 5 ), chemical oxygen demand (COD), total suspended solids (TSS), total Kjeldahl nitrogen (TKN), ammonia, nitrate, total phosphorus and chlorine (Table 1). The biological sludge is discarded from the UASB reactors, dewatered in geotextile bags for 21 days and sent for final disposal in a municipal landfill 22 (twenty-two) kilometers away from the WWTP. The operation phase included the electricity and chemicals consumed, the air and water emissions, and the transport of residues (biological sludge, solid residues, sand and greases) to the landfill. The air emissions, sludge generation and methane dissolved from the UASB reactor were calculated by the mass balance of the fractions of COD proposed by Lobato et al. (2012). The COD fractions load is shown in Table 2. It was used an emission factor for kg CH4 per kg BOD and kg N2O-N per kg N (for domestic wastewater) to calculate the methane (CH4) and nitrous oxide (N2O) emissions from the constructed wetlands (CW).

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Table 1 Wastewater physicochemical characteristics. Parameters

Unit

Inlet

Outlet

Removal

BOD5 concentration COD concentration TSS concentration Ammonia Total Kjeldahl nitrogen Total phosphorous Nitrate Chlorine

mg O2 L−1 mg O2 L−1 mg TSS L−1 mg N-NH3 L−1 mg TKN L−1 mg TP L−1 −1 mg N-NO− 3 L mg Cl2 L−1

321.5 767.8 278.0 41.3 46.2 7.3

21.3 95.5 18.0 39.5 45.7 7.9 1.8 0.8

93% 88% 94% 4% 1%

The equations provided by the Intergovernmental Panel Climate Change Report were used (IPCC, 2013). The general equation for estimating the CH4 emissions from CW for domestic wastewater treatment is given by Eq. (1). CH4 emissions ¼

X   X   j TOW j  EF j j TOW j  EF j þ

ð1Þ

where: CH4 emissions expressed in kg CH4 per year TOWj = total organic load in domestic wastewater expressed in kg BOD or COD per year EFj = emission factor, kg CH4 per kg BOD (for domestic wastewater) j = type of CW The CH4 emission factor for constructed wetlands is shown in Eq. (2). EFj ¼ Bo  MCFj

ð2Þ

where: Bo = maximum CH4 producing capacity, kg CH4 per kg BOD or COD MCF = methane correction factor (fraction) j = type of CW According to IPCC (2013), the default Bo value for domestic wastewater is 0.6 kg CH4 per kg BOD. The methane correction factors (MCF) for HSF CW is equal to 0.1. The general equation for estimating the N2O emissions from CW for domestic wastewater treatment is given by Eq. (3). N2 O emissions ¼

X   j N j  EF j  44=28

ð3Þ

where: N2O emission = kg N2O per year Nj = total nitrogen load in domestic wastewater (kg N per year) Nj = total nitrogen in industrial wastewater (kg N per year) EFj = emission factor, kg N2O-N/kg N j = type of CW The factor 44/28 is the conversion of kg N2O-N into kg N2O.

Fig. 1. System boundaries.

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3. Results and discussion

Table 2 COD fractions result from mass balance. COD fractions

Contribution

Influent COD Effluent COD

100% 30% 42.5% 7.9% 2.2% 2.4% 14.9%

Methane (CH4)

Biogas Dissolved Waste gas

Sulfate reduction Biological Sludge

3.1. Impact assessment of the construction and operation phases

Load 3.07 0.92 1.31 0.24 0.07 0.07 0.46

kg kg kg kg kg kg kg

h−1 h−1 h−1 h−1 h−1 h−1 h−1

The N2O emission factor for HSF CW is 0.0079 kg N2O-N per kg N (IPCC, 2013). GHG emissions are important sustainable development indicators for wastewater treatment plants. However, according to Gallego-Schmid and Tarpani (2019), only half of the analyzed studies in developing countries included direct GHG emissions and 30% estimated any N2O emissions. The direct CH4 emissions from UASB reactors are difficult to estimate because of their measurements, and due to the influence of specific site conditions, such as climate and organic matter load. The direct CH4 emissions from the UASB reactor were based on mass balance, which was based on specific Brazilian conditions, therefore increasing the representativeness of the data. However, the same could not be done for the GHG emissions from the CW, which were based on emission factors found only in the literature (IPCC, 2013). Despite the GHG emissions from the CW being influenced by soil, climate and plants management (Mander et al., 2014), it was used the emissions factor from the literature. Although with some uncertainty, it is better to use data from the literature than to exclude these direct emissions. One of the premises of the CML method is that the carbon dioxide produced by the degradation of organic matter present in wastewater is biogenic. Therefore, according to this method, this amount of CO 2 is part of the natural carbon cycle and should not be counted as a pollutant in emissions to air (Renou et al., 2008; FOLEY et al., 2010). It is noteworthy that the CO2 produced in the UASB reactor and constructed wetlands was considered biogenic and the quantity is negligible when included in the natural carbon cycle on a planetary scale. It is necessary to replace the support material (gravel) of each CW bed every five years due to clogging. That has been taken into account in the LCI and the contaminated gravel removed was considered as waste (Table 3). A detailed LCA is critical to the interpretation of results in the face of material and energy flows, since the LCA intends to identify the impact chain from extraction to final disposal. Therefore, it is necessary to know which inputs, background processes and outputs are related to the potential impacts shown in the results.

2.4. Life cycle impact assessment The Impact Assessment was carried out using the CML 2 baseline 2000 and Cumulative Energy Demand (CED) assessment method provided in SimaPro® 8.1, which has been frequently used for midpoint impact categories. Gallego-Schmid and Tarpani (2019) conducted an extensive literature review and demonstrated that the CML impact assessment method is one of the well-established methods for performance tracking and the most applied in LCA related to WWTP in developing countries. The contribution analysis was used for the interpretation of the impact assessment results. The midpoint impact categories included in our study were: abiotic depletion (AD), global warming (GW), ozone layer depletion (OLD), human toxicity (HT), fresh water ecotoxicity (FWE), marine aquatic ecotoxicity (MAE), terrestrial ecotoxicity (TE) photochemical oxidation (PO), Acidification (AC), eutrophication (EU).

The Fig. 2 shows the impact potential of each wastewater treatment step by using the CML method. The result shows that impacts that are more relevant are the WWTP construction and operation phases. The WWTP_Co shows the greatest impact potential for Abiotic depletion, Ozone layer depletion, all toxicity categories and Acidification, mainly, due to the use of reinforcing steel during concrete production. Although several LCA studies in WWTP point out that the operation phase has an impact potential greater than the construction phase (Renou et al., 2008; Foley et al., 2010; Lopsik, 2013; Limphitakphong et al., 2016). The result shows that the WWTP_Co phase is responsible for a significant potential impact, mainly recognizing that this configuration (UASB + CW) is a low operational complexity WWTP. Cornejo et al. (2013) analyzing a system composed by a UASB reactor and maturation ponds, concluded that the construction phase has a greater impact than the operation phase for embodied energy due to the low electricity and material consumption needed to operate and maintain this system. Lutterbeck et al. (2017) noted that 67% of the environmental impacts were related to the construction phase of the WWTP, composed by a UASB reactor combined with an anaerobic filter, subsurface constructed wetlands, and disinfection with ultraviolet radiation. Although low complexity treatment technologies require less energy, they occupy large areas and much raw material for their construction. Despite UASB reactors followed by post-treatment not being common in Europe and developed countries, some authors highlight the importance of evaluating the construction phase of CW (Dixon et al., 2003; Lopsik, 2013). The construction phase should not be excluded in LCA studies of low complexity wastewater treatment technologies (e.g. UASB reactor, anaerobic filters, constructed wetlands and stabilization pond systems). In such cases, there is a trade-off between the use of materials and energy for the construction and the low energy and materials consumption during the operation phase. The WWTP_Op phase is responsible for a great impact potential for Global warming (96%) and for Photochemical oxidation (94%) due to methane (CH4) and dinitrogen monoxide (N2O) direct air emissions (Fig. 2). One of the main characteristics of anaerobic reactors is the biogas generation, mainly composed of CH4. The biogas generation in UASB reactors plays an important role, since it can be positive, if this biogas is recovered, or negative if this biogas is sent directly to the atmosphere. Unfortunately, in most WWTPs built in developing countries, biogas is sent to the atmosphere without treatment. Therefore, the search for eco-efficiency in these WWTP needs to consider this aspect and seek technological solutions for the use of biogas. However, one of the main challenges in implementing the principles of circular economy in small WWTP is how to take advantage of the biogas energy in small WWTP without raising operating costs. The impacts from Sewer system_Co and Sludge disposal_Op are negligible mainly due to low material and energy consumption. The studied WWTP can be considered small and decentralized which means that the sewer collection is provided by a free flow system without pumping, the extension of the sewage collection network is approximately equal to 1.1 km it is not a significant source of CH4 emission as can be seen in Fig. 2. 3.2. Energy consumption for the WWTP The electricity consumption at the WWTP for the operation phase was 0.18 kWh m−3, whereas for all WWT systems it was 0.30 kWh m −3 . This result is below average for non-extensive treatments, which explains the low impact potential of the operation phase for some impact categories. When comparing the studies conducted in Europe to the ones conducted in countries with an electricity mix

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Table 3 Life cycle inventory (LCI) of wastewater treatment system. Inputs

SDc

Source

a

Sewer system_Co Cement, Portland {RoW} Sand {GLO} Gravel, crushed {GLO} Tap water {RoW} Extrusion, plastic pipes {GLO}

0.013 0.040 0.040 0.008 0.005

kg kg kg kg kg

m−3 m−3 m−3 m−3 m−3

1.13 1.13 1.13 1.13 1.13

WWTP Project

Pre treatment_Coa Reinforcing steel {GLO} Cement, Portland {RoW} Sand {GLO} Gravel, crushed {GLO} Tap water {RoW} Extrusion, plastic pipes {GLO} Sawnwood, hardwood, raw, kiln dried {RoW} Electricity, medium voltage {BR} Transport, freight, lorry N32 metric ton, {RoW}

0.002 0.007 0.325 0.022 0.005 0.001 0.001 0.001 0.003

kg m−3 kg m−3 kg m−3 kg m−3 kg m−3 kg m−3 m3 m−3 kWh m−3 tkm m−3

1.13 1.13 1.13 1.13 1.13 1.13 1.13 1.13 2.02

WWTP Project

Pre treatment_Opb Electricity, medium voltage {BR} Transport, freight, lorry N32 metric ton, {RoW}

0.114 0.001

kWh m−3 tkm m−3

1.13 2.34

WWTP Project

WWTP_Coa Reinforcing steel {GLO} Cement, Portland {RoW} Sand {GLO} Gravel, crushed {GLO} Tap water {RoW} Extrusion, plastic pipes {GLO} Sawnwood, hardwood, raw, kiln dried {RoW} Brick {GLO} Glass fibre {GLO} Electricity, medium voltage {BR} Transport, freight, lorry N32 metric ton, {RoW}

0.055 0.078 0.704 1.479 0.053 0.002 0.001 0.003 0.001 0.001 0.010

kg m−3 kg m−3 kg m−3 kg m−3 kg m−3 kg m−3 m3 m−3 kg m−3 kg m−3 kWh m−3 tkm m−3

1.13 1.13 1.13 1.13 1.13 1.13 1.13 1.13 2.07 1.13 2.34

WWTP Project

WWTP_Opb Electricity, medium voltage {BR} Gravel, crushed {GLO} Sodium hypochlorite, without water, in 15% solution{GLO}

0.180 0.925 0.030

kWh m−3 kg m−3 kg m−3

1.06 1.13 1.22

WWTP Project

0.351 0.001

kg m−3 kg m−3

1.32 1.49

Lobato et al., 2012 IPCC, 2013

0.925

kg m−3

1.63

Operation report

Sludge Disposal_Op Sludge Transport, freight, lorry N32 metric ton, {RoW}

0.115 0.003

kg m−3 tkm m−3

1.52 2.34

Operation report

Water emissions Solids, inorganic Nitrogen Phosphorus Potassium

0.005 0.001 0.001 0.001

kg kg kg kg

m−3 m−3 m−3 m−3

1.63 1.63 1.63 1.63

Lima et al., 2018

Effluent Discharge_Coa Cast iron {GLO}

0.003

kg m−3

1.13

WWTP Project

Effluent Discharge_Op Electricity, medium voltage {BR}

0.137

kWh m−3

1.13

WWTP Project

Water emissions BOD5, biological oxygen demand COD, chemical oxygen demand TSS, suspended solids, unspecified Nitrogen, total (TKN) Nitrate Phosphorus, total Chlorine free Methane dissolved

0.021 0.096 0.018 0.046 0.002 0.008 0.001 0.136

kg kg kg kg kg kg kg kg

m−3 m−3 m−3 m−3 m−3 m−3 m−3 m−3

1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

Laboratory analysis

Air emissions Methane, biogenic Dinitrogen monoxide Final waste Waste, final, inert b

b

GLO means global and represents activities, which are considered to be an average valid for all countries in the world. RoW represents the Rest-of-the-World. in Ecoinvent® database. BR (Brazil) – geographic location. a Co = construction. b Op = Operation. c SD = Standard Deviation.

Operation report Lobato et al., 2012

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3.3. The contribution of air emissions and nutrient removal

based on renewable energy, it could be seen that the energy consumption may not have a great potential impact during the WWTP life cycle. According to Gallego-Schmid and Tarpani (2019), in the review of a LCA applied to wastewater treatment, in developing countries the average electricity consumption for domestic wastewater treatments was 0.42 kWh m −3, while in developed countries this value was 0.50 kWh m−3. The Brazilian electricity mix and its wastewater treatment technologies of low operational complexity, which does not present high energy and materials consumption, contribute to a reduction of the impact potential for some categories. Otherwise, these technologies would produce treated effluents with a slightly higher content of organic matter and nutrients, which would compromise other impact categories, such as Eutrophication. Moreover, the results shows the WWTP_Co phase had a significantly contribution to the Cumulative Energy Demand (CED) than the operation phase (Fig. 3). The construction materials consumption shows a significant impact potential because of the use of reinforcing steel, the cement Portland, and in less extension, the gravel. The reinforcing steel has a greater impact potential because of the production process, which includes the mining and the manufacturing of the steel. Igos et al. (2014) show that the useful life of reinforced concrete and steel used in the infrastructure is an important parameter since the infrastructure impact is amortized over its lifetime. Therefore, the results highlight the importance of including infrastructure in LCA related to WWTP in a transparent and consistent manner, specifying what materials are included and lifetime.

The emissions from WWTP_Op, including direct and indirect emissions, were 8.01 kg CO2-eq m−3 (Fig. 4), which is much higher than the ones found in the literature. Cornejo et al. (2013) found 2.0 kg CO2-eq m−3 of direct emissions when analyzing a WWTP composed by a UASB reactor followed by a stabilization pond; the authors did not include the N2O emissions. Nevertheless, Fuchs et al. (2011) compared the vertical and horizontal flow constructed wetlands including the CH4 e N2O emissions, and have shown that there was a huge influence on climate change when including the N2O emissions during the operation phase. It is worth mentioning that the CH4 production on the anaerobic process depends primarily on the quantity of degradable organic matter in the wastewater inflow, and on the temperature (between or higher than 24-32 °C at local WWTP/Northeast of Brazil), and that the temperature increases the CH4 production (IPCC, 2019). The UASB reactors are the largest contributors to CH4 emissions if they are not recovered or flared. According to Bressani-Ribeiro et al. (2019), the use of thermal energy for biogas recovery has proven to be a good alternative to mitigate environmental impacts resulting from the use of UASB reactors and small scale WWTP (2000 ≥ PE b 10,000 inhabitants). Furthermore, the use of a UASB reactor as a pre-treatment for CW could prevent gravel bed clogging and consequently reduce the formation of GHG in this system. Since CH4 emissions are the most important air emissions, it is suggested that a UASB reactor with CW could reduce the impacts of Global warming and Photochemical oxidation. The results point out the trade-off between the low operation consumption and the air emissions from a UASB reactor as a pretreatment of CW. Greenhouse gas emissions (e.g. CH4 and N2O) have a significant impact on WWTP_Op. Therefore, wastewater treatment experts should not neglect the air emissions in the assessment of the impacts from WWTP, especially those that apply anaerobic route to some of the process steps, such as sludge digestion, emphasizing the need to mitigate the GHG direct emissions. The results obtained from laboratory analysis on aliquots collected in the studied WWTP showed that UASB reactors followed by HSF CW was not effective in removing nitrogen and phosphorus. These macronutrients present in a treated effluent were responsible for the Discharge_Op impacts (98%) in the Eutrophication category as can be seen in Fig. 2. The eutrophication potential was 0.046 kgPO4eq m−3 by treated wastewater. This result is similar to the ones Cornejo et al. (2013) found for the stabilization pond system (0.034 kgPO4eq m−3) and the UASB followed by a stabilization pond (0.051 kgPO4eq m−3). Eutrophication is considered as a key category in LCA studies of WWTP because its results define the trade-off between process efficiency and effluent quality.

Fig. 3. Cumulative Energy Demand (CED) for the total WWT system. Legend: Co – Construction phase; Op – Operation phase.

Fig. 4. Global warming (GWP100a) for the total WWT system. Legend: Co – Construction phase; Op – Operation phase.

Fig. 2. Description of the WWTP impacts with the CML impact assessment method. Legend: Co – Construction phase; Op – Operation phase.

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The HSF CW are primarily designed to remove organics and suspended solids and do not promote significant nutrient removal. Proper management of macrophytes in CW beds contributes to better nutrient removal. Considering the results, which have shown high GWP for WWTP_Op, it is evident that there is a straight correlation between the nutrients removal efficiency and the Global warming potential. Saeed and Sun (2017) carried out a broad review of the literature on nutrient removal in HSF CW. These authors concluded that the removal of phosphorus was only possible with the insertion of P-adsorbing materials in the bed filter. Phosphorus is the limiting nutrient for the occurrence of eutrophication in aquatic environments; what explains the high impact potential for Discharge_Op. The LCA considers impacts in the local context to be as important as those that occur far away and later on (Gallego-Schimid and Tarpani, 2019). The results are consistently by pointing out the potential environmental impacts that play a role locally and globally for wastewater treatment process studied. Furthermore, it stands out the relationship between the potential impacts pointed out in the LCA study and the planet's boundaries that already been transgressed, going therefore against the safety of humanity. Some of those aspects are the climate change, and nitrogen and phosphorus flows, which emphasize the importance of evaluating and improving the environmental performance of WWTP (Steffen et al., 2015). The LCA does not prioritize any impact category for WWT, since it would require knowledge of local specificities to determine priority actions for improving the environmental performance of the WWTP (Rodriguez-Garcia et al., 2014). However, it is clear that the layout and design of a wastewater treatment plant must be aligned with the concepts of resource recovery. Moreover, the environmental laws and regulations established in developing countries need to integrate the life cycle assessment, including not only discharge restrictions but also how to stimulate the reduction of energy and water consumption, and waste generation, besides enabling the recycling of nutrients, biogas recovery and water reclaim. One possible way is to follow some recommendations of the European Water Framework Directive that promoting integration of pollution prevention and control and environmental analysis of WWTP. Therefore, WWTP operation problems influence the results of the impact assessment. For example, the clogging and the accumulation of vegetation in the HSF CW beds, and the direct emissions of biogas without burning or reuse decrease the environmental performance of the studied system. However, the LCA studies applied to WWTP do not evaluate operational problems, as the tool does not measure whether the operation is proper, which may result in a misinterpretation. The next LCA studies should discuss if the WWT process is operating properly. The LCA does not evaluate the efficiency of treatment technologies and the operating conditions of the system. Given this, the importance of a detailed LCI was highlighted, which reflects the efficiency and operational conditions of a WWTP. In a future work, it is recommended to evaluate how to improve the process to develop the environmental performance of a WWTP.

4. Conclusions The lack of LCA studies applied to the analysis of a complete WWTS composed by a UASB reactor as a pre-treatment of CW, and the representativeness of data in developing countries represent barriers for the dissemination of this tool in these regions. Considering significant environmental impacts and the large wastewater treatment deficit in Latin America, it is very important to create conditions to disseminate LCA tools that can contribute to the evaluation and improvement of the environmental performance of a WWTP in developing countries. The results of a LCA study for the construction and operation phases of a full-scale WWTP composed of a UASB reactor followed by constructed wetlands allowed to conclude that:

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- The construction phase should not be excluded in LCA of low complexity operational wastewater treatment technologies. The use of materials and energy for construction is high when compared with the low energy and materials consumption during the operation phase. Furthermore, energy mix based on hydropower contributes to the small impact potential of this phase. - Air emissions from the UASB reactor have a great potential impact on global warming, indicating the need to mitigate GHG direct emissions. There is a correlation between nutrients removal efficiency and Global warming potential. Therefore, WWTP operation problems influence the results of the impact assessment. LCA studies should discuss if the WWT process is operating properly. The results show a correlation between operation – GHG emissions – eutrophication. - One of the main challenges for LCA studies to be used for wastewater stakeholders in developing countries is to improve data quality.

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