Abstract

The biogas produced in UASB-based sewage treatment plants (STPs) is rarely used for energy purposes and its potential is often unknown. This study aimed to propose a simple and reliable method based on energy balance to determine the technical feasibility of biogas use and the energy self-sufficiency of UASB reactors. To this end, we considered (i) electric power production (E) and (ii) electric power consumption (Econ) ascribed to sewage pumping stations (SPSs) at different pressure heads (0 to 4 m, 4.1 to 8 m, 8.1 to 12 m, and 12.1 to 16 m). The technical feasibility of biogas use was assessed by evaluating if the flow of biogas produced in the STPs would be sufficient for the functioning of a commercial motor-generator. The linear model fit to estimate the biogas energy potential (y-axis) in STPs and the sewage flow (x-axis) is represented by y = 122.65x (R2 = 0.64). In total, 1,054 STPs in Brazil use UASB reactors as treatment units, of which nearly 31% are located in the southeast. However, only 11.2% of these STPs, which serve populations of over 29,981, presented technical feasibility to recover biogas. The mathematical equations proposed in this study to estimate the net electric power production in UASB-based STPs are relevant tools for sanitation companies and can enable studies to be performed for the implementation of energy self-sufficiency projects in Brazil.

HIGHLIGHTS

  • Only 11.2% of UASB-based STPs in Brazil present technical feasibility for biogas production.

  • Among the assessed STPs, only those serving populations over 29,981 presented technical feasibility for biogas use.

  • The energy self-sufficiency of UASB reactors can be determined from mathematical equations using simple input data.

INTRODUCTION

The use of effective sewage treatment systems is essential to maintain appropriate conditions of sanitation by reducing the sewage's pollution potential, and consequently protect public health (Marzouk & Othman 2017). Among the technological alternatives to treat sewage in Brazil, Upflow Anaerobic Sludge Blanket (UASB) reactors are outstanding due to their low implementation cost, low space requirements, simple operation, and the potential for energy recovery (Khan et al. 2011). A recent survey carried out in Brazil found more than 650 full-scale reactors in operation that altogether had an installed capacity able to treat the sewage of nearly 23 million inhabitants or a flow rate of approximately 43 m3 s−1 (Chernicharo et al. 2018). According to Metcalf & Eddy (2016), the UASB reactor is the most widespread anaerobic process used to treat domestic sewage in the world.

Biogas is the main by-product of UASB reactors, and its use as an energy source could benefit the sewage treatment plant (STP) by reducing sludge volume if the exhaust gases produced in a power generator are used for drying. The use of biogas for energy purposes is widely supported in the literature; however, according to Freitas et al. (2019), this practice is still rare in Brazilian STPs. According to Santos et al. (2016), in developing countries, a great part of the biogas produced in STPs is not destined for energy production, or its use is rare and limited to a small number of STPs.

Gu et al. (2017) state that the optimization of energetic efficiency in STPs is essential, considering the increasing energy costs and the concerns on global climate changes. The authors also highlight that such energetic optimization can be achieved through energy recovery in sewage treatment processes.

In UASB-based STPs, the major energy demands are usually for the sewage pumping stations (SPSs) (Rosa et al. 2016; Vassalle et al. 2020). Although many studies have been carried out to estimate the biogas energy potential of UASB reactors (Santos et al. 2016; Mensah et al. 2021), there is scarce research that considers and evaluates the energy demands in STPs.

Energetic self-sustainability is one of the main aspects to be developed in the future of sewage treatment, especially with respect to the use of biogas for electric power production. Energy self-sufficient STPs can be defined as those that are able to produce 100% or more of their energy demand from the by-products of the sewage treatment process (Svardal & Kroiss 2011). Therefore, the energy self-sufficiency of an STP will be achieved when the energy gains from biogas recovery supply the energy demand of the treatment process. For this purpose, studies need to consider: (i) the energy potential of STPs' by-products; (ii) the energy demand for the full operation of an STP, and (iii) the generation of energy for the benefit of the STP, according to its own local demand. Obviously, the higher the difference between the available potential and the STP's power demand, the higher the energy production demand, either thermal or electric.

In order to assess the self-sufficiency of an STP, it is necessary to assess the technical feasibility of biogas use. Even though small-scale UASB-based STPs can produce biogas during sewage treatment, the biogas flow may not be sufficient for the functioning of a commercial motor-generator, which makes unfeasible its use for energy production. It is important to highlight that in such cases, other alternatives for biogas recovery can be explored, such as thermal conversion through direct combustion. The heat generated in the process can be used for other purposes in the STP, such as sanitation or thermal drying of sludge (Vassalle et al. 2020).

To contribute to this research area, this study focuses on the estimation of the energy balance in UASB-based STPs in Brazil considering the biogas production/recovery and the energy consumption by the SPSs. The innovation is the proposal of an assessment of the technical feasibility of using the biogas produced in sewage treatment processes for energy purposes as well as the energy balance considering different pressure heads used in the SPSs in all UASB-based STPs in Brazil.

METHODS

Overview and spatial distribution of UASB-based STPs in Brazil

An evaluation of the biogas energy potential in UASB-based STPs in Brazil was carried out using secondary data provided by the National Water Agency (ANA) corresponding to the most recent data on sanitation in Brazil (ANA 2017). This database consisted of population served, sewage flow, treatment process and biochemical oxygen demand (BOD) removal efficiency. The STPs were classified by size according to CONAMA Resolution no. 377/2006 (CONAMA 2006) into three groups: (i) small-sized STPs (sewage flow <56 L s−1), (ii) medium-sized STPs (56 L s−1 ≤ sewage flow ≤434 L s−1), and (iii) large STPs (sewage flow >434 L s−1).

Energetic self-sustainability in UASB-based STPs in Brazil

The energy balance was used to evaluate the energy self-sufficiency of UASB-based STPs. For that purpose, we considered: (i) the electric power production from biogas in STPs; and (ii) the electric power consumption based on the principle that the main energy consumption is associated with the SPS.

Electric power production from biogas in UASB-based STPs

The biogas energy potential in the evaluated STPs was determined using the methodology proposed by Lobato et al. (2012). The model developed by these authors to estimate the biogas energy potential considered three different scenarios: worst, typical, and best case. These scenarios were established as a function of the different characteristics of the raw sewage. The worst-case scenario is characterized by: (i) reactor fed with diluted sewage; (ii) high concentration of sulfate in sewage; (iii) low efficiency of chemical oxygen demand (COD) removal; (iv) high rates of methane losses. The best-case scenario is characterized by: (i) reactor fed with concentrated sewage, (ii) low concentration of sulfate in sewage; (iii) high efficiency of COD removal; (iv) low rates of methane losses. The typical-case scenario corresponds to intermediate conditions between the other two scenarios (worst case and best case).

The model developed by Lobato et al. (2012) was validated using monitoring data for the Laboreaux STP (Itabira, Brazil) and the Onça STP (Belo Horizonte, Brazil). Most of the results obtained by those authors for biogas production and consequent energy recovery potential for the UASB reactors in the assessed STPs focused on the value ranges simulated for the typical-case and worst-case scenarios. However, there were some values below the tendency line for the worst-case scenario. Therefore, in order to carry out a more conservative survey and avoid the overestimation of the real potential of the assessed STPs, in the current study, the estimate of the energy potential of anaerobic reactors in Brazil considered the worst-case scenario.

The model developed to estimate the biogas energy potential was conceptually structured based on COD conversion routes and methane flows in UASB reactors. The variability of input data (Table 1) was incorporated into the model through Uncertainty Analysis, which is based on the performance of a high number of simulations (in this case, the number of UASB-based STPs), called ‘Monte Carlo’ simulation. For each model run, a different set of input values is randomly selected according to a uniform distribution within pre-established ranges. The value ranges for the model input data were derived from a review of the literature as presented in Lobato et al. (2012). The value ranges were scaled for the three scenarios. For the worst-case scenario, we considered reduced COD and sulfate removal efficiencies after treatment, higher sulfate concentration in the sewage and lower percentage of CH4 in the biogas.

Table 1

Input data used in the model

ParameterUnitScenario
References
WorstTypicalBest
Contributing population (PopInhab. 1,000 to 1,000,000 – 
Per capita sewage contribution (PSC) m3·inhab−1·d−1 0.12 to 0.22 Von Sperling & Chernicharo (2005)  
Per capita COD contribution (PSCCODkgDQO·inhab−1·d−1 0.09 to 0.11 Von Sperling & Chernicharo (2005)  
Efficiency of COD removal (ECOD60 65 70 Von Sperling & Chernicharo (2005)  
Sulfur concentration in sewage (CSO4kgSO4·m−3 0.08 0.06 0.04 Singh & Viraraghavan (1998); Metcalf & Eddy (2016); Glória et al. (2008)  
Efficiency of sulfur reduction (ESO480 75 70 Souza (2010)  
Operational temperature in the reactor (T°C 20 to 30 Von Sperling & Chernicharo (2005)  
Percentage of CH4 in the biogas (CCH470 75 80 Von Sperling & Chernicharo (2005)  
ParameterUnitScenario
References
WorstTypicalBest
Contributing population (PopInhab. 1,000 to 1,000,000 – 
Per capita sewage contribution (PSC) m3·inhab−1·d−1 0.12 to 0.22 Von Sperling & Chernicharo (2005)  
Per capita COD contribution (PSCCODkgDQO·inhab−1·d−1 0.09 to 0.11 Von Sperling & Chernicharo (2005)  
Efficiency of COD removal (ECOD60 65 70 Von Sperling & Chernicharo (2005)  
Sulfur concentration in sewage (CSO4kgSO4·m−3 0.08 0.06 0.04 Singh & Viraraghavan (1998); Metcalf & Eddy (2016); Glória et al. (2008)  
Efficiency of sulfur reduction (ESO480 75 70 Souza (2010)  
Operational temperature in the reactor (T°C 20 to 30 Von Sperling & Chernicharo (2005)  
Percentage of CH4 in the biogas (CCH470 75 80 Von Sperling & Chernicharo (2005)  

Source: Adapted from Lobato et al. (2012).

Once the model input data had been defined, the different portions of the input COD (removed from the system, converted into sludge, and consumed during sulfate reduction) were estimated. The anaerobic digestion is a complex biochemical process in which the organic matter is degraded by different types of anaerobic microorganisms through sequential stages. Other than the methanogenic route, another stage can be included in the process, the sulfidogenesis, which is responsible for the production of sulfides by the sulfate-reducing bacteria (Chernicharo 2016). According to Lobato et al. (2012), the mass balance of COD in UASB reactors has to consider all possible portions involved in the process, such as: (i) portion converted into methane (present in the biogas or that escapes dissolved in the effluent or residual gas); (ii) portion due to sulfate reduction; (iii) portion that is converted into sludge (that can be subdivided into sludge retained in the reactor or carried with the effluent); and (iv) portion that is solubilized in the effluent. For this reason, Lobato et al. (2012), reported the importance of considering all metabolic routes of conversion of organic matter and biogas losses in the mass balance of COD. The portion related to sulfate reduction influences the portion converted into sludge, thus even with low sulfur concentrations in the effluent, this conversion route can interfere in the assertiveness of the estimation of biogas production.

Also, high levels of inorganic nitrogen such as ammonia and nitrate can inhibit the production of methane in the anaerobic process (Sheng et al. 2013). However, municipal sewage has low concentrations of ammonia, which makes it difficult for this effect to occur in the anaerobic process (Zuo et al. 2020).

Then the total COD converted into CH4, and consequently its volumetric production, was calculated. The volume of CH4 effectively available for energy use was calculated considering the losses of CH4 dissolved in the effluent and in the gaseous phase, along with the residual gas, as well as other eventual losses in the gaseous phase, such as leaks. Through the definitions of such losses, the available energy potential was calculated. Table 2 shows the equations used for calculating the portions of the mass balance of COD and the biogas energy potential.

Table 2

Equations used for calculating the portions of the mass balance of COD and the biogas energy potential

PortionsEquationsNotes
Estimate of mean influent flow rate  Fmean = Mean influent flow rate (m3·d−1)
Pop = population (inhab.)
PSC = per capita sewage contribution (m3·inhab−1·d−1
Estimate of daily COD mass removed from the system  CODremov = daily COD mass removed from the system (kgCOD·d−1)
PSCCOD = per capita COD contribution (kgCOD·inhab−1·d−1)
ECOD = efficiency of COD removal (%) 
Estimate of daily COD mass used by the biomass 
 
CODsludge= daily COD mass converted into biomass (kgCODsludge·d−1)
YCOD= sludge yield, as COD (kgCODsludge·kgCODrem−1)
Y = sludge yield, as total volatile solids (TVS) (0.15 kgTVS·kgCODrem−1)
KTVS-COD = conversion factor (1 kgTVS = 1.42 kgCODsludge
Estimate of sulfate load converted into sulfide  COSO4converted = load of SO4 converted into
sulfide (kgSO4·d−1)
CSO4 = Sulfur concentration in sewage (kgSO4·m−3)
ESO4= Sulfur efficiency reduction (%) 
Estimate of daily COD mass used in sulfate reduction  CODSO4 = COD used by the sulfate-reducing bacteria for sulfate reduction (kgCODSO4·d−1)
KCOD-SO4 = COD consumed in sulfate reduction (0.667 kgCODSO4·kgSO4−2
Estimate of daily COD mass converted into methane 

 
CODCH4 = daily COD mass converted into methane (kgCODCH4·d−1)
QCH4 = theoretical volumetric production of methane (m3·d−1)
R = gas constant (0.08206 atm·L·mol−1·K−1)
T = operational temperature of the reactor (°C)
P = atmospheric pressure (1 atm)
KCOD = COD of one mole of CH4 (0.064 kgCODCH4·mol−1
Estimate of methane loss 

 
QW-CH4 = methane loss as waste gas (m3·d−1)
pw = percentage of methane in the gaseous phase lost as waste gas (7.5%)
QO-CH4= other methane losses in the gaseous phase (m3·d−1)
pO= percentage of methane in the gaseous phase considered as other losses (7.5%)
QL-CH4= loss of dissolved methane in the liquid effluent (m3·d−1)
pL = concentration of dissolved methane in the liquid effluent (0.025 kg·m−3)
fCH4 = conversion factor of methane mass into COD mass (4 kgCOD·kgCH4−1
Estimate of actual methane production   Qactual-CH4 = actual production of methane available for energy recovery (m3·d−1
Energy recovery potential 
 
PEactual-CH4 = available energy potential per day (MJ)
QN-actual-CH4 = normalized methane production (Nm3·d−1)
f= temperature correction factor (2.9 kgDQO·m−3)
ECH4 = calorific value of methane (35.9 MJ·Nm−3
PortionsEquationsNotes
Estimate of mean influent flow rate  Fmean = Mean influent flow rate (m3·d−1)
Pop = population (inhab.)
PSC = per capita sewage contribution (m3·inhab−1·d−1
Estimate of daily COD mass removed from the system  CODremov = daily COD mass removed from the system (kgCOD·d−1)
PSCCOD = per capita COD contribution (kgCOD·inhab−1·d−1)
ECOD = efficiency of COD removal (%) 
Estimate of daily COD mass used by the biomass 
 
CODsludge= daily COD mass converted into biomass (kgCODsludge·d−1)
YCOD= sludge yield, as COD (kgCODsludge·kgCODrem−1)
Y = sludge yield, as total volatile solids (TVS) (0.15 kgTVS·kgCODrem−1)
KTVS-COD = conversion factor (1 kgTVS = 1.42 kgCODsludge
Estimate of sulfate load converted into sulfide  COSO4converted = load of SO4 converted into
sulfide (kgSO4·d−1)
CSO4 = Sulfur concentration in sewage (kgSO4·m−3)
ESO4= Sulfur efficiency reduction (%) 
Estimate of daily COD mass used in sulfate reduction  CODSO4 = COD used by the sulfate-reducing bacteria for sulfate reduction (kgCODSO4·d−1)
KCOD-SO4 = COD consumed in sulfate reduction (0.667 kgCODSO4·kgSO4−2
Estimate of daily COD mass converted into methane 

 
CODCH4 = daily COD mass converted into methane (kgCODCH4·d−1)
QCH4 = theoretical volumetric production of methane (m3·d−1)
R = gas constant (0.08206 atm·L·mol−1·K−1)
T = operational temperature of the reactor (°C)
P = atmospheric pressure (1 atm)
KCOD = COD of one mole of CH4 (0.064 kgCODCH4·mol−1
Estimate of methane loss 

 
QW-CH4 = methane loss as waste gas (m3·d−1)
pw = percentage of methane in the gaseous phase lost as waste gas (7.5%)
QO-CH4= other methane losses in the gaseous phase (m3·d−1)
pO= percentage of methane in the gaseous phase considered as other losses (7.5%)
QL-CH4= loss of dissolved methane in the liquid effluent (m3·d−1)
pL = concentration of dissolved methane in the liquid effluent (0.025 kg·m−3)
fCH4 = conversion factor of methane mass into COD mass (4 kgCOD·kgCH4−1
Estimate of actual methane production   Qactual-CH4 = actual production of methane available for energy recovery (m3·d−1
Energy recovery potential 
 
PEactual-CH4 = available energy potential per day (MJ)
QN-actual-CH4 = normalized methane production (Nm3·d−1)
f= temperature correction factor (2.9 kgDQO·m−3)
ECH4 = calorific value of methane (35.9 MJ·Nm−3

Source: Adapted from Lobato et al. (2012).

After running the mathematical model for all STPs, a linear regression equation was obtained for ‘sewage flow’ (x-axis) and ‘biogas energy potential’ (y-axis). This equation was used to determine the biogas energy potential (PEactual-CH4) of the UASB-based STPs in Brazil, according to ANA (2017). The electric power production (E) was calculated considering the use of internal combustion engines (ICEs). According to the manufacturer ER-BR – Energias Renováveis Ltda, the motor-generator functions 8,000 h per year, which corresponds to 22 h per day, deducting the hours destined to the maintenance of the equipment. Thus, we considered an average operating time of 22 hours (t); the conversion coefficients of the motor-generator and the alternator are indicated in Table 3. Lastly, we created theme maps that enabled quick visualization of the biogas energy potential of the UASB-based STPs all over Brazil.

Table 3

Equations used to estimate energy consumption and net electric power of SPSs in UASB-based STPs

PortionsEquationsNotes
Electric power production 
Electric power   Pot= electric power per day (MJ)
PEactual-CH4 = energy potential of biogas per day (MJ)
ηe = fuel conversion efficiency (33.0%) (CETESB 2006)
ηg= engine-alternator performance (91.5%) 
Electric power available  E = electric power production per day (kWh)
tice= ICE operating time (22 h d−1
Electric power consumption 
Required pump power  Pb = pump power (kW)
γ = specific weight of water (1,000 kg m−3)
g = acceleration of gravity (9.8 m s−2)
Fmean = mean influent flow rate (m3s−1)
Hb = pressure head (m)
ηb = pumping efficiency (60.0%) 
Energy consumption   Econ = electric power consumption per day (kWh)
tsps = SPS operating time (22 h d−1
Excess energy (Energy balance) 
Net electric power production   Enet = net electric power production per day (kWh) 
PortionsEquationsNotes
Electric power production 
Electric power   Pot= electric power per day (MJ)
PEactual-CH4 = energy potential of biogas per day (MJ)
ηe = fuel conversion efficiency (33.0%) (CETESB 2006)
ηg= engine-alternator performance (91.5%) 
Electric power available  E = electric power production per day (kWh)
tice= ICE operating time (22 h d−1
Electric power consumption 
Required pump power  Pb = pump power (kW)
γ = specific weight of water (1,000 kg m−3)
g = acceleration of gravity (9.8 m s−2)
Fmean = mean influent flow rate (m3s−1)
Hb = pressure head (m)
ηb = pumping efficiency (60.0%) 
Energy consumption   Econ = electric power consumption per day (kWh)
tsps = SPS operating time (22 h d−1
Excess energy (Energy balance) 
Net electric power production   Enet = net electric power production per day (kWh) 

The ICE was selected based on the characteristics associated with this alternative, considering the reality of Brazilian STPs. According to Freitas et al. (2019), ICEs, gas turbines, and microturbines are the main alternatives for combined generation of electricity and heat from biogas. The ICEs present the advantages of moderate investment cost, simple maintenance, great potential of energy recovery, stable operation, and high reliability, in addition to being a mature and widely used technology for energy generation from biogas. Conversely, gas turbines have high acquisition and operational costs, and microturbines have lower efficiency when compared to ICEs. Therefore, the ICEs were considered more appropriate for energy production from biogas in Brazilian STPs.

Electric power consumption in UASB-based STPs

A study developed by Rosa et al. (2016) for UASB-based STPs showed that almost all of the energy required at these plants was related to the operation of the SPSs. Similarly, to assess the energy self-sufficiency of a UASB-based STP, Vassalle et al. (2020) assumed that the energy demand of a UASB system is that required for pumping the sewage. Thus, the evaluation of the energy self-sufficiency of STPs in the current study was based on an assessment of the difference between the electric power that can be produced in the STPs and the electric power consumption in the SPSs.

The equations used to estimate the electric power consumption in the SPSs are presented in Table 3 (electric power consumption). As in the calculation of the electric power production, the energy consumption in the SPSs was incorporated into the model through a Monte Carlo simulation. To do so, different pressure heads for each of the 250 simulations carried out were randomly selected into three different ranges: 0 to 4 m, 4.1 to 8 m, 8.1 to 12 m, and 12.1 to 16 m (Figure 1). For each model run, a different set of input values was randomly selected, within the pre-established ranges.

Figure 1

Schematics of the different pressure heads used to estimate energy consumption in the SPSs: (a) 0 to 4 m; (b) 4.1 to 8 m; (c) 8.1 to 12 m; (d) 12.1 to 16 m.

Figure 1

Schematics of the different pressure heads used to estimate energy consumption in the SPSs: (a) 0 to 4 m; (b) 4.1 to 8 m; (c) 8.1 to 12 m; (d) 12.1 to 16 m.

To calculate the power of the pumping sets (Pb), we considered a motor-pump set yield of 60%, minimum reference value reported by Mota (1969). The excess electric power production in each STP (Enet) was calculated based on the difference between the electric power that could be produced by using the biogas in the STPs and the energy consumption associated with the SPSs, as indicated in Table 3 (excess energy).

In order to establish the relationship between sewage flow and electric power production in the STPs, after the model run, the least squares method was used to provide a regression equation (‘sewage flow’ on the x-axis and ‘net electric power production’ on the y-axis), and a first-degree linear model was fit to the data. To verify whether the STPs operating in Brazil (ANA 2017) have the capacity to produce excess energy, the STPs' flow data were applied to the fitted regression equation.

Technical feasibility of biogas use in UASB-based STPs

After determining the net electric power production in the assessed STPs, an evaluation of the technical feasibility of using the biogas to produce energy was carried out. This evaluation was based on the assumption that STPs which serve small populations could not produce sufficient biogas for the functioning of a motor-generator, which would stop the conversion of the produced biogas into electric power. For that assessment, we consulted the catalogs of the biogas-powered motor-generators available on the market in order to identify the minimum flow required for their functioning. After defining the lowest biogas flow required for the operation of the consulted motor-generators, we calculated the methane and biogas flows that could be produced in each of the STPs assessed, using Equations (1) and (2), respectively:
formula
(1)
where
  • PEactual-CH4 = available energy potential per day (MJ)

  • QN-actual-CH4= normalized methane production (Nm3.d−1)

  • ECH4= calorific value of methane (35.9 MJ·Nm−3)
    formula
    (2)
    where
  • Qbiogas= normalized biogas production (Nm3.d−1)

  • CCH4= percentage of CH4 in the biogas (%).

The percentage of CH4 in the biogas was 70%, considering that this value was used by Lobato et al. (2012) to represent the worst-case scenario assessed for estimating the energy content in biogas (Table 1).

The biogas flow that could be produced in each of the assessed STPs was compared to the minimum flow required for the operation of the motor-generators available on the market (336 Nm3 d−1) (ENERMAC 2020). The STPs which presented biogas flow higher than the minimum for operation of the motor-generator were defined as those for which the biogas energy use is technically feasible.

RESULTS AND DISCUSSION

Overview and spatial distribution of the UASB-based STPs in Brazil

In the database available at ANA (2017), 1,054 STPs using UASB reactors as treatment units were identified in Brazil. Figure 2 shows the UASB-based STPs in Brazil, classified by size according to the directions of the CONAMA Resolution no. 377 (CONAMA 2006).

Figure 2

Size of the UASB-based STPs in Brazil.

Figure 2

Size of the UASB-based STPs in Brazil.

Among the post-treatment alternatives at the STPs are anaerobic filters, biological filters, stabilization ponds, activated sludge, aerated ponds, physical-chemical treatment or soil disposal. The global BOD removal efficiencies of these STPs ranged from 46 to 99%. However, nearly 73% of them have BOD removal efficiencies higher than 70%, which is the typical value described by Von Sperling (2007) for UASB reactors treating domestic sewage.

There is a predominance of small-sized STPs in the country, a total of 911, that serve populations of 15 to 37,407 inhabitants. Such STPs are especially in the south and southeast. This fact was also observed by Noyola et al. (2012), who reported a large number of small-sized STPs operating with low flows (<25 L s−1) or very low flows (<5 L s−1) in Latin America. Only 10 STPs were classified as large, of which five are in the southeast, three in the south, and two in the central west.

Electric power production from biogas in UASB-based STPs

After running the model to estimate the biogas energy potential (Table 2), using the input data presented in Table 1, we obtained the estimates of this potential presented in Figure 3. Table 4 shows the fitted linear model considering the simulated data to estimate the biogas energy potential and the sewage flow, obtained through linear regression. The proposed model enabled a more precise estimation of biogas production from COD degradation since it considered all degradation routes – methanogenesis, sulfidogenesis, and methane losses in the reactor (as residual gas or dissolved in the effluent) – avoiding the overestimation of biogas production. Also, the model allowed us to simulate the biogas energy potential for different sizes of STPs.

Table 4

Regression equation and determination coefficient (R2) (sewage flow × biogas energy potential) for the UASB-based STPs in Brazil

By-productRelation (x,y)Statistical modelR2
Biogas L·s−1 x MJ y = 122.65x 0.64 
By-productRelation (x,y)Statistical modelR2
Biogas L·s−1 x MJ y = 122.65x 0.64 

Note: y = biogas energy potential per day (MJ), x = sewage flow (L·s−1), R2 = determination coefficient.

Figure 3

Estimates of the potential energy recovery from biogas in UASB reactors treating domestic sewage. Note: In the UASB-based STPs operating in Brazil, the sewage flow ranges from 0.01 a 2,200 L s−1.

Figure 3

Estimates of the potential energy recovery from biogas in UASB reactors treating domestic sewage. Note: In the UASB-based STPs operating in Brazil, the sewage flow ranges from 0.01 a 2,200 L s−1.

Figure 4 presents the electric power production potential of the UASB-based STPs in Brazil. Most of the STPs present energy production lower per day than 1,000 kWh and more than 50% of the Brazilian states produce per day up to 5,000 kWh. Also, the STPs with higher energy potential are those in the states of Paraná (PR), Minas Gerais (MG), and São Paulo (SP). According to Chernicharo et al. (2018), 89% of the STPs in PR, 79% in MG, and 12% in SP use UASB reactors for sewage treatment. Those authors also highlight that this predominance of UASB reactors in PR and MG is due to a preference for compact systems, with lower acquisition and maintenance costs compared to aerobic systems, in addition to research incentives for this type of treatment system in these states.

Figure 4

Electric power production potential (E) in Brazil by STP and region.

Figure 4

Electric power production potential (E) in Brazil by STP and region.

According to Valente (2015), the use of UASB reactors in large STPs in Brazil is seen as an opportunity for the use of biogas to produce electricity. This opportunity is based on studies that assessed indicators such as economic feasibility for the installation of collection infrastructure, storage, treatment and biogas compression, and the generation of electricity.

Despite the advantages of using biogas for energy purposes, it is important to consider the need for its treatment. Biogas can contain H2S in its composition, which, in levels over 300–500 ppm after combustion, can damage the internal combustion engine and reduce its lifespan (Holm-Nielsen et al. 2009). Therefore, the biogas desulfurization is necessary, either by physical–chemical or biological processes. Biogas compression, in turn, guarantees a suitable biogas flow into the motor-generator (Valente 2015).

Figure 5 shows that the southeast presents the highest potential, followed by the south. This potential is associated with the geographic distribution of the STPs in Brazil since nearly 31% of the studied STPs are located in the southeast. This region, according to ANA (2017), also presents the best sewage treatment indices in the country, where 54% of the population is served by sanitation services. Conversely, the north is lacking with respect to the availability of basic sanitation, and only 12% of the population is served by sanitation services. Consequently, this region has the lowest potential for electric power production.

Figure 5

Distribution of electric power production potential from biogas in the Brazilian regions.

Figure 5

Distribution of electric power production potential from biogas in the Brazilian regions.

The small-sized STPs had the lowest electric power production potential, showing values per day between 0.6 and 515 kWh and a mean value of 91 kwh. Conversely, the large STPs presented energy production per day between 4,329 and 20,753 kwh. Although there are only 10 large STPs, the electric power production values they presented are between 400 and 875 times the production values presented by the small-sized STPs (911 STPs).

A greater variability in electric power production potential was observed for the large STPs, which was related to the presence of STPs with sewage flows between 412 and 2,200 L s−1 (contributing population of 229,661 to 604,895 inhabitants). As for the medium-sized STPs (133 STPs), an electric power production potential per day from 540 to 3,979 kWh was observed. This range is coherent with the study carried out by Rosa et al. (2018), who assessed the electric power production potential of the Itabira STP (Itabira, MG), which presents a mean sewage flow of 78 L s−1, and obtained an electric power production per day of 3,045 kWh from biogas. Additionally, we estimate that all STPs together (small, medium, and large), with a total population of 21,436,482 inhabitants, could produce per day 350,994 kwh.

When assessing the unitary relationship of energy production in the STPs per sewage volume, we verified that the UASB reactors present an estimated biogas production of nearly 1.4 MJ m−3. This value was similar to that obtained from the simulations carried out by Lobato et al. (2012), who showed a mean value of 1.5 MJ m−3 in the worst-case scenario evaluated.

Net electric power production in UASB-based STPs

Table 5 presents the equations, considering the simulated data, to estimate the ‘net electric power production’ (y-axis) as a function of the variable ‘sewage flow’ in the UASB-based STPs (x-axis) according to different pressure heads. The linear statistical model indicated a significant regression coefficient (p-value <0.05) that points to a model fit at the 5% significance level.

Table 5

Linear statistical model for each pressure head

Pressure head (m)Small
Medium
Large
Statistical model¹R2Statistical modelR2Statistical modelR2
0 to 4 y = 9,329.2x 0.85 y = 9,833.2x 0.86 y = 10,148.0x 0.86 
4.1 to 8 y = 7,865.5x 0.79 y = 8,388.4x 0.82 y = 8,718.6x 0.82 
8.1 to 12 y = 6,404.7x 0.72 y = 6,927.0x 0.75 y = 7,295.3x 0.76 
12.1 to 16 y = 5,511.9x 0.68 y = 6,042.4x 0.70 y = 5,569.4x 0.69 
Pressure head (m)Small
Medium
Large
Statistical model¹R2Statistical modelR2Statistical modelR2
0 to 4 y = 9,329.2x 0.85 y = 9,833.2x 0.86 y = 10,148.0x 0.86 
4.1 to 8 y = 7,865.5x 0.79 y = 8,388.4x 0.82 y = 8,718.6x 0.82 
8.1 to 12 y = 6,404.7x 0.72 y = 6,927.0x 0.75 y = 7,295.3x 0.76 
12.1 to 16 y = 5,511.9x 0.68 y = 6,042.4x 0.70 y = 5,569.4x 0.69 

Note: ¹ y = net electric power production per day (kWh); x = sewage flow (m3 s−1); R2 = coefficient of determination.

Note: Equations for STPs with sewage flows ranging from 0.01 to 2,500 L s−1.

The electric power potential of the STPs was obtained from the equations indicated in Table 5 and flow data for the 1,054 STPs operating in Brazil. The results for the different STP sizes and pressure heads are shown in Figure 6. The results show that the electric power produced from biogas would be sufficient to maintain the operation of SPSs and still produce excess energy in UASB-based STPs operating in Brazil. The net electric power could supply other sectors and activities at the STPs such as sludge dehydration units, sludge pumps, laboratory equipment, lighting, administration, post-treatment units or even to be fed back to the network.

Figure 6

Net electric power production considering different ranges of pressure heads and STPs of different sizes (small, medium, and large).

Figure 6

Net electric power production considering different ranges of pressure heads and STPs of different sizes (small, medium, and large).

Figure 7

Indication of the UASB-based STPs operating in Brazil with technical feasibility for biogas energy use.

Figure 7

Indication of the UASB-based STPs operating in Brazil with technical feasibility for biogas energy use.

Figure 6 shows that the highest net electric power values occurred in large STPs with SPSs that have up to 4 m of pressure head. This result is justified by the direct proportional relationship between sewage flow and electric power production, as shown by the regression equation in Table 4. Additionally, SPSs with lower pressure heads require less energy for sewage pumping, which consequently results in a higher net production of electric power in such situations.

Mathematical equations are relevant tools for sanitation companies and their use can enable studies for the implementation of energy self-sufficiency projects using simple input data. The linear statistical model can be used to determine the net electric power production in UASB reactors using simple parameters (sewage flow and pressure head) and stands out for its simplicity and ease of use. However, it is important to highlight that the energy balance of the STPs carried out in this study considered only the potential for energy supply of the SPSs, and other demands were not taken into account.

Although the main energy demand in UASB-based STPs is associated with the operation of the SPSs (Rosa et al. 2016), another important process to be considered is sludge dehydration, as mentioned by Sillanpaa (2020). However, assessing the energy demand for such process is still a challenge due to the lack of public data regarding the type of system used in the STPs, which can be mechanical (filter press, centrifuge, among others) or natural systems (drying beds). Also, when using mechanical equipment, the energy consumption depends on the operational conditions and the concentration of the sludge removed during disposal routines, which makes it difficult to perform a holistic assessment involving the main energy demands for STPs all over the country. Therefore, future research can evaluate the energy demands from sludge dehydration, if data for such analysis are available.

Technical feasibility of biogas use in UASB-based STPs

Despite the fact that all UASB-based STPs presented a positive energy balance, i.e., the capacity to supply the energy demands of the SPSs, only 11.2% of the STPs (118 units) presented the technical feasibility for biogas energy recovery, considering 336 Nm3 d−1 as the minimum biogas flow. Among the STPs assessed in the country, only those with sewage flow higher than 70.3 L s−1 would be able to produce enough biogas to be considered technically feasible, corresponding to the STPs with contributing populations of over 29,981. Among them, 10 are classified as large, with contributing populations between 229,661 and 604,895 inhabitants, and 108 as medium-sized STPs (29,981 to 293,380 inhabitants) (Figure 7). Therefore, according to the mathematical model used in this study, the small-sized UASB-based STPs operating in Brazil do not have technical feasibility for biogas energy recovery.

Despite this study's indication of 118 STPs in Brazil with technical feasibility for biogas energy use, a survey carried out by Lopes et al. (2020) showed that only four UASB-based STPs make use of such potential effectively, two of them in Minas Gerais, one in São Paulo, and one in Paraná.

The net electric power production per day at STPs with technical feasibility ranged from 562 to 4,148 kWh (0 to 4 m), 480 to 3,539 kWh (4.1 to 8 m), 396 to 2,922 kWh (8.1 to 12 m), and 345 to 2,549 kWh (12.1 to 16 m) in medium-sized STPs. Large STPs presented values from 4,657 to 22,326 kWh (0 to 4 m), 4,001 to 19,181 kWh (4.1 to 8 m), 3,348 to 16,050 kWh (8.1 to 12 m), and 2,556 to 12,253 kWh (12.1 to 16 m). Thus, the size of the STP has an expressive impact on its self-sufficiency.

The assessment carried out in this study provides relevant tools for sanitation companies and will enable further studies for the design of self-sufficiency projects in UASB-based STPs to be performed using simple input data. Lopes et al. (2020) also highlighted the positive energy potential in UASB reactors but considered only unitary relationships from the literature to estimate the electric power consumption, disregarding the main parameter in this kind of evaluation (pressure head).

It is important to highlight that although the evaluation of the energy self-sufficiency of STPs based on the energy consumption of their SPSs can be applied to a high proportion of the Brazilian STPs, the investigation of additional energy requirements such as lighting, administrative and laboratorial consumption, post-treatment operation units, and other equipment should be carried out. With respect to the cost of post-treatment operation units, we verified that nearly 67% of the UASB-based STPs operating in Brazil use only UASB reactors or present post-treatment technologies with low energy demand, such as biological filters or stabilization ponds. Thus, it is possible to say that the energy self-sufficiency assessment proposed in this study can still be applied to most of the UASB-based STPs in the country, even if they present post-treatment configurations other than UASB reactors.

Implications of the present work and future research

The contributions of the present work are associated with the improvement of energy studies on UASB reactors, focusing on the recovery of electric power from biogas in STPs. The information presented by this study shows an advance in research on sustainability of sewage treatment systems, considering the proposal of a model that uses data that can be easily obtained in STPs as input parameters. Because it requires simple input data, it can incentivize biogas use in STPs and allow sanitation systems managers to identify their net energy capacity for use in other sectors. Also, this study provides the tools for verifying the technical feasibility of biogas use in STPs for energy purposes considering the contributing population or the minimum sewage flow, which represents another contribution to the sanitation sector. Finally, the energy balances are essential for decision-making and can be used in studies on the economic feasibility of biogas energy recovery in UASB reactors.

From this study, some other aspects can be objective of future investigations, such as: (i) study on the energy self-sufficiency of UASB-based STPs considering the energy demands of different technologies for post-treatment and sludge management; (ii) different operational conditions and temperature ranges of UASB reactors, when taking into account, for instance, the energetic self-sustainability of STPs in temperate climate countries, and the influence of seasonality (summer/winter); (iii) lastly, to improve the discussion of UASB-based STPs' energetic self-sustainability, additional studies involving the investigation of the economic feasibility associated with the technical feasibility should also be considered.

CONCLUSIONS

The results showed that there are 1,054 UASB-based STPs in Brazil, with a predominance of small-size units. According to the assessed model, all STPs operating in Brazil present potential to produce excess energy. However, only 11.2% of these STPs present technical feasibility for biogas energy recovery. Among them, 10 are classified as large and 108 as medium-sized STPs. Among all STPs, only those with sewage flow higher than 70.3 L s−1 would be able to produce enough biogas flow to be considered technically feasible. In terms of contributing population, thses STPs have populations of over 29,981. The energetic self-sustainability of UASB reactors was determined from mathematical equations using simple input data. The equations proposed in this study can estimate the net electric power production in UASB-based STPs according to different pressure heads and STP sizes. Therefore, these equations are considered relevant tools for sanitation companies and their use can enable studies for the implementation of energy self-sufficiency projects by using simple input data.

DATA AVAILABILITY STATEMENT

All relevant data are included in the paper or its Supplementary Information.

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