**Life Cycle Assessment of the Mesophilic, Thermophilic, and Temperature-Phased Anaerobic Digestion of Sewage Sludge**

### **Iryna Lanko 1,2,\*, Laura Flores 1, Marianna Garfí 1, Vladimir Todt 3, John A. Posada 4, Pavel Jenicek <sup>2</sup> and Ivet Ferrer 1,\***


Received: 18 August 2020; Accepted: 3 November 2020; Published: 10 November 2020

**Abstract:** In this study the environmental impact of the anaerobic digestion (AD) of sewage sludge within an activated sludge wastewater treatment plant (WWTP) was investigated. Three alternative AD systems (mesophilic, thermophilic, and temperature-phased anaerobic digestion (TPAD)) were compared to determine which system may have the best environmental performance. Two life cycle assessments (LCA) were performed considering: (i) the whole WWTP (for a functional unit (FU) of 1 m<sup>3</sup> of treated wastewater), and (ii) the sludge line (SL) alone (for FU of 1 m3 of produced methane). The data for the LCA were obtained from previous laboratory experimental work in combination with full-scale WWTP and literature. According to the results, the WWTP with TPAD outperforms those with mesophilic and thermophilic AD in most analyzed impact categories (i.e., Human toxicity, Ionizing radiation, Metal and Fossil depletion, Agricultural land occupation, Terrestrial acidification, Freshwater eutrophication, and Ozone depletion), except for Climate change where the WWTP with mesophilic AD performed better than with TPAD by 7%. In the case of the SL alone, the production of heat and electricity (here accounted for as avoided environmental impacts) led to credits in most of the analyzed impact categories except for Human toxicity where credits did not balance out the impacts caused by the wastewater treatment system. The best AD alternative was thermophilic concerning all environmental impact categories, besides Climate change and Human toxicity. Differences between both LCA results may be attributed to the FU.

**Keywords:** anaerobic digestion (AD); biogas; life cycle assessment (LCA); methane; waste activated sludge (WAS); wastewater treatment plant (WWTP)

#### **1. Introduction**

In conventional activated sludge wastewater treatment plants (WWTP), excess sludge is continuously formed at the biological reactor of the wastewater treatment line. WWTP operational expenses to handle the produced excess biological sludge, namely waste activated sludge (WAS), together with primary sludge may go up to 50% [1–3]. It has been a long time since AD was adopted as one of the most effective solutions of sewage sludge treatment in terms of sludge reduction, stabilization, and resource recovery [4–6]. Previously, sewage sludge was considered only as waste, and its disposal

on a regular basis was quite challenging [7,8]. Population growth and natural resources exhaustion made it crucial to find a way out of this situation. Nowadays, sludge is considered as a source of substances that can be recovered and reused [9–11].

The zero-waste approach and circular economy paradigm change the angle at which nutrients, metals, organic matter, and other substances from WAS can be converted into valuable materials like biofuels and biofertilizers. Resource recovery processes are being widely adopted, even though recovery of certain substances, for instance, phosphorus still can be nonprofitable from the perspective of economics [12] or environmental impacts [13]. This is mostly because of the low concentration of valuable substances in the influent wastewater. However, as the world prices for phosphorus as for irreplaceable fertilizer are increasing, its recovery from sludge has become extremely important in a long-term perspective [14]. Currently, the attention is drawn to the reject water obtained after the AD process where the concentration of nutrients is significantly higher than in the influent wastewater [15]. However, the temperature regime and configuration of AD may significantly influence the nutrient concentration in the reject water and its volume [1,16,17].

AD is a biological process where organic matter is being biodegraded under anaerobic conditions, leading to the production of biogas, a gaseous biofuel mostly composed of methane, along with the digestate, which may be reused as biofertilizer. AD can be implemented with some variations in temperature (mesophilic (M), 35–40 ◦C and thermophilic (T), 55–70 ◦C) [18] and configuration (one- and two-stage reactors) [1,19]. Normally, the AD process consists of four main stages, namely hydrolysis, acidogenesis, acetogenesis and methanogenesis, which take place in the same reactor in the case of one-stage AD. Separate functioning of the first thermophilic (hydrolytic and acidogenic) and second mesophilic (acetogenic and methanogenic) stages in two-stage AD is accomplished to overcome the drawbacks of one-stage systems [20,21].

The most widely used anaerobic digester is a mesophilic one-stage, since its operation is known as the most simple and stable [22,23]. Nevertheless, the tendency changes towards more metabolically efficient and pathogenically safe digesters such as thermophilic one-stage or temperature-phased two-stage reactors [24]. Temperature phased anaerobic digestion (TPAD) implies a combination of thermophilic and mesophilic one-stage digesters and performs with better stability than thermophilic and higher organic matter degradation rate than mesophilic, which means increased energy efficiency and better control of process parameters [21,25].

Despite the increasing interest in thermophilic and TPAD systems' application, there are few studies comparing the environmental impact of full-scale WWTP with different AD systems [26] and none concerning the comparison of the environmental impact of mesophilic, thermophilic, and TPAD systems. The environmental impact assessment would allow for defining which AD system is the most beneficial in terms of environmental protection. Thus, the objective of this study is to evaluate and compare the environmental impacts of WWTP with different AD systems (M, T, TPAD) using the life cycle assessment (LCA) methodology.

One methodological challenge that leads to variability in LCA results for multiproduct systems, such as WWTPs, is the choice of a functional unit (FU) and its effect on the ecosystem. In this study, two FUs are selected in order to demonstrate a more comprehensive picture of environmental influence of AD implemented in the sludge line alone and at the whole WWTP [27].

The LCA approach is here used not only as a standard practice to estimate the environmental burden of the technological process [22,28,29] on a micro level to compare the three AD options, but also as an alternative to build up a regulatory planning system on a meso level to increase the efficiency of project-level decision-making and to provide advice on potential improvements for the sector's management, and also to ensure the realization of strategic environmental goals [30].

#### **2. Materials and Methods**

#### *2.1. Anaerobic Digestion Systems*

The LCA compared three different AD systems, namely, mesophilic, thermophilic, and TPAD. Data on the operation and performance of these systems treating the same sewage sludge was gathered from three lab-scale digesters which were run during five months [31]. The substrate was thickened WAS, disintegrated through centrifugation (total solids (TS) = 71.8 ± 3.4 g/L, volatile solids (VS) = 42.3 ± 4.1 g/L, chemical oxygen demand (COD) = 64.1 ± 4.1 g/L). The main features of the mesophilic, thermophilic, and TPAD lab-scale systems are shown in Table 1.



#### *2.2. Life Cycle Assessment*

LCA is an analytical tool which allows to assess the environmental impacts of a product, technology, or process according to the "cradle-to-grave" approach. This time-tested technique allows not only to evaluate the potential environmental risks, but also define the life cycle stage and type of environmental impacts. The application of this method may help to improve the studied product, technology, or process by making its life cycle more friendly to the environment. LCA consists of four main steps according to ISO 14040 (2006), and ISO 14042 (2006): (i) goal and scope definition; (ii) inventory analysis; (iii) impact assessment; (iv) result interpretation.

#### 2.2.1. Goal and Scope Definition

The goal of this study was to compare the potential environmental impacts of three types of AD processes: (i) mesophilic; (ii) thermophilic; (iii) TPAD systems.

To this end, two LCA cases with two different functional units (FU) were conducted: first for an activated sludge WWTP with the three different AD systems (here named as WWTP-LCA); second for the sludge line alone with the three different AD systems (here named as SL-LCA).

Since it has been reported in literature that the choice of the FU may change the overall balance of environmental impacts from harmful to beneficial and vice-versa [28], these two FUs were chosen considering the major outputs and functions of a WWTP. For the first case, the FU was 1 m3 of treated wastewater, as the main function of the WWTP is to treat the wastewater stream. For the second case, the FU was 1 m<sup>3</sup> of produced methane, as one of the main functions in AD systems (also the secondary one within WWTP) is to produce energy out of the methane contained in the biogas. Methane was taken instead of biogas, as biogas might have a different content of methane depending on the AD system.

The two FUs were coupled with the system expansion approach (the alternative production of energy and fertilizers) and adopted to evaluate the environmental burden of AD at both scales, the whole WWTP (to assess the contribution of the sludge line to the whole WWTP) and the sludge line alone (to highlight the potential environmental benefits from methane production as an additional function of the system beyond the wastewater treatment). The application of two FUs would demonstrate a deeper, more comprehensive and more transparent picture of AD implementation at the sludge line and at the WWTP. Thus, applying the two FUs helps to present the environmental profile of each AD from different points of view [4,27].

For both LCAs, a period of one-year operation was considered, as it is a timescale that is long enough to assess the averaged operational parameters of any WWTP, including the fact that the construction part was not estimated in the impacts' analysis. The impacts of the construction phase were not accounted for, since the dimensioned WWTP is the same for all three scenarios and LCAs, and it would make the difference among three AD systems' exploitation less evident [4,32].

To sum up, the system's boundaries—for the first and second LCAs—consider the year-around operation of the whole WWTP with three different AD technologies (Figure 1a), and the sludge line alone with three different AD technologies (Figure 1b), respectively. Thus, three scenarios were considered in each LCA; namely mesophilic (M), thermophilic (T), and temperature-phased anaerobic digestion (TPAD).

#### 2.2.2. Inventory Analysis

Inventory data for the WWTP-LCA and SL-LCA are summarized in Tables 2 and 3. Among the inputs and outputs, the flows of materials and energy resources, gaseous emissions, and solid wastes were considered. When possible, data from a full-scale facility was used, which was complemented by data gathered in the lab-scale set-up described previously (Section 2.1) [33].

Full-scale data were taken from a WWTP with thermophilic AD operated by Veolia Cesk ˇ á Republica, a.s. The full-scale operation was used to scale-up and validate the laboratory reactor results. The rest of the information for the mesophilic one-stage and TPAD systems was calculated based on different literature sources and benchmarking data of Veolia, a.s., as described below.

The input parameters included energy consumption, anti-bulking, anti-foaming and dewatering agent dosage, gaseous emissions from the disposed digestates, digestate amounts. Calculated parameters were energy consumption according to the literature [34], specific biogas production based on benchmarking data of Veolia, a.s., as well as anti-bulking, anti-foaming and dewatering agents' dosages.

The final digestate amount for each AD system was estimated in correspondence with the VS destruction observed in the lab-scale digesters (Table 1), which was consistent with other AD systems studied in the literature [19,35,36].

Since the lab-scale set-up treated WAS and the full-scale plant used sewage sludge with 32.5% WAS, the annual biogas production was recalculated for the thermophilic scenario based on the specific biogas production of the corresponding laboratory reactor.

The heat and electricity production was calculated based on the annual biogas production and technical equipment data (efficiency of combined heat and power unit) given by Veolia, a.s.

Annual gas emissions (CH4 and N2O) from the wastewater treatment process and disposed digestates were estimated according to the literature [37,38].

Background data (chemicals, avoided fertilizers—that are contained in the digestate and can be used in agriculture, transportation, wastewater treatment in a municipal wastewater treatment plant, solid wastes, energy provider) were taken from Ecoivent 3.1 database [33]. For all electricity requirements, the Czech electricity mix was considered since the full-scale WWTP is located in the Czech Republic [39] (which is composed of fossil 58.5%, nuclear 35.3%, solar 2.8%, hydro 2.7%, wind −0.7%).

**Figure 1.** Flowcharts: (**a**) for life cycle assessment of the whole wastewater treatment plant (WWTP-LCA) and (**b**) for life cycle assessment of the sludge line alone (SL-LCA).


#### **Table 2.** Inventory data for the whole WWTP LCA (FU: 1 m3 of treated wastewater).

Note: For T and TPAD, the transportation distance was 40 km to the sludge handling plant. According to the microbiological analyses and other sources [40], TPAD and T digestates meet the requirements of Class A biosolids. In case of M, due to pathogenic unsafety, the digestate was additionally treated by composting before its agricultural application. Therefore, it was transported over 2 × 40 km to the composting plant and back, so an additional energy consumption of 16 kWh/t of digestate for the purposes of composting was included [41].



#### 2.2.3. Impact Assessment

The LCA was performed with the software of *SimaPro*® *8*. The potential environmental impacts were calculated by the ReCiPe midpoint method V1.12/Europe Recipe H [33].

Characterization was conducted for the following environmental impact categories: Climate change, Ozone depletion, Terrestrial acidification, Freshwater eutrophication, Human toxicity, Ionizing radiation, Agricultural land occupation, Metal depletion, and Fossil depletion [4]. The above mentioned nine environmental impact categories were selected and assessed considering their close connection with processes that take place in activated sludge WWTP with AD and that have been used in previous LCA studies [33,42].

Classification and characterization were performed as the only compulsory steps of impact assessment in terms of standards—ISO 14040 (2006) and ISO 14042 (2006).

#### 2.2.4. Sensitivity Analysis

A sensitivity analysis on the digestate volume obtained from the TPAD system for both cases WWTP-LCA and SL-LCA was performed in order to take into account the influence that this parameter may have on the environmental impacts associated to digestate transport, treatment, and reuse.

The sensitivity analysis allowed to evaluate if and how the uncertainty of the assumed value in the inventory table could influence the final results. A variation of ±5% of the digestate volume was set for the TPAD scenario only, according to the variability of lab data obtained by the previous studies [19,26,35], and shortage of the reported data from full-scale WWTPs, since TPAD is the least spread AD system worldwide among others [43].

This analysis is done through the sensitivity coefficient (S) which indicates the sensitivity of a particular model output to the changes in the variable being considered. The S is calculated according to the following equation [44]:

$$\text{Sensitivity coefficient} \left( \text{S} \right) = \left( \frac{\text{Outputhigh} - \text{Outputlow}}{\text{Outputbaseline}} \right) / \left( \frac{\text{Inputhigh} - \text{Inputlow}}{\text{Inputbaseline}} \right) \tag{1}$$

where Input is the value of the input variable (i.e., digestate amount), and Output is the value of indicator according to the correspondent impact category.

#### **3. Results and Discussion**

#### *3.1. Life Cycle Assessment*

#### 3.1.1. WWTP-LCA with Mesophilic, Thermophilic, or Temperature-Phased Anaerobic Digestion

The results of the LCA for the whole WWTP (WWTP-LCA) are shown in the Figure 2. This figure includes all environmental impact categories considered in this study, and within each impact category there are three scenarios: mesophilic, thermophilic, and TPAD. For each scenario, results are shown for the whole WWTP, and separately for the wastewater treatment line and the sludge treatment line; this disaggregation of results was done to better identify the contributions of each process stage to the overall impacts. Positive values represent the environmental impacts, while negative values refer to the avoided environmental impacts.

According to the results (Figure 2), the differences among the three AD scenarios are not significantly large, however there are some trends that are discussed here. First, the wastewater treatment line would lead to larger environmental impacts than those cases where the sludge line is incorporated into the AD system. Thus, any implemented AD improves the environmental status of the WWTP mainly due to the credits obtained from the substitution of electricity generation from the fossil fuels [45]. Similar results have been reported for other LCA studies on full-scale AD plants [4,26].

In general terms, TPAD has the lowest environmental impacts, in comparison to T and M, for eight out of the nine impact categories presented in Figure 2, except for Climate change. Furthermore, a one-to-one comparison between T and M shows that their calculated environmental impacts are virtually the same for five out the nine compared categories (i.e., Ionizing radiation, Agricultural land occupation, Metal depletion, Fossil depletion, and Freshwater eutrophication), and with a slightly better environmental performance (meaning lower environmental impacts) for T over M in two impact categories (i.e., Terrestrial acidification and Ozone depletion). T outperforms both M and TPAD in one category (i.e., Climate change), and has a slightly better performance than M in only one category (i.e., Human toxicity).

**Figure 2.** Potential environmental impacts for the three scenarios of the whole WWTP (WWTP-LCA): Mesophilic (M), Thermophilic (T), and Temperature-Phased Anaerobic Digestion (TPAD). WWTP: wastewater treatment plant; WW: wastewater line; SL: sludge line. Results shown for the FU: 1 m3 of treated wastewater.

In the case of Climate change, the biggest impacts are caused by the wastewater treatment line (Figure 2). Conversely, the sludge line decreases the Climate change impacts up to 38% for M, around 35% for TPAD, and 24% for T. Climate change is related to nonrenewable energy consumption, which is especially high in the biological reactor of activated sludge WWTP, accounting for more than 50% of the total energy consumption—Table 2 and [46]. The positive influence of sludge line mainly comes from AD which supplies with the fertilizer obtained after WAS is digested (Sludge disposal\_SL) that substituted the industrial production of the fertilizer with its harmful effect through Climate change. Additionally, AD generates renewable energy out of the biogas produced as a result of the organic matter biodegradation, and counterbalances nonrenewable energy consumption that would otherwise be required to fuel the process. The highest avoided impacts on Climate change are obtained with the mesophilic digestion (M) which is 40% and 42% better than T and TPAD, respectively. These avoided impacts occur due to a type of digestate disposal (which is composting and consequent agricultural land application for M, agricultural land application alone—for T and TPAD) and to its larger amount in comparison to T and TPAD (Table 1). In terms of the energy balance, TPAD is more beneficial than T and M by more than 50% within the sludge line. The lowest total avoided impact on Climate change is obtained with the thermophilic digestion, as a consequence of the energy balance of the process, i.e., energy produced vs. energy consumed by each AD system—Figure 3.

The results of WWTP-LCA regarding all constituents are depicted in Figure 3.

With regard to the factors that contributed the most to the environmental impact of Climate change, those emissions to the air (Air emissions\_WW) and from the energy demand (Electricity\_WW) in the wastewater treatment line are the most significant ones (i.e., around 60% and 25%, respectively, of all contributors from the wastewater treatment line). The contribution from the emissions to the air in the sludge line (Air emissions\_SL) are only 5% (Figure 3). Hence, the total environmental impact was partly compensated by land application as the final sludge disposal (Sludge disposal\_SL) and energy produced from the methane (Electricity\_SL) obtained during AD with the following percentage of these two factor contributions, respectively: 72% and 28% for T, 82% and 18% for M, and 54% and 46% for TPAD. The balance of these two factors for TPAD shows better long-term performance of this AD technology.

For Human toxicity (Figure 2) the wastewater line constituents are quite similar in all scenarios, however, the absolute value of the sludge line varies: the larger negative effect to the environment is for M, 0.377 kg 1.4-DB eq, and the smaller one is for TPAD, 0.282 kg 1.4-DB eq, which is almost 25% less than that of M, and 15% less than T. This happens due to the higher total amount of digestate produced at M conditions rather than at T or TPAD. In particular for the Human toxicity category, less than 3% of the avoided environmental impacts are given by the energy production at TPAD conditions. The main contributor to this impact category is land application (Sludge disposal\_SL) due to the heavy metals and other toxic substances that are still present in the digestate (41–45%)—Figure 3. The other major contributors are the energy consumption in the wastewater treatment line (26–29%), followed by the water body pollution (Water pollution\_WW) made by treated wastewater discharge (19–22%) and, finally, by the different chemicals' consumption (Chemicals\_WW) used at different stages of the wastewater treatment processes such as phosphorus precipitation and coagulation (all around 5%).

**Figure 3.** Contribution analysis of the potential environmental impacts for the three scenarios of both wastewater and sludge lines (WWTP-LCA): Mesophilic (M), Thermophilic (T), and Temperature-Phased Anaerobic Digestion (TPAD). Results shown for the FU: 1 m3 of wastewater treated.

In terms of the Ionizing radiation impact category, even though the absolute values for both lines are lower than <sup>±</sup>0.1 kBq U235 eq/m3 of treated wastewater, the avoided environmental impacts given by the sludge line of WWTP compensates the negative influence of wastewater treatment line for more than 40% for both T and M, and around 90% for TPAD (Figure 2). The latter leads to a better balance of both avoided and overall environmental impacts for TPAD. The rest of the contributions are given by different chemicals' consumption (Chemicals\_WW) used for wastewater treatment processes such as phosphorus precipitation and coagulation (all less than 9%)—Figure 3. The factors that represent the avoided environmental impact are land application as the final sludge disposal (Sludge disposal\_SL) and the energy production (Electricity\_SL), both are from the sludge line of WWTP. The percentage contributions of them, respectively, are 45% and 55% for T, 43% and 57% for M, 27% and 73% for TPAD. For TPAD, the distribution is significantly different from T and M due to the better energy balance after AD.

In the context of other impact categories such as Agricultural land occupation, and Metal and Fossil depletion, the avoided impacts of the sludge line made mainly by land application as the final sludge disposal (Sludge disposal\_SL) and energy production (Electricity\_SL) completely captures the negative influence of wastewater treatment line given by energy consumption (Electricity\_WW) and chemicals' consumption (Chemicals\_WW)—Figure 3.

The environmental impact represented through the rest of the assessed impact categories show relatively low absolute values: <0.0052 kg SO2 eq/m3 of treated wastewater for Terrestrial acidification, <sup>&</sup>lt;0.0011 kg P eq/m3 of treated wastewater for Freshwater acidification, and<−1.0×10−<sup>7</sup> kg CFC-11 eq/m3 of treated wastewater for Ozone depletion.

Terrestrial acidification impacts are built up due to the gaseous emissions (Air emissions\_WW) from the wastewater treatment line, <10% from energy demand (Electricity), and <5% from chemicals (Chemicals\_WW) used at wastewater treatment line—Figure 3.

Freshwater eutrophication is mostly affected by water body pollution (Water pollution\_WW) with a 45–50% contribution—Figure 3—and by energy consumption (Electricity\_WW) with a 25% contribution from the wastewater treatment line.

Ozone depletion results are driven by the avoided environmental impacts of both the energy produced (Electricity\_SL)—around 60% for T and M, and more than 65% for TPAD; and the land application (Sludge disposal\_SL)—around 20% for T and M, and around 15% for TPAD (see Figure 3). These avoided impacts are significantly bigger than those caused by Electricity\_WW and Chemicals\_WW consumption.

Concerning the factors mainly contributing to the different environmental impact categories negatively, there are certain ones confirming their prevailing parts in the total environmental burden. In the case of WWTP-LCA, the major contributors are the gaseous emissions from the open biological step reservoirs to the air, the energy consumption for aeration tanks [47], and the water body secondary pollution given by treated wastewater discharge—see Figure 3. All of them are related to the wastewater treatment line.

For the Climate change impact category, both the gaseous emissions to the air and the energy consumption—again related to the wastewater treatment line—are the biggest contributors to the environmental burden, followed by Chemicals consumption—related to the wastewater treatment line—and the gaseous emissions to air—from the sludge line—with around 10–15% all together.

#### 3.1.2. SL-LCA with Mesophilic, Thermophilic, or Temperature-Phased Anaerobic Digestion

The LCA results of the sludge line (SL-LCA) including methane production are presented in Figure 4 using the second FU: 1 m<sup>3</sup> of methane produced (unlike Figures 2 and 3 which use the FU: 1 m3 of wastewater treated). Figure 4 includes all environmental impact categories considered in this study, and within each impact category there are three scenarios: mesophilic, thermophilic, and TPAD. Furthermore, the different contributions from all process inputs and outputs are included for each of the three scenarios and for all categories. Positive values represent the environmental impacts, while negative values refer to the avoided environmental impacts (here considered as environmental credits).

**Figure 4.** Contribution analysis of the potential environmental impacts for the three scenarios of the sludge line (SL-LCA): Mesophilic (M), Thermophilic (T), and Temperature-Phased Anaerobic Digestion

(TPAD). Results shown for the FU: 1 m3 of methane produced.

The aggregated SL-LCA results for the three scenarios lead to overall avoided environmental impacts in all categories with exception of Human toxicity. From the three scenarios, T outperforms M and TPAD in seven out of the nine impact categories here analyzed (except for Climate change and Human toxicity) (Figure 4). M is consistently the second best scenario in six out of the nine categories, except for Climate change (where it performs the best), and both Ionizing radiation and Human health (where it performs worse). Finally, TPAD has the lowest environmental impacts for Human health (by over 50%), while it also has the least avoided environmental impacts for seven categories out of the nine here analyzed (Figure 4).

In all SL-LCA scenarios, the contributing factors with the largest absolute values (i.e., either potential impacts (for Human toxicity) or avoided impacts (for all the other categories)) are the final sludge disposal (starting from 15% for Ozone depletion to almost 80% for Human toxicity), energy balance (from 12% for Climate change to over 75% for Ozone depletion), and water pollution (from 11% for Human toxicity and Ionizing radiation to 22% for Fossil depletion). It is also important to highlight that the factor of gaseous emissions to the air contributes significantly in a harmful way only for Climate change (more than 80% of caused environmental impact and only less than 8% of total environmental impact) due to the digestate accumulated at the landfill [26].

In the case of specific impact categories, the avoided environmental impacts in Climate change for both T and M are larger than those of TPAD by 24% and 38%, respectively—Figure 4. The only factor causing environmental impacts on Climate change for the three scenarios are the gaseous emissions from AD installations (Air emissions). On the contrary, the avoided environmental impacts have been credited by the following factors: additional reject water treatment (WWTP load concerning each scenario: 53% for T, 40% for M, and 47% for TPAD), final sludge disposal (Sludge disposal: 34% for T, 49% for M, and 29% for TPAD) and energy production (Electricity: 13% for T, 11% for M, and 24% for TPAD). Further minor avoided impacts are related to chemical consumption (Chemicals) (around 10% for all AD types) and transportation (Transportation) (around 5% for T and TPAD, and around 11% for M due to longer distance—a round trip—to the composting site).

In terms of Human toxicity, TPAD demonstrates the best results with the lowest environmental impacts at SL-LCA (Figure 4). The TPAD's impacts on Human toxicity are 46% lower than T, and 58% lower than M. The most substantial contribution to Human toxicity is coming from the final sludge disposal (Sludge disposal—95% for T, 96% for M, and 99% for TPAD) which makes sense as it is the agricultural land application for the T and TPAD scenarios and agricultural land application via composting for M scenario—Figure 4 and Table 3. The rest of the impacts on Human toxicity are mostly caused by the energy consumption (Electricity) with 4% and 3%, for T and M, respectively. While for TPAD, the energy balance is slightly positive, meaning that the system produces surplus energy with respect to its total consumption which leads to avoided impacts by almost 6%. Hence, the TPAD scenario for SL can be considered as energy self-sufficient process and an electricity supplier. Furthermore, for Human toxicity there are some minor avoided impacts from additional reject water treatment (WWTP load—100% for T and M and 94% for TPAD) which is highly polluted, meaning that it can be used as an additional source for resource recovery [15,48].

Interestingly, Human toxicity is the only impact category that does not result in overall avoided impacts at the sludge line. This happens due to the sufficient amounts of heavy metals and other toxic pollutants that are not completely removed during AD operation. Knowing that, T's and TPAD's digestates are considered to be pathogenically safe, and their final disposal can be a direct land application as fertilizers [35]. M digestate undergoes an additional step of composting prior to its application in agriculture. However, the gaseous emissions as well as the traces of heavy metals (Table 3) result in certain danger to the human health [9].

Looking at the Freshwater eutrophication impact category, the TPAD scenario shows both the lowest environmental impacts (50% lower than T and M, with energy consumption—Electricity—as the main contributor) and the lowest avoided environmental impacts. In the latter case, the prevailing contributors are digestate usage for the agricultural land application (Sludge disposal) and water body pollution reduction (WWTP load).

The rest of the impact categories (i.e., Ionizing radiation, Agricultural land occupation, Metal and Fossil depletion, Terrestrial acidification, Freshwater eutrophication, and Ozone depletion) follow a similar pattern. For all SL-LCA scenarios, the overall result can be referred as avoided impacts, with the best results being obtained for T, followed by M, and finally by TPAD. The main contributors are Sludge disposal and Electricity, and the WWTP load to a lower extent (with a maximum of 20% for Terrestrial acidification and lesser for other impact categories).

#### *3.2. Sensitivity Analysis*

The sensitivity response (i.e., the sensitivity coefficient "S" as described in Section 2.2.4) of all studied environmental impact categories was analyzed with respect to the assumed values for the digestate volume (with ±5% of the baseline value for the TPAD scenario, i.e., 90,332 t/year > 85,816 t/year > 81,299 t/year). Only the TPAD scenario was considered for sensitivity analysis due to the variability of the experimental data obtained by the previous studies [19,26,35], and shortage of the reported data from full-scale WWTPs, especially considering that TPAD is the least spread AD system worldwide among others [43].

The sensitivity coefficients were analyzed considering the processing conditions of TPAD for both the WWTP and the SL alone as shown in Table 4.

**Table 4.** Sensitivity coefficients (S) and environmental impacts of the whole WWTP (WWTP-LCA) and SL (SL-LCA) with respect to the TPAD baseline value assumed for the digestate volume.


Note: Sensitivity coefficients (S) are unitless; Units of each environmental impact category consider the specific FU for WWTP and SL, i.e., 1 m3 of treated wastewater and 1 m3 of produced methane, respectively. Bold numbers are for the most sensitive impact categories (with S > 1.0).

A positive value of the sensitivity coefficient (S) refers to a straight influence of the studied parameter on the environmental results: e.g., the more sludge that is considered, the higher the (avoided) environmental impacts are. On the contrary, a negative sensitivity coefficient means an opposite influence of the studied parameter on the environmental results, it is e.g., the more sludge that is considered, the less the (avoided) environmental impacts are.

In this study, negative sensitivity coefficients are obtained only for WWTP-LCA, concerning four impact categories: Climate change, Ionizing radiation, Terrestrial acidification, and Freshwater eutrophication.

In a case of the potential environmental impacts related to the Climate change, Ionizing radiation, and Terrestrial acidification (Table 4), this behavior occurs due to an increased (proportional to the digestate volume) amount of both digestate as fertilizer substituent and energy recovered as biogas. In the case of Freshwater eutrophication, this opposite behavior occurs since an increase in the digestate volume leads to an additional amount of highly polluted reject water (that in turn needs to be further treated) generating a minor amount additional environmental impacts but that overall reduces the total avoided impacts.

On the contrary, the sensitivity coefficients for SL-LCA are positive values in all impact categories indicating a positive relation between the input variable (i.e., the assumed digestate volume) and the out variable (each environmental impact category). In this case, larger digestate volumes lead to the larger (either potentially caused or avoided) environmental impacts. In particular for the Human toxicity category, impacts are higher with the increase in the digestate volume (due to the proportional increase in the present pollutants in the digestate), while all the other categories included in Table 4 result in larger avoided environmental impacts with the increment in the digestate volume (due to the production of the avoided products such as fertilizers and electricity).

The most sensitive environmental impact categories in terms of ±5% variation in the digestate amount are, at SL-LCA, Human toxicity and Freshwater eutrophication, as S is positive and higher than 1.0.

The digestate amount variation of +5% increases the environmental burden of Human toxicity by 6.5% from the baseline value at SL-LCA. At WWTP-LCA, the digestate amount of ±5% had the influence of around 2.0% referring to the baseline value. It is also important to mention that the Human toxicity impact category is the only one with positive sensitivity coefficients at both LCAs, and for SL-LCA the sensitivity coefficient is higher than 1.0. Hence, it is important to mention that such sensitivity behavior of the Human toxicity category reveals that the major environmental concern based the variability of the digestate amounts would be on this impact category.

For Freshwater eutrophication at SL-LCA, the avoided environmental impacts increase by over 7.0% along with the increment in the digestate amount applied in agriculture as a fertilizer. At WWTP-LCA, the sensitivity coefficient at this impact category is negative and lower than 1.0, and can be neglected.

At the WWTP-LCA, the rest of the impact categories (i.e., apart from the ones with negative sensitivity coefficient) result in S values lower than 1.0. The sensitivity coefficient values higher than 0.5 are for the impact categories Metal and Fossil depletion. These two impact categories are affected by 2.5% to 5%, respectively (Table 4), and they refer to overall avoided environmental impacts. Furthermore, the sensitivity coefficients for Metal and Fossil depletion at WWTP-LCA are higher than those at SL-LCA. A reason for such a difference is the contribution in the energy balance (Electricity\_WW) at WW line (Tables 3 and 4). The absolute values of avoided environmental impacts at ±5% of digestate are essentially higher at SL-LCA than at WWTP-LCA for Metal depletion (on over 92%) and for Fossil depletion (on over 95%) due to the energy consumption at the WW line concerning both impact categories.

In general terms, it can be said that the WW line has a higher harmful effect on the environment than SL line itself, and the larger its scale is, the larger the potential environmental impacts will be, contrary to the SL line.

Other general trends from the sensitivity analysis are that the sensitivity gives a clear overview that AD, namely TPAD, affects the environment mainly due to the toxic substances' content and air emissions derived from the digestate, which are proportional to its volume. The digestate production affects the environment negatively by the contribution to Human toxicity due to the final sludge disposal (Sludge disposal) coming from the SL line which relates to both WWTP-LCA and SL-LCA (Figures 3 and 4). At the same time, digestate production has also a positive effect given by resource (fertilizer) and energy (electricity and heat) recovery (Sludge disposal and Electricity, respectively) and also due to the additional reject water treatment (WWTP load) derived from the SL line (Figure 4).

Therefore, the impact categories of Human toxicity, Metal and Fossil depletion which are directly related to the produced digestate amount are of major attention for these types of processes. Considering the case of the TPAD scenario, it can also be said that ±5% of digestate production does not affect most of the (avoided) environmental impacts. Only three environmental impact categories have S > 1.0, namely: Human toxicity (SL-LCA), Ionizing radiation (WWTP-LCA), and Freshwater eutrophication (SL-LCA). These S values, bigger than 1.0, are strongly related to several contributing factors such as energy consumption (WWTP-LCA), final sludge disposal, and reject water treatment (SL-LCA)—Figures 3 and 4, and Table 4. Hence, these findings of the sensitivity analysis should be considered and taken into account for future designs of WWTPs and AD systems.

Based on the sensitivity analysis performed, it can be said that the main factor that contributes to the environmental impact through Human toxicity impact category is digestate quality (pathogenic safety, presence of the toxic substances, and gaseous emissions) and its amount. Therefore, by considering and changing the final digestate disposal, the total environmental impact can be reduced.

#### **4. Conclusions**

In this study, a comparative LCA analysis was carried out to evaluate the environmental impacts of three alternative AD processes (mesophilic, thermophilic, and TPAD) used for sludge treatment in activated sludge WWTP. The environmental burden was evaluated at two scales, namely the whole WWTP (to assess the contribution of the sludge line to the whole WWTP)—with a FU of 1 m3 treated wastewater—and the sludge line alone (to highlight the potential environmental benefits from methane production as an additional function of the system beyond the wastewater treatment)—with a FU of 1 m3 produced methane.

In the WWTP-LCA, five (Climate change, Human toxicity, Ionizing radiation, Terrestrial acidification, and Freshwater eutrophication) out of the nine environmental impact categories analyzed showed potential environmental impacts. The rest of the environmental impact categories (Agricultural land occupation, Metal and Fossil depletion, Ozone depletion) showed avoided environmental impacts, since the WW line led to potential environmental impacts in all impact categories, while the SL line led to avoided environmental impacts for most environmental impact categories (except for Human toxicity). Among all scenarios, the WWTP with TPAD outperformed those with mesophilic and thermophilic AD in all the environmental impact categories, besides Climate change.

The SL-LCA showed mostly avoided impacts, being the highest for thermophilic AD, followed by mesophilic AD and TPAD, except for Climate change where mesophilic AD was the most beneficial. The only potential environmental impact was Human toxicity, being the lowest for TPAD.

Differences between both LCA results may be attributed to the FU.

In addition, it can be also concluded that such products as nutrients and energy recovered from the AD systems and incorporated into the sludge treatment create an amount of credits that make the whole WWTP more environmentally friendly.

**Author Contributions:** Conceptualization, P.J., I.F. and M.G.; Methodology, J.A.P., M.G. and I.F.; software, I.L. and L.F.; validation, M.G., V.T., P.J. and I.F.; formal analysis, I.L.; investigation, I.L.; resources, V.T. and P.J.; data curation, I.L. and L.F.; Writing—original draft preparation, I.L.; Writing—review and editing, J.A.P., I.F. and P.J.; supervision, P.J. and I.F.; project administration, P.J.; funding acquisition, P.J. and I.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** The research was funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 676070. This communication reflects only the authors' views and the Research Executive Agency of the EU is not responsible for any use that may be made regarding the information it contains.

**Acknowledgments:** I.F. and M.G. are grateful to the Government of Catalonia (Consolidated Research Group 2017 SGR 1029). M.G. acknowledges the Spanish Ministry of Economy and Competitiveness (RYC-2016-20059).

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **Abbreviations**


#### **References**


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## **Impact of Nanoscale Magnetite and Zero Valent Iron on the Batch-Wise Anaerobic Co-Digestion of Food Waste and Waste-Activated Sludge**

**Ghada Kassab 1,\*, Dima Khater 2, Fadwa Odeh 3, Khaldoun Shatanawi 1, Maha Halalsheh 4, Mazen Arafah <sup>5</sup> and Jules B. van Lier <sup>6</sup>**


Received: 29 February 2020; Accepted: 28 April 2020; Published: 30 April 2020

**Abstract:** As a potential approach for enhanced energy generation from anaerobic digestion, iron-based conductive nanoparticles have been proposed to enhance the methane production yield and rate. In this study, the impact of two different types of iron nanoparticles, namely the nano-zero-valent-iron particles (NZVIs) and magnetite (Fe3O4) nanoparticles (NPs) was investigated, using batch test under mesophilic conditions (35 ◦C). Magnetite NPs have been applied in doses of 25, 50 and 80 mg/L, corresponding to 13.1, 26.2 and 41.9 mg magnetite NPs/gTS of substrate, respectively. The results reveal that supplementing anaerobic batches with magnetite NPs at a dose of 25 mg/L induces an insignificant effect on hydrolysis and methane production. However, incubation with 50 and 80 mg/L magnetite NPs have instigated comparable positive impact with hydrolysis percentages reaching approximately 95% compared to 63% attained in control batches, in addition to a 50% enhancement in methane production yield. A biodegradability percentage of 94% was achieved with magnetite NP doses of 50 and 80 mg/L, compared to only 62.7% obtained with control incubation. NZVIs were applied in doses of 20, 40 and 60 mg/L, corresponding to 10.8, 21.5 and 32.2 mg NZVIs/gTS of substrate, respectively. The results have shown that supplementing anaerobic batches with NZVIs revealed insignificant impact, most probably due to the agglomeration of NZVI particles and consequently the reduction in available surface area, making the applied doses insufficient for measurable effect.

**Keywords:** anaerobic co-digestion; food wastes; waste-activated sludge; nano magnetite; iron oxide nano particles; nano zero valent iron; sewage sludge; nano particles; organic wastes

#### **1. Introduction**

Anaerobic digestion (AD) converts organic matter into biogas, a renewable source of energy, and digestate, a valuable fertilizer and soil conditioner [1,2]. Due to the increasing demand on renewable energy and the progressively adopted waste management policies that request diverting wastes from landfills, the AD process has been used for the treatment of different types of organic wastes, including sewage sludge, food waste (FW), animal manure and agricultural wastes. Nevertheless, when FW is used as a single substrate, the digestion process stability can be hampered because of (i) a possible imbalance between acidogenesis and methanogenesis when high loads of rapid fermentable organic matter are applied, (ii) potential nutrients imbalance, a high carbon to nitrogen (C/N) ratio, and (iii) the high variability of FW composition [3]. A feasible and reliable approach to overcome these limitations is the use of sewage sludge as co-substrate for food waste digestion.

In the AD process, four major steps are involved, viz. hydrolysis, acidogenesis, acetogenesis and methanogenesis. Generally, the process is limited by one or two major steps, depending on the nature of the substrate. Hydrolysis is often the rate limiting step if complex organic solids are being digested. On the other hand, if the substrate is soluble organic matter, methanogenesis is generally the rate limiting step [4].

In recent years, several studies have shown that the supplementation of conductive nanoparticles has a positive effects on the anaerobic digestion process, particularly in relation to the enhancement of methane production yield and rate, the reduction in startup and recovery periods, in addition to stability improvement [5,6]. In particular, iron oxide nanoparticles (IONPs) that include magnetite, maghemite and hematite, in addition to the nano-zero-valent-iron particles (NZVIs) hold high potentials for AD enhancement and improvement of process robustness [5]. IONPs have specifically great potentials due to its high chemical stability and magnetic properties [7,8]. Most importantly, IONPs are conductive materials that may stimulate the direct interspecies electron transfer (DIET) in anaerobic digestion, in which interspecies electron transfer is not mediated by diffusive electron carriers (i.e. hydrogen or formate) but by direct transfer of electrons released from electron donating bacteria (i.e., oxidizing bacteria that can extracellularly release electrons to conductive materials) to electron capturing microorganism (i.e. methanogenic archaea) that can reduce carbon dioxide to methane using electrons transferred from the electron donating bacteria via the conductive materials [7,9]. The primary mechanism suggested to explain the enhancing behaviors of IONPs in syntrophic methanogenesis via DIET [10] is that (semi) conductive iron oxides act as electron conduits to accelerate DIET in syntrophic methanogesis. Jiang et al. [11] suggested that electron transfer takes place via the biochemical dynamic cycling among the Fe(III) (mineral)-Fe (II)-Fe (III) mineral of the (semi)conductive iron oxides. Wherein, the released electrons are accepted by Fe(III) (mineral) of iron oxides and is reduced to produce Fe(II), then the unbounded Fe(II) transfers electron to methanogens. Fe(II) itself is readsorbed and oxidized back to original structural Fe(III) (mineral) through precipitation.

Early studies tackling the impact of IONPs on anaerobic digestion have used simple substrates (such as propionate, butyrate, and methanol), thus focusing on the syntrophic methanogenesis process. Kato et al. [12] showed that supplementing rice paddy soil with (semi)conductive iron oxide NPs (magnetite, hematite), significantly stimulated methanogenesis from acetate and ethanol in terms of onset time and production rate, attributing these results to the DIET through the (semi) conductive iron oxides. Possibly, in their research, syntrophic acetate oxidation was an important methanogenic pathway, although recent research showed a direct stimulatory effect of added hydrochar to the acetoclastic methanogen *Methanosaete*, which was also ascribed to DIET [13]. Likewise, Zhang and Lu [14] showed that methane production from butyrate oxidation in lake sediments was significantly accelerated in the presence of magnetite NPs, suggesting that DIET mediated syntrophic methanogenesis. Focusing on methanogenic propionate degradation, Cruz Viggi et al. [15] showed that the supplementation of magnetite NPs to a methanogenic sludge obtained from a pilot scale anaerobic digester fed with wasted-activated sludge (WAS) resulted in a 33% enhancement in the maximum rate of methane production. Authors proposed that this stimulatory effect has most probably resulted from the establishment of a DIET with magnetite NPs serving as electron conduits between propionate oxidizing acetogens and carbon-dioxide-reducing methanogens.

The positive effects reported on the impact of conductive iron oxides on methane production yield and rate, using simple substrates, have pushed the research forward into studying the impact of IONPs on the anaerobic digestion of complex organics. Realizing that the hydrolysis of particulate organics is the rate limiting step in anaerobic digestion of complex organics, the majority of these studies have investigated the impact of IONPs on the hydrolysis and acidification processes as well as on syntrophic methanogenesis [16–18]. The outcomes of these studies have shown that magnetite NPs can positively impact the hydrolysis of complex organic materials, thus providing abundant substrates for methanogens and promoting the anaerobic digestion process. Nevertheless, the mechanisms in which such impacts are attained are still not clear yet.

In a similar manner, several studies have been previously conducted to assess the impact of NZVIs on the anaerobic digestion process. Results have shown improvement on methane production yield with the supplementation of NZVIs, attributing such enhancement to:


Additionally, hydrogen evolution from iron corrosion could enhance both hydrogentrophic methanogenesis and homoacetogenesis resulting from the increased H2 flux as intermediary electron carrier [22–24], making the microbial consortia more susceptible for DIET. Other researchers observed that the addition of NZVIs leads to an increased conversion of complex organics to volatile fatty acids (VFAs) (i.e., improved hydrolysis and acidogenesis), which, in turn, enhanced the overall methanogenesis of complex substrates [25]. Yu et al. [26] studied the impact of NZVIs on the anaerobic digestion of WAS and found that the addition of 10 g/L NZVIs improved the hydrolysis-acidification process in which methanogenesis was completely inhibited. The results showed an 83% increase in total VFA concentration compared to the control incubation. The observed enhancement effect was accredited to enrichment of acid-forming bacteria, especially *Clostridia*. Feng et al. [22] also investigated the effect of NZVIs on the hydrolysis-acidification of waste-activated sludge when methanogenesis was inhibited. They observed an improvement in protein and polysaccharide conversion to 36.7% and 29.6%, respectively, at an NZVI dose of 4 g/L, compared to only 25.6% and 22.9% achieved in the control incubation. Moreover, the VFA production at an NZVI dose of 4 g/L was 37.3% higher compared to control incubation. Authors have attributed the enhanced hydrolysis-acidification to the increased activities of key enzymes. The results showed that the activities of protease and cellulase were increased by 85% at an NZVI dosage of 4 g/L, compared to the control incubations. The activities of acid-forming enzymes, including acetate kinase (AK), Phosphotransacetylase (PTA), butyrate kinase (BK) and phosphotransbutytrylase (PTB), were increased by 52.2% to 67.3%.

Despite the previously stated positive effects, NZVIs can cause inhibitory effects if added at elevated doses. Such inhibitory effects can be attributed to the strong reducing conditions developed at the NZVI surface, which can rapidly inactivate bacteria by causing severe damage to the cell membranes and to the respiratory activities through reductive decomposition of protein functional groups [27,28] and, possibly, to the rapid hydrogen production and accumulation that leads to the accumulation of VFAs [29].

Realizing the conceivable positive impacts of magnetite NPs and the NZVIs on the anaerobic digestion process, this research intended to study the effects of these two iron-based conductive materials on the co-digestion of food wastes and sewage sludge. This research aimed explicitly at investigating the impact of iron-based NPs on the hydrolysis process by measuring the extent of particulate organics solubilization. Moreover, the effects on the acidification and methane production yield and rate were examined as well.

#### **2. Materials and Methods**

#### *2.1. Substrates and Inoculum*

Two types of substrates were used in this study, FW and thickened WAS. FW was obtained from the main restaurant of the University of Jordan campus in Amman, Jordan; wherein, the entire quantities of kitchen wastes and dishes leftovers produced in the sampling day (approximately 60 kg) were manually assorted to eliminate non-biodegradable materials, such as aluminum cans, glasses, styrofoam and plastic products. The residual food waste that included vegetables, fruits, dairy products, starchy food, and meat-based food was subsequently mixed thoroughly and approximately a 5-kg sample was collected. To ensure homogeneity and increase specific surface area, FW samples were subsequently grinded using a kitchen grinder and stored at 4 ◦C for less than two days before being used in the batch tests. It is worth mentioning that FW characterization was conducted using grinded samples. Thickened WAS was obtained from the Abu-Nussier Wastewater Treatment Plant (Amman, Jordan). The treatment plant receives a yearly average flow of 3700 m3/d of municipal wastewater with chemical oxygen demand (COD) and total suspended solids (TSS ) concentrations of 960 and 470 mg/L, respectively.

#### *Inoculum*

Anaerobically digested sludge obtained from Al Shallaleh Wastewater Treatment Plant (Irbid, Jordan) was used as a source of inoculum. The anaerobic digester is a completely mixed reactor, operated at 37 ◦C and 20 days solids retention time. Total solids (TS) content of 21.2 g/L ± 1.4 was identified, along with volatile solids (VS) content of 15.2 g/L ± 0.85. The methanogenic activity test that was performed in triplicates using sodium acetate as the substrate at a concentration of 1 g/L and under initial substrate to inoculum ratio of 0.5gCOD/gVS [30] revealed an inoculum-specific methanogenic activity of 0.12 gCH4-COD/gVS.d.

Before being used in the anaerobic digestion batch tests, the inoculum was pre-incubated under anaerobic conditions at 35 ◦C for four days to remove any residual biodegradable organic material that may have been present.

#### *2.2. Preparation and Characteristics of the Nanoparticles*

Magnetite NPs were synthesized according to the protocol described in Kang et al. [31]. A volume of 0.85 mL of 12.1 N HCl and 25 mL of purified deoxygenated water were combined and 5.2 g FeCl3 along with 2.0 g FeCl2 were dissolved into the solution under stirring conditions. The resulting solution was added drop wise into 250 mL of 1.5 M NaOH solution under vigorous stirring, generating an instant black precipitate of magnetite (Fe3O4). The precipitate was isolated using magnetic field (S-30-10 N webcraft Uster, Swizterland). Dynamic light scattering (DLS) data indicated a hydrodynamic size of 29.5 nm and polydispersity index of 0.91.

NZVI stock solution was freshly prepared by reducing ferrous chloride with sodium borohydride as reported by He et al. [32]. Briefly, 200 mL of 0.2 % w/w of sodium carboxy methyl cellulose (CMC, capping agent, Sigma –Aldrich) dissolved in deionized water was purged with high purity argon for at least 25 min. Then, 50 mL of 0.625 M of ferrous chloride tetrahydrate (FeCl2·4H2O, 98%, BBC chemicals) was gradually added to 200 mL of 0.2% CMC under argon gas purging. Finally, 31 mL of 4 M sodium borohydride (NaBH4, 98%, Sigma Aldrich) was added drop wise to the 250 mL Fe-CMC complex while the solution was vigorously shacked at 1100 rpm at room temperature. The final concentrations of NZVIs and CMC in stock solution were 0.11 M and 0.14% w/w, respectively. DLS data indicated a hydrodynamic size of 110 nm and polydispersity index of 0.85.

#### *2.3. Anaerobic Co-Digestion Batch Tests*

Anaerobic batch tests were conducted using the OxiTop® system that is designed to collect and store pressure data. The tests were performed in triplicates using batch test bottles of 1000 mL (1135 mL working volume). Necessary macro and micronutrients were added according to Angelidaki et al. [33]. The substrate that consisted of FW and WAS was added at a ratio of 1.5:1 (FW: WAS), determined based on the VS content of each type of substrate. The amounts of substrate added were calculated according to Pabon et al. [34] and based on: (i) the maximum pressure increase allowed by the OxiTop measuring system, which is 0.3 atm, (ii) a minimum substrate concentration of 1 gCOD/L, (iii) a liquid volume of 300 mL, and (iv) a maximum biomethane composition of 30%. As for the inoculum, the amounts added were based on a substrate to inoculum ratio of 1.0 gCODsubstrate/gVSinoculum.

After the addition of medium solution, inoculum, substrate, and 200 mL of demineralized water, different aliquots of prepared nanoparticles stock solutions were added to reach desired nanoparticles concentrations. Afterward, demineralized water was added to reach 300 mL liquid volume and bottles were tightly sealed with OxiTop® measuring heads. Subsequently, the air in the headspace was flushed with nitrogen gas for 3 min to achieve anaerobic conditions. Then, bottles were incubated at 35 ± 1 ◦C with continuous shaking at 100 rpm agitation speed. It is worth mentioning that the pressure that was built up in the first two hours was released since it is mainly due to the, dissolution of gases, upon temperature increase. For bottles used as the control, only the medium solution, inoculum, substrate that includes FW and WAS and demineralized water were added.

Biogas production was measured through the detection of pressure increase at constant volume, using the OxiTop® measuring heads. The methane content in the biogas was analyzed until the test was completed; i.e., the cumulative biogas curve reached a plateau. Soluble COD and VFA concentrations were followed by taking 2 mL of liquid sample every two days. Three blank bottles, containing all additions except substrates, were used to correct for inoculum methane production.

#### *2.4. Analytical Methods*

Total and volatile solids content were analyzed according to the Standard Methods for the Examination of Water and Wastewater [35]. Total nitrogen (TN), total phosphorous (TP), total ammonia nitrogen (TAN), chloride ion (Cl−), in addition to the pH and electrical conductivity (EC) that were measured employing a waste to distilled water ratio of 1:10, were all analyzed according to Radojevic and Bashkin [36]. Elementary analyses of carbon, oxygen, hydrogen and nitrogen were performed using an elementary analyzer (Perkin-Elmer-Vector 8910) following the manufacturer's instructions.

To determine soluble COD and VFA for FW, a room temperature water extraction was performed on 25 g of grounded FW sample in 250 mL of distilled water for 1 h under agitation. The mixture was then centrifuged (3000 rpm) for 30 min and soluble COD and VFA were determined in the supernatant after being filtered using 0.45-μm filter paper. For WAS, the samples were immediately centrifuged and soluble COD and VFA were determined in the supernatant after filtration using 0.45-μm filter paper as well. Soluble COD was determined using the HACH Lange cuvette test and evaluated by a DR3900 HACH Lange Spectrophotometer. The individual VFAs (viz. acetic, propionic and butyric acids) were analyzed using a gas chromatograph (Varian 3300) equipped with packed column (2 m length, 2 mm internal diameter) and flame ionization detector (FID). Helium was used as the carrier gas at a flowrate of 30 mL/min. The detector temperature was 250 ◦C. The pH of filtered sample was adjusted to less than 2 using formic acid prior to VFA analysis. Methane content in the biogas was analyzed using a gas chromatograph (PYE-NICAM 4500), equipped with packed column (1.5 m length, 4 mm internal diameter) and flame ionization detector (FID). Argon was used as a carrier gas at a flowrate of 30 mL/min. The detector temperature was 150 ◦C. Certified gas standards (Spantech Products) were employed for the standardization of methane. Scanning electronic microscope (SEM) images were taken using the SEM Quanta Feg 450 instrument; samples were placed on carbon stub and sputtered with gold (5 mm thickness). As for the samples' insertion, image capturing and measurement were all performed according to manufacturer instruction.

#### **3. Calculations**

#### *3.1. Theoretical Biochemical Methane Potential*

The empirical mole composition of the FW and WAS, computed from the elementary analysis, allows for determining the theoretical biochemical methane potential (BMPTh) relying on the stoichiometry of the substrate anaerobic degradation reaction [37].

$$\begin{array}{l} \text{CH}\_{\text{a}}\text{H}\_{\text{b}}\text{O}\_{\text{c}}\text{N}\_{\text{d}} + \left(\frac{4\text{a}-\text{b}-2\text{c}-3\text{d}}{4}\right)\text{H}\_{2}\text{O} \\ \rightarrow \left(\frac{4\text{a}+\text{b}-2\text{c}-3\text{d}}{8}\right)\text{CH}\_{\text{4}} + \left(\frac{4\text{a}-\text{b}+2\text{c}+3\text{d}}{8}\right)\text{CO}\_{2} + \text{dNH}\_{3} \end{array} \tag{1}$$

Therefore,

$$\text{BMP}\_{\text{Th}} \left( \text{LCH}\_4 / \text{kgVS} \right) = \frac{22.4 \times \left( \left( 4\text{a} + \text{b} - 2\text{c} - 3\text{d} \right) / 8 \right) \times 1000}{12\text{a} + \text{b} + 16\text{c} + 14\text{d}} \tag{2}$$

where 22.4 correspond to the volume (L) occupied by an ideal gas under standard conditions (temperature of 273 Kelvin (K) and pressure of 101.3 kpa). The 1000 refers to the volume conversion factor from L to mL.

#### *3.2. Theoretical COD*

The theoretical COD (CODTh) can by computed from the stoichiometry of the substrate oxidation reaction

$$\mathrm{Ca\_4H\_6O\_6N\_d} + \left(\frac{4\mathrm{a} + \mathrm{b} - 2\mathrm{c} - 3\mathrm{d}}{4}\right) \mathrm{O\_2} \rightarrow \mathrm{a}\,\mathrm{CO\_2} + \left(\frac{\mathrm{b} - 3\mathrm{d}}{2}\right) \mathrm{H\_2O} + \mathrm{dNH\_3} \tag{3}$$

Therefore;

$$\text{COD}\_{\text{Th}}(\text{gCOD}/\text{gVS}) = \frac{32 \times ((4\text{a} + \text{b} - 2\text{c} - 3\text{d})/4)}{12\text{a} + \text{b} + 16\text{c} + 14\text{d}} \tag{4}$$

#### *3.3. Experimental Biochemical Methane Potential*

The experimental biochemical methane potential (BMPexperimental) was calculated based on the maximum methane production attained in batch test bottles after being corrected by the maximum methane production of the blank bottles [34].

$$\begin{array}{l} \text{BMP}\_{\text{experimental}} \,(\text{LCH}\_4 / \text{kgVS})\\ = \frac{\left[ \left( \frac{(\text{P}\_k + \text{P}\_{\text{lbm}}) \times \text{V}}{\text{R} \times \text{T}} \right) \times \text{CH}\_4 \,\% \right] - \left[ \left( \left( \frac{(\text{P}\_{\text{lbm}} + \text{P}\_{\text{lbm}}) \times \text{V}}{\text{R} \times \text{T}} \right) \times \text{CH}\_4 \,\%\_{\text{blark}} \right] \right]}{\text{S}\_{\text{O}}} \times 22.4 \end{array} \tag{5}$$

where Ps is the pressure accumulated inside the test bottle (pa), Patm is the atmospheric pressure (pa), Pblank is the pressure accumulated in the blank bottle (pa), V is the headspace volume (m3), T is the temperature in Kelvin (K), R is the universal gas constant, and CH4%S and CH4%blank are the accumulated biogas methane percent for the test and blank bottles, respectively. The So is the amount of substrate added in terms of VS.

#### *3.4. Biodegradability, Hydrolysis and Acidification Percentages*

Anaerobic biodegradability was assessed based on the percent of experimental BMP to the theoretical BMP.

$$\text{Biodegradability} \%= \frac{\text{BMP}\_{\text{experimental}}}{\text{BMP}\_{\text{Th}}} \times 100\tag{6}$$

The hydrolysis percent was assessed based on the percent of the solubilized COD relative to the substrate initial particulate COD.

$$\text{Hydrolysis} \%= \frac{\text{COD}\_{\text{CH}\_4\text{t}} + \text{COD}\_{\text{s},\text{t}} - \text{COD}\_{\text{s},\text{t}=0}}{\text{COD}\_{\text{Th},\text{initial}} - \text{COD}\_{\text{s},\text{t}=0}} \times 100\tag{7}$$

where CODCH4,t is the COD equivalent of methane produced at any time t, CODs,t is the soluble COD at any time t, CODs,t<sup>=</sup><sup>0</sup> is the soluble COD at time t = 0 and CODTh,initial is the initial theoretical COD.

The acidification percent was assessed based on the percent of the acidified COD relative to the substrate initial theoretical COD.

$$\text{Acidicization }\%= \frac{\text{COD}\_{\text{CH}\_4,t} + \text{COD}\_{\text{VFA},t} - \text{COD}\_{\text{VFA},t=0}}{\text{COD}\_{\text{Th},\text{initial}}} \times 100\tag{8}$$

where CODCH4,t is the COD equivalent of methane produced at any time t, CODVFA,t is the VFA equivalent COD at any time t, CODVFA,t<sup>=</sup><sup>0</sup> is the VFA equivalent COD at time t = 0 and CODTh,initial is the initial theoretical COD.

#### *3.5. Statistical Analysis*

The statistical analyses were performed using the IBM SPSS statistics (version 23). Data collected for characterization of the FW and WAS were demonstrated with a mean ( x), standard deviation (σ) and coefficient of variation percent (CV). For the evaluation of the NZVIs and magnetite NPs' impact on the anaerobic co-digestion process, an ANOVA test with Bonferroni correction was used with a confidence interval of 95%.

#### *3.6. Modeling of Methane Production*

The modified Gompertz model was used to describe the progression of cumulative methane production [38].

$$\mathbf{Y}(\mathbf{t}) = \mathbf{Y}\_{\mathbf{m}} \times \exp\left\{-\exp\left[\frac{\mu\_{\mathbf{m}} \mathbf{e}}{\mathbf{Y}\_{\mathbf{m}}} \times (\boldsymbol{\lambda} - \mathbf{t}) + 1\right]\right\} \tag{9}$$

where Y(t) is the cumulative methane yield at a digestion time t (LCH4/kgVS), Ym is the maximum methane production (LCH4/kgVS), μ<sup>m</sup> is the maximum rate of methane production (LCH4/ kgVS.d), λ is the lag phase time (d), and t is the incubation time (d), e = exp (1) = 2.718.

#### **4. Results and Discussions**

#### *4.1. Characteristics of Substrates*

The average data and coefficient of variations for the FW and WAS characteristics are presented in Table 1. The FW-measured pH (4.1 ± 0.5) is indeed low compared to the average values reported in the literature. Fisgativa et al. [39], who compiled and analyzed FW characteristics data from 70 studies that evaluated 120 different food wastes, revealed an FW pH value of 5.1 ± 0.7. Apparently, acidification was already instigated during storage time.

The total solid content of FW was 30%, which lies within the range stated in the literature, although it is among the highest reported [39–42]. The high VS/TS ratio (95.6%) highlights the high organic transformation potential. Nevertheless, the low level of soluble COD compared to theoretical COD (0.2) indicates the predominance of particulate COD in the FW, which can reduce the rate of degradation due to a limitation in hydrolysis.

The carbon to nitrogen ratio (C/N) of FW (17.6) is to some extent below the generally recommended level of 20–30 for an optimal anaerobic digestion process [40]. Moreover, upon co-digestion with the WAS that is generally characterized by a low C/N ratio (5.5), the resultant C/N ratio will be even lower. However, several researchers have demonstrated that the co-digestion of FW with WAS can be successfully performed under C/N ratios ranging from 8.8 to 13 [43–46].

With respect to nutrients content, the FW total Kjeldahl nitrogen (35.1 gN/kgVS) observed in this study is higher than the average values stated by Fisgativa et al. [39] but compatible to those reported by Zhang et al. [47], El Mashad and Zhang [48], Zhang et al. [49] and Agyeman and Tao [50] for types of FW similar to the one tested within this study. Phosphorous concentration (2.6 gP/kgVS) was found to be below the values reported in the literature [39,48,51], which are in the order of 5 gP/kgTS. Hence, in the context of nutrient supplementation, the comparison of the measured COD:N:P ratio (350:7.1:0.53), with what is reported in literature for successful and stable anaerobic digestion process (350:5:1) [52], confirms the deficiency of the phosphorous, for which the level obtained represents only 53% of the recommended value.


**Table 1.** Food waste (FW) and wasted-activated sludge (WAS) characteristics.

In regard of the ammoniacal nitrogen, the results obtained within this study (2.30 gN/kgVS) are considerably higher than those reported in the literature [39,53]. Increased ammonia concentrations result in an increased buffering capacity for the anaerobic digestion process.

On the whole, the FW and WAS mixture obtained physicochemical characteristics, which accentuate the numerous benefits of FW co-digestion with WAS: (i) improving the moisture content for wet digestion, taking into consideration the WAS moisture content of 97.8%, (ii) enhancing the nutrients balance for bacterial growth; total Kjeldah nitrogen and total phosphorous contents in WAS equals of 107.7 gN/kgVS and 20.9 gP/kgVS, respectively, and (iii) the development of buffering capacity for the stable anaerobic digestion process.

In connection with the anaerobic biodegradability, the calculated BMPTh for FW and WAS were 564.5 LCH4/kgVS and 392.5 LCH4/kgVS, respectively, computed based on the empirical mole composition of C18.0H29.4O9.6N for FW and C6.3H12.2O4.7N for WAS, assuming full COD conversion. The contribution of sulfur was considered negligible since the elementary analysis results, revealed below detection limit sulfur content. Also based on the empirical composition, the CODTh for FW and WAS were 1.73 and 1.12 gO2/gVS, respectively. It is worth mentioning that the CODTh of the WAS deviated from the typical theoretical value of 1.42, which is linked to the overall elemental biomass composition C5H7O2N. Apparently, the used WAS sample was more stabilized.

#### *4.2. E*ff*ects of Magnetite NPs and NZVIs on Hydrolysis and Acidification*

Due to the importance of hydrolysis in the kinetics of anaerobic digestion and the fact that it is usually the rate-limiting step, the impact of magnetite NPs on COD solubilization was assessed. Magnetite NP concentrations of 25, 50 and 80 mg/L were employed in anaerobic batch tests, corresponding to 13.1, 26.2 and 41.9 mg magnetite NPs/gTS of substrate calculated for the initial conditions. The results (Figure 1) show that the maximum soluble COD concentration achieved in the control incubation was 799 mg/L, which was reached after an incubation period of one day. Batches incubated with magnetite NPs had maximum soluble COD concentrations of 2280, 1852, and 1420 mg/L for magnetite NP doses of 80, 50 and 25 mg/L, respectively. Peak values were reached after six days with cumulative methane production of 49, 57 and 110 LCH4/kgVS, for magnetite NP doses of 80, 50 and 25 mg/L, respectively. For the same incubation period (i.e., six days) the cumulative methane

production in the control incubation reached 170 LCH4/kgVS. Accordingly, to clarify whether increased soluble COD in magnetite NPs amended batches was due to the accumulation of soluble COD as a result of reduced consumption rates by methanogens (as discussed in Section 4.3 below) or due to stimulated hydrolysis, the hydrolysis percentages achieved after six days were computed. The results show that batches incubated with 80, 50 and 25 mg/L magnetite NPs, achieved hydrolysis percentages of 88%, 78%, and 55%, respectively, compared to hydrolysis percentage of 50% attained in control incubation. Hence, we concluded that magnetite NPs induced a stimulatory effect on the hydrolysis. The hydrolysis percentages achieved by the end of incubation periods in magnetite NPs amended batches were 65.1% for the 25 mg/L dose and 94.4% and 94.9% for the 50 and 80 mg/L doses, compared with 63.0% achieved in the control incubation. The positive impact induced by magnetite on hydrolysis process has been previously reported by several researchers. Zhao et al. [54], reported a twofold increase in waste-activated sludge protein hydrolysis, with magnetite (0.2 mm in diameter) dose of 10 g/L. Moreover, they have revealed an enhancement in the activity of protease and α-glycosidase enzymes by 63% and 27%, respectively. The positive impact of magnetite on hydrolysis of WAS was reported applying even bigger magnetite particle (8–12 mm), achieving a 31.2% and 11.6% increase in soluble protein and polysaccharides at a dose of 27 g/L [17]. Zhang et al. [18] reported that in batches incubated with 1 g/L magnetite NPs and with methanogenesis inhibition, the total polysaccharide decomposition was increased by 15.8% compared to the control incubation.

**Figure 1.** Effect of different magnetite NP doses on soluble COD.

Since methane yields are directly related to VFA production from substrate acidification, the impact of magnetite NPs on the availability of VFAs as precursors for methanogenesis was evaluated as well. The results show that acetate production was significantly stimulated, reaching maximum concentrations of 500, 749 and 1214 mg/L for magnetite NP doses of 25, 50 and 80 mg/L within 6 days, respectively, whereas the maximum acetate concentration in the control incubation was limited to 107 mg/L, which was reached after an incubation period of one day. Figure 2 shows that acetate was the predominant VFA, and its production is apparently directly related to the dose of the magnetite NPs. Concomitantly, methane production dropped with the increase in magnetite NPs. After the six-day incubation period, VFA concentrations started to decline, coinciding with the time at which the methane generation rate started to increase significantly, as shown in Section 4.3. To calculate the net increase in VFA production induced by magnetite NPs, the acidification percentage that takes into consideration methane production (i.e., VFA consumption) in addition to VFA generation, was computed after the six-day incubation period. The obtained results show a positive impact induced by magnetite NPs on the acidification process, with percentages reaching 54.2%, 56.6%, and 84.0% in

batches incubated with magnetite NPs doses of 25, 50, and 80 mg/L, respectively. This is compared to 40.0% achieved in the control incubation. These results are compatible with those reported by Zhao et al. [54], who also reported that acetate is the main VFA generated in magnetite-amended digesters, revealing a 1.6-fold increase in acetate concentration relative to the control when amino acids were used as the substrate, and a 1.75-fold increase over the control when monosaccharides were used as the substrate. Moreover, Zhang et al. [55], who assessed acidogenesis via hydrogen yield, revealed a 1.2-fold increase in hydrogen yield compared to the control upon addition of 50 mg/L magnetite NPs.

**Figure 2.** Effect of different magnetite NP doses on VFA production; (**a**) acetate, (**b**) propionate and (**c**) butyrate.

Magnetite NPs stimulatory impact on hydrolysis and acidification might be linked to the observed increased biomass aggregation that progressed along the incubation period, exclusively in batches incubated with magnetite NPs. Our results are congruent to the observed increased excretion of extracellular polymeric substances (EPS), brought about by magnetite supplementation, previously reported by Yin et al. [56] and Yan et al. [57]. Figure 3 shows formed aggregates after an incubation period of 8 days, along with the SEM images that were taken at the end of the incubation period. As shown by the SEM images, bacteria appeared to be aggregated and enveloped by what seems to be EPS, whereas the EPS fill the intercellular spaces within the aggregates. Observations support the hypothesis that enhanced EPS excretion may have played an essential adhesive role in the formation of aggregates and the maintenance of their integrity. Accordingly, considering the EPS sorptive capacities and their possible role in immobilizing the extracellular enzymes, the observed accelerated hydrolysis and acidification process can be explained by (i) the physical trapping of particulate and colloidal organics by means of the EPS, which leads to enhanced hydrolysis; (ii) immobilization and localization of extracellular enzymes by EPS; (iii) the minimization of hydrolysis and acidification product diffusion distances as a result of aggregation [58]. The enhanced aggregation of biomass and solid substrates implies that both enzymes and hydrolysis/acidification products remain relatively close to microbial cells, thus reducing the need for maintaining high levels of extracellular enzymes in the bulk solution and reducing the diffusive losses of products away from cells [59].

**Figure 3.** (**a**) Photos of the anaerobic batches, showing the biomass aggregation in batches incubated with magnetite NPs compared to the control incubation; (**1**) 80 mg/L (left) and 25 mg/L (right); (**2**) 50 mg/L, (**3**) 0 mg/L-control. (**b**) Scanning electronic microscope (SEM) images of aggregated biomass obtained from batches incubated with magnetite NPs by the end of the incubation period. (**1**) 25 mg/L; (**2**) 50 mg/L; (**3**) 80 mg/L.

Enhanced biomass aggregation resulting from magnetite nano or micro particles additions has been previously reported. Baek et al. [60,61] have studied the effect of magnetite particles (size 100–700 nm) supplementation on the anaerobic digestion of dairy effluent in a completely stirred tank reactor CSTR. Authors stated that added magnetite adhered to microbial cells' surfaces and induced microbial aggregation. Cruz Viggi et al. [15] and Li et al. [62] have studied the effect of magnetite particles on the anaerobic degradation of propionate and butyrate and showed through scanning electron micrography analysis that the magnetite particles were adsorbed on cell surfaces. This resulted in larger agglomerates, with magnetite particles appeared bridging the microbial cells. Undoubtedly, the effect of IONPs on biomass aggregation needs to be explored further so as to help clarify possible functional mechanisms of these conductive materials in enhancing aggregation.

Concerning the impact of NZVIs, results showed only slight increases in soluble COD and VFA concentrations with increased doses of NZVIs along the whole incubation period (Figures 4 and 5). Nevertheless, calculated hydrolysis and acidification percentages showed a statistically insignificant difference. Possibly, the strong clustering or agglomeration of NZVIs particles caused this negligible effect.

**Figure 4.** Effect of different nano-zero-valent-iron particle (NZVI) doses on soluble COD.

**Figure 5.** Effect of different nano-zero-valent-iron particle (NZVI) doses on total VFA production.

#### *4.3. E*ff*ects of Magnetite NPs and NZVIs on Methane Production*

The observed enhanced hydrolysis and acidification process will also impact subsequent methanogenesis. By the end of the incubation period, the cumulative methane production in the magnetite NPs amended batches (Section 4.3) reached 341.5, 478.3 and 481.5 LCH4/kgVS, for magnetite NPs concentrations of 25, 50 and 80 mg/L, respectively. If compared with the control incubation, the batches incubated with magnetite NPs dose of 25 mg/L showed a methane production enhancement level of 7%, which was found to be statistically insignificant. With respect to the 50 and 80 mg/L magnetite NPs concentrations, results have shown a statistically significant increased methane production of 49.8% and 50.8%, respectively. These results resemble biodegradability percentages of 62.7% for the control incubation and 67.1%, 93.9% and 94.4% for incubations with 25, 50 and 80 mg/L magnetite NPs, respectively. Results undoubtedly indicated that addition of magnetite NPs increased methane production yield from anaerobic co-digestion of FW and WAS.

The addition of magnetite NPs to the batches, clearly retarded methanogenesis from the solubilized substrates (Figure 6), as also evidenced by the accumulating VFAs (Figure 2). Modeling experimental methane production data with the modified Gompertz model (Figure 6b) shows retardation periods (i.e. lag periods) of 2.8, 5.4 and 5.9 days for batches incubated with magnetite NPs doses of 25, 50, and 80 mg/L, respectively. However, after this period, the maximum methane production rate was accelerated, especially for batches incubated with magnetite NPs doses of 50 and 80 mg/L to attain an

increase of 21.3% and 45.2%, relative to the control incubation (Figure 7). The initial retardation might be due to the rapid acid production resulting in a low local pH, initially inhibiting methanogenesis. Further research is required to unravel the observed phenomenon. However, if compared with the control incubation, the enhanced methane production yield in magnetite amended batches can be undoubtedly attributed to improved hydrolysis and acidification.

**Figure 6.** Cumulative methane production at different magnetite NP doses; (**a**) experimental data, (**b**) modified Gompertz model fit.

**Figure 7.** Effect of different magnetite NP doses on maximum methane production rates, computed from the modified Gompertz model.

Concerning the impact of NZVIs (Figure 8), the statistical analysis of computed results has revealed no measurable effect on methane generation for the three applied doses of 20, 40, and 60 mg NZVIs/L, which are equivalent to 10.8, 21.5 and 32.2 mg NZVIs/gTS of substrate, respectively. In details, the cumulative methane production at NZVIs doses of 20, 40 and 60 mg/L were 332.4, 338.3 and 343.0 LCH4/kgVS, compared to 341.6 LCH4/kgVS obtained with the control incubation. In literature, the impact of NZVIs on anaerobic digestion has been assessed either related to toxicity phenomena or conversion rate enhancement. The studies focusing on toxicity assessment have employed doses in the range of 55–2000 mg/L of NZVIs. Yang et al. [29] studied the impact of NZVIs on flocculent anaerobic sludge using glucose as the substrate and reported methane production inhibition levels of 20% at NZVIs doses of 1 and 10 mM (i.e. 55.9 and 558.5 mg NZVIs/L). Elevating the NZVIs dose

to 30 mM (1675.5 mg NZVIs/L) resulted in 69% methane production inhibition. Authors attributed the increased inhibition to increased hydrogen accumulation resulting in reduced VFA conversion. He et al. [63] have also reported substantial methane production inhibition at NZVIs doses of 30 mM (1675.5 mg NZVIs/L) applied to flocculent sewage sludge. Jia et al. [64] have reported not only methane production inhibition but also a lag period of 15 days when treating flocculent sewage sludge with NZVIs doses of 1500 and 2000 mg/L. Studies focusing on methane production enhancement have employed NZVIs doses in the range of 1 to 10 mg NZVIs/gTS, with greater attention given to the impact on anaerobic digestion of sewage sludge. Su et al. [19] and Suanon et al. [65] have shown that the anaerobic digestion of sewage sludge in the presence of NZVIs at a concentration of 1 and 5 mg NZVIs/gTS resulted in 40.4% and 45.8% methane production yield enhancement. Substantially higher enhancement levels were achieved by Lizama et al. [21] at NZVIs doses of 3.4, 4.7 and 6.0 mg NZVIs/gTS, attaining enhancement levels of 88%, 126%, and 186%, respectively. Putting the results of this study in the context of previous studies shows that with the applied doses of the NZVIs, an enhancement of methane production is anticipated. It is considered that the insignificant impact attained may be attributed to the aggregation of NZVIs particles in form of clusters. Expectedly, aggregation of NZVIs particles will adversely affect their activity since increased size will inevitably reduce the hydrogen and ferrous iron release rates [29,66]. Consequently, the doses employed in this study may have become insufficient to lead into a notable enhancement in methane production. Actually, several previous studies have accentuated on NZVIs strong tendency for aggregation, particularly due to attractive magnetic interaction [29,67,68]. Accordingly, further investigations on the impact of NZVIs on anaerobic digestion are certainly indispensable.

**Figure 8.** Cumulative methane production at different nano-zero- valent- iron particle (NZVI) doses.

#### **5. Economic and Environmental Considerations**

The obtained results, with the significant increase in methane production yield, show that supplementing the co-digestion process with magnetite NPs presents an opportunity for increased economic feasibility. On the one hand, improved methane production efficiency implies increased revenues from the elevated generation of power and heat energy. Moreover, the fact that magnetite NPs are inexpensive to produce [69,70] and can be effectively separated and reused [71] will only limitedly increase the operational costs. On the other hand, realizing effective industrial implementation necessitates a detailed economic analysis that requires further technical and scientific research to specify critical technical information, such as the maximum endurable organic loading rates, and optimum magnetite NP dose, both determined according to substrate characteristics and operating conditions.

Moreover, the results show that the addition of magnetite NPs, enhances anaerobic biodegradability percentages substantially, which consequently leads to higher volatile solids destruction. Accordingly, the quantities of generated digestate will be reduced, and thus the capital and operational cost of post digestion processes will be decreased. However, the impact of using magnetite NPs on the quality of the digestate needs to be investigated in conjunction with different operating conditions and magnetite NP doses. Particularly, if generated digestate is being considered for use as organic fertilizers. On the positive side, numerous studies have shown that IONPs have a beneficial impact on plants and lead to the improvement of crop agronomic traits [72–77]. Other studies, with the purpose of discarding toxic impacts, have shown that irrigating with water solutions containing magnetite NP concentrations as high as 1000 mg/L [78] or foliar feeding with magnetite NP solution of 10,000 mg/L [79], had no toxic impacts on plant growth. Nevertheless, and despite such promising results, the effects associated with the presence of magnetite NPs in digestate vary according to the physical and chemical characteristics of nanoparticles, soil characteristics, plant species, in addition to the rate of applications. Thus, the use of magnetite NPs on industrial scale necessitates integrated planning and management that must be supported by scientific customized studies.

#### **6. Conclusions**

This study investigated the effect of magnetite nanoparticles and nano-zero-valent-iron particles on the anaerobic co-digestion of food waste with sewage sludge. The results show that supplementing anaerobic co-digestion batches with magnetite NPs at doses of 26.2 and 41.9 mg magnetite NPs/gTS has led to a significant increase in hydrolysis percentages to a level of 94.4% and 94.8%, respectively. This is compared to 63.0% attained with the control incubation. Acidification was significantly improved as well, with acetate being the predominant VFA. Acidification percentages reached 56.6% and 84.0% in batches incubated with magnetite NP doses of 26.2 and 41.9 mg magnetite NPs/gTS, respectively, compared to only 40.0% achieved in the control incubation. The cumulative methane production yield reached 478.3 and 481.5 LCH4/kgVS in batches incubated with 26.2 and 41.9 mg magnetite NPs/gTS, respectively. These production yields present an increase of 49.8% and 50.8% compared to the yield attained in the control incubation. Regarding the effect of nano-zero-valent-iron particles, the results show no impact, neither on methane production nor on hydrolysis or acidification.

**Author Contributions:** Conceptualization, G.K., F.O. and M.H.; Data curation, K.S. and M.A.; Formal analysis, J.B.v.L.; Funding acquisition, G.K.; Investigation, G.K., D.K. and F.O.; Methodology, G.K. and D.K.; Project administration, G.K.; Writing—original draft, G.K.; Writing—review & editing, M.H. and J.B.v.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Abdul Hameed Shoman Foundation/ The Scientific Research Support Fund (3/2016). Jordan.

**Conflicts of Interest:** The authors declare no conflict of interest

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## **Formulation and Characterization of a Heterotrophic Nitrification-Aerobic Denitrification Synthetic Microbial Community and its Application to Livestock Wastewater Treatment**

### **Qi-yu Zhang 1,3, Ping Yang 2, Lai-sheng Liu 1,\* and Zeng-jin Liu <sup>3</sup>**


Received: 4 December 2019; Accepted: 9 January 2020; Published: 13 January 2020

**Abstract:** There have been many studies on single strains in wastewater treatment and a new synthetic microbial community was prepared in this study, which provides a reference for the application of heterotrophic nitrification-aerobic denitrification in actual wastewater treatment. The growth period distribution of the composite bacteria was determined by plotting growth curves with different sole nitrogen sources, and the influence of the carbon source, carbon to nitrogen ratio (C/N) ratio, pH, and temperature on ammonia removal by the composite heterotrophic nitrifying-aerobic denitrifying strain was investigated. The optimal conditions for the heterotrophic nitrification process were sodium citrate as the carbon source, a C/N ratio of 10, a pH of 7, and a temperature of 30 ◦C, and only trace amounts of nitrate and nitrite were observed during the process. When the sequencing batch reactor (SBR) of a pig farm wastewater treatment plant was inoculated with the synthetic microbial community, the average removals of the chemical oxygen demand (COD) and ammonia nitrogen in the effluent were 92.61% and 20.56%, respectively. From the results, the synthetic microbial community was able to simultaneously perform heterotrophic nitrification-aerobic denitrification indicating great potential for full-scale applications.

**Keywords:** synthetic microbial community; ammonium; heterotrophic nitrification; aerobic denitrification; livestock wastewater

#### **1. Introduction**

In recent years, the livestock and poultry breeding industry has gradually moved towards specialized and large-scale centralized feeding methods [1]. Compared with traditional distributed breeding, large-scale breeding can significantly improve production efficiency, reduce production costs, and increase economic benefits. The development of large-scale farms has also led to an increase in the amount of livestock and poultry manure runoff, which has placed tremendous pressure on the ecological water environment. Livestock and poultry aquaculture wastewaters contain large amounts of suspended solids, COD, nitrogen, and phosphorus, which cause the eutrophication of water bodies and water pollution. In China, the COD and total nitrogen from the livestock wastewater account for 96% and 38% of the total agricultural wastewater, respectively [2]. In addition, the wastewater usually varies considerably in concentration and volume during different seasons or under management processes. Livestock and poultry wastewaters are not a commonly considered pollutant but contain abundant resources, including phosphorus and potassium, and the current comprehensive utilization

efficiency of livestock and poultry wastewater in China is less than 60% [3,4]. By promoting the utilization of excreta and urine resources, livestock and poultry breeding wastes can become valuable products, such as biogas, organic fertilizer, and reclaimed water, which can effectively alleviate the shortage of agricultural resources in China and control non-point source pollution [5]. Efficient and economical livestock and poultry breeding industry wastewater treatment methods are urgently needed to achieve sustainable development in the modern swine breeding industry and environmental protection [6].

To remove these pollutants, biological methods are preferred in consideration of operational ease and cost [7]. A promising process called biological nitrogen removal treatment can partially and effectively dispose of both the solid and liquid fractions of manure [8]. However, there have been periodic reports on anaerobic ammonium oxidation [9] and aerobic denitrification [10], indicating that although aerobic biological processes have been applied to treat livestock and poultry breeding industry wastewaters effectively, the nitrification–denitrification process has presented challenges due to the long time required, high cost, and difficulty of management [11]. For instance, the cost of floor space and construction for the nitrification–denitrification method is high, and nitrifying bacteria grow slowly, so different conditions are required [12]. The sludge treatment process is cumbersome and easily causes secondary pollution and additional costs. Therefore, a more economical and convenient biological process is necessary [13]. The academic research on livestock and poultry breeding industry wastewaters has mainly aimed to develop a new biological nitrogen removal process and to cultivate superior strains to degrade high-concentration ammonia nitrogen wastewater. Since Robertson et al. discovered that *Thisphaera pantotropha* had heterotrophic nitrification ability in 1985, researchers have discovered a variety of heterotrophic nitrifying microorganisms with nitrification activity in soil, sludge, lake water, and the deep sea [14]. Studies have found that the heterotrophic nitrification process of *T. pantotropha* requires energy consumption. Unlike autotrophic nitrifying bacteria, *T. pantotropha* does not accumulate NO2 −-N when ammonia is oxidized under aerobic conditions [15]. With the discovery of heterotrophic nitrification-aerobic denitrification bacteria, the theory and technology of biological nitrogen removal have made important breakthroughs. Heterotrophic nitrification-aerobic denitrification has attracted extensive attention as a new type of biological nitrogen removal technology [16]. Compared with traditional biological nitrogen removal, the heterotrophic nitrification-aerobic denitrification process has higher removal efficiency of nitrogen and COD and less nitrous oxide production [17]. This process can realize the unification of nitrification and denitrification in the same time and space, greatly simplifying the process of traditional biological nitrogen removal, and therefore save operating and infrastructure costs [18]. At present, simultaneous nitrification–denitrification technology is a new method of nitrogen removal.

Removal widely occurs in the natural environment and has been successfully realized in oxidation ditches, SBR reactors and other systems [19]. Significantly, studies have shown that changes in factors such as the carbon source, dissolved oxygen, floc characteristics, and sludge concentration affect the reaction process in simultaneous nitrification and denitrification [20]. Studies have shown that many bacteria, actinomycetes, fungi, and even algae have heterotrophic nitrification capabilities. Fungi, such as *Aspergillus flavus* [21], *Penicillium* sp. [22], *Verticillium* sp. [23], *Absidia cylindrospora* [24], etc. are considered to be the most abundant and most efficient heterotrophic nitrifying microorganisms [25]; *lactobacillus*, such as *Mycobacterium*, *Nocardia*, *Micromonospora,* and algae, such as *Chlorella*, salt algae, *Phaeodactylum tricornutum* [26] also perform heterotrophic nitrification. Furthermore, many heterotrophic bacteria, such as *Pseudomonas* [27], *Alcaligenes* sp. [28], *Arthrobacter* sp. [29], and *Alcaligenes faecalis* [30] can oxidize ammonia nitrogen to nitrite nitrogen or other states [31].

As mentioned above, many single-species heterotrophic nitrification-aerobic denitrifying microorganisms and their characteristics have been discovered thus far. The synthetic microbial community can couple their efficiency, work together, and have strong environmental adaptability, and their treatment effect is better than that of single microorganisms. Nevertheless, information on the combined treatment effects and characteristics of these strains is still very limited. The purpose of

this study was to develop an ammonia nitrogen degradation composite composed of heterotrophic nitrification-aerobic denitrifying strains, determine its reaction characteristics and its application in livestock wastewater treatment, and provide an experimental basis and theoretical support for future applications.

#### **2. Materials and Methods**

#### *2.1. Media and Reagents*

The beef extract peptone medium consisted of the following components: beef cream 3 g·L−1, peptone 10 g·L<sup>−</sup>1, and NaCl 5 g·L<sup>−</sup>1. The heterotrophic nitrification medium was composed of NH4Cl 0.38 g·L<sup>−</sup>1, C4H4Na2O4 5.62 g·L<sup>−</sup>1, and 50 mL Vickers salt solution. The denitrification medium was made up of KNO3 0.72 g·L<sup>−</sup>1, C4H4Na2O4 2.80 g·L<sup>−</sup>1, KH2PO4 1 g·L<sup>−</sup>1, MgSO4·7H2O1g·L<sup>−</sup>1, and 2 mL/<sup>L</sup> trace element solution. The BTB (bromothymol blue) medium contained KNO3 1 g·L<sup>−</sup>1, L<sup>−</sup>asparagine 1 g·L−1, Na3C6H5O7·5H2O 8.50 g·L−1, KH2PO4 1 g·L−1, MgSO4·7H2O1g·L−1, CaCl2 0.20 g·L−1, FeCl3·6H2O 0.05 g·L−1, and 5 mL/L 1% thymol blue. The LB (Luria−Bertani) medium consisted of peptone 10 g·L<sup>−</sup>1, yeast extract 5 g·L<sup>−</sup>1, and NaCl 5 g·L<sup>−</sup>1.

The Vickers salt solution contained KH2PO4·3H2O 6.5 g·L<sup>−</sup>1, MgSO4·7H2O 2.5 g·L<sup>−</sup>1, NaCl 2.5 g·L<sup>−</sup>1, FeSO4·7H2O 0.05 g·L<sup>−</sup>1, and MnSO4·7H2O 0.04 g·L<sup>−</sup>1. The trace element solution [32] contained EDTA 50 g·L<sup>−</sup>1, CaCl2 5.5 g·L<sup>−</sup>1, ZnSO4 2.2 g·L<sup>−</sup>1, CuSO4·5H2O 1.57 g·L<sup>−</sup>1, FeSO4·7H2O 5.0 g·L<sup>−</sup>1, CoCl2·6H2O 1.61 g·L<sup>−</sup>1, and MnCl2·4H2O 25.06 g·L<sup>−</sup>1.

All the media mentioned above were adjusted to an initial pH of 7.0 to 7.2 and sterilized at 121 ◦C and the pressure of 0.12 MPa for 20 min.

#### *2.2. Screening and Identification of Heterotrophic Nitrifying-Aerobic Denitrifying Strains*

To obtain a high-purity single strain, it was necessary to treat pig farm sludge. Pig farm biogas slurry samples and aerobic sludge samples (10 mL) were collected, separated, efficiently transferred to a 250 mL flask containing sterilized 0.90% NaCl solution (90 mL) and glass beads and, then, shaken at 200 rpm to obtain a uniform bacterial suspension. The solution was, then, subjected to gradient dilution, and the resulting solution was inoculated on beef extract peptone medium in an incubator at 30 ◦C. Through five consecutive enrichment cultures, different single colonies were picked for separation and purification and then inoculated in 100 mL, which was efficiently separated into heterotrophic nitrifying liquid medium. The change in the concentration of ammonia nitrogen in the culture was qualitatively tested to complete the initial screening by observing the colour change of the Nessler reagent. Then, the obtained suspensions of different concentrations were uniformly coated on the surface of BTB medium and placed in a constant-temperature incubator to verify whether there was aerobic-denitrification activity.

The strains obtained by the primary screening were rescreened, and four strains with preferable COD degradation ability and denitrification performance were selected as the target strains and inoculated onto an inclined surface at 4 ◦C. The screened strains were subjected to Gram staining and observed by optical microscopy [33]. Single colonies were picked and cultured in a liquid medium to log phase, and the culture solution was used for genome extraction. The 16S rRNA sequences of the strains, amplified by universal primers 27F and 1492R, were submitted to NCBI for comparative analysis with GenBank data.

The strains selected from the biogas slurry and the aerobic sludge were prepared at a ratio of 1:1:1:1, which corresponded to the best COD degradation and denitrification performance.

#### *2.3. Configuring the Synthetic Microbial Community and Measuring Its Growth Curve*

The synthetic microbial community was transferred to NM liquid medium and cultured at 30 ◦C and 150 r/min for 24 h. The ammonia nitrogen removal efficiency reached an average of 91.32% at 24 h.

To determine the changes in the growth curve of the complex strain under different nitrogen sources, NH4Cl, KNO3, and NaNO2 were selected as the only nitrogen source digestion media. During cultivation, the concentration of the synthetic microbial community, the nitrogen source concentration, and the COD concentration in the reactor were measured. The concentration of the strain was determined by regular measurements of OD600, which is the absorbance of the bacterial suspension at a wavelength of 600 nm. The absorbance and the time were taken as the ordinate and the abscissa, respectively, to plot the growth curves of the synthetic microbial community, which were fitted by exponential growth curves.

#### *2.4. E*ff*ect of Di*ff*erent Factors on Heterotrophic Nitrification-Aerobic Denitrification*

To analyse the effect of different carbon sources on heterotrophic nitrification, glucose, sodium acetate, sodium succinate, and potassium sodium tartrate were selected as electron donors for the synthetic microbial community. In the experiment, the components, other than the carbon source and the nitrogen source in the NM medium, composed the basal medium. For convenience of analysis, the nitrogen source added to the medium was only ammonia nitrogen, and the carbon source to be tested was separately added to maintain a carbon to nitrogen ratio (molecular ratio) of 10.

A bevelled surface stored in a refrigerator at 4 ◦C was used as the source of the strains, and rings were picked into an Erlenmeyer flask containing 100 mL of NM fluid medium. The strains were cultured for 24 h under aerobic shaking at 30 ◦C and 150 r/min. The culture conditions were as described above.

To analyse the effect of the C/N ratio on heterotrophic nitrification, glucose was the only carbon source, and the fixed nitrogen source concentration was 156.14 mg·L−<sup>1</sup> in the experiment. The carbon to nitrogen ratio (C/N) was changed by adjusting the carbon source concentration so that the C/N ratio was 1, 4, 7, 10, or 13. The strains were cultured in liquid medium at 30 ◦C and 150 r/min for 24 h under aerobic shaking.

To determine the optimum environmental pH or pH range of the synthetic microbial community, the pH was set to 5 different values. In this experiment, the effects of pH values of 5, 6, 7, 8, and 9 on the growth of the strains were studied.

The heterotrophic nitrification-aerobic denitrification strain was activated in culture medium until reaching log phase. The bacterial suspension was centrifuged at 8000 rpm for 10 min. The supernatant was removed and resuspended in sterile water, and this procedure was repeated 3 times. The sterilized bacterial suspension was added to a 250 mL conical flask containing 100 mL of heterotrophic nitrification medium and cultured at 20 ◦C, 25 ◦C, 30 ◦C, 35 ◦C, or 40 ◦C with a rotating speed of 150 rpm. After culturing in a shaking bed for 24 h, the culture solution was centrifuged to remove the cells, and the supernatant was diluted to determine the ammonia nitrogen concentration.

#### *2.5. Optimizing the Proportion of Strains Used to Prepare the Synthetic Microbial Community*

The synthetic microbial community was activated in the LB medium to prepare a heterotrophic nitrification-aerobic denitrification medium. According to the above experiment regarding the effects of different factors on heterotrophic nitrification-aerobic denitrification, the culture conditions were set to a carbon source of glucose, the C/N ratio of 10, pH of 7, the temperature of 30 ◦C, and rotation speed of 150 rpm. The ratios of the synthetic microbial community are shown in Table 1. After 48 h of culture, the supernatant taken from bacterial fluid centrifuged at 8000 rpm for 5 min was used to determine the concentration of ammonia nitrogen, and the results were compared with the results for the blank group.


**Table 1.** The ratio of the synthetic microbial community.

#### *2.6. Application of the Synthetic Microbial Community for Pig Farm Wastewater Treatment*

The wastewater came from a pig farm located in Chongqing, China, and the main pollutants contained in the manure sewage of the pig farm were organic matter, suspended matter, and ammonia nitrogen which is a high-concentration component of organic wastewater. The average flow efficiency was 2.5 m3/d, and the COD concentration and ammonia nitrogen concentration of the influent water were 1.5 g·L−<sup>1</sup> and 1 g·L<sup>−</sup>1, respectively. The synthetic microbial community were added to the SBR reactor to remove the COD; the ammonia nitrogen reaction cycle was 12 h, including 9 h of influent flow and 3 h of precipitation, and the wastewater was discharged once every two cycles. The length, width, and height of the SBR reactor were 2400, 1000, and 1100 mm, respectively. Sludge loading and the sludge concentration were 0.15 kgCOD/kgMLSS·d and 4.0 kgMLSS/L, respectively. The range of the DO (dissolved oxygen) concentration threshold is relatively wide and is not clearly defined. In this experiment, the concentration of DO in the feed water was controlled on average to about 0.001 g·L−<sup>1</sup> to control its stability. Experimental wastewater collection began on August 29, and COD and ammonia removal efficiency monitoring ended on October 10. The startup mode can be divided into asynchronous startup and synchronous startup according to the startup steps. The pH and temperature of the SBR reactor were approximately pH 7 to 8.2 and 30 ◦C, respectively. Samples were taken from the tank for the measurement of ammonia and COD in the influent and the effluent, and the data presented in this study were obtained after bioaugmentation.

#### *2.7. Analytical Methods*

pH was measured by a PHS-3B precision pH meter. Ammonium, nitrate, nitrite, and total nitrogen were measured by standard methods [34]. Ammonium was determined by the Nessler's reagent spectrophotometric method [35]. Nitrite was determined by the N-(1-naphthalene)-diaminoethane photometry method. Nitrate was measured by the ultraviolet spectrophotometric method [36], and the total nitrogen was measured by alkaline potassium persulfate digestion-UV spectrophotometry. The COD was measured by a closed reflux colorimetric method. Bacterial growth was monitored by monitoring the optical density at 600 nm (OD600) using a spectrophotometer. The removal efficiency of ammonia nitrogen in the heterotrophic nitrification-aerobic denitrification process was calculated using Equation (1):

$$
\eta\_1 = (\mathbb{C}\_1 - \mathbb{C}\_2) / \mathbb{C}\_1 \times \mathbf{100\%} \tag{1}
$$

where *C*<sup>1</sup> is the corresponding concentration of ammonia nitrogen at time t1 in mg·L−<sup>1</sup> and *C*<sup>2</sup> is the corresponding concentration of ammonia nitrogen at time t2 in mg·L<sup>−</sup>1.

The removal efficiency of nitrate in the heterotrophic nitrification-aerobic denitrification process was calculated using Equation (2):

$$
\eta\_2 = (\text{N}\_1 - \text{N}\_2) / \text{N}\_1 \times 100\text{\%} \tag{2}
$$

where *<sup>N</sup>*<sup>1</sup> is the corresponding concentration of nitrate at time t3 in mg·L−<sup>1</sup> and *<sup>N</sup>*<sup>2</sup> is the corresponding concentration of nitrate at time t4 in mg·L<sup>−</sup>1.

The removal efficiency of COD in the heterotrophic nitrification-aerobic denitrification process was calculated using Equation (3):

$$
\eta\_3 = (D\_1 - D\_2) / D\_1 \times 100\% \tag{3}
$$

where *<sup>D</sup>*<sup>1</sup> is the corresponding concentration of COD at time t5 in mg·L−<sup>1</sup> and *<sup>D</sup>*<sup>2</sup> is the corresponding concentration of COD at time t6 in mg·L<sup>−</sup>1. Larger values of <sup>η</sup> 1, <sup>η</sup> 2, and <sup>η</sup> <sup>3</sup> implied a higher capability of nitrogen and contaminant removal.

The 16S rRNA gene sequences of the strains were amplified by using the genomic DNA as the template and 16S rRNA universal primers [37]. The purified PCR products were sequenced and compared with the published data in GenBank by using BLAST [38].

#### **3. Results and Discussion**

#### *3.1. Isolation and Identification of the Strains*

After the separation, purification, and rescreening of the fifteen strains, four heterotrophic nitrifying strains were picked and named SBR-2, P6, SBR3-2, and SBR-1. The SBR-2 colony was pale yellow with a wrinkled, moist and translucent surface and irregular rectangular edges, and single colonies were short rod shaped. The P6 colony bulged with a shiny surface and milky white and opaque folded edges, and single colonies were rod shaped. The SBR3-2 colony was round and opaque and had a moist surface, and single colonies were long and rod shaped. The SBR-1 colony was yellow with a smooth and moist surface and neat edges, and single colonies were rod shaped.

The genomes of the four heterotrophic nitrifying strains were used as templates to carry out PCR amplification, and partial 16S rRNA fragments of the four strains of bacteria were obtained. A neighbour-joining tree based on the 16S rRNA gene sequences was constructed to show the phylogenetic positions of SBR3-2, SBR-1, SBR-2, P6, and representatives of some other related taxa. Bootstrap values (expressed as percentages of 1000 replications) are shown at the branch points; the scale bar represents 0.02 substitutions per nucleotide position. The measured sequences were compared to nucleic acid sequences in the GenBank database. By comparing the results and morphological characteristics mentioned above, strains SBR-2, P6, SBR3-2, and SBR-1 were identified as *Pseudomonas* sp., *Acinetobacter* sp., *Bacillus* sp., and *Sphingobacterium* sp., respectively, and their sequence similarities were all over 99%. An NJ tree was constructed using MEGA 7.0.26 (Figure 1).

The synthetic microbial community was prepared from the four strains at a ratio of 1:1:1:1. Under conditions of 30 ◦C and 150 r/min for 24 h, the ammonia nitrogen removal efficiency of the synthetic microbial community reached an average of 91.32%.

**Figure 1.** Phylogenetic tree based on 16S rDNA sequences of the isolates and related standard bacteria.

#### *3.2. Growth Curves of Di*ff*erent Unique Nitrogen Sources*

Microbial growth and reproduction mainly proceed via several stages, i.e., the adaptation, logarithmic, stable, and decay stages [39]. To understand the growth cycle of the synthetic microbial community, the growth curve of the synthetic microbial community cultured in nitrification medium with NH4Cl as the sole nitrogen source for 24 h was calculated and is shown in Figure 2; the removal efficiencies of ammonia nitrogen and COD were 98.90% and 94.46%, respectively. From the change in absorbance at OD600, the synthetic microbial community grew rapidly during the 0 to 4 h adaptation period, and the strain grew rapidly into the logarithmic growth phase after four hours After 22 h, the strain population reached a maximum and entered the stable phase. The concentration of NH4 + decreased slowly from 0 to 4 h, and the decrease in efficiency at 4 h was rapid. There was a very small amount of NO2 − accumulation during the reaction, while the remaining ammonia nitrogen was partially converted into gaseous nitrogen via the desorption reaction and partially converted into other nitrogen-containing substances in solution.

The growth curve of the synthetic microbial community cultured in nitrification medium with KNO3 as the sole nitrogen source for 24 h is shown in Figure 3, and the removal efficiencies of ammonia nitrogen and COD were 95.02% and 65.65%, respectively. The same observation method revealed that the synthetic microbial community was in the adaptation period from 0 to 2 h. After 2 h, the strains grew rapidly into the logarithmic growth phase, and the population was still increasing after 24 h. The concentration of NO3 − decreased slowly from 0 to 2 h, and the efficiency of decline increased significantly at 2 h; NO2 − accumulated throughout the reaction process. This result was in contrast to some heterotrophic nitrification-aerobic denitrification strains, such as LD3 [40], that have a large amount of nitrite accumulation during the reaction. Because nitrite reductase and nitrate reductase

existed simultaneously in the synthetic microbial community and had high activity, the nitrite nitrogen produced during denitrification was rapidly reduced by the high-activity nitrite reductase [41].

**Figure 2.** Growth curve of synthetic microbial community with NH4Cl as the sole nitrogen source.

**Figure 3.** Growth curve of synthetic microbial community with KNO3 as the sole nitrogen source.

The growth curve of the synthetic microbial community cultured in nitrification medium with NaNO2 as the sole nitrogen source for 24 h is shown in Figure 4, and the removal efficiency of ammonia nitrogen and COD was 98.60% and 76.45%, respectively. The synthetic microbial community was in the adaptation period from 0 to 2 h. After 2 h, the strain population increased rapidly into the logarithmic growth phase, and the population reached a maximum after 22 h. Although generally, high nitrite concentrations were toxic to the strain and inhibited its growth and metabolism, some strains, such as Y-11, have a certain tolerance to high nitrite [42]. Similarly, the synthetic microbial community showed better tolerance and denitrification capacity.

The results of the batch test indicated that the synthetic microbial community had a good effect on the degradation of nitrogen and the removal of COD in media with different sole nitrogen sources. The use of NH4Cl as the sole nitrogen source resulted in a better degradation efficiency, COD removal efficiency, and strain growth than those obtained when using NaNO2/KNO3 as the nitrogen source. The fact that nitrite had no obvious inhibitory effect on the growth and denitrification of the synthetic microbial community showed good environmental adaptability and potential application in the treatment of nitrite sewage. In summary, the synthetic microbial community can be grown for organic removal under different nitrogen sources, including ammonia nitrogen, nitrate nitrogen, and nitrite nitrogen, and the growth efficiency and organic matter removal efficiency of the synthetic microbial community are affected by the nitrogen source.

**Figure 4.** Growth curve of synthetic microbial community with NaNO2 as the sole nitrogen source.

#### *3.3. E*ff*ect of Carbon Source on Heterotrophic Nitrification-Aerobic Denitrification*

The carbon source is not only an energy source for microbial nitrogen removal but also directly or indirectly affects the growth efficiency of microorganisms and the efficiency of nitrogen removal [43]. The fixed nitrogen source concentration (NH4 <sup>+</sup>-N) was 156.14 mg·L−1, and the results in Figure 5 indicate that more carbon sources could be utilized by the synthetic microbial community. In addition, potassium sodium tartrate had a very poor effect as a carbon source, and the removal efficiency of ammonia nitrogen was 98.56%, 98.75%, and 99.51%, respectively, when glucose, sodium acetate, and sodium succinate were used as the carbon sources. The effect of sodium tartrate as the sole carbon source is poor because the concentration of different carbon sources in our experiments remains the same. The reaction process using sodium tartrate as a carbon source generally requires a higher carbon source concentration, which reflects the effect deviation. In summary, different carbon sources affect the heterotrophic nitrification ability of the composite bacteria. A suitable carbon source is one of the keys to improving the ammonia nitrogen removal efficiency. The most suitable substance for heterotrophic nitrification by the synthetic microbial community was sodium succinate in this experiment.

#### *3.4. E*ff*ect of the C*/*N Ratio on Heterotrophic Nitrification-Aerobic Denitrification*

The NH4 <sup>+</sup>-N removal percentages were significantly different among C/N ratios of one to 13, as shown in Figure 5. According to the experimental data, the ammonia nitrogen removal efficiency was only 15.92% when the C/N ratio was one, and the main reason was that an insufficient carbon supply could damage both microbial growth and the denitrification of electron donors [44]. As the C/N ratio increased, the ammonia nitrogen removal efficiency increased gradually until the C/N ratio reached 10, and the ammonia nitrogen removal efficiency reached a maximum at 98.98%. However, when the C/N ratio increased from 10 to 13, the ammonia nitrogen removal efficiency decreased, and the explanation was as follows: the higher carbon-nitrogen ratio made the carbon source content so high that some organic matter was directly embedded into the enzyme structure, affecting enzyme activity [45]. Experiments have shown that the amount of organic carbon plays an essential role in cell growth and denitrification. If the carbon source was insufficient, there was not enough electron flow to provide enough energy for the growth of the cells, and thus the denitrification capacity was relatively low. If the carbon source provided had a much higher content than the demand of the cells, the carbon source was no longer a limiting factor; the growth and metabolic activity of the cells were in a stable phase and can even have undergone reverse growth, and the denitrification capacity was stabilized or decreased. The experimental results showed that the optimal carbon to nitrogen ratio was 10, and the findings for other denitrifying bacteria, such as Vibrio diabolic SF16, seem consistent [46].

#### *3.5. E*ff*ect of Changes in pH on Heterotrophic Nitrification-Aerobic Denitrification*

The pH in the environment has a significant influence on the life activities of microorganisms. The primary role of pH is to cause a change in the charge of the cell membrane, thereby affecting the

absorption of nutrients by the microorganism and affecting the enzyme activity [47]. As shown in Figure 5, the synthetic microbial community demonstrated acid and alkali inhibition at pH five and pH nine, respectively. The strain achieved the highest ammonia removal efficiency of 99.13% at pH seven, and the ammonia nitrogen removal efficiency of the synthetic microbial community could reach 98% or more in the range of pH six to nine.

In general, most heterotrophic nitrification-aerobic denitrification bacteria prefer a neutral or slightly alkaline environment, and the optimal pH range is six to nine [48]. However, when the culture medium is different, the optimum pH of heterotrophic nitrifying bacteria will also change. In beef extract peptone medium, the nitrification activity of the strain was not very sensitive, but in glucose-ammonium acetate medium, the nitrification activity was affected by changes in pH.

#### *3.6. E*ff*ect of Changes in Temperature on Heterotrophic Nitrification-Aerobic Denitrification*

The ammonia nitrogen removal efficiency of the synthetic microbial community at different temperatures is shown in Figure 5. In the range 20–40 ◦C, the denitrification performance of the synthetic microbial community was very good, and a value of 98% was maintained. Although the synthetic microbial community maintained an ammonia nitrogen removal efficiency of 98.01%, it had a slight decline at 40 ◦C. What caused this decline was that under high-temperature conditions, the active substances, such as enzymes, in microorganisms are denatured [49], and some cell functions are decreased or even terminated. These results suggested that average temperatures did not play an essential role in the process of heterotrophic nitrification of the synthetic microbial community. Taking cost-effectiveness into consideration, 30 ◦C was the most suitable reaction temperature.

#### *3.7. Optimizing the Proportions of the Strains Used to Prepare the Synthetic Microbial Community*

It can be concluded from Table 2, that the ammonia nitrogen removal efficiency and nitrate removal efficiency dropped significantly upon increasing the proportion of *Acinetobacter* sp., even to the relative contents corresponding to ratios two, six, and seven. When the ratio of *Pseudomonas* sp. and *Bacillus* sp. was kept constant, while increasing the proportion of *Sphingobacterium* sp. and *Acinetobacter* sp., the ammonia nitrogen removal rate and nitrate removal efficiency increased, and the maximum value was obtained at ratio number four. This result could have been obtained because the metabolites of a particular strain could have stimulated the growth of other strains or affect their functions, and thus affected the function of the whole system [50]. Comparing experimental group one and experimental group two" experimental group eight and experimental group nine, a single increase of the ratio of *Acinetobacter* sp. or a single decrease of the ratio of *Pseudomonas* sp. is harmful to the entire system. However, from the perspective of the interaction between microorganisms, it is suitable for the whole system to reduce the ratio of *Pseudomonas* sp. and *Bacillus* sp. and increase the ratio of *Acinetobacter* sp. and *Sphingobacterium* sp. simultaneously. In conclusion, the synthetic microbial community ratio with the highest ammonia nitrogen removal efficiency is *Pseudomonas* sp.: *Sphingobacterium* sp.: *Bacillus* sp.: *Acinetobacter* sp. = 1:2:1:2 (volume ratio).



#### *3.8. Application of the Synthetic Microbial Community for Pig Farm Wastewater Treatment*

In this application, a bioenhancement scheme was mainly adopted, and the optimized synthetic microbial community was added to the SBR reactor. To enhance the ammonia nitrogen and nitrate removal performance, the reaction conditions were adjusted to the optimal conditions obtained by experimental analysis, i.e., glucose as a carbon source, a C/N ratio of 10, a pH of 7, and temperature of 30 ◦C. The SBR reactor had been operating stably for 40 days, and the average ammonia nitrogen concentration of the effluent water, the average ammonia nitrogen removal efficiency, and the average COD removal efficiency were 42.53 mg·L<sup>−</sup>1, 92.61%, and 76.45%, respectively, as shown in Figures 6 and 7. To confirm whether ammonia nitrogen eventually became nitrogen gas, the total nitrogen was detected in the effluent. The total nitrogen value per day was slightly higher than that of ammonia nitrogen, which proved that the ammonia-degrading composite agent had indeed played its intended role and completed the biological denitrification process of ammonia from nitrogen to nitrogen. It is worthwhile mentioning that due to the rain, the effluent was diluted, and the ammonia nitrogen in the inlet water was lower than usual. According to the analysis, the excessively high ammonia nitrogen concentration in the inlet water would not be suitable for microbial reactions. After the ammonia nitrogen concentration was appropriately reduced, the removal rate was significantly increased. These results indicate that the use of the synthetic microbial community would result in a significant improvement in the biological nitrogen removal of pig farm wastewater.

**Figure 6.** Ammonia nitrogen concentration change in the SBR reactor.

**Figure 7.** COD concentration change in the SBR reactor.

#### **4. Conclusions**

In this study, four heterotrophic nitrification aerobic denitrification strains, SBR2, P6, SBR3-2, and SBR-1, were isolated and identified as *Pseudomonas* sp., *Acinetobacter* sp., *Bacillus* sp., and *Sphingobacterium* sp., respectively. The synthetic microbial community was composed of the four above strains in a ratio of 1:1:1:1, and its growth curve was drawn under different nitrogen sources. By adjusting the reaction conditions, including the carbon source, carbon to nitrogen ratio, pH, and temperature, and considering the economic benefits and nitrogen removal performance, the reaction conditions of the synthetic microbial community were determined to be sodium succinate as a carbon source at C/N of 10, pH of 7, and 30 ◦C. The configuration scheme was optimized by adjusting the ratio of the four strains to 1:2:1:2 and detecting their denitrification performance, and the final synthetic microbial community was obtained and applied in pig farm wastewater treatment. In summary, the synthetic microbial community is a promising candidate for extensive application in various pollution control systems, including livestock wastewater and the aquaculture industry, and the next step is to determine the growth characteristics and denitrification performance of the synthetic microbial community under extreme temperature, pH, and ammonia nitrogen concentration values.

**Author Contributions:** L.-s.L. contributed to the conception of the study; P.Y. contributed significantly to analysis and manuscript preparation; Q.-y.Z. performed the data analyses and wrote the manuscript; Z.-j.L. helped perform the analysis with constructive discussions. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Ministry of Science and Technology of China grant number No. 2018YFC0408103.

**Acknowledgments:** This research was supported by a grant from the National Key Research and Development Program of China on Domestic Sewage Treatment Technology Development (no. 2018YFC0408103).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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