Determination of the major factor responsible for soluble organic matter release during nitrite/free nitrous acid pre-treatment of waste activated sludge

Abstract

Soluble chemical oxygen demand (SCOD) release by free nitrous acid (FNA)/NO2 system is usually called “FNA disintegration”, despite lack of evidence that FNA is the main agent responsible for organic matter breakdown. The aim of this study was to investigate whether FNA or NO2 is the primary disintegration factor of thickened secondary sludge in a wide spectrum of process parameters (T=48h, 0-2280 mgNO2-N/L, pH 3.2-6.4 and FNA between 0 and 47.4 mgHNO2-N/L). Statistical analysis based on multiple regression and the Akaike Information Criterion showed that NO2, not FNA, is a main disintegrating factor leading to SCOD release (p=0.005206 and 0.00009 respectively) and that the FNA concentration is without statistical significance (p=0.800234 and 0.328099 respectively). These findings are important as understanding key factors is essential for productive future research and technology development. Moreover, these findings give doubts about the role of FNA in its other applications such as inhibition of nitrification.

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Determination of the major factor responsible for soluble organic matter re‐
lease during nitrite/free nitrous acid pre-treatment of waste activated sludge
Dorota Szypulska, Stanisław Miodoński, Mateusz Muszyński-Huhajło,
Bartosz Zięba, Kamil Janiak
PII: S0960-8524(21)00256-X
DOI: https://doi.org/10.1016/j.biortech.2021.124917
Reference: BITE 124917
To appear in: Bioresource Technology
Received Date: 8 January 2021
Revised Date: 22 February 2021
Accepted Date: 24 February 2021
Please cite this article as: Szypulska, D., Miodoński, S., Muszyński-Huhajło, M., Zięba, B., Janiak, K.,
Determination of the major factor responsible for soluble organic matter release during nitrite/free nitrous acid
pre-treatment of waste activated sludge, Bioresource Technology (2021), doi: https://doi.org/10.1016/j.biortech.
2021.124917
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1
1Determination of the major factor responsible for soluble organic matter release during
2nitrite/free nitrous acid pre-treatment of waste activated sludge
3 Dorota Szypulskaa, Stanisław Miodońskia, Mateusz Muszyński-Huhajłoa, Bartosz Ziębaa, Kamil
4 Janiaka,b*
5aFaculty of Environmental Engineering, Wroclaw University of Science and Technology,
6Wybrzeże Wyspiańskiego 27, 50-370 Wroclaw, Poland
7b Wroclaw Municipal Water and Sewage Company, Na Grobli 14/16 50-421 Wroclaw, Poland
8* corresponding author: kamil.janiak@pwr.edu.pl
9
10 Abstract
11 Soluble chemical oxygen demand (SCOD) release by free nitrous acid (FNA)/NO2 system
12 is usually called “FNA disintegration”, despite lack of evidence that FNA is the main agent
13 responsible for organic matter breakdown. The aim of this study was to investigate whether FNA
14 or NO2 is the primary disintegration factor of thickened secondary sludge in a wide spectrum of
15 process parameters (T=48h, 0-2280 mgNO2-N/L, pH 3.2-6.4 and FNA between 0 and 47.4
16 mgHNO2-N/L). Statistical analysis based on multiple regression and the Akaike Information
17 Criterion showed that NO2, not FNA, is a main disintegrating factor leading to SCOD release
18 (p=0.005206 and 0.00009 respectively) and that the FNA concentration is without statistical
19 significance (p=0.800234 and 0.328099 respectively). These findings are important as
20 understanding key factors is essential for productive future research and technology development.
21 Moreover, these findings give doubts about the role of FNA in its other applications such as
22 inhibition of nitrification.

2
23 Keywords: Free nitrous acid; Nitrite; Waste activated sludge pre-treatment; AIC; multiple
24 regression
25 1. Introduction
26 Biological wastewater treatment processes generate a significant amount of waste
27 activated sludge (WAS), which later needs to be stabilized. One of the most effective ways for
28 WAS stabilization is anaerobic digestion, which converts organic matter into digestion gas
29 containing 50-70% of methane. This can cover part of a wastewater treatment plant’s (WWTP)
30 energy requirement, in turn reducing its carbon footprint. Anaerobic digestion is typically divided
31 into four steps, including hydrolysis, acidogenesis, acetogenesis, and methanogenesis, among
32 which hydrolysis is a rate-limiting step when solid substrates are taken into account. WAS is
33 particularly difficult to hydrolyze due to its complex composition and floc structures (Zhen et al.,
34 2017). Pre-treatment technologies that enhance hydrolysis, and therefore methane production,
35 include a variety of solutions that are achieved by different means. Biological methods can
36 enhance the biodegradability of WAS by adding selected bacterial strains (Nzila, 2017), enzymes
37 (Bonilla et al., 2018), or substrates that promote methanogenic activity (Montecchio et al., 2019).
38 Among the many methods based on physical processes, ultrasonic and thermal pre-treatment can
39 be distinguished (Choi et al., 2018; Lippert et al., 2020). Chemical methods are mostly based on
40 the use of either strong reagents like acids and alkali (Tulun and Bilgin, 2019), or oxidants that
41 break down sludge cells, in turn, increases the availability of organic matter (Sun et al., 2018).
42 The majority of these techniques generate high investment and operating costs, which usually
43 outweigh the benefits. An emerging chemical method based on FNA/NO2 is one of the alternative
44 methods for disintegration, which can be seen to be an important area of recent research (Duan et
45 al., 2020).

3
46 It was proved in several studies that FNA/NO2 pre-treatment improves WAS
47 solubilization, methane production, and sludge dewaterability. Wang et al. (2013) observed the
48 highest solubilization of WAS after 24 hours of being exposed to 2.13 mg HNO2-N/L. The
49 obtained soluble chemical oxygen demand (SCOD) was six times higher than that obtained in a
50 sample without the addition of FNA/NO2. The efficiency of WAS pre-treatment using various
51 FNA concentrations was studied in biochemical methane potential (BMP) tests by Karimi et al.
52 (2020), Wang et al. (2020), and Zhang et al. (2019), who achieved 25%, 19%, and 31-35%
53 increases in methane yield, respectively. FNA pre-treatment of secondary sludge was also studied
54 in a continuous lab-scale anaerobic digester, resulting in a methane production increase of 16%
55 (Wei et al. 2018). Meng et al. (2020), in pilot-scale research, observed a 37% growth of methane
56 yield and approximately a 50% reduction of WAS viscosity as a result of FNA disintegration.
57 Furthermore, FNA pre-treatment improved sludge dewaterability by 13% (Wei et al 2018).
58 Considering the higher volatile solids destruction, the total reduction of the dewatered sludge
59 volume achieved in that study was 16-17%.
60 In the studies mentioned above, it is arbitrarily assumed that FNA is a disintegration
61 factor. This is supported by Chislett et al. (2020) who demonstrates that FNA rather than NO2 or
62 H+ breaks down a range of cell envelope molecules soluted in water. They tested the effect of
63 FNA on selected molecules representing cell envelope components, while not examined the FNA
64 effects on living cells within the real WAS. Contradicting reports suggesting that NO2, rather than
65 FNA, is a true factor can also be found and those references are based on experiments conducted
66 on real streams. The efficiency of WAS pre-treatment by comparable nitrite concentrations at a
67 pH of 5.5 and 6.7 was tested by Romero-Güiza et al. (2019), who observed similar methane
68 production in both cases, indicating that a lower pH and increase in FNA concentration does not

4
69 lead to better results than a practically FNA free control. Zahedi et al. (2018) observed that the
70 WAS exposure to low FNA concentrations of 0.06 – 0.15 mg HNO2-N/L (174 – 432 mg NO2-
71 N/L) at a pH of 6.8 resulted in a significant SCOD increase after 4h of exposure. In contrast, the
72 same FNA concentrations tested at a pH of 5.5 (9 - 22 mg NO2-N/L) did not cause an increase in
73 SCOD. Additionally, the percentage of damaged cells varied at the same FNA concentrations
74 (but with different nitrite/pH combinations). The observed increase in cell mortality was
75 associated with a growth in nitrite concentration rather than FNA concentration. This suggests
76 that FNA can be less harmful than nitrite, or that a minimum level of nitrite concentration is
77 necessary to cause cell damage.
78 Taking into consideration research papers published to date, it is still highly debatable
79 whether nitrite or FNA is the main factor responsible for the disintegration effect. This research
80 aims to clarify the influence of the major agents (FNA, NO2, pH) on the obtained increase in
81 SCOD concentrations. SCOD is chosen as a disintegration indicator as this parameter is not laden
82 by the influence of other factors contrary for example to BMP. For this purpose, a wide spectrum
83 of FNA/nitrite concentrations at various pH levels was tested during two days of exposure. The
84 obtained results were decomposed on the role of pH and NO2/HNO2 and analyzed using multiple
85 regression and the Akaike Information Criterion (AIC). This is the first paper that examines the
86 importance of N-NO2 and FNA in the mechanism of the disintegration process.
87 2. Material and methods
88 2.1. Sludge sources
89 The Waste activated sludge was collected from a secondary sludge thickener of a
90 biological nutrient removal WWTP (more than 500 000 PE) with a sludge retention time of 25 d
91 in south-west Poland. The main characteristics of the WAS used in this study were total solids

5
92 (TS) - 41.00 ± 2.64 g TS/kg, volatile solids (VS) - 29.04 ± 2.03 g VS/kg, pH - 6.65 ± 0.08, total
93 chemical oxygen demand (TCOD) - 46 380 ± 5 190 mg TCOD/L, and soluble chemical oxygen
94 demand (SCOD) - 95.44 ± 27.58 mg SCOD/L.
95 2.2. Sludge pre-treatment
96 To assess the influence of each disintegration factor, tests at various pH levels were
97 conducted for samples with and without the addition of nitrites. The pre-treatment conditions of
98 all the tests are presented in Table 1. The batch tests were conducted in 2.0 L flasks. Each flask
99 was filled with 1.0 kg of WAS. A stock solution of NaNO2 (20 gN/L) was added to the flasks in
100 order to provide nitrites in the required concentrations. The stock solution was diluted to a
101 volume of 200 ml with distilled water to maintain the same sludge parameters (TS, VS) in all
102 tests regardless of different nitrite concentrations. The pH of the sludge was corrected with a 24%
103 solution of H2SO4.
104 The flasks were mixed in an overhead shaker at a speed of 13 rpm for 48 hours. During this time,
105 changes in pH and N-NO2 were noticed. The desired FNA levels were maintained by daily
106 manual pH and N-NO2 corrections with the reagents mentioned above. The temperature of the
107 samples was recorded throughout all the tests. The FNA concentration was calculated using Eq.1
108 (Park and Bae, 2009) with regards to the average temperature and maintained N-NO2 in each
109 series.
110
𝑆
𝐻𝑁𝑂
2
―
𝑁
=
𝑆
𝑁𝑂
2
―
𝑁
1
+
(
𝑒𝑥𝑝
―
2300/(273
+
𝑇)
·10
𝑝𝐻
)
(1)
111 2.3. Analytical methods
112 Soluble chemical oxygen demand (SCOD) and nitrite were measured using HACH LCK
113 cuvette tests. To determine dissolved substances, the samples were centrifuged for 5 minutes at
114 5 000 rpm, subsequently filtrated through 1.2 µm pore diameter strainers. TS and VS were

6
115 established by following the instructions from Standard Methods (APHA, 2012). The temperature
116 and pH were measured with Hach-Lange LDO and PHC probes, respectively.
117 2.4. Statistical analysis
118 Statistical analysis was performed using Statistica software (Version 13, 2017). Multiple
119 regression and the Akaike information criterion were performed for 17 observations, to which
120 nitrites were added (tests 11-27). The AIC values were calculated for multiple regression models
121 created on the basis of dependent variables with normal distribution, and a power function was
122 chosen as the binding function.
123 3. Results and discussion
124 3.1. General data
125 The SCOD concentrations observed after 48 h of exposure to FNA/nitrite pre-treatment
126 generally increased with increasing nitrite/FNA concentrations (Figure 1). The obtained SCOD
127 concentrations ranged from 2 924 to 6 604 mg O2/L for 33 mg NO2-N/L (pH 5.1) and 2280 mg
128 NO2-N/L (pH 5.6), respectively. These values were 2.1 to 4.7 times higher than the average
129 achieved for the triplicate control sample (test 1-3, pH 6.4). This is in accordance with several
130 studies that reported an increase of released SCOD concentration as a result of FNA/nitrite pre-
131 treatment. Nitrite concentration close to presented in the literature (222 mg NO2-N/L, pH 4.6, 24h
132 exposure) released a 5.3 times higher SCOD than the nitrite-free sample (pH 6.4, 24h). This
133 result was slightly lower than SCOD increase (6 times higher SCOD compared to the control
134 sample) reported by Wang et al. (2013) as a result of WAS exposure to 250 mg NO2-N/L (pH
135 5.5) for 24 hours. The same nitrite concentration (250 mg NO2-N/L) at a pH of 5.0 tested by
136 Meng et al. (2020) yielded over a 7 times greater SCOD value after 24h than without
137 pretreatment. Please note, that in this study as well as in studies mentioned above (Meng et al.,

7
138 2020; Wang et al., 2013), the characteristics of the thickened WAS were comparable in terms of
139 TS (all in range of 40.1 – 42.6 g/L). However, the organic content in this studies was lower
140 compared to Wang et al. (2013) (33.7 gVS/L, 54.1 mgO2/L) and Meng et al. (2020) (33.2 gVS/L,
141 54.4 mgO2/L). The differences in VS may be responsible for the slightly lower increase in SCOD
142 as a result of similar disintegration conditions. The maximum SCOD/VS ratio obtained in this
143 and cited studies was similar at c.a. 0.16 mg SCOD/mg VS. However, in this study it was
144 achieved by applying higher NO2/FNA concentrations, probably due to a significantly longer
145 SRT in this studies (25 d) compared to studies by other authors indicated above (15 d), which
146 resulted in greater degree of WAS mineralization.
147 During the experiment, a decrease in nitrite concentration was noted. This decrease was
148 greater with a lower pH and higher FNA. Such a dependence indicates that the main mechanism
149 responsible for nitrite loss was the decay of HNO2 following the reaction (Eq.2) (Park and Lee,
150 1988).
151
2𝐻𝑁𝑂
2
→
𝑁𝑂
+
𝑁𝑂
2
+
𝐻
2
𝑂 (2)
152 It is coherent with the release of brown gas and chlorine smell (probably nitrogen dioxide), which
153 was especially observed in the flasks with the lowest pH and high FNA concentrations. This
154 phenomenon requires further research, which is not in the scope of this article. The loss of nitrites
155 was not associated with denitrification due to the fact that all the prepared FNA concentrations
156 exceed those reported in literature as inhibitory for that process by over 5 times. Zhou et al.
157 (2011) indicate that even a concentration of 0.066 - 0.2 mg HNO2-N/L can completely inhibit the
158 growth of denitrifying bacteria. Lou et al. (2015) noted total inhibition of the COD removal
159 process at 0.18 mg HNO2-N/L. Moreover, the lack of denitrification during our tests was
160 confirmed experimentally (data not shown).

8
161 3.2. pH impact on WAS disintegration
162 Figure 2 presents the SCOD concentrations obtained after the following days of exposure
163 to various pH levels without the addition of nitrites (tests 1-10). No significant change in SCOD
164 release was observed in the pH range of 5.2 - 6.4. However, it escalated quickly when the pH
165 value dropped to 4.3. The highest recorded SCOD concentrations were approximately 3 000 mg
166 O2/L, which were achieved in the pH range of 3.2 - 3.8. However, this is of little relevance and
167 does not warrant further analysis. The performance observed for the lowest analyzed pH during
168 the following days resulted in an additional SCOD release by nearly 100% in comparison to the
169 control sample (pH 6.4). This is following finding of Lu et al. (2019) who observed an
170 approximately 50% higher soluble total organic carbon (STOC) after 2 days of WAS exposure to
171 a pH of 5.5 than 7.0 (no nitrite addition). Zahedi et al. (2017) also reported a substantial influence
172 of pH adjustment on WAS solubilization, as they observed a 75% higher SCOD release after 8h
173 of exposure to pH 5.5 than without pH control (no nitrite addition). The maximum concentrations
174 of SCOD released by the pH control (in this study and studies mentioned above) were
175 approximately 45 - 70% of the maximum SCOD values obtained in presence of FNA/NO2
176 throughout these studies. This indicates that positive results can be obtained when pH is used as
177 the sole agent for WAS disintegration. Nevertheless, the cumulative methane production
178 presented by Zahedi et al. (2017) shows that this additional SCOD release may not correspond to
179 an increase in methane yield. This issue should be clarified in another study.
180 3.3. Establishment of FNA/NO2 influence
181 Mentioned above results on pH influence evidently indicate that pH is an important factor
182 that leads to substantial SCOD release. It is therefore clear that to obtain the true influence of
183 FNA/NO2, the impact of pH has to be withheld. The net disintegration effect of FNA/NO2 pre-

9
184 treatment on SCOD release was calculated by subtracting data on the influence of pH (Figure 2)
185 from the overall results (Figure 1). Those data are presented in Figure 3 while averaged values of
186 these calculations are shown in Table 2 in the last column. Comparison of raw data with the
187 overlapping influence of pH and net disintegration effect of FNA/NO2 leads to different
188 conclusions. For example, WAS exposure to 0.8 mg HNO2-N/L and 5.0 mg HNO2-N/L (34 and
189 31 mg NO2-N/L) resulted in SCOD release equal to 2 990 mg O2/L and 4 122 mg O2/L
190 respectively, which indicates that increase in FNA is responsible for enhanced disintegration.
191 However, exclusion of pH influence resulted in very similar net SCOD values of 1 447 (31 mg
192 NO2-N/L) and 1 497 mg O2/L (34 mg NO2-N/L) despite important differences in FNA
193 concentrations. That example shows that the difference in SCOD release between samples is due
194 to a difference in pH, and an increase of FNA from 0.8 to 5.0 mgHNO2-N/L leads to no effect, as
195 applied NO2 concentrations are similar. In most cases, the comparison of raw data shows that
196 when pH influence is included SCOD yield increased with FNA increase. However, exclusion of
197 the influence of pH reveals NO2 as true influencing factor. It is therefore found that the released
198 SCOD generally increases with a rise in NO2, rather than pH and FNA values (Table 2, last
199 column). This is further proved by statistical analysis presented below.
200 The net SCOD values were plotted against nitrite concentrations (Figure 3a) and FNA
201 (Figure 3b). It is impossible to match the appropriate curve for the data presented in Figure 3b
202 due to the weak correlation between the FNA concentration and released SCOD values (R2 =
203 0.1294). A significantly better fit of the curve is obtained when the results were presented as the
204 nitrite function (R2 = 0.7504). Despite some outliers, the data in Figure 3a fits well to the
205 estimated curve. To exclude the influence of the highest FNA and NO2 concentrations, both
206 diagrams show curves matched with the exclusion of 2 280 mg NO2-N/L (Figure 3a) and 47.4 mg

10
207 HNO2-N/L (Figure 3b). In both cases, the R2 values, as well as the curves' shapes, are similar to
208 those matched to the whole range of data. However, the difference in p-values indicates that NO2
209 in the 33 – 350 mg NO2-N/L range (p = 0.000014) is statistically more significant than in the
210 entire data range (p = 0.004257). An opposite finding was noted for FNA. In the range of 0.7-
211 16.1 mg HNO2-N/L p-value (p = 0.677367) was greater than in the entire FNA range (p =
212 0.505055) but obtained p-values were significantly higher than for NO2 indicating that the latter
213 variable is statistically more significant. It is obvious that this simple model does not enable for
214 perfect estimation of disintegration effects nor the data obtained during the experiment are
215 perfect, however, it is clearly seen that NO2 is a far more dominant factor.
216 The statistical analysis was deepened and multiple regression and the Akaike information
217 criterion studies were conducted to finally identify whether NO2 or FNA is the main factor
218 responsible for the SCOD release and to confirm or reject conclusions based on studying Table 2
219 and Figure 3. The multiple regression model has been successfully used to determine correlations
220 between variables affecting sludge disintegration results by among others Kavitha et al. (2017)
221 and Shehu et al. (2012). The analyzed data included net SCOD values after 48 hours of exposure
222 as dependent variables, and NO2-N, HNO2-N concentrations as explanatory variables. The results
223 of the multiple regression analysis are presented in Table 3 and the model equation is as follows:
224
𝑌
=
1913.451
+
1.646·
𝑁𝑂
2
+
6.181·𝐹𝑁𝐴 (3)
225 The coefficient of determination is low (R2 = 0.4633), however, this is due to the approximation
226 of results by the linear curve and does not change the overall conclusion. The slope coefficient
227 (b), as well as probability (p), were most meaningful for a constant term (1913.45 and 0.000056
228 respectively). The probability level recorded for NO2 was two orders of magnitude lower than
229 that obtained for FNA (0.005206 vs 0.800234). It was assumed that p<0.05 indicates that the

11
230 variable is statically significant, while higher p values point to a relatively low impact on the
231 SCOD release. Therefore, NO2 was statistically significant in influencing the efficiency of WAS
232 disintegration, while FNA was not. Please note that the p-value for FNA was extremely high in
233 comparison to the p-value for NO2.
234 According to the Akaike criterion definition - the lower its value, the better quality of the model
235 (Motulsky and Christopoulos, 2004). The AIC calculated for the model based on NO2 as the only
236 independent variable was the lowest of any recorded (Table 4). The addition of FNA to the model
237 as the second independent variable increased the recorded AIC from 281.96 to 283.93 and p
238 values from 0.000090 to 0.000470, and thus deteriorated the model's quality. The model based on
239 FNA as the only independent variable has a noticeably higher calculated AIC value than the
240 others (296 vs ca. 282), pointing to its weakest quality. The p-value of the nitrite-based model (p
241 = 0.000090) was significantly lower than 0.05, which is in contrast to the value recorded for the
242 FNA based model (p = 0.328099).
243 The AIC provides data on the probability of which model is correct. According to Motulsky
244 (2004), differences between AIC scores, and not the AIC scores themselves, are the basis for
245 determining probabilities. If the AIC values obtained for two models are equal, it means a 50%
246 chance that each of these models is correct. When the difference between AIC values is 2.0, the
247 probability that a model with a lower AIC is correct increases to 73%. The general relation
248 between the difference in AIC scores and probabilities, as well as the differences obtained in this
249 study, are shown in Figure 4. The probability that the NO2 based model is correct amounts to
250 over 99% when compared to the model based on FNA, as the difference in AIC scores is ca. 16
251 (Figure 4). The two variable-based model (NO2 and FNA), compared to the NO2 based model,

12
252 has a lower probability of being correct (27%), which is in comparison to 73% for the NO2
253 model.
254 The analysis mentioned above indicates that NO2, rather than FNA, is a decisive factor in
255 WAS solubilization. A clear explanation of this issue has important implications for the design of
256 technology and future research. Assuming that NO2 is the major agent, there is no need for pH
257 reduction. This is confirmed by Romero-Güiza et al. (2019), who according to the results of
258 methane production in a continuous lab-scale anaerobic digester concluded that nitrite sludge pre-
259 treatment without acidification is equally effective as FNA pre-treatment. The elimination of
260 requirement for acid to reduce pH brings substantial benefits of improved safety for workers and
261 lower operating costs - over 50% reduction of annual pre-treatment cost reported Romero-Güiza
262 et al. (2019). FNA/NO2 treatment is an emerging solution for various other problems such as
263 inhibition of nitrite oxidizing bacteria in the deammonification process (Tomaszewski et al.,
264 2017) or prevention of sulfide generation by inactivating sewer biofilm (Duan et al., 2020). It is
265 out of the scope of this paper to assess universality of obtained results. However, if that is the
266 case, mentioned above implication will influence not only WAS disintegration process.
267 4. Conclusions
268 Nitrite in combination with pH, rather than FNA, is the main disintegration factor. A
269 substantially better correlation between released SCOD and NO2 compared to FNA was found.
270 The Akaike information criterion and the significance level indicate the best validity of the
271 nitrite-based model. The probability that the NO2-based model is correct rather than the model
272 based on FNA was over 99%. Moreover, the multiple regression indicated a greater impact of
273 NO2 than FNA on the SCOD release.

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274 Declaration of Competing Interest
275 The authors have no competing interests to declare.
276 Acknowledgements
277 The authors gratefully acknowledge co-funding from the National Centre for Research and
278 Development (grant no POIR.04.01.04-00-0109/17-00).
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370 https://doi.org/10.1016/j.watres.2011.06.025
371

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372
373 Figure 1. SCOD after 48 h of disintegration. The pH ranges include the following tests according to Table 1: pH 3.2
374 (test 10), pH 3.8 (test 9), pH 4.0-4.3 (test 8, 17, 18, 22-24), pH 4.6 (test 25), pH 5.0-5.3 (test 6,7, 11-15, 19-21), pH
375 5.5-5.6 (test 5, 16, 26), pH 6.0 (test 4), pH 6.4-6.5 (test 1-3)
376

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377
378 Figure 2. Impact of pH adjustment on sludge disintegration for 24h and 48h of exposure. The average results are
379 presented for replicated tests (pH 5.2 and 6.4).

20
381
382 Figure 3. The average SCOD values obtained for selected a) nitrite concentrations, orange trend line created for NO2
383 value range 33 – 350 mg NO2-N/L (F = 45.59416, p = 0.000014); blue trend line created for the entire NO2 range (F
384 = 11.604587, p = 0.004257); b) FNA concentrations, orange trend line created for HNO2 value range 0.7 – 16.1 mg
385 HNO2-N/L (F = 0.181128, p = 0.677367); blue trend line created for the entire HNO2 range (F = 0.468046, p =
386 0.505055).
387

21
388
389
390 Figure 4. The relationship between the differences in AIC scores (AICA – AICB) and the probability that each model
391 is accurate (AICNO2 – nitrite based model, p = 0.00009; AICFNA – FNA based model, p = 0.328099; AICNO2,FNA –
392 nitrite and FNA based model, p = 0.000470)
393

22
394 Table 1. Sludge pre-treatment conditions, (average value through test ± standard deviation)
FNA,
Nitrite,
FNA,
Nitrite,
Test
mg HNO2-N/L
mg NO2-N/L
pH
Test
mg HNO2-N/L
mg NO2-N/L
pH
1
0.0 ± 0.0
0 ± 0
6.5 ± 0.1*
15
2.0 ± 0.6
83 ± 10
5.0 ± 0.1
2
0.0 ± 0.0
0 ± 0
6.4 ± 0.1*
16
2.1 ± 0.5
280 ± 38
5.5 ± 0.1
3
0.0 ± 0.0
0 ± 0
6.4 ± 0.1*
17
4.6 ± 3.2
29 ± 17
4.1 ± 0.2
4
0.0 ± 0.0
0 ± 0
6.0 ± 0.1
18
5.4 ± 4.2
33 ± 14
4.3 ± 0.3
5
0.0 ± 0.0
0 ± 0
5.6 ± 0.2
19
7.6 ± 2.1
347 ± 21
5.1 ± 0.1
6
0.0 ± 0.0
0 ± 0
5.3 ± 0.3
20
8.0 ± 2.1
348 ± 24
5.1 ± 0.1
7
0.0 ± 0.0
0 ± 0
5.2 ± 0.3
21
5.8 ± 4.4
350 ± 27
5.1 ± 0.2
8
0.0 ± 0.0
0 ± 0
4.3 ± 0.4
22
12.4 ± 4.8
73 ± 22
4.0 ± 0.2
9
0.0 ± 0.0
0 ± 0
3.8 ± 0.5
23
10.9 ± 7.0
69 ± 25
4.2 ± 0.3
10
0.0 ± 0.0
0 ± 0
3.2 ± 0.3
24
11.4 ± 7.8
76 ± 16
4.3 ± 0.3
11
0.7 ± 0.5
33 ± 17
5.1 ± 0.2
25
14.0 ± 6.2
222 ± 50
4.6 ± 0.2
12
0.8 ± 0.4
36 ± 12
5.1 ± 0.1
26
16.1 ± 4.7
2280 ± 245
5.6 ± 0.1
13
1.9 ± 0.7
83 ± 18
5.1 ± 0.1
27
47.4 ± 16.1
286 ± 73
4.0 ± 0.1
14
1.9 ± 0.5
83 ± 12
5.0 ± 0.1
*uncorrected pH value
395

23
396 Table 2. The average SCOD values with the influence of pH included and excluded (average value through test ±
397 standard deviation)
average SCOD after 2d, mg O2/L
nitrite
concentration,
mg NO2-N/L
calculated FNA
concentration,
mg HNO2-N/L
pH
number
of
samples
Raw data (pH
influence
included)
Net FNA/NO2
effect (pH
influence
excluded)
31 ± 3
5.0 ± 0.5
4.2 ± 0.2
2
4122 ± 412
1447 ± 412
34 ± 2
0.8 ± 0.1
5.1 ± 0.0
2
2990 ± 93
1497 ± 93
73 ± 3
11.6 ± 0.8
4.2 ± 0.1
3
4263 ± 338
1501 ± 338
83 ± 0
1.9 ± 0.1
5.0 ± 0.0
3
3341 ± 180
1848 ± 180
222
14.0
4.6
1
4670
1995
280
2.1
5.5
1
3635
2081
286
47.4
4.0
1
5714
2779
348 ± 2
7.1 ± 1.2
5.1 ± 0.1
3
5957 ±145
4464 ± 145
2280
16.1
5.6
1
6604
5050
398

24
399 Table 3. Multiple regression summary of dependent variable SCOD (Standard deviation of estimation: 1026.7,
400 R2=0.4633, F(2, 14) = 6.0420 p<0.01283).
b
standard
deviation
p
Constant term
1913.45
336.66
0.000056
NO2
1.65
0.50
0.005206
FNA
6.18
23.97
0.800234
401

25
402 Table 4. Comparison of multiple regression models according to the Akaike information criterion.
Independent
variable
Degrees of
freedom
AIC
p
Only NO2
1
281.96
0.000090
Only FNA
1
296.33
0.328099
NO2, FNA
2
283.96
0.000470
403
404 Highlights:
405 A wide range of FNA/NO2 concentrations was tested at various pH levels.
406 Without the addition of nitrite, SCOD release increased with a lower pH.
407 Statistical analysis was performed with multiple regression and the AIC.
408 Nitrite was statistically significant in influencing the efficiency of SCOD release.
409 Nitrite, rather than FNA, was the main disintegration factor.
410
411