- Email: [email protected]
Stabilization process in reed bed systems for sludge treatment
Ecological Engineering 102 (2017) 381–389
Contents lists available at ScienceDirect
Ecological Engineering journal homepage: www.elsevier.com/locate/ecoleng
Stabilization process in reed bed systems for sludge treatment Eleonora Peruzzi a,∗ , Cristina Macci a , Serena Doni a , Renato Iannelli b , Grazia Masciandaro a a b
CNR – Institute of Ecosystem Study, Via Moruzzi 1, 56124 Pisa, Italy DESTEC – UNIPI, Via Gabba 22, 56121 Pisa, Italy
a r t i c l e
i n f o
Article history: Received 21 December 2016 Received in revised form 17 February 2017 Accepted 17 February 2017 Keywords: Heavy metal fractionation Humification Logistic fitting Mineralization Persistent organic pollutant Sludge treatment wetlands
a b s t r a c t Reed bed systems (RBS) represent an innovative and ecologically sound treatment method for the stabilization of sludge from wastewater treatment plants (WWTPs), which is also able to provide several ancillary ecosystem services. In this study, the performance of sludge stabilization achieved during the operation of an RBS for the stabilization of excess sludge extracted from a WWTP located in Central Italy (“La Fontina” WWTP, 15,000 p.e.) was studied. In order to evaluate the process of sludge stabilization, parameters representing the biochemical, chemical and chemico-structural properties of organic sludge matter have been tracked during the entire period of operation (6 years). The main aim of this paper is to monitor the stabilization process of sludge organic matter occurring during the main RBS operational stages (commissioning, operation and resting), in order to derive useful rules and parameters for the formulation of novel guidelines for RBS design and operation. Each singular operational stage was characterized by the predominance of a specific process of organic matter stabilization as follows: 1) During the commissioning phase, the mineralization of fresh organic matter turned out to be the primary process, as highlighted by the values of water soluble carbon (4195 mg C/kg dw) and dehydrogenase activity (25.5 mg INTF/kg dw h) reached at 24 months; 2) During the operating phase, the mineralization of pseudo-stable organic matter proved to prevail over the humification process, as demonstrated by the decrease of toluene (from 27.5% to 22.9%) derived from chemical-structural organic matter characterization performed by the Py-GC technique; 3) During the resting period, humification and sanitation processes became predominant, thus enabling a final safe reuse of stabilized sludge as biosolids for land application, proved by the absence of Escherichia coli and Salmonella, and by the values of polycyclic aromatic hydrocarbons (1.53 mg/kg dw), di-2-ethylhexyl-phthalate (3.63 mg/kg dw), nonyl-phenols (20.9 mg/kg dw), and linear alkyl benzene sulfonates (4.99 mg/kg dw). © 2017 Elsevier B.V. All rights reserved.
1. Introduction Natural treatment systems, such as constructed treatment wetlands and waste stabilization ponds, have long been recognized as sources of ecosystem services beyond their primary function of water quality improvement, and as key constituents of a green infrastructure approach to water treatment. Ecologically engineered treatment systems have been identified as sources of provisioning services (such as biomass production for energy gen-
∗ Corresponding author. E-mail address: [email protected] (E. Peruzzi). http://dx.doi.org/10.1016/j.ecoleng.2017.02.017 0925-8574/© 2017 Elsevier B.V. All rights reserved.
eration), regulating services (such as carbon sequestration), habitat and cultural services (Ghermandi and Fichtman, 2015). Constructed wetlands or reed bed systems (RBS) for sludge dewatering and stabilization can be considered as an ecological technology also able to provide several ancillary ecosystem services. Kiviat (2013) recognized the use of Phragmites australis in constructed wetlands for sludge dewatering as a waste-treatment ecosystem service. RBS have also been widely considered as a valid technology for sludge treatment, being cost-efficient and environmentally friendly (Uggetti et al., 2011). In RBSs, sewage sludge is loaded onto the surface of the basins over several years, where it is dewatered, stabilized and turned into biosolids with a high dry solid content for use as an organic
382
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Table 1 Wastewater treatment plants and loading program. RBS – La Fontina Population equivalent (p.e.) Basin area (m2 ) Loading rate (kg dw m−2 y−1 ) Sludge type
30,000 (15,000) 1210 (11 beds) 38 Activated sludge
Commissioning period Loading/Resting Autumn–Winter–Spring (days) Loading/Resting Summer (days)
2005–2007 (1–24 months) 1/20 1/10
Operating period Loading/Resting Autumn–Winter–Spring (days) Loading/Resting Summer (days)
2007–2010 (25–60 months) 1/14 1/7
Resting period before emptying
2010–2011 (60–72 months)
fertilizer on agricultural land (Nielsen et al., 2014). The stabilization process, resulting from the synergic action of plant, organic matter and microorganisms, is a combination of the processes of mineralization and humification of organic matter. The RBS technology was clearly proven to be effective not only in dewatering the sludge (Stefanakis and Tsihrintzis, 2011; Giraldi and Iannelli, 2009; Iannelli et al., 2013) and reducing its pollutant content (Peruzzi et al., 2011b; Matamoros et al., 2012) and pathogen content (Nielsen, 2007), but also in improving the organic matter quality (Uggetti et al., 2010; Peruzzi et al., 2011a; Kołecka and Obarska-Pempkowiak, 2013). However, the simplicity and the low energy and monitoring requirements of this technology are often counterbalanced by possible operational problems, consisting of slow and insufficient dewatering, poor vegetation growth, odour generation, and possible poor mineralization of the sludge residues (Nielsen, 2005). Indeed, operational failures can occur quite often, and are the main cause of the reputation of this technology to be unpredictable (De Maeseneer, 1997; Dominiak et al., 2011). A better comprehension of the stabilization processes occurring in RBSs can enable the possibility to formulate new guidelines for reed bed design and operation, thus leading to improve the competitiveness of RBS sludge treatment by making it more efficient and reliable (Dominiak et al., 2011), thus enabling it to be properly considered as a valid alternative to the traditional sludge treatment strategies, specially feasible for green infrastructure planning. The main aim of this paper is to monitor the process of sludge organic matter stabilization, in relationship to the three main RBS operation phases of commissioning, operation and resting. It is possible to state that different organic matter stabilization phases prevail during the different phases of operation. To achieve this purpose, parameters correlated to chemical, biochemical and chemical-structural properties of organic sludge matter were determined and correlated each other by statistical methods. 2. Materials and methods 2.1. Reed bed system In this paper we report results about the stabilized sludge during one entire cycle (6 years) of full operation (commissioning, operating loading/resting phases, resting period before emptying) (Table 1). La Fontina RBS is located in Pisa (Tuscany, Italy), as part of an urban wastewater treatment plant (WWTP) operated by the
Acque SpA water utility. The RBS system was implemented by refurbishing a set of pre-existing drying beds, which are now equipped with a bottom 25 cm draining layer of 40/70 mm coarse gravel topped with a 15 cm layer of 5 mm fine gravel. Fifty percent of the sludge produced by the WWTP was applied to the basins, while the other 50% was transferred to another WWTP for mechanical dewatering. P. australis seedlings were planted 50 cm apart in August 2005 and watered with effluent from WWTP to enhance plant rooting. The outlet of the drainage system is collected by gravity and then pumped back to the WWTP. The full coverage of plant vegetation was reached after 24 months; in this period, the loading program was less frequent than it was during the operating period. Sludge sampling was carried out since December 2005 for 6 years (3, 6, 9, 12, 18, 24, 30, 36, 42, 48, 54, 60 and 72 months). For each bed, five subsamples were taken, which were mixed in order to obtain a representative sample of each bed. The samples were collected near the gravel layer, after removing plant material. About 20 days before the sampling, the sludge applications were stopped. The last sludge loading was applied after 60 months, and then the full system entered its final resting phase. Characteristics of sewage sludge from WWTP are reported in Table 2. 2.2. Methods pH was estimated on water extract (1:10, w/v), while TOC and TN were assessed by RC-412 multiphase carbon and FP-528 protein/nitrogen (LECO Corporation, St. Joseph, Michigan, USA). Water soluble carbon (WSC), fulvic acids (FA), and humic acids (HA) were determined according to the method of Yeomans and Bremner (1988), while dehydrogenase enzyme (DHase) was measured according to Masciandaro et al. (2000) protocol. Escherichia coli and Salmonella spp. were chosen as faecal bacteria indicators; the presence of E. coli was assessed with the method ISO/DIS 166492 (2001), while Salmonella spp. was detected with APHA method (1998). Chemical-structural analyses were performed following Ceccanti et al. (2007) and Macci et al. (2012) procedures. Briefly, the dried sample was put into microtubes in a CDS Pyroprobe 190 (Oxford, Pennsylvania, USA), then pyrolysis was carried out at 800 ◦ C for 10 s, with a heat gradient of 10 ◦ C/ms directly connected to a Carlo Erba (Milan, Italy) 6000 gas chromatograph with a flame ionization detector (FID). The pyrograms obtained were quantified by normalizing the areas of the characteristic seven peaks (acetic acid, acetonitrile, benzene, toluene, furfural, pyrrole, and phenol). The heavy metal fractionation was determined using the Mocko and Waclawek procedure (2004). Di-2-ethylhexyl-phthalate (DEHP), nonyl-phenols (the sum of nonylphenol, nonyl-phenol-ethoxylate with the one ethoxy group, and nonyl-phenol-ethoxylates with two ethoxy groups (NPE), and linear alkyl benzene sulfonates (LAS)) were simultaneously extracted from air-dried samples with methanol by microwaveassisted extraction, according to Villar et al. (2007). Polycyclic aromatic hydrocarbons (PAH) were extracted with acetone:hexane mixture by microwave assisted extraction, according to Villar et al. (2004). Chromatographic analysis was performed on an Agilent 1100 series high-performance liquid chromatograph (HPLC) equipped with an ultraviolet diode array (DAD) and fluorescence detectors (FL), following Santos et al. (2007), Pakou et al. (2009)
Table 2 Chemical characteristics (means and deviation standard) of the influent sludge. pH; total solids (TS, g/L); volatile solids (VS, %); total nitrogen (TN, %dw); total organic carbon (TOC, %dw); heavy metal total content (mg/kg dw). pH
TS (g/L)
VS (%)
TN (%dw)
TOC (%dw)
Cr (mg/kg dw)
Cu (mg/kg dw)
Ni (mg/kg dw)
Cd (mg/kg dw)
Pb (mg/kg dw)
Zn (mg/kg dw)
6.9 ± 0.5
3.9 ± 0.3
94.4 ± 1.7
8.5 ± 1.2
81.2 ± 7.2
42 ± 16
361 ± 149
31 ± 16
<2
82 ± 23
1015 ± 304
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
383
Fig. 1. Water soluble carbon (mg C/kg dw) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
and Pule et al. (2010) methods. The PAH detected were acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, 1,2-benzanthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, dibenzo[a,h]anthracene, benzo[g,h,i]perylene, and indeno[1,2,3-cd]pyrene. 2.3. Statistical analysis The time courses of the studied parameters were fitted using the logistic curve, a model widely reported for biodegradation of organic compounds such as LAS in sea waters (Perales et al., 2006), AES in sea water (López-Galindo et al., 2010) and glucosinolates in soils (Gimsing et al., 2006). The logistic degradation curve is characterized by an initial phase at a slow rate, followed by a period with fast processes, which follow kinetics similar to first-order reactions, followed in turn by a phase with a slow rate. The logistic curve is given by the function y = K/(1 + ce−rt ), where y is the parameter concentration, t is the time, and K, c, and r are parameters found by fitting. The parameters r and K can be considered as the rate constant and the expected value at the end of the process, respectively. This curve has been previously used for modelling data in RBS (Peruzzi et al., 2015). The procedures for logistic (Geogebra) and for the non-liner model (Prism) were used for data fitting. Analysis of variance (ANOVA) was used to evaluate the differences (p < 0.05%) between times. Principal component analysis (PCA) was applied to all results obtained during the experiments, following Pardo et al. (2004). PCA and ANOVA were determined using STATISTICA 7.0 software. For all statistical analysis each software procedure was followed. 3. Results and discussion 3.1. Organic matter mineralization The pH decreased significantly over time, reaching lower values at the end of each different management period. Stefanakis et al. (2011) reported a significant reduction during the resting phase, due to concomitant processes of dewatering and organic matter decomposition, which led to acid production in sludge residue (Table 3). TOC and TN followed a similar trend over time, as result of organic matter mineralization process, reaching their lowest values at the end of the operational period and during the resting
Table 3 pH, total organic carbon (TOC, %C) and total nitrogen (TN, %N) and Escherichia coli (E. coli, MPN/g dw). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Ns, not sampled. Months
pH
TOC (%C)
TN (%N)
E. coli (MPN/g dw)
3 6 9 12 18 24
6.26b 7.15a 6.50b 5.45c 5.97bc 5.53c
36.61a 30.19b 29.69b 28.15b 25.59c 29.30b
5.43a 5.19a 4.42b 3.77b 3.57bc 4.79ab
1.02E+06a 1.60E+05a ns 3.64E+04ab 1.68E+04b ns
30 36 42 48 54
6.49b 6.27b 5.99bc 5.80bc 5.41c
30.73b 28.00b 25.30c 27.55b 25.15c
4.29b 3.90b 3.82b 3.54bc 2.65c
ns 6.52E+03bc ns <1.00E+03c <1.00E+03c
60 72
6.39b 5.75c
27.67b 25.08c
2.87c 3.18c
ns <1.00E+03c
phases (Table 3). The effectiveness of RBS in mineralizing organic matter was particularly evident in both trends of soluble water carbon (WSC) and dehydrogenase activity (DHase): the former represents the labile fraction of organic matter easily degradable by microorganisms, while the latter indicates the overall metabolic activity (Izquierdo et al., 2005). It is noteworthy that both variables dramatically plummeted during the commissioning period and the values remained low during the operating and resting periods (Figs. 1 and 2). Both processes occurred at the same rate, as proved by the insignificantly different rate constants obtained by the logistic model: 0.025 and 0.073, for WSC and DHase, respectively. Moreover, the logistic fitting obtained the final values of 3178 mg C/kg dw for WSC and 10.2 mg INTF/kg dw h for DHase; these very low values indicated that sludge reached, at the end of the resting period, a notably stable status (Table 6). Similar values were reported by Peruzzi et al. (2015) for a different RBS treating civil sludge. Also hygienization level was an important parameter to track in order to assess the effectiveness of RBSs in stabilizing sludge. E. coli and Salmonella spp. were chosen as faecal bacteria indicators (Table 3): E. coli significantly decreased over time, reaching very small values (<1000 MPN/g dw) since the beginning of the operation phase, while, Salmonella spp., was present in low quan-
384
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Fig. 2. Dehydrogenase activity (mg INTF/kg dw h) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
tities during all periods, from commissioning to final resting (<2 MPN/g dw), thus confirming the findings of Nielsen (2005, 2007) and Uggetti et al. (2012). 3.2. Organic matter humification The transformations of organic matter during the stabilization process, with special reference to the formation of humic substances (humification), have a key role in monitoring the effectiveness of RBSs in sludge stabilization. Humic substances can be classified in two different components: fulvic acids, which identify the less stable part of humic matter, and humic acids, which include the most stable fraction of humic matter. Fulvic acids significantly decreased over time, particularly during the commissioning period, and reached their lowest values at the end of the operational period and during the resting phase (Fig. 3), thus confirming that fulvic acids represent the biodegradable part of humic substances. Conversely, humic acids increased over time after the commissioning period, thus indicating that progressive humification process occurred in the RBS (Fig. 3). The final values found by the logistic fitting (19,333 mg C/kg dw for FA and 17,076 mg C/kg w for HA) were in agreement with the results found for a different reed bed treating civil sludge (Peruzzi et al., 2015). It is noteworthy that these processes proceeded at a comparable degree over time (Table 6), with similar rate constants obtained by the logistic fitting for FA (0.1011) and HA (0.1182). Interesting results, in terms of representativeness of the stabilization process, came also from the chemical-structural organic matter characterization performed by the Py-GC technique (Table 4). The trend of aliphatic carbon (C-AL, constituted by acetic acid and furfural) revealed an initial increase exhibited during the commissioning period, followed by a plateau during the operating phase, and a significant decline during the final resting period. Since acetic acid and furfural derive from lipid compounds (fats and waxes), carbohydrates and lignocellulosic materials, their decrease highlights the occurrence of mineralization process involving the fresh organic matter loaded in the RBS. It is noteworthy that a secondary mineralization process, dependent on pseudo-aromatic substances with long aliphatic chains (pseudo-stable aromatic carbon, C-AR P, constituted by toluene) took place: the C-AR P content remained stable during the commissioning period, then significantly declined during operating and resting phases. Con-
Table 4 Pyrolytic fragments of the sludge. C-AL (acetic acid and furfural, %); C-AR P (toluene, %); C-AR S (benzene and phenol, %), N (acetonitrile and pyrrole, %). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Months
C-AL (%)
C-AR P (%)
C-AR S (%)
N (%)
6 12 18 24
20.88a 25.95b 24.10ab 28.22b
32.59a 29.45ab 29.17ab 28.51ab
26.46ab 27.99ab 25.73ab 24.31a
20.07ab 16.62a 21.00ab 18.96ab
30 36 42 48 54
22.46ab 22.73ab 26.68b 25.64b 29.21b
27.47b 27.37b 24.97bc 24.60bc 22.90c
29.32ab 26.74ab 27.99ab 28.58ab 27.15ab
20.75ab 23.17b 20.36ab 21.17b 20.39ab
60 72
30.02b 25.69b
19.91cd 19.49d
28.30ab 32.29b
22.18b 21.52b
versely, the trend of stable aromatic carbon (C-AR S) highlighted the occurrence of humification. C-AR S, another pyrolytic compound group mainly represented by benzene and phenol deriving from stable condensed aromatic structures, significantly increased, in particular during the resting period. Similar results about toluene decrease and benzene increase were observed by El Fels et al. (2014) during sewage sludge composting. Pyrolytic nitrogen compounds (N) remained quite stable during the commissioning period and slightly increased during operating and resting periods. N is constituted by acetonitrile and pyrrole, two nitrogen compounds which derive from biologically and chemically stable compounds (Song and Farwell, 2008) that are usually correlated, respectively, to humic and fulvic acids (Song and Farwell, 2004). This trend hence demonstrated the establishment of humic substances with a great degree of condensation. 3.3. Heavy metals The detected total metal concentrations (Table 5) are comparable with those observed by Fytili and Zabaniotou (2008) for European sewage sludge and by Matamoros et al. (2012) for stabilized sludge treated in RBS. The procedure for heavy metal fractionation allowed us to individuate the following four fractions characterized by the decreasing degree of bioavailability:
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
385
Fig. 3. Fulvic acids (mg C/kg dw) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Humic acids (mg C/kg dw) during the commissioning period (blue squares), the operating period (orange squares), and the resting period (green squares); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 5 Heavy metal total content of the sludge (mg/kg dw). All results are expressed in mg/kg dw. Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Typical heavy metal content in wastewater sludge (Fytili and Zabaniotou, 2008) and heavy metal concentration in a stabilized sludge in RBS (Matamoros et al., 2012) (range and median values, mg dw/kg). Months
Cr (mg/kg dw)
Cu (mg/kg dw)
Ni (mg/kg dw)
Cd (mg/kg dw)
Pb (mg/kg dw)
Zn (mg/kg dw)
6 12 18 24 30 36 42 48 54 60 72
29a 59b 57b 60b 123c 24a 37ab 55b 14a 38ab 32ab
362a 410a 422ab 550b 573b 556b 578b 549b 390a 611b 492b
67b 34a 45ab 55ab 52ab 32a 33a 34a 34a 47ab 46ab
2.7a <2a 3.7b <1.5a 2.53b 1.62a 2a 2a 1.91a 1.52a 1.67a
91 93 104 60 86 99 69 43 78 66 91
917a 1297ab 1332ab 1760b 1836b 1538b 1437ab 1705b 1209a 1853b 1765b
Fytili and Zabaniotou (2008) Matamoros et al. (2012)
10–990 (500) 42–71 (56)
84–17,000 (800) 184–330 (256)
2–5300 (80) 30–43 (41)
1–3.41 (1) 61–152 (88)
13–26,000 (500) 1098–1550 (1366)
101–49,000 (1700) 1.3–2.3 (1.8)
- Fraction 1 (exchangeable fraction) which is the most mobile portion, potentially toxic for plants. In this fraction, metals are adsorbed on sludge components or present in the form of Fe and Mn hydroxides; - Fraction 2 (reducible fraction) where heavy metals are strongly bound to Fe and Mn oxides, but get thermodynamically unstable when in acidic and anoxic conditions; - Fraction 3 (oxidizable fraction bound to organic matter) where heavy metals are complexed by humic substances and become soluble when organic matter is degraded in oxidizing conditions. This fraction is considered to be neither bioavailable nor mobile; - Fraction 4 (residual fraction) which is considered to be not extractable and in an inert form, with heavy metals included in crystalline structures within the residuals solids.
The concentrations of different metals (expressed in mEq/kg) were summed for each fraction (Figs. 4 and 5). Fraction 1 and fraction 2 content significantly declined over time, as already noticed in other papers (Kołecka and Obarska-Pempkowiak, 2013; Peruzzi et al., 2013), as the stabilization proceeded in RBS. Other authors found higher content of metals associated with fraction 1 and fraction 2 in sewage sludge stabilized with traditional methods (Walter et al., 2006; Fuentes et al., 2008). On the basis on the results pub-
lished by Walter et al. (2006), 11.8% and 26.2% heavy metals in anaerobic sewage sludges, were mainly associated with fraction 1 and 2, respectively; similarly, Fuentes et al. (2008) found that the sum of fraction 1 and fraction 2 reached 31.3% and 40.9% in aerobic sludges and heat treated sludges, respectively. As the bioavailable fraction dropped, the fraction 3, bound to organic matter significantly rose, as a consequence of humification process (Peruzzi et al., 2015). The two processes, in fact, occurred similarly, as highlighted by the insignificant rate constant of logistic fitting (0.075 and 0.056 for Fr 1 and Fr 3, respectively). It is noteworthy that these rate constants are quite similar to the rate constants of FA and HA trends, thus pointing out that all stabilization processes in RBS proceeded to the same degree. The final value found by the logistic fitting (12.5% and 48.2% for Fr 1 and Fr 3, respectively) were in agreement with the results found for a different reed bed treating civil sludge (Table 6) (Peruzzi et al., 2015).
3.4. Toxic organic compounds The aerobic conditions of the basins affected not only the extent of mineralization and humification, but also the biodegradation of toxic organic compounds, such as polycyclic aromatic hydrocarbons (PAH), nonylphenol and nonylphenol ethoxylates
386
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Fig. 4. Heavy metal fractionation (%).
Fig. 5. Fraction 1 (%) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Fraction 3 (%) during the commissioning period (blue squares), the operating period (orange squares), and the resting period (green squares); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 6 Logistic fitting. Rate constant, final value, coefficient c and R2 . Different letters mean values significantly different (HSD Tukey—p < 0.05) over time.
WSC Dhase FA HA (x > 30) Fr 1 Fr 3
Rate constant (r)
Final value (K)
c
2 Radj
0.025a 0.073ab 0.1011b 0.1182b 0.075ab 0.056ab
3178 mg C/kg dw 10.2 mg INTF/kg dw h 19,333 mg C/kg dw 17,076 mg C/kg dw 12.5% 48.2%
−1.02 −1.00 −1.35 3.29 −1.00 2.84
0.9873 0.9875 0.9803 0.9952 0.9861 0.9714
(NPE), di-2-ethylhexyl-phthalate (DEHP) and linear alkylbenzene sulfonates (LAS). The presence of these compounds may affect the possible land application of stabilized sludges as biosolid; hence, it is important that RBS managers monitor the presence of such compounds, especially during the final resting period. For this reason, several European countries (Tunc¸al et al., 2011) and local author-
ities have set regulations for land application of biosolids, which consider the presence of priority toxic organic compounds as a possible threat to human health. Results about toxic organic compounds are reported in Table 7. As reported by Mezzanotte et al. (2016), PAH inputs in wastewater sewage sludge can be estimated by the phenanthrene/anthracene and fluoranthene/pyrene ratios. Combustion of various natural and synthetic compounds and deposition from atmosphere are correlated to values >1 for fluoranthene/pyrene ratio (1.59) and <10 for phenanthrene/anthracene ratio (1.82). The mean PAH content found in influent sludge was 4.74 mg/kg dw, among which 44.6% of low molecular weight (Ace, Flu, Phe, Ant and Fln, with 2–3 rings), 30.0% of middle molecular weight (Pyr, BaA, Chr, BaF and BkF, 4 rings) and 25.4% of high molecular weight (BaP, DahA, BghiP and InP, 5–6 rings). PAH content reached 1.55 mg/kg (67,4% decrease) at the end of the operation period (after 60 months) and 1.39 mg/kg (70.8% decrease) after the resting
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
387
Fig. 6. Principal component analysis: score plots. (a) PC 1 and PC 2. (b) PC 3 and PC 2. Commissioning period (blue squares), operating period (orange squares), resting period (green squares). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 7 Toxic organic compounds in influent sludge and in stabilized sludges at 60 and 72 months (mg/kg dw). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Acenaphthene (Ace), fluorene (Flu), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fln), pyrene (Pyr), 1,2-benzanthracene (BaA), chrysene (Cry), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), dibenzo[a,h]anthracene (DahA), benzo[g,h,i]perylene (BghiP), indeno[1,2,3-cd]pyrene (InP), linear alkylbenzene sulfonates (LAS), nonylphenols (NPE) and di-2-ethylhexyl-phthalate (DEHP). Compound (mg/kg dw)
Influent sludge
60 months
72 months
Ace Flu Phe Ant Fln Pyr BaA Cry BbF BkF BaP DahA BghiP InP LAS NPE DEHP
0.347a 0.530a 0.459a 0.252a 0.527a 0.331a 0.266a 0.246a 0.269a 0.311a 0.394a 0.339a 0.258a 0.314a 464a 62.9a 11.4a
0.329a 0.410a 0.237b <0.05b 0.065b 0.066b <0.05b 0.143b 0.061b <0.05b <0.05b 0.109b 0.074b 0.354a 7.18b 41.9b 3.47b
0.322a 0.111b 0.302b <0.05b <0.05b <0.05b <0.05b 0.149b 0.050b <0.05b <0.05b 0.119b 0.056b 0.126b 4.99b 20.9c 3.63b
period, thus demonstrating that mineralization process involved also hydrocarbon compounds. For low, medium and high molecular weight compounds, Cui et al. (2015) observed a removal efficiency of 67.7%, 79.3% and 52.8% after 60 months and 62.9%, 80.5% and 73.1% after 72 months, respectively. It is worth noticing that the process involved not only the low and medium molecular weight compounds, but also the more recalcitrant compounds, especially in the final resting period: the high molecular weight reduction rate increased from 52.8% (after 60 months) to the final 73.1%. Similar reduction levels can be observed for NPE and DEHP, which are hydrophobic compounds deriving from hygienic/cleaning products and plastic softeners, respectively. At the end of the operative phase (60 months), NPE declined of about 33.4% from the initial content of 62.9 mg/kg dw and DEHP declined of 69.6% from the initial content of 11.4 mg/kg dw. Moreover, during the resting period, NPE content halved, reaching a final concentration of 20.9 mg/kg dw. As expected, LAS, easily biodegradable surfactants arising from detergents, were easily degraded in RBS, reaching the very small value of 7.18 mg/kg dw after 60 months (decrease of 98.5%) from the initial influent sludge concentration of 464 mg/kg dw. All these results present similarities with the concentrations of organic pollutants detected by Matamoros et al. (2012), Peruzzi et al. (2011b, 2013) and Cui et al. (2015) in RBS stabilized sludge.
388
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Table 8 Principal component analysis. PC 1
PC 2
PC 3
TOC TN pH Dhase WSC FA HA C-AL (Py) C-AR P (Py) C-AR S (Py) N (Py) Fr 1 Fr 2 Fr 3
0.33 0.55 0.61* 0.94* 0.68* 0.85* 0.09 −0.23 0.55 −0.05 0.01 0.94* 0.78* −0.46
0.64* 0.70* 0.40 0.18 0.56 0.40 −0.87* −0.32 0.65* −0.03 0.06 0.02 0.05 −0.26
0.50 0.05 0.51 −0.05 0.03 0.09 0.25 0.49 −0.25 0.83* 0.77* −0.17 −0.33 0.67*
Total proportionality
0.35
0.21
0.20
*
Variables with component loading used to interpret the PC, threshold level 0.7.
3.5. Principal component analysis The PCA of the data set indicated 76.3% of the data variance as being contained in the first three components (Table 8). PC1, PC2 and PC3 accounted for 35.0%, 21.0% and 20.0% of the total variance, respectively. PC1 was closely associated with all parameters linked to the primary mineralization of organic matter: Dhase activity, WSC, pH, fulvic acids, fraction 1 and fraction 2. The parameters connected to the secondary mineralization were significant on PC2: total organic carbon, total nitrogen, humic acids and C-AR P. Conversely, PC3 was mainly associated to humification process: C-AR S, N and fraction 3. The score plots provide a graphical representation of the different sampling times, by identifying the parameters that exhibited the highest level of association. In the plot PC1 × PC2 (Fig. 6a), all times were characterized by the same position on PC 1, with the exception of 6 months, which was located to the right of the plot. This shift demonstrates that the primary mineralization process principally occurred during the commissioning period. Considering PC2, the times of operating phase were segregated in the top, while the resting period was located at the bottom, thus underlining that secondary mineralization process principally occurred during the operating phase. In the PC3 × PC2 plot (Fig. 6b), the different phases of commissioning, operating and resting were clearly discriminated along PC3, with the commissioning phase located in the left, the operative period in the middle, and the resting phase in the right of the plot. This progressive shift across PC3 clearly shows that humification process affected the operative phase and, even more, the resting phase. 4. Conclusions This study demonstrated the pathways of organic matter stabilization occurring in a sludge stabilization reed bed during a complete 72 month-long cycle. The biological stabilization, depending on fresh organic matter, was underlined by the decrease of water-soluble carbon, dehydrogenase activity, fulvic acids and bioavailable heavy metals. The mineralization of pseudo-stable substances and the progressive humification were clearly proven by the humic acid content and by the trend of chemical-structural parameters. Each different operational phase was characterized by the prevalence of a specific process of organic matter stabilization: 1) The mineralization of fresh organic matter was the main process observed during the initial commissioning phase;
2) The mineralization of pseudo-stable organic matter prevailed over the humification process during the central operating phase; 3) The humification process became prevalent during the final resting period. Moreover, during the last resting period, a significant reduction of persistent organic compounds and faecal bacteria indicators was reached, thus enabling a possible safe reuse of stabilized sludge as biosolids for land application. Finally, the logistic fitting described the overall trend of the organic matter sludge stabilization, thus allowing us to provide useful information for the formulation of new reed bed design and operation guidelines. Additional studies devoted to the quantification of the ecosystem services provided by RBSs are advisable, as they could further improve the competitiveness of this environmental-friendly technique of sludge stabilization over conventional technologies especially in green urban infrastructure planning. Acknowledgement This work was supported by ACQUE SpA (Pisa, Italy). References APHA, 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. American Public Health Association, New York. Ceccanti, B., Masciandaro, G., Macci, C., 2007. Pyrolysis-gas chromatography to evaluate the organic matter quality in a mulched soil. Soil Tillage Res. 97, 71–78. Cui, Y., Zhang, W., Sun, H., Wu, W.M., Zou, X., 2015. Polycyclic aromatic hydrocarbon accumulation in Phragmites australis grown on constructed wetland for sludge stabilization. J. Residuals Sci. Technol. 12 (4), 215–220. De Maeseneer, J.L., 1997. Constructed wetlands in Europe. Water Sci. Technol. 35, 279–285. Dominiak, D., Christensen, M.L., Keiding, K., Nielsen, P.H., 2011. Sludge quality aspects of full-scale reed bed drainage. Water Res. 45 (19), 6453–6460. Draft International Standard ISO/DIS 16649-2, 2001. Microbiology of Food and Animal Feeding Stuffs, Horizontal Method for the Enumeration of Presumptive. El Fels, L., Lemee, L., Ambles, A., Hafidi, M., 2014. Identification and biotransformation of lignin compounds during co-composting of sewage sludge-palm tree waste using pyrolysis-GC/MS. Int. Biodeterior. Biodegrad. 92, 26–35. ˜ J.F., Meseguer, V.F., 2008. Fuentes, A., Lloréns, M., Sáez, J., Isabel Aguilar, M., Ortuno, Comparative study of six ls. Bioresour. Technol. 99 (3), 517–525, http://dx.doi. org/10.1016/j.biortech.2007.01.025. Fytili, D., Zabaniotou, A., 2008. Utilization of sewage sludge in EU application of old and new methods—a review. Renew. Sustain. Energy Rev. 12, 116–140. Ghermandi, A., Fichtman, E., 2015. Cultural ecosystem services of multifunctional constructed treatment wetlands and waste stabilization ponds: time to enter the mainstream? Ecol. Eng. 84 (C), 615–623. Gimsing, A.L., Sorensen, J.C., Tovgaard, L., Friis Jorgensen, A.M., Bruun Hansen, H.C., 2006. Degradation kinetics of glucosinolates in soil. Environ. Toxicol. Chem. 25, 2038–2044. Giraldi, D., Iannelli, R., 2009. Short-term water content analysis for the optimization of sludge dewatering in dedicated constructed wetlands (reed bed systems). Desalination 246, 92–99. Iannelli, R., Nielsen, S., Peruzzi, E., Piras, F., Støvring, M., Masciandaro, G., 2013. Short-term performance analysis of sludge treatment reed beds. Water Sci. Technol. 68, 1520–1528. Kiviat, E., 2013. Ecosystem services of Phragmites in North America with emphasis on habitat functions. AoB Plants 5, 1–29. Kołecka, K., Obarska-Pempkowiak, H., 2013. Potential fertilizing properties of sewage sludge treated in the sludge treatment reed beds (STRB). Water Sci. Technol. 68, 1412–1418. Izquierdo, I., Caravaca, F., Alguacil, M.M., Hernández, G., Roldán, A., 2005. Use of microbiological indicators for evaluating success in soil restoration after revegetation of a mining area under subtropical conditions. Appl. Soil Ecol. 30, 3–10. López-Galindo, C., Garrido, M.C., Casanueva, J.F., Nebot, E., 2010. Degradation models and ecotoxicity in marine waters of two anti-fouling compounds: sodium hypochlorite and an alkylamine surfactant. Sci. Total Environ. 408, 1779–1785. Macci, C., Doni, S., Peruzzi, E., Ceccanti, B., Masciandaro, G., 2012. Pyrolysis-gas chromatography to evaluate the organic matter quality of different degraded soil ecosystems. In: Advanced Gas Chromatography—Progress in Agricultural, Biomedical and Industrial Applications., pp. 283–306.
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389 Masciandaro, G., Ceccanti, B., Ronchi, V., Bauer, C., 2000. Kinetic parameter of dehydrogenase in the assessment of the response of soil to vermicompost and inorganic fertilisers. Biol. Fertil. Soils 32, 479–483. Matamoros, V., Nguyen, L.X., Arias, C.A., Nielsen, S., Laugen, M.M., Brix, H., 2012. Musk fragrances, DEHP and heavy metals in a 20 years old sludge treatment reed bed system. Water Res. 46, 3889–3896. Mezzanotte, V., Anzano, M., Collina, E., Marazzi, F.A., Lasagni, M., 2016. Distribution and removal of polycyclic aromatic hydrocarbons in two italian municipal wastewater treatment plants in 2011–2013. Polycycl. Aromat. Compd. 36 (3), 213–228. Mocko, A., Waclawek, W., 2004. Three-step extraction procedure for determination of heavy metals availability to vegetables. Anal. Bioanal. Chem. 380, 813–817. Nielsen, S., 2005. Sludge reed bed facilities: operation and problems. Water Sci. Technol. 9, 99–107. Nielsen, S., 2007. Helsinge sludge reed bed system—reduction of pathogenic microorganisms. Water Sci. Technol. 56 (3), 175–182. Nielsen, S., Peruzzi, E., Macci, C., Doni, S., Masciandaro, G., 2014. Stabilisation and mineralisation of sludge in reed bed systems after 10–20 years of operation. Water Sci. Technol. 69, 539–545. Pakou, C., Kornaros, M., Stamatelatou, K., Lyberatos, G., 2009. On the fate of LAS, NPEOs and DEHP in municipal sewage sludge during composting. Bioresour. Technol. 100 (4), 1634–1642. Pardo, R., Helena, B.A., Cazurro, C., Guerra, C., Deban, L., Guerra, C.M., Vega, M., 2004. Application of two- and three-way principal component analysis to the interpretation of chemical fractionation results obtained by the use of the B.C.R. procedure. Anal. Chim. Acta 523, 125–132. Perales, J.A., Manzano, M., Garrido, M.C., Sales, D., Quiroga, J.M., 2006. Biodegradation kinetics of linear alkylbenzene sulphonates in sea water. Biodegradation 18, 63–70. Peruzzi, E., Masciandaro, G., Macci, C., Doni, S., Ravelo, S.G.M., Peruzzi, P., Ceccanti, B., 2011a. Heavy metal fractionation and organic matter stabilization in sewage sludge treatment wetlands. Ecol. Eng. 37, 771–778. Peruzzi, E., Masciandaro, G., Macci, C., Doni, S., Ceccanti, B., 2011b. Pollutant monitoring in sludge treatment wetlands. Water Sci. Technol. 64, 1558–1565. Peruzzi, E., Nielsen, S., Macci, C., Doni, S., Iannelli, R., Chiarugi, M., Masciandaro, G., 2013. Organic matter stabilization in reed bed systems: Danish and Italian examples. Water Sci. Technol. 68, 1888–1894. Peruzzi, E., Macci, C., Doni, S., Volpi, M., Masciandaro, G., 2015. Organic matter and pollutants monitoring in reed bed systems for sludge stabilization: a case study. Environ. Sci. Pollut. Res. 22, 2447–2454. Pule, B.O., Mmualefe, L.C., Torto, N., 2010. Analysis of Polycyclic Aromatic Hydrocarbons in Soil with Agilent SampliQ QuEChERS AOAC Kit and HPLC-FLD. 5990-5452EN, Application note available on http://www.agilent.com/cs/ agilent/en-us/promotions/applicationfinder.
389
Santos, J.L., Aparicio, I., Alonso, E., 2007. A new method for the routine analysis of LAS and PAH in sewage sludge by simultaneous sonication-assisted extraction prior to liquid chromatographic determination. Anal. Chim. Acta 605 (1), 102–109. Song, X., Farwell, S.O., 2004. Pyrolysis gas chromatography atomic emission detection method for determination of N-containing components of humic and fulvic acids. J. Anal. Appl. Pyrolysis 71, 901–915. Song, X., Farwell, S.O., 2008. Forms of soil organic nitrogen in a Pactola soil as seen by pyrolysis/gas chromatography/atomic emission detection (Py–GC/AED). J. Anal. Appl. Pyrolysis 83, 190–196. Stefanakis, A.I., Tsihrintzis, V.A., 2011. Dewatering mechanisms in pilot-scale sludge drying reed beds: effect of design and operational parameters. Chem. Eng. J. 172, 430–443. Stefanakis, A.I., Komilis, D.P., Tsihrintzis, V.A., 2011. Stability and maturity of thickened wastewater sludge treated in pilot-scale sludge treatment wetlands. Water Res. 45, 6441–6452. Tunc¸al, T., Jangam, S.V., Günes¸, E., 2011. Abatement of organic pollutant concentrations in residual treatment sludges: a review of selected treatment technologies including drying. Dry. Technol. 29 (14), 1601–1610. Uggetti, E., Ferrer, I., Llorens, E., García, J., 2010. Sludge treatment wetlands: a review on the state of the art. Bioresour. Technol. 101 (9), 2905–2912. Uggetti, E., Ferrer, I., Molist, J., García, J., 2011. Technical, economic and environmental assessment of sludge treatment wetlands. Water Res. 45 (2), 573–582. Uggetti, E., Ferrer, I., Nielsen, S., Arias, C., Brix, H., García, J., 2012. Characteristics of biosolids from sludge treatment wetlands for agricultural reuse. Ecol. Eng. 40, 210–216. Villar, M., Callejon, M., Jiménez, J.C., Alonso, E., Guiraúm, A., 2007. Optimization and validation of a new method for analysis of linear alkylbenzene sulfonates in sewage sludge by liquid chromatography after microwave-assisted extraction. Anal. Chim. Acta 599 (1), 92–97. Villar, P., Callejon, M., Alonso, E., Jiménez, J.C., Guiraúm, A., 2004. Optimization and validation of a new method of analysis for polycyclic aromatic hydrocarbons in sewage sludge by liquid chromatography after microwave assisted extraction. Anal. Chim. Acta 524 (1–2), 295–304. Walter, I., Martínez, F., Cala, V., 2006. Heavy metal speciation and phytotoxic effects of three representative sewage sludges for agricultural uses. Environ. Pollut. 139 (3), 507–514, http://dx.doi.org/10.1016/j.envpol.2005.05.020. Yeomans, J.C., Bremner, J.M., 1988. A rapid and precise method for routine determination of organic carbon in soil. Commun. Soil Sci. Plant Anal. 19, 1467–1476.
Contents lists available at ScienceDirect
Ecological Engineering journal homepage: www.elsevier.com/locate/ecoleng
Stabilization process in reed bed systems for sludge treatment Eleonora Peruzzi a,∗ , Cristina Macci a , Serena Doni a , Renato Iannelli b , Grazia Masciandaro a a b
CNR – Institute of Ecosystem Study, Via Moruzzi 1, 56124 Pisa, Italy DESTEC – UNIPI, Via Gabba 22, 56121 Pisa, Italy
a r t i c l e
i n f o
Article history: Received 21 December 2016 Received in revised form 17 February 2017 Accepted 17 February 2017 Keywords: Heavy metal fractionation Humification Logistic fitting Mineralization Persistent organic pollutant Sludge treatment wetlands
a b s t r a c t Reed bed systems (RBS) represent an innovative and ecologically sound treatment method for the stabilization of sludge from wastewater treatment plants (WWTPs), which is also able to provide several ancillary ecosystem services. In this study, the performance of sludge stabilization achieved during the operation of an RBS for the stabilization of excess sludge extracted from a WWTP located in Central Italy (“La Fontina” WWTP, 15,000 p.e.) was studied. In order to evaluate the process of sludge stabilization, parameters representing the biochemical, chemical and chemico-structural properties of organic sludge matter have been tracked during the entire period of operation (6 years). The main aim of this paper is to monitor the stabilization process of sludge organic matter occurring during the main RBS operational stages (commissioning, operation and resting), in order to derive useful rules and parameters for the formulation of novel guidelines for RBS design and operation. Each singular operational stage was characterized by the predominance of a specific process of organic matter stabilization as follows: 1) During the commissioning phase, the mineralization of fresh organic matter turned out to be the primary process, as highlighted by the values of water soluble carbon (4195 mg C/kg dw) and dehydrogenase activity (25.5 mg INTF/kg dw h) reached at 24 months; 2) During the operating phase, the mineralization of pseudo-stable organic matter proved to prevail over the humification process, as demonstrated by the decrease of toluene (from 27.5% to 22.9%) derived from chemical-structural organic matter characterization performed by the Py-GC technique; 3) During the resting period, humification and sanitation processes became predominant, thus enabling a final safe reuse of stabilized sludge as biosolids for land application, proved by the absence of Escherichia coli and Salmonella, and by the values of polycyclic aromatic hydrocarbons (1.53 mg/kg dw), di-2-ethylhexyl-phthalate (3.63 mg/kg dw), nonyl-phenols (20.9 mg/kg dw), and linear alkyl benzene sulfonates (4.99 mg/kg dw). © 2017 Elsevier B.V. All rights reserved.
1. Introduction Natural treatment systems, such as constructed treatment wetlands and waste stabilization ponds, have long been recognized as sources of ecosystem services beyond their primary function of water quality improvement, and as key constituents of a green infrastructure approach to water treatment. Ecologically engineered treatment systems have been identified as sources of provisioning services (such as biomass production for energy gen-
∗ Corresponding author. E-mail address: [email protected] (E. Peruzzi). http://dx.doi.org/10.1016/j.ecoleng.2017.02.017 0925-8574/© 2017 Elsevier B.V. All rights reserved.
eration), regulating services (such as carbon sequestration), habitat and cultural services (Ghermandi and Fichtman, 2015). Constructed wetlands or reed bed systems (RBS) for sludge dewatering and stabilization can be considered as an ecological technology also able to provide several ancillary ecosystem services. Kiviat (2013) recognized the use of Phragmites australis in constructed wetlands for sludge dewatering as a waste-treatment ecosystem service. RBS have also been widely considered as a valid technology for sludge treatment, being cost-efficient and environmentally friendly (Uggetti et al., 2011). In RBSs, sewage sludge is loaded onto the surface of the basins over several years, where it is dewatered, stabilized and turned into biosolids with a high dry solid content for use as an organic
382
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Table 1 Wastewater treatment plants and loading program. RBS – La Fontina Population equivalent (p.e.) Basin area (m2 ) Loading rate (kg dw m−2 y−1 ) Sludge type
30,000 (15,000) 1210 (11 beds) 38 Activated sludge
Commissioning period Loading/Resting Autumn–Winter–Spring (days) Loading/Resting Summer (days)
2005–2007 (1–24 months) 1/20 1/10
Operating period Loading/Resting Autumn–Winter–Spring (days) Loading/Resting Summer (days)
2007–2010 (25–60 months) 1/14 1/7
Resting period before emptying
2010–2011 (60–72 months)
fertilizer on agricultural land (Nielsen et al., 2014). The stabilization process, resulting from the synergic action of plant, organic matter and microorganisms, is a combination of the processes of mineralization and humification of organic matter. The RBS technology was clearly proven to be effective not only in dewatering the sludge (Stefanakis and Tsihrintzis, 2011; Giraldi and Iannelli, 2009; Iannelli et al., 2013) and reducing its pollutant content (Peruzzi et al., 2011b; Matamoros et al., 2012) and pathogen content (Nielsen, 2007), but also in improving the organic matter quality (Uggetti et al., 2010; Peruzzi et al., 2011a; Kołecka and Obarska-Pempkowiak, 2013). However, the simplicity and the low energy and monitoring requirements of this technology are often counterbalanced by possible operational problems, consisting of slow and insufficient dewatering, poor vegetation growth, odour generation, and possible poor mineralization of the sludge residues (Nielsen, 2005). Indeed, operational failures can occur quite often, and are the main cause of the reputation of this technology to be unpredictable (De Maeseneer, 1997; Dominiak et al., 2011). A better comprehension of the stabilization processes occurring in RBSs can enable the possibility to formulate new guidelines for reed bed design and operation, thus leading to improve the competitiveness of RBS sludge treatment by making it more efficient and reliable (Dominiak et al., 2011), thus enabling it to be properly considered as a valid alternative to the traditional sludge treatment strategies, specially feasible for green infrastructure planning. The main aim of this paper is to monitor the process of sludge organic matter stabilization, in relationship to the three main RBS operation phases of commissioning, operation and resting. It is possible to state that different organic matter stabilization phases prevail during the different phases of operation. To achieve this purpose, parameters correlated to chemical, biochemical and chemical-structural properties of organic sludge matter were determined and correlated each other by statistical methods. 2. Materials and methods 2.1. Reed bed system In this paper we report results about the stabilized sludge during one entire cycle (6 years) of full operation (commissioning, operating loading/resting phases, resting period before emptying) (Table 1). La Fontina RBS is located in Pisa (Tuscany, Italy), as part of an urban wastewater treatment plant (WWTP) operated by the
Acque SpA water utility. The RBS system was implemented by refurbishing a set of pre-existing drying beds, which are now equipped with a bottom 25 cm draining layer of 40/70 mm coarse gravel topped with a 15 cm layer of 5 mm fine gravel. Fifty percent of the sludge produced by the WWTP was applied to the basins, while the other 50% was transferred to another WWTP for mechanical dewatering. P. australis seedlings were planted 50 cm apart in August 2005 and watered with effluent from WWTP to enhance plant rooting. The outlet of the drainage system is collected by gravity and then pumped back to the WWTP. The full coverage of plant vegetation was reached after 24 months; in this period, the loading program was less frequent than it was during the operating period. Sludge sampling was carried out since December 2005 for 6 years (3, 6, 9, 12, 18, 24, 30, 36, 42, 48, 54, 60 and 72 months). For each bed, five subsamples were taken, which were mixed in order to obtain a representative sample of each bed. The samples were collected near the gravel layer, after removing plant material. About 20 days before the sampling, the sludge applications were stopped. The last sludge loading was applied after 60 months, and then the full system entered its final resting phase. Characteristics of sewage sludge from WWTP are reported in Table 2. 2.2. Methods pH was estimated on water extract (1:10, w/v), while TOC and TN were assessed by RC-412 multiphase carbon and FP-528 protein/nitrogen (LECO Corporation, St. Joseph, Michigan, USA). Water soluble carbon (WSC), fulvic acids (FA), and humic acids (HA) were determined according to the method of Yeomans and Bremner (1988), while dehydrogenase enzyme (DHase) was measured according to Masciandaro et al. (2000) protocol. Escherichia coli and Salmonella spp. were chosen as faecal bacteria indicators; the presence of E. coli was assessed with the method ISO/DIS 166492 (2001), while Salmonella spp. was detected with APHA method (1998). Chemical-structural analyses were performed following Ceccanti et al. (2007) and Macci et al. (2012) procedures. Briefly, the dried sample was put into microtubes in a CDS Pyroprobe 190 (Oxford, Pennsylvania, USA), then pyrolysis was carried out at 800 ◦ C for 10 s, with a heat gradient of 10 ◦ C/ms directly connected to a Carlo Erba (Milan, Italy) 6000 gas chromatograph with a flame ionization detector (FID). The pyrograms obtained were quantified by normalizing the areas of the characteristic seven peaks (acetic acid, acetonitrile, benzene, toluene, furfural, pyrrole, and phenol). The heavy metal fractionation was determined using the Mocko and Waclawek procedure (2004). Di-2-ethylhexyl-phthalate (DEHP), nonyl-phenols (the sum of nonylphenol, nonyl-phenol-ethoxylate with the one ethoxy group, and nonyl-phenol-ethoxylates with two ethoxy groups (NPE), and linear alkyl benzene sulfonates (LAS)) were simultaneously extracted from air-dried samples with methanol by microwaveassisted extraction, according to Villar et al. (2007). Polycyclic aromatic hydrocarbons (PAH) were extracted with acetone:hexane mixture by microwave assisted extraction, according to Villar et al. (2004). Chromatographic analysis was performed on an Agilent 1100 series high-performance liquid chromatograph (HPLC) equipped with an ultraviolet diode array (DAD) and fluorescence detectors (FL), following Santos et al. (2007), Pakou et al. (2009)
Table 2 Chemical characteristics (means and deviation standard) of the influent sludge. pH; total solids (TS, g/L); volatile solids (VS, %); total nitrogen (TN, %dw); total organic carbon (TOC, %dw); heavy metal total content (mg/kg dw). pH
TS (g/L)
VS (%)
TN (%dw)
TOC (%dw)
Cr (mg/kg dw)
Cu (mg/kg dw)
Ni (mg/kg dw)
Cd (mg/kg dw)
Pb (mg/kg dw)
Zn (mg/kg dw)
6.9 ± 0.5
3.9 ± 0.3
94.4 ± 1.7
8.5 ± 1.2
81.2 ± 7.2
42 ± 16
361 ± 149
31 ± 16
<2
82 ± 23
1015 ± 304
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
383
Fig. 1. Water soluble carbon (mg C/kg dw) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
and Pule et al. (2010) methods. The PAH detected were acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, 1,2-benzanthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, dibenzo[a,h]anthracene, benzo[g,h,i]perylene, and indeno[1,2,3-cd]pyrene. 2.3. Statistical analysis The time courses of the studied parameters were fitted using the logistic curve, a model widely reported for biodegradation of organic compounds such as LAS in sea waters (Perales et al., 2006), AES in sea water (López-Galindo et al., 2010) and glucosinolates in soils (Gimsing et al., 2006). The logistic degradation curve is characterized by an initial phase at a slow rate, followed by a period with fast processes, which follow kinetics similar to first-order reactions, followed in turn by a phase with a slow rate. The logistic curve is given by the function y = K/(1 + ce−rt ), where y is the parameter concentration, t is the time, and K, c, and r are parameters found by fitting. The parameters r and K can be considered as the rate constant and the expected value at the end of the process, respectively. This curve has been previously used for modelling data in RBS (Peruzzi et al., 2015). The procedures for logistic (Geogebra) and for the non-liner model (Prism) were used for data fitting. Analysis of variance (ANOVA) was used to evaluate the differences (p < 0.05%) between times. Principal component analysis (PCA) was applied to all results obtained during the experiments, following Pardo et al. (2004). PCA and ANOVA were determined using STATISTICA 7.0 software. For all statistical analysis each software procedure was followed. 3. Results and discussion 3.1. Organic matter mineralization The pH decreased significantly over time, reaching lower values at the end of each different management period. Stefanakis et al. (2011) reported a significant reduction during the resting phase, due to concomitant processes of dewatering and organic matter decomposition, which led to acid production in sludge residue (Table 3). TOC and TN followed a similar trend over time, as result of organic matter mineralization process, reaching their lowest values at the end of the operational period and during the resting
Table 3 pH, total organic carbon (TOC, %C) and total nitrogen (TN, %N) and Escherichia coli (E. coli, MPN/g dw). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Ns, not sampled. Months
pH
TOC (%C)
TN (%N)
E. coli (MPN/g dw)
3 6 9 12 18 24
6.26b 7.15a 6.50b 5.45c 5.97bc 5.53c
36.61a 30.19b 29.69b 28.15b 25.59c 29.30b
5.43a 5.19a 4.42b 3.77b 3.57bc 4.79ab
1.02E+06a 1.60E+05a ns 3.64E+04ab 1.68E+04b ns
30 36 42 48 54
6.49b 6.27b 5.99bc 5.80bc 5.41c
30.73b 28.00b 25.30c 27.55b 25.15c
4.29b 3.90b 3.82b 3.54bc 2.65c
ns 6.52E+03bc ns <1.00E+03c <1.00E+03c
60 72
6.39b 5.75c
27.67b 25.08c
2.87c 3.18c
ns <1.00E+03c
phases (Table 3). The effectiveness of RBS in mineralizing organic matter was particularly evident in both trends of soluble water carbon (WSC) and dehydrogenase activity (DHase): the former represents the labile fraction of organic matter easily degradable by microorganisms, while the latter indicates the overall metabolic activity (Izquierdo et al., 2005). It is noteworthy that both variables dramatically plummeted during the commissioning period and the values remained low during the operating and resting periods (Figs. 1 and 2). Both processes occurred at the same rate, as proved by the insignificantly different rate constants obtained by the logistic model: 0.025 and 0.073, for WSC and DHase, respectively. Moreover, the logistic fitting obtained the final values of 3178 mg C/kg dw for WSC and 10.2 mg INTF/kg dw h for DHase; these very low values indicated that sludge reached, at the end of the resting period, a notably stable status (Table 6). Similar values were reported by Peruzzi et al. (2015) for a different RBS treating civil sludge. Also hygienization level was an important parameter to track in order to assess the effectiveness of RBSs in stabilizing sludge. E. coli and Salmonella spp. were chosen as faecal bacteria indicators (Table 3): E. coli significantly decreased over time, reaching very small values (<1000 MPN/g dw) since the beginning of the operation phase, while, Salmonella spp., was present in low quan-
384
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Fig. 2. Dehydrogenase activity (mg INTF/kg dw h) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
tities during all periods, from commissioning to final resting (<2 MPN/g dw), thus confirming the findings of Nielsen (2005, 2007) and Uggetti et al. (2012). 3.2. Organic matter humification The transformations of organic matter during the stabilization process, with special reference to the formation of humic substances (humification), have a key role in monitoring the effectiveness of RBSs in sludge stabilization. Humic substances can be classified in two different components: fulvic acids, which identify the less stable part of humic matter, and humic acids, which include the most stable fraction of humic matter. Fulvic acids significantly decreased over time, particularly during the commissioning period, and reached their lowest values at the end of the operational period and during the resting phase (Fig. 3), thus confirming that fulvic acids represent the biodegradable part of humic substances. Conversely, humic acids increased over time after the commissioning period, thus indicating that progressive humification process occurred in the RBS (Fig. 3). The final values found by the logistic fitting (19,333 mg C/kg dw for FA and 17,076 mg C/kg w for HA) were in agreement with the results found for a different reed bed treating civil sludge (Peruzzi et al., 2015). It is noteworthy that these processes proceeded at a comparable degree over time (Table 6), with similar rate constants obtained by the logistic fitting for FA (0.1011) and HA (0.1182). Interesting results, in terms of representativeness of the stabilization process, came also from the chemical-structural organic matter characterization performed by the Py-GC technique (Table 4). The trend of aliphatic carbon (C-AL, constituted by acetic acid and furfural) revealed an initial increase exhibited during the commissioning period, followed by a plateau during the operating phase, and a significant decline during the final resting period. Since acetic acid and furfural derive from lipid compounds (fats and waxes), carbohydrates and lignocellulosic materials, their decrease highlights the occurrence of mineralization process involving the fresh organic matter loaded in the RBS. It is noteworthy that a secondary mineralization process, dependent on pseudo-aromatic substances with long aliphatic chains (pseudo-stable aromatic carbon, C-AR P, constituted by toluene) took place: the C-AR P content remained stable during the commissioning period, then significantly declined during operating and resting phases. Con-
Table 4 Pyrolytic fragments of the sludge. C-AL (acetic acid and furfural, %); C-AR P (toluene, %); C-AR S (benzene and phenol, %), N (acetonitrile and pyrrole, %). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Months
C-AL (%)
C-AR P (%)
C-AR S (%)
N (%)
6 12 18 24
20.88a 25.95b 24.10ab 28.22b
32.59a 29.45ab 29.17ab 28.51ab
26.46ab 27.99ab 25.73ab 24.31a
20.07ab 16.62a 21.00ab 18.96ab
30 36 42 48 54
22.46ab 22.73ab 26.68b 25.64b 29.21b
27.47b 27.37b 24.97bc 24.60bc 22.90c
29.32ab 26.74ab 27.99ab 28.58ab 27.15ab
20.75ab 23.17b 20.36ab 21.17b 20.39ab
60 72
30.02b 25.69b
19.91cd 19.49d
28.30ab 32.29b
22.18b 21.52b
versely, the trend of stable aromatic carbon (C-AR S) highlighted the occurrence of humification. C-AR S, another pyrolytic compound group mainly represented by benzene and phenol deriving from stable condensed aromatic structures, significantly increased, in particular during the resting period. Similar results about toluene decrease and benzene increase were observed by El Fels et al. (2014) during sewage sludge composting. Pyrolytic nitrogen compounds (N) remained quite stable during the commissioning period and slightly increased during operating and resting periods. N is constituted by acetonitrile and pyrrole, two nitrogen compounds which derive from biologically and chemically stable compounds (Song and Farwell, 2008) that are usually correlated, respectively, to humic and fulvic acids (Song and Farwell, 2004). This trend hence demonstrated the establishment of humic substances with a great degree of condensation. 3.3. Heavy metals The detected total metal concentrations (Table 5) are comparable with those observed by Fytili and Zabaniotou (2008) for European sewage sludge and by Matamoros et al. (2012) for stabilized sludge treated in RBS. The procedure for heavy metal fractionation allowed us to individuate the following four fractions characterized by the decreasing degree of bioavailability:
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
385
Fig. 3. Fulvic acids (mg C/kg dw) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Humic acids (mg C/kg dw) during the commissioning period (blue squares), the operating period (orange squares), and the resting period (green squares); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 5 Heavy metal total content of the sludge (mg/kg dw). All results are expressed in mg/kg dw. Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Typical heavy metal content in wastewater sludge (Fytili and Zabaniotou, 2008) and heavy metal concentration in a stabilized sludge in RBS (Matamoros et al., 2012) (range and median values, mg dw/kg). Months
Cr (mg/kg dw)
Cu (mg/kg dw)
Ni (mg/kg dw)
Cd (mg/kg dw)
Pb (mg/kg dw)
Zn (mg/kg dw)
6 12 18 24 30 36 42 48 54 60 72
29a 59b 57b 60b 123c 24a 37ab 55b 14a 38ab 32ab
362a 410a 422ab 550b 573b 556b 578b 549b 390a 611b 492b
67b 34a 45ab 55ab 52ab 32a 33a 34a 34a 47ab 46ab
2.7a <2a 3.7b <1.5a 2.53b 1.62a 2a 2a 1.91a 1.52a 1.67a
91 93 104 60 86 99 69 43 78 66 91
917a 1297ab 1332ab 1760b 1836b 1538b 1437ab 1705b 1209a 1853b 1765b
Fytili and Zabaniotou (2008) Matamoros et al. (2012)
10–990 (500) 42–71 (56)
84–17,000 (800) 184–330 (256)
2–5300 (80) 30–43 (41)
1–3.41 (1) 61–152 (88)
13–26,000 (500) 1098–1550 (1366)
101–49,000 (1700) 1.3–2.3 (1.8)
- Fraction 1 (exchangeable fraction) which is the most mobile portion, potentially toxic for plants. In this fraction, metals are adsorbed on sludge components or present in the form of Fe and Mn hydroxides; - Fraction 2 (reducible fraction) where heavy metals are strongly bound to Fe and Mn oxides, but get thermodynamically unstable when in acidic and anoxic conditions; - Fraction 3 (oxidizable fraction bound to organic matter) where heavy metals are complexed by humic substances and become soluble when organic matter is degraded in oxidizing conditions. This fraction is considered to be neither bioavailable nor mobile; - Fraction 4 (residual fraction) which is considered to be not extractable and in an inert form, with heavy metals included in crystalline structures within the residuals solids.
The concentrations of different metals (expressed in mEq/kg) were summed for each fraction (Figs. 4 and 5). Fraction 1 and fraction 2 content significantly declined over time, as already noticed in other papers (Kołecka and Obarska-Pempkowiak, 2013; Peruzzi et al., 2013), as the stabilization proceeded in RBS. Other authors found higher content of metals associated with fraction 1 and fraction 2 in sewage sludge stabilized with traditional methods (Walter et al., 2006; Fuentes et al., 2008). On the basis on the results pub-
lished by Walter et al. (2006), 11.8% and 26.2% heavy metals in anaerobic sewage sludges, were mainly associated with fraction 1 and 2, respectively; similarly, Fuentes et al. (2008) found that the sum of fraction 1 and fraction 2 reached 31.3% and 40.9% in aerobic sludges and heat treated sludges, respectively. As the bioavailable fraction dropped, the fraction 3, bound to organic matter significantly rose, as a consequence of humification process (Peruzzi et al., 2015). The two processes, in fact, occurred similarly, as highlighted by the insignificant rate constant of logistic fitting (0.075 and 0.056 for Fr 1 and Fr 3, respectively). It is noteworthy that these rate constants are quite similar to the rate constants of FA and HA trends, thus pointing out that all stabilization processes in RBS proceeded to the same degree. The final value found by the logistic fitting (12.5% and 48.2% for Fr 1 and Fr 3, respectively) were in agreement with the results found for a different reed bed treating civil sludge (Table 6) (Peruzzi et al., 2015).
3.4. Toxic organic compounds The aerobic conditions of the basins affected not only the extent of mineralization and humification, but also the biodegradation of toxic organic compounds, such as polycyclic aromatic hydrocarbons (PAH), nonylphenol and nonylphenol ethoxylates
386
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Fig. 4. Heavy metal fractionation (%).
Fig. 5. Fraction 1 (%) during the commissioning period (blue points), the operating period (orange points), and the resting period (green points); logistic fitting (black line) with confidence interval (blue lines). Fraction 3 (%) during the commissioning period (blue squares), the operating period (orange squares), and the resting period (green squares); logistic fitting (black line) with confidence interval (blue lines). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 6 Logistic fitting. Rate constant, final value, coefficient c and R2 . Different letters mean values significantly different (HSD Tukey—p < 0.05) over time.
WSC Dhase FA HA (x > 30) Fr 1 Fr 3
Rate constant (r)
Final value (K)
c
2 Radj
0.025a 0.073ab 0.1011b 0.1182b 0.075ab 0.056ab
3178 mg C/kg dw 10.2 mg INTF/kg dw h 19,333 mg C/kg dw 17,076 mg C/kg dw 12.5% 48.2%
−1.02 −1.00 −1.35 3.29 −1.00 2.84
0.9873 0.9875 0.9803 0.9952 0.9861 0.9714
(NPE), di-2-ethylhexyl-phthalate (DEHP) and linear alkylbenzene sulfonates (LAS). The presence of these compounds may affect the possible land application of stabilized sludges as biosolid; hence, it is important that RBS managers monitor the presence of such compounds, especially during the final resting period. For this reason, several European countries (Tunc¸al et al., 2011) and local author-
ities have set regulations for land application of biosolids, which consider the presence of priority toxic organic compounds as a possible threat to human health. Results about toxic organic compounds are reported in Table 7. As reported by Mezzanotte et al. (2016), PAH inputs in wastewater sewage sludge can be estimated by the phenanthrene/anthracene and fluoranthene/pyrene ratios. Combustion of various natural and synthetic compounds and deposition from atmosphere are correlated to values >1 for fluoranthene/pyrene ratio (1.59) and <10 for phenanthrene/anthracene ratio (1.82). The mean PAH content found in influent sludge was 4.74 mg/kg dw, among which 44.6% of low molecular weight (Ace, Flu, Phe, Ant and Fln, with 2–3 rings), 30.0% of middle molecular weight (Pyr, BaA, Chr, BaF and BkF, 4 rings) and 25.4% of high molecular weight (BaP, DahA, BghiP and InP, 5–6 rings). PAH content reached 1.55 mg/kg (67,4% decrease) at the end of the operation period (after 60 months) and 1.39 mg/kg (70.8% decrease) after the resting
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
387
Fig. 6. Principal component analysis: score plots. (a) PC 1 and PC 2. (b) PC 3 and PC 2. Commissioning period (blue squares), operating period (orange squares), resting period (green squares). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 7 Toxic organic compounds in influent sludge and in stabilized sludges at 60 and 72 months (mg/kg dw). Different letters mean values significantly different (HSD Tukey—p < 0.05) over time. Acenaphthene (Ace), fluorene (Flu), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fln), pyrene (Pyr), 1,2-benzanthracene (BaA), chrysene (Cry), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), dibenzo[a,h]anthracene (DahA), benzo[g,h,i]perylene (BghiP), indeno[1,2,3-cd]pyrene (InP), linear alkylbenzene sulfonates (LAS), nonylphenols (NPE) and di-2-ethylhexyl-phthalate (DEHP). Compound (mg/kg dw)
Influent sludge
60 months
72 months
Ace Flu Phe Ant Fln Pyr BaA Cry BbF BkF BaP DahA BghiP InP LAS NPE DEHP
0.347a 0.530a 0.459a 0.252a 0.527a 0.331a 0.266a 0.246a 0.269a 0.311a 0.394a 0.339a 0.258a 0.314a 464a 62.9a 11.4a
0.329a 0.410a 0.237b <0.05b 0.065b 0.066b <0.05b 0.143b 0.061b <0.05b <0.05b 0.109b 0.074b 0.354a 7.18b 41.9b 3.47b
0.322a 0.111b 0.302b <0.05b <0.05b <0.05b <0.05b 0.149b 0.050b <0.05b <0.05b 0.119b 0.056b 0.126b 4.99b 20.9c 3.63b
period, thus demonstrating that mineralization process involved also hydrocarbon compounds. For low, medium and high molecular weight compounds, Cui et al. (2015) observed a removal efficiency of 67.7%, 79.3% and 52.8% after 60 months and 62.9%, 80.5% and 73.1% after 72 months, respectively. It is worth noticing that the process involved not only the low and medium molecular weight compounds, but also the more recalcitrant compounds, especially in the final resting period: the high molecular weight reduction rate increased from 52.8% (after 60 months) to the final 73.1%. Similar reduction levels can be observed for NPE and DEHP, which are hydrophobic compounds deriving from hygienic/cleaning products and plastic softeners, respectively. At the end of the operative phase (60 months), NPE declined of about 33.4% from the initial content of 62.9 mg/kg dw and DEHP declined of 69.6% from the initial content of 11.4 mg/kg dw. Moreover, during the resting period, NPE content halved, reaching a final concentration of 20.9 mg/kg dw. As expected, LAS, easily biodegradable surfactants arising from detergents, were easily degraded in RBS, reaching the very small value of 7.18 mg/kg dw after 60 months (decrease of 98.5%) from the initial influent sludge concentration of 464 mg/kg dw. All these results present similarities with the concentrations of organic pollutants detected by Matamoros et al. (2012), Peruzzi et al. (2011b, 2013) and Cui et al. (2015) in RBS stabilized sludge.
388
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389
Table 8 Principal component analysis. PC 1
PC 2
PC 3
TOC TN pH Dhase WSC FA HA C-AL (Py) C-AR P (Py) C-AR S (Py) N (Py) Fr 1 Fr 2 Fr 3
0.33 0.55 0.61* 0.94* 0.68* 0.85* 0.09 −0.23 0.55 −0.05 0.01 0.94* 0.78* −0.46
0.64* 0.70* 0.40 0.18 0.56 0.40 −0.87* −0.32 0.65* −0.03 0.06 0.02 0.05 −0.26
0.50 0.05 0.51 −0.05 0.03 0.09 0.25 0.49 −0.25 0.83* 0.77* −0.17 −0.33 0.67*
Total proportionality
0.35
0.21
0.20
*
Variables with component loading used to interpret the PC, threshold level 0.7.
3.5. Principal component analysis The PCA of the data set indicated 76.3% of the data variance as being contained in the first three components (Table 8). PC1, PC2 and PC3 accounted for 35.0%, 21.0% and 20.0% of the total variance, respectively. PC1 was closely associated with all parameters linked to the primary mineralization of organic matter: Dhase activity, WSC, pH, fulvic acids, fraction 1 and fraction 2. The parameters connected to the secondary mineralization were significant on PC2: total organic carbon, total nitrogen, humic acids and C-AR P. Conversely, PC3 was mainly associated to humification process: C-AR S, N and fraction 3. The score plots provide a graphical representation of the different sampling times, by identifying the parameters that exhibited the highest level of association. In the plot PC1 × PC2 (Fig. 6a), all times were characterized by the same position on PC 1, with the exception of 6 months, which was located to the right of the plot. This shift demonstrates that the primary mineralization process principally occurred during the commissioning period. Considering PC2, the times of operating phase were segregated in the top, while the resting period was located at the bottom, thus underlining that secondary mineralization process principally occurred during the operating phase. In the PC3 × PC2 plot (Fig. 6b), the different phases of commissioning, operating and resting were clearly discriminated along PC3, with the commissioning phase located in the left, the operative period in the middle, and the resting phase in the right of the plot. This progressive shift across PC3 clearly shows that humification process affected the operative phase and, even more, the resting phase. 4. Conclusions This study demonstrated the pathways of organic matter stabilization occurring in a sludge stabilization reed bed during a complete 72 month-long cycle. The biological stabilization, depending on fresh organic matter, was underlined by the decrease of water-soluble carbon, dehydrogenase activity, fulvic acids and bioavailable heavy metals. The mineralization of pseudo-stable substances and the progressive humification were clearly proven by the humic acid content and by the trend of chemical-structural parameters. Each different operational phase was characterized by the prevalence of a specific process of organic matter stabilization: 1) The mineralization of fresh organic matter was the main process observed during the initial commissioning phase;
2) The mineralization of pseudo-stable organic matter prevailed over the humification process during the central operating phase; 3) The humification process became prevalent during the final resting period. Moreover, during the last resting period, a significant reduction of persistent organic compounds and faecal bacteria indicators was reached, thus enabling a possible safe reuse of stabilized sludge as biosolids for land application. Finally, the logistic fitting described the overall trend of the organic matter sludge stabilization, thus allowing us to provide useful information for the formulation of new reed bed design and operation guidelines. Additional studies devoted to the quantification of the ecosystem services provided by RBSs are advisable, as they could further improve the competitiveness of this environmental-friendly technique of sludge stabilization over conventional technologies especially in green urban infrastructure planning. Acknowledgement This work was supported by ACQUE SpA (Pisa, Italy). References APHA, 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. American Public Health Association, New York. Ceccanti, B., Masciandaro, G., Macci, C., 2007. Pyrolysis-gas chromatography to evaluate the organic matter quality in a mulched soil. Soil Tillage Res. 97, 71–78. Cui, Y., Zhang, W., Sun, H., Wu, W.M., Zou, X., 2015. Polycyclic aromatic hydrocarbon accumulation in Phragmites australis grown on constructed wetland for sludge stabilization. J. Residuals Sci. Technol. 12 (4), 215–220. De Maeseneer, J.L., 1997. Constructed wetlands in Europe. Water Sci. Technol. 35, 279–285. Dominiak, D., Christensen, M.L., Keiding, K., Nielsen, P.H., 2011. Sludge quality aspects of full-scale reed bed drainage. Water Res. 45 (19), 6453–6460. Draft International Standard ISO/DIS 16649-2, 2001. Microbiology of Food and Animal Feeding Stuffs, Horizontal Method for the Enumeration of Presumptive. El Fels, L., Lemee, L., Ambles, A., Hafidi, M., 2014. Identification and biotransformation of lignin compounds during co-composting of sewage sludge-palm tree waste using pyrolysis-GC/MS. Int. Biodeterior. Biodegrad. 92, 26–35. ˜ J.F., Meseguer, V.F., 2008. Fuentes, A., Lloréns, M., Sáez, J., Isabel Aguilar, M., Ortuno, Comparative study of six ls. Bioresour. Technol. 99 (3), 517–525, http://dx.doi. org/10.1016/j.biortech.2007.01.025. Fytili, D., Zabaniotou, A., 2008. Utilization of sewage sludge in EU application of old and new methods—a review. Renew. Sustain. Energy Rev. 12, 116–140. Ghermandi, A., Fichtman, E., 2015. Cultural ecosystem services of multifunctional constructed treatment wetlands and waste stabilization ponds: time to enter the mainstream? Ecol. Eng. 84 (C), 615–623. Gimsing, A.L., Sorensen, J.C., Tovgaard, L., Friis Jorgensen, A.M., Bruun Hansen, H.C., 2006. Degradation kinetics of glucosinolates in soil. Environ. Toxicol. Chem. 25, 2038–2044. Giraldi, D., Iannelli, R., 2009. Short-term water content analysis for the optimization of sludge dewatering in dedicated constructed wetlands (reed bed systems). Desalination 246, 92–99. Iannelli, R., Nielsen, S., Peruzzi, E., Piras, F., Støvring, M., Masciandaro, G., 2013. Short-term performance analysis of sludge treatment reed beds. Water Sci. Technol. 68, 1520–1528. Kiviat, E., 2013. Ecosystem services of Phragmites in North America with emphasis on habitat functions. AoB Plants 5, 1–29. Kołecka, K., Obarska-Pempkowiak, H., 2013. Potential fertilizing properties of sewage sludge treated in the sludge treatment reed beds (STRB). Water Sci. Technol. 68, 1412–1418. Izquierdo, I., Caravaca, F., Alguacil, M.M., Hernández, G., Roldán, A., 2005. Use of microbiological indicators for evaluating success in soil restoration after revegetation of a mining area under subtropical conditions. Appl. Soil Ecol. 30, 3–10. López-Galindo, C., Garrido, M.C., Casanueva, J.F., Nebot, E., 2010. Degradation models and ecotoxicity in marine waters of two anti-fouling compounds: sodium hypochlorite and an alkylamine surfactant. Sci. Total Environ. 408, 1779–1785. Macci, C., Doni, S., Peruzzi, E., Ceccanti, B., Masciandaro, G., 2012. Pyrolysis-gas chromatography to evaluate the organic matter quality of different degraded soil ecosystems. In: Advanced Gas Chromatography—Progress in Agricultural, Biomedical and Industrial Applications., pp. 283–306.
E. Peruzzi et al. / Ecological Engineering 102 (2017) 381–389 Masciandaro, G., Ceccanti, B., Ronchi, V., Bauer, C., 2000. Kinetic parameter of dehydrogenase in the assessment of the response of soil to vermicompost and inorganic fertilisers. Biol. Fertil. Soils 32, 479–483. Matamoros, V., Nguyen, L.X., Arias, C.A., Nielsen, S., Laugen, M.M., Brix, H., 2012. Musk fragrances, DEHP and heavy metals in a 20 years old sludge treatment reed bed system. Water Res. 46, 3889–3896. Mezzanotte, V., Anzano, M., Collina, E., Marazzi, F.A., Lasagni, M., 2016. Distribution and removal of polycyclic aromatic hydrocarbons in two italian municipal wastewater treatment plants in 2011–2013. Polycycl. Aromat. Compd. 36 (3), 213–228. Mocko, A., Waclawek, W., 2004. Three-step extraction procedure for determination of heavy metals availability to vegetables. Anal. Bioanal. Chem. 380, 813–817. Nielsen, S., 2005. Sludge reed bed facilities: operation and problems. Water Sci. Technol. 9, 99–107. Nielsen, S., 2007. Helsinge sludge reed bed system—reduction of pathogenic microorganisms. Water Sci. Technol. 56 (3), 175–182. Nielsen, S., Peruzzi, E., Macci, C., Doni, S., Masciandaro, G., 2014. Stabilisation and mineralisation of sludge in reed bed systems after 10–20 years of operation. Water Sci. Technol. 69, 539–545. Pakou, C., Kornaros, M., Stamatelatou, K., Lyberatos, G., 2009. On the fate of LAS, NPEOs and DEHP in municipal sewage sludge during composting. Bioresour. Technol. 100 (4), 1634–1642. Pardo, R., Helena, B.A., Cazurro, C., Guerra, C., Deban, L., Guerra, C.M., Vega, M., 2004. Application of two- and three-way principal component analysis to the interpretation of chemical fractionation results obtained by the use of the B.C.R. procedure. Anal. Chim. Acta 523, 125–132. Perales, J.A., Manzano, M., Garrido, M.C., Sales, D., Quiroga, J.M., 2006. Biodegradation kinetics of linear alkylbenzene sulphonates in sea water. Biodegradation 18, 63–70. Peruzzi, E., Masciandaro, G., Macci, C., Doni, S., Ravelo, S.G.M., Peruzzi, P., Ceccanti, B., 2011a. Heavy metal fractionation and organic matter stabilization in sewage sludge treatment wetlands. Ecol. Eng. 37, 771–778. Peruzzi, E., Masciandaro, G., Macci, C., Doni, S., Ceccanti, B., 2011b. Pollutant monitoring in sludge treatment wetlands. Water Sci. Technol. 64, 1558–1565. Peruzzi, E., Nielsen, S., Macci, C., Doni, S., Iannelli, R., Chiarugi, M., Masciandaro, G., 2013. Organic matter stabilization in reed bed systems: Danish and Italian examples. Water Sci. Technol. 68, 1888–1894. Peruzzi, E., Macci, C., Doni, S., Volpi, M., Masciandaro, G., 2015. Organic matter and pollutants monitoring in reed bed systems for sludge stabilization: a case study. Environ. Sci. Pollut. Res. 22, 2447–2454. Pule, B.O., Mmualefe, L.C., Torto, N., 2010. Analysis of Polycyclic Aromatic Hydrocarbons in Soil with Agilent SampliQ QuEChERS AOAC Kit and HPLC-FLD. 5990-5452EN, Application note available on http://www.agilent.com/cs/ agilent/en-us/promotions/applicationfinder.
389
Santos, J.L., Aparicio, I., Alonso, E., 2007. A new method for the routine analysis of LAS and PAH in sewage sludge by simultaneous sonication-assisted extraction prior to liquid chromatographic determination. Anal. Chim. Acta 605 (1), 102–109. Song, X., Farwell, S.O., 2004. Pyrolysis gas chromatography atomic emission detection method for determination of N-containing components of humic and fulvic acids. J. Anal. Appl. Pyrolysis 71, 901–915. Song, X., Farwell, S.O., 2008. Forms of soil organic nitrogen in a Pactola soil as seen by pyrolysis/gas chromatography/atomic emission detection (Py–GC/AED). J. Anal. Appl. Pyrolysis 83, 190–196. Stefanakis, A.I., Tsihrintzis, V.A., 2011. Dewatering mechanisms in pilot-scale sludge drying reed beds: effect of design and operational parameters. Chem. Eng. J. 172, 430–443. Stefanakis, A.I., Komilis, D.P., Tsihrintzis, V.A., 2011. Stability and maturity of thickened wastewater sludge treated in pilot-scale sludge treatment wetlands. Water Res. 45, 6441–6452. Tunc¸al, T., Jangam, S.V., Günes¸, E., 2011. Abatement of organic pollutant concentrations in residual treatment sludges: a review of selected treatment technologies including drying. Dry. Technol. 29 (14), 1601–1610. Uggetti, E., Ferrer, I., Llorens, E., García, J., 2010. Sludge treatment wetlands: a review on the state of the art. Bioresour. Technol. 101 (9), 2905–2912. Uggetti, E., Ferrer, I., Molist, J., García, J., 2011. Technical, economic and environmental assessment of sludge treatment wetlands. Water Res. 45 (2), 573–582. Uggetti, E., Ferrer, I., Nielsen, S., Arias, C., Brix, H., García, J., 2012. Characteristics of biosolids from sludge treatment wetlands for agricultural reuse. Ecol. Eng. 40, 210–216. Villar, M., Callejon, M., Jiménez, J.C., Alonso, E., Guiraúm, A., 2007. Optimization and validation of a new method for analysis of linear alkylbenzene sulfonates in sewage sludge by liquid chromatography after microwave-assisted extraction. Anal. Chim. Acta 599 (1), 92–97. Villar, P., Callejon, M., Alonso, E., Jiménez, J.C., Guiraúm, A., 2004. Optimization and validation of a new method of analysis for polycyclic aromatic hydrocarbons in sewage sludge by liquid chromatography after microwave assisted extraction. Anal. Chim. Acta 524 (1–2), 295–304. Walter, I., Martínez, F., Cala, V., 2006. Heavy metal speciation and phytotoxic effects of three representative sewage sludges for agricultural uses. Environ. Pollut. 139 (3), 507–514, http://dx.doi.org/10.1016/j.envpol.2005.05.020. Yeomans, J.C., Bremner, J.M., 1988. A rapid and precise method for routine determination of organic carbon in soil. Commun. Soil Sci. Plant Anal. 19, 1467–1476.