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Roles of composts in soil based on the assessment of humification degree of fulvic acids
Ecological Indicators 72 (2017) 473–480
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Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind
Roles of composts in soil based on the assessment of humification degree of fulvic acids Yue Zhao a , Yuquan Wei a , Yun Zhang a , Xin Wen a , Beidou Xi b , Xinyu Zhao a , Xu Zhang a , Zimin Wei a,∗ a b
College of Life Science, Northeast Agricultural University, Harbin 150030, China Laboratory of Water Environmental System Engineering, Chinese Research Academy of Environmental Science, Beijing 100012, China
a r t i c l e
i n f o
Article history: Received 30 March 2016 Received in revised form 24 August 2016 Accepted 26 August 2016 Keywords: Mature composts Fulvic acids Humification degree Projection pursuit regression EEM-PARAFAC Soil application
a b s t r a c t This study was conducted to assess the humification degree in fulvic acids (FA) from different composts, and to reveal their roles after soil amending based on their excitation-emission matrices (EEM) of the fluorescence spectra and projection pursuit regression (PPR) analysis. Two peaks were detected in EEM spectra of FA from all composts, and three components were identified by the parallel factor analysis (PARAFAC) model. The assessment of the humification degree of FA using the ratios between the values of the percent fluorescence response in the visible and ultraviolet regions (PI,n /PII,n ) generally agreed with that using the distributions of FA components (C1, C2 and C3). The PPR considering the parameters (PI,n /PII,n , C1, C2 and C3) further ranked the composts with similar of FA, and the FA humification degree decreased in the order: GW, TSW, LW and SW > CM, MSW, and PM > MC and KW. The results showed that the compositions of FA were similar to each other in composts from different materials, but there were distinct differences in the humification degree of FA owing to the different distributions of each component in composts. Therefore, based on the redistribution of components, a method for regulating the humification degree of FA during composting was presented. Furthermore, the suitable soil application of composts with different humification degrees was also demonstrated. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Composting is defined as an economical and environmentfriendly biological process of aerobic thermophilic microbial degradation of wastes by populations of indigenous microorganisms, which can convert organic wastes into a soil amendment rich in humic substances and nutrients, mitigate groundwater contamination and reduce air pollution and greenhouse gas (GHG) emissions (He et al., 2011a; Yan et al., 2016; Zhang et al., 2016). Organic matter is partially transformed into more stable and complex macromolecules such as humic substances in the biological process of composting (Lashermes et al., 2012). Understanding the characteristic of the humic substances formed during composting is relevant because they constitute a stable fraction of carbon, thus regulating the carbon cycle and the release of nutrients, such as nitrogen, phosphorous and sulfur. After soil application, they play
∗ Corresponding author at: Northeast Agricultural University, College of Life Science, No. 59 Mucai Street Xiangfang District, Harbin 150030, China. Tel.: +86 451 55190413; Fax: +86 451 55190413. E-mail addresses: [email protected], [email protected] (Z. Wei). http://dx.doi.org/10.1016/j.ecolind.2016.08.051 1470-160X/© 2016 Elsevier Ltd. All rights reserved.
an important role in global carbon cycling and in the regulation of the mobility and fate of environmental contaminants and also have many positive benefits in creating a suitable medium for plant growth (Christl et al., 2005; Harrison, 2008). Over the years, a number of hypotheses have been presented on how humic matter is formed. Though there is not enough evidence to support the hypothesis that the de novo formation of humic polymers is quantitatively relevant for humus formation (Schmidt et al., 2011), the view relied on alkali and acid extraction methods from previous soil chemists has dominated for years, that is, fulvic acids (FA; soluble at all pH values) were a relatively more lively group constituent in humic substances when compared with humic acids (HA; soluble in alkaline media and insoluble in acidic media) (Ryan and Weber, 1982; Bai et al., 2008). Various parameters have been proposed to study the degree of humification such as humification index (HI), a ratio of peak A (fulvic acid-like substances) to peak C (humic acid-like) in Excitation emission matrix (EEM) fluorescence spectroscopy; fluorescence index (FI), the ratio of emission intensity at 450 nm and 500 nm at 370 nm excitation (McKnight et al., 2001; Ohno, 2002). Since composting implies the formation of some humic-like substances by microorganisms whose metabolism
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predominantly occurs in the water-soluble phase (Said-Pullicino et al., 2007; Bernal et al., 2009), a study of the degree of humification occurring in the water-extract FA may be useful for assessing compost. However, most reports focused on the characteristics of dissolved organic matter (DOM) during composting, and few studies have examined the humification degree in humic substances of different composts. FA contain characteristic structures such as aromatic rings with three to five substituents (mainly hydroxyl, methoxyl or aliphatic hydrocarbon groups with some aldehyde and keto functional groups also attached to some of the aromatic nuclei), aromatic–aliphatic ethers, carboxylic groups, sugars and amino acids. Traditionally, the fractions of fulvic acids were characterized by size exclusion chromatography, elemental analysis (C, H, N, S), as well as spectroscopic techniques, including ultraviolet visible (UV-VIS), Cross-Polarization Magic Angle Spinning Carbon-13 Nuclear Magnetic Resonance (CP-MAS 13C NMR), Fourier transform infrared spectroscopy (FT-IR), and fluorescence spectroscopy (Christl et al., 2005). Specifically, fluorescence spectroscopy is used as a non-destructive, simple, non-separative and accurate tool to quantify the humification and maturity during composting (Hur et al., 2009; Fernandez-Romero et al., 2016). The fluorescence characteristics of DOM have been extensively investigated owing to the technological advances in fluorescence spectroscopy, especially the development excitation – emission (EEMs) (Coble, 1996). Application of EEM as a tool for assessment of compost products is well documented, owing to its high sensitivity and simplicity (Yu et al., 2010a; Wu et al., 2012). The parameters used to assess the humification degree of humic substances include an intensity ratio between the fluorescence peaks at different wavelengths (Zsolnay et al., 1999), an area ratio between different fluorescence spectra regions in traditional fluorescence spectra (Kalbitz et al., 1999), and the percentage of fluorescence response (Pi,n ) calculated by fluorescence regional integration (FRI) in an excitation – emission matrix (EEM) fluorescence spectra (Chen et al., 2003). They also include the distribution of components identified by EEM fluorescence spectra combined with parallel factor analysis (EEM-PARAFAC) (Yu et al., 2010b; Markechova et al., 2014). Apart from the analysis methods of FRI and EEM-PARAFAC in fluorescence spectra, there was also a useful method based on second derivative synchronous fluorescence to characterize DOM (Yu et al., 2013). EEM is a powerful tool for determining DOM substances (Yu et al., 2010a). EEM offers several major advantages over single-scan methodologies such as providing new information regarding the fluorescence DOM composition of a sample (Coble et al., 1993). However, to conquer the difficulty in identifying individual fluorescence components in sample, simple and multivariate data analysis technique PARAFAC have been used (Stedmon et al., 2003). PARAFAC analysis can decompose fluorescence EEMs into independent groups of fluorescence components and provide a unique solution to the FA EEM dataset, and it is regarded as an important analytical tool to characterize the FA in composting (He et al., 2013). The use of fluorescence spectral techniques to characterize the same sample can generate a large number of fluorescence parameters, and the humification degree of FA could be affected by a combination of multiple fluorescence parameters, not necessarily by each measure individually. Therefore, an assessment method utilizing multiple fluorescence parameters would be necessary. Projection pursuit regression (PPR) is a nonlinear multivariate regression procedure proposed by Friedman and Stuetzle (1981). Its basic idea is to project high dimension to low dimensional space, and it tries to find the intrinsic structural information hidden in the high dimensional data. At present, it has been applied successfully to tackle some chemical problems (Ghasemi and Zolfonoun, 2013). The objectives of this study were (1) to obtain FA fluorescence characteristics from different composts; (2) to select fluorescence
parameters, which were suitable for estimating the humification degree in DOM; (3) to assess the humification degree of FA from different composts using EEM-PARAFAC and PPR; (4) to suggest suitable application methods of composts with different humification degrees. 2. Materials and methods 2.1. Sample collection and storage Nine trapezoidal piles of Green waste (GW), Kitchen waste (KW), Tomato stem waste (TSW), Chicken manure (CM), Straw waste (SW), Litter waste (LW), Municipal solid waste (MSW), Pig (Swine) manure (PM) and a co-compost (MC) mixed with biogas residue. All the composts were prepared by Shanghai Songjiang Composting Plant, and each composting pile contained approximately 2 t of raw material (1.5 m high with a 2 × 3 m base). The C/N was adjusted about 25 for each material by mixing sawdust at the initial stage of composting. The composting time was approximately 45 days according to the composting period of the plant. When the composting finished, approximately 3 kg of samples were collected from several sites of the compost pile and stored at 4 ◦ C for the analysis of FA. The samples for analysis were homogenized using the methods of coning and quartering (Bernabé et al., 2011). And all the samples for analyzing FA were carried out by triplicate. Details of the composting properties are described in Table S1. 2.2. Extraction of fulvic acid Compost samples (10 g) were mixed with 0.1 M (NaOH + Na4 P2 O7 ) with a solid to water ratio of 1:10 (w/v). The mixtures were shaken for 24 h with a rotational speed of 150 rpm at room temperature and centrifuged at 10,000 rpm for 15 min. The obtained supernatant was filtered through a 0.45 m membrane filter and then acidified to a pH of 1 with 6 M HCl. The mixtures were allowed to stand for 24 h at 4 ◦ C and again centrifuged at 10,000 rpm for 15 min. The obtained supernatant was passed through an XAD-8 macroporous resin column and an H+ -saturated cation exchange resin for further FA purification (He et al., 2011b). The stationary phases used for the FA purification were XAD-8 resin and 732 cation exchange resin, which have been described by He et al. (2011b). The mean final concentrations of FA in different composts were 116.04 ± 2.05 mg/L (GW), 148.04 ± 3.21 mg/L (KW), 168.51 ± 3.13 mg/L (TSW), 188.00 ± 4.30 mg/L (CM), 82.60 ± 1.51 mg/L (SW), 77.55 ± 1.95 mg/L (LW), 183.32 ± 2.54 mg/L (MSW), 156.13 ± 3.75 mg/L (PM) and 60.54 ± 0.85 mg/L (MC), respectively. 2.3. Fluorescence spectroscopy analysis Fluorescence spectroscopy was recorded using a Hitachi F7000 fluorescence spectrophotometer (Hitachi High Technologies, Japan) in a 1 cm clear quartz cuvette at room temperature (20 ± 2 ◦ C). The emission wavelength was recorded from 250 to 600 for 2 nm increments and excitation wavelength was recorded from 200 to 550 for 10 nm increments. The concentration of FA was diluted to the same level of 10 mg/L before the measurement to decrease the influence of varying FA concentrations among the compost samples in contribution to fluorescence intensities (Yu et al., 2009). The EEM spectra were recorded for the excitation spectra from 200 to 550 nm at intervals of 10 nm while the emission spectra ranged between 250 and 600 nm, with data saved for every 2 nm increments. The scan speed was set at 1200 nm min−1 . The fluorescence intensities were converted to Roman Unit (R.U.). Meanwhile, Milli-Q water blank EEMs were deducted from the
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Fig. 1. EEM fluorescence spectra of FA in different composts.
sample EEM to decrease the influence of the Rayleigh and Raman scattering.
3. Results and discussion 3.1. EEM fluorescence spectroscopy
2.4. Regional integration analysis Fluorescence regional integration, a quantitative technique that integrates the volume beneath an EEM, was developed to analyze EEMs. EEM was delineated into two excitation-emission regions based on fluorescence of model components, FA fractions. Volumetric integration under the EEM within each region, normalized to the projected excitation-emission area within that region, resulted in a normalized region-specific EEM volume (PI,n ). 2.5. PARAFAC analysis PARAFAC analysis was applied to the three-dimensional data array using MATLAB2010 with the DOM Fluor toolbox, and all EEM spectra data of each molecular weights (MW) fraction comprised a three-dimensional data array (27 samples × 41 Ex × 45 Em). The array was decomposed into three matrices: score, Ex loading, and Em loading matrices (Stedmon and Bro, 2008). The scores in the score matrix, which were expressed as Fmax values, were used to evaluate the concentration of the fluorescence components determined through EEM–PARAFAC analysis in accordance with previous reports. 2.6. Multivariate statistical analysis SPSS version 17.0 was used for significance test and Origin 8.0 was used to analyze the relationships among fluorescence parameters and draw the plots. Matlab R2010b was employed to perform PPR program using in-house-developed MATLAB software (PPR analysis). Furthermore, PARAFAC analysis was carried out in MATLAB with the DOM Fluor toolbox, following the procedure described by Stedmon and Bro (2008).
EEM fluorescence spectra could provide a large amount of information about the structure of FA. The EEM fluorescence spectra of FA are shown in Fig. 1. All of the EEM fluorescence spectra of FA exhibited two peaks at Ex/Em of 230–240/421–448 nm (peak a), 330–350/424–442 nm (peak b), which were related to FA area of the visible region and the FA area of the ultraviolet region, respectively. The differences in the intensities of fluorescence and the wavelengths of peaks of FA in different samples indicated that there were slight differences in the amount and distribution of components of FA from composts. Besides, as shown in Fig. 1 and Table S2, the intensities of peak a from different composts are all significantly higher than those of peak b. According to the previous research by Chen et al. (2003), the peaks in the region I represent for complex structure materials. Therefore, the complex structure components account for a large proportion of FA in all compost samples. According to a previous study by Chen et al. (2003), EEM fluorescence spectra of dissolved organic matter could be divided into five regions. However, five regions for FA may not be fully applicable because of the absence of protein regions or negligible portions in the EEM fluorescence spectra of FA (Fig. 1). To compare the humification correctly, the EEM fluorescence spectra of FA was divided into two regions. The percentage of fluorescence response (Pi,n ) of each region was calculated based on the regional integration of fluorescence (Chen et al., 2003). Region I in the visible region could be associated with the presence of high molecular weight fractions, while region II in the ultraviolet region may be attributed to simple structural components in FA (Senesi et al., 1991; Wei et al., 2014). Therefore, the ratio of PI,n /PII,n can be an indicator of the humification degree for FA. Moreover, as the composting progressed, organic matters reach stability through mineralization and humification
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process and the FRI values in long wavelength from mature composting present higher than that of fresh composting (Yu et al., 2011; He et al., 2013). Therefore, in this study, the higher ratio value of PI,n /PII,n represented a higher humification degree of composts. These percentages of PI,n /PII,n varied from 1.99 to 4.10 for all the samples, indicating that there were distinct differences in the humification degree for FA in these composts. Based on the value of PI,n /PII,n , the humification degree was the highest for GW (3.90), TSW (4.10), SW (3.76) and LW (3.94), and lower for MC (1.99) and KW (2.20), with intermediate values for CM (2.71), MSW (2.73) and PM (2.68). 3.2. PARAFAC analysis PARAFAC analysis, which can decompose EEMs into various individual fluorescent components (Andersen and Bro, 2003; Hunt and Ohno, 2007), was conducted to investigate the composition of FA from different composts. Three components were identified for FA from all samples (Fig. 2). Component 1 (C1) had a primary (and secondary) fluorescence peak at an excitation/emission wavelength of 240 (340) nm/437 nm. Component 2 (C2) exhibited a fluorescence peak at <200 (260) (400) nm/475 nm. Component 3 (C3) possessed a primary (and secondary) fluorescence peak at an excitation/emission wavelength of 240 (280) nm/410 nm (Fig. 2). Fluorescence component C1 was characterized as fulvic acid fluorophore group which was similar to the fluorescence spectra of anthraquinone2,6-disulfonate (AQDS) (Cory and McKnight, 2005; Stedmon and Markager, 2005). Component C2 was similar to the fulvic acid fluorophore group which was similar to the fluorescence spectra of 2,6- anthrahydroquinone disulphonate (AHDS) (Cory and McKnight, 2005; Murphy et al., 2008). Component C3 was characterized as humic materials similar to the fluorescence spectra of lawsone (Cory and McKnight, 2005; Murphy et al., 2008). Generally, according to the previous research, the increase of the molecular complexity and the structural condensation and polymerization of FA could be related with the increase of the wavelength of peak position for FA (Wei et al., 2007; He et al., 2013). Therefore, the humification degree of FA components would be C2 > C1 > C3. Besides, Table S3 provides the excitation and emission characteristics of the DOM components with identified and examples of matching components identified by other researchers. All the composting samples were collected to carry out the PARAFAC analysis, and the 3-component model was successfully validated in the data set. Although three individual components were determined for this dataset using the PARAFAC model, our results do not suggest that only three types of fluorophores were present in all samples or that all three components were present in the majority of the composting samples. Other fluorescent groups were certainly present, however, their influence was so weak that they could not be separated from the noise. Therefore, these three components could explain most of the variation. Variation in the Fmax values of components in FA is displayed in Fig. 3. There were significant differences in Fmax among components of FA from different composts (F = 37.13, p < 0.001), and the sequence was as follows: C1 (44.97% ± 4.83%) > C2 (36.94% ± 6.85%) > C3 (18.09% ± 8.26%). During the composting process, fresh organic matter was decomposed along with the formation of HA and FA (He et al., 2013). In this study, FA from different maturity composts were separated and the fluorescence components were all attributed to FA. Each fluorescence components present differently content in different composts. This may due to the variety of substance in the raw composting material. The majority of FA fluorescence could be described by a combination of C1 and C2, constituting over 80% of the total PARAFAC components in the Fmax values for all samples, except for MC and KW, in which the Fmax values of C3 were 32.26%,
Fig. 2. Components identified by EEM-PARAFAC analysis.
and 28.51%, respectively (Fig. 3a, b). The result suggests that the FA in the two samples would be associated with simple condensation and polymerization. Generally, as the total Fmax value of C1 and C2 with the peaks at a long wavelength for FA increases, the humification degree of FA increases. Therefore, the humification degree of FA was ranked as GW (93.60%), TSW (89.55%), LW (87.27%) and SW (84.45%) > PM (81.87%), CM (81.26%) and MSW (80.07%) > KW (71.49%), and MC (67.64%). Besides, according to the results of the values of PI,n /PII,n from different composts, the humification degree of FA was ranked as GW, TSW, LW, and SW > PM, CM and MSW > KW and MC (Fig. S1). Therefore, these two results, which represented for the FA humification degree of different composts were similar to each other. 3.3. Correlation analysis There were no significant correlations between C1 and the other two components (C2, C3), while the Fmax of C3 was negatively correlated with that of C2 (r2 = 0.610, p = 0.008) (Fig. 4a). We hypothesized that C3 could be a precursor of C2, and the high humification degree of FA was caused by the transition from C3 to C2 during composting. The PI,n /PII,n of regional integration in EEM
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Fig. 3. The box chart (a) and distributions (b) of Fmax in FA components from different composts.
Fig. 4. the correlations of C2 with C3 (a), PI,n /PII,n with C1(b) and C3 (c).
spectra was positively correlated with the Fmax of C1 (r2 = 0.578, p = 0.010) (Fig. 4b) and negatively correlated with the Fmax of C3 (r2 = 0.819, p = 0.000) (Fig. 4c). The results agreed with those of the assessment of the humification degree of FA, i.e., in EEM spectra, the humification degree of FA caused by the peak at long wavelength. However, there was no significant correlation between the PI,n /PII,n and the Fmax of C2 at the longest wavelength among FA components. One reason was that the wavelengths of peak a and peak b in the EEM spectra were similar to that of C1 and C3 as identified by PARAFAC analysis, and C2, with a small relative fluorescence intensity, was covered by peak a and peak b in the EEM spectra (Figs. 1 and 2). Another reason was that the PI,n /PII,n calculated by regional integration in the EEM spectra in this study only considered the differences in fluorescence intensities at the excitation wavelength, while the components based on the EEM-PARAFAC only involved the differences of fluorescence intensities at the emission wavelength. In the EEMs, there were two obvious fluorescence peaks. Actually, there were several fluorescence peaks covered in these two fluorescence peaks. While the technology of PARAFAC can separate fluorescence peaks from EEMs into individual component. The results of the relationships between fluorescence components C1, C3 and PI,n /PII,n suggest that the fluorescence components C1, C3 and PI,n /PII,n can reflect the humification degree of FA. FRI cannot represent for the fluorescence component C2. FRI analysis divided EEMs into two regions, and it
is more suitable for small sample size to characterize the humification degree of FA. PARAFAC can decompose EEMs into various individual fluorescent components. And some authors also indicated that EEM combined PARAFAC could be employed to trace the properties of composting-derived FA (Plazaa et al., 2007; Lv et al., 2014). Furthermore, PARAFAC analysis is more suitable for large sample size to characterize the humification degree of FA. Above all, regional integration agreed with PARAFAC for the assessment of the humification degree of FA with different spectral properties. For instance, the two analysis methods were all ranked by the assessment of the humification degree of FA as GW, TSW, LW and SW > PM, CM and MSW > KW and MC. However, the two analysis methods were all limited for similar spectral properties of FA. For instance, regional integration disagreed with the PARAFAC analysis for the assessment of the humification degree of FA derived from GW, TSW, LW and SW. Therefore, a multi-index evaluation for the humification degree of FA considering the regional integration and PARAFAC analysis is necessary. 3.4. PPR analysis The above analysis suggested that a multi-index evaluation could reveal more detailed humification characteristics of FA than each index individually. Therefore, an integrated tool utilizing multiple fluorescence parameters would be necessary. In this study,
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of FA, even in humic substances. For instance, the three components identified by EEM-PARAFAC (Fig. 3) and the peaks at similar wavelength (Fig. 2) indicated that the compositions of FA were similar to each other despite being composed of composts from different sources. The differences in the humification degree of FA were mainly caused by the distribution of each component for the composts. Therefore, composting with a mixture of different raw materials can regulate the humification degree of FA through the redistribution of components. Take for example Fig. 5; we can mix GW with KW in a certain proportion to decrease the humification degree of FA in GW, or increase that of FA in KW in a certain period of composting. In addition, multiple raw materials will benefit from the microbial diversity during composting owing to the multiple carbon sources, increasing composting efficiency.
3.6. Roles of composts with different humification degrees of FA in soil Fig. 5. Projection values of FA from different composts. Different colors of column represent for the significantly differences between the projection values of different composts (p < 0.05).
PPR was performed to rank the humification degree of FA for these composts using the data (Fmax values of C1, C2, C3, and PI,n /PII,n ). Moreover, the values of C1, C2 and PI,n /PII,n were positively correlated with the humification degree of FA, and the Fmax value of C3 was negatively correlated with the humification degree of FA. As shown in Fig. 5, the projection values of different composts present significantly different from each other. The higher projection values represent for the higher humification degree of FA. The results were consistent with those obtained with the Fmax values of C1, C2 and C3, and the values of PI,n /PII,n , respectively, suggesting that PPR could be as an integrated tool for the assessment of the humification degree of FA. Furthermore, the projection values also rank the humification degree of FA at each level. For instance, the humification degree in FA was GW > TSW and LW > SW at the highest level, CM > MSW > PM at the intermediate level, and KW > MC at the lowest level. The results indicated that the assessment of the humification degree of FA using a PPR model could distinguish the slight differences, which were not recognized by PI,n /PII,n or the individual distributions of the Fmax of FA components. 3.5. The relationship between humification degree of FA and composition of raw materials The above analysis shows that the humification degree of FA was affected by the composition of raw materials. According to the reports on the humification degree of DOM (Tan, 2014; Wei et al., 2014), a high humification degree of FA may be attributed to raw materials with a high distribution of macromolecular organic matter. For instance, cellulose was the primary component of the raw materials of GW, TSW, LW and SW, which resulted in the highest humification degree of FA in those compost samples. While the raw materials dominated by low molecular weight fractions would lead to a low humification degree of FA, such as in KW, which had high concentrations of protein and fat. The lowest humification degree of FA occurred in MC mixed with biogas residue, due to the low molecular weight organic acids in the biogas residue. During the biological process of composting, more stable and complex macromolecules (humic substances) would be formed by organic matter. Therefore, understanding the relationship between the fluorescent components of FA and the composition of raw materials is important for the regulation of the humification degree
It is known that composting is also a form of a humification process of humic substance. After amending, the FA from composts through the soil profile influence the cycling of nutrients and microbial activities (Esteves da Silva and Oliveira, 2002). FA also interact with a number of inorganic and organic pollutants because of the presence of oxygen-containing and organic aromatic functional groups in its constituents (Pemrinova et al., 2001). Generally, as the humification degree of FA increases, the bioavailability decreases. Therefore, when composts are land applied, composts can be used in different ways based on the humification degree of FA. Take for example Fig. 5, the compost with a low humification degree of FA (MC and KW) is suitable for increasing soil fertilizer because of the high bioavailability of FA. After amending the soil, FA in the compost can provide plants with nutrients as decomposition occurs. However, considering the effect of aromatic and humiclike components on binding heavy metals and organic pollutants (He et al., 2014; Peng et al., 2014), the FA with high humification degree in the compost could adsorb pollutants or form stable complexes with them. Besides, the strong metal binding sites in high humification degree of FA could result in the stable chelates of FA and metal, which are generally very resistant to microbial decomposition and difficult to absorb in organisms (low bioavailability) (Al-Reasi et al., 2013). The characteristics of FA with high humification degree predict potential protective impacts of composts on metal toxicity after applying the compost to the contaminated soil. Therefore, the compost with a high humification degree of FA (GW, TSW, LW and SW) seems more appropriate for the restoration of soils contaminated by metals or organic pollutants. For the FA (CM, MSW, and PM) with a medium humification degree in the compost, it would be better off used as a degenerated soil amendment. This FA with both labile and refractory fractions serves many roles in the soil, ranging from improving soil structure, increasing the water-holding capacity and infiltration through structural and porosity changes, improving nutrient conservation and availability and decreasing soil erosion (Weng et al., 2002). In addition, the application of FA with different humification degrees is also suitable for HA. Considering the aim of precise fertilization to meet the needs of different soils, we expect to carry out the further study to investigate the suitable amount and ratio of different composts with different humification degree as soil amendments. Generally, the amounts of composting products could be determined according to the aim and cost, such as 5% in agricultural soils for increasing soil fertilizer (approximately 7500 kg/ha); 10% in a degenerated soil to improve soil structural properties (approximately 15,000 kg/ha); 15% in the soils contaminated by metals or organic pollutants to restore the soils (approximately 22,500 kg/ha). They would pro-
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vide numerous essential nutrients for plants growth and have their special effects on different soils. 4. Conclusion Both the values of PI,n /PII,n and the distributions of the Fmax of C1, C2 and C3 indicated that the humification degree of FA was ranked as GW, TSW, LW and SW > PM, CM and MSW > KW and MC. The PPR analysis further ranked the samples with similar humification degrees compared to the assessment based on the values of PI,n /PII,n or the distributions of the Fmax of C1, C2 and C3. Though the compositions of FA were similar in composts from different sources, the differences in the humification degree of FA could be caused by the distribution of each component for the composts. Therefore, mixing different raw materials was suggested to regulate the humification degree of FA through the redistribution of components. Additionally, the roles of composts with different humification degrees of FA were demonstrated, that is, the composts with a low, medium and high humification degree of FA are suitable for increasing soil fertilizer, improving degenerated soils and the restoration of soils contaminated by metals or organic pollutants, respectively. Further study is needed to investigate the suitable amount and ratio of composts with different humification degrees as amendments to achieve the aim of precise fertilization based on the needs of different soils. Acknowledgments This work was financially supported by the National Natural Science Foundation of China (No. 51178090 and No. 51378097) and the National Key Technology R&D Program (No. 2012BAJ21B02-02). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ecolind.2016. 08.051. References Al-Reasi, H.A., Wood, C.M., Smith, D.S., 2013. Characterization of freshwater natural dissolved organic matter (DOM): mechanistic explanations for protective effects against metal toxicity and direct effects on organisms. Environ. Int. 59, 201–207. Andersen, C.M., Bro, R., 2003. Practical aspects of PARAFAC modeling of fluorescence excitation-emission data. J. Chemom. 17, 200–215. Bai, Y.C., Wu, F.C., Liu, C.Q., Guo, J.Y., Fu, P.Q., Li, W., Xing, B.S., 2008. Interaction between carbamazepine and humic substances: a fluorescence spectroscopy study. Environ. Toxicol. Chem. 27, 95–102. Bernabé, G.A., Almeida, S., Ribeiro, C.A., Crespi, M.S., 2011. Evaluation of organic molecules originated during composting process. J. Therm. Anal. Calorim. 106 (3), 773–778. Bernal, M.P., Alburquerque, J.A., Moral, R., 2009. Composting of animal manures and chemical criteria for compost maturity assessment. A review. Bioresour. Technol. 100 (22), 5444–5453. Chen, W., Westerhoff, P., Leenheer, J.A., Booksh, K., 2003. Fluorescence excitation–emission matrix regional integration to quantify spectra for dissolved organic matter. Environ. Sci. Technol. 37, 5701–5710. Christl, I., Metzger, A., Heidmann, L., Kretzschmar, R., 2005. Effect of humic and fulvic acid concentrations and ionic strength on copper and lead binding. Environ. Sci. Technol. 39, 5319–5326. Coble, P.G., 1996. Characterization of marine and terrestrial DOM in seawater using excitation-emission matrix spectroscopy. Mar. Chem. 51, 325–346. Coble, P.G., Mopper, K., Schultz, C.S., 1993. Fluorescence contouring analysis of DOC intercalibration experiment samples: a comparison of techniques. Mar. Chem. 47, 173–178. Cory, R.M., McKnight, D.M., 2005. Fluorescence spectroscopy reveals ubiquitous presence of oxidized and reduced quinones in dissolved organic matter. Environ. Sci. Technol. 39 (21), 8142–8149. Esteves da Silva, J.C., Oliveira, C.J., 2002. Metal ion complexation properties of fulvic acids extracted from composted sewage sludge as compared to a soil fulvic acid. Water Res. 36, 3404–3409.
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Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind
Roles of composts in soil based on the assessment of humification degree of fulvic acids Yue Zhao a , Yuquan Wei a , Yun Zhang a , Xin Wen a , Beidou Xi b , Xinyu Zhao a , Xu Zhang a , Zimin Wei a,∗ a b
College of Life Science, Northeast Agricultural University, Harbin 150030, China Laboratory of Water Environmental System Engineering, Chinese Research Academy of Environmental Science, Beijing 100012, China
a r t i c l e
i n f o
Article history: Received 30 March 2016 Received in revised form 24 August 2016 Accepted 26 August 2016 Keywords: Mature composts Fulvic acids Humification degree Projection pursuit regression EEM-PARAFAC Soil application
a b s t r a c t This study was conducted to assess the humification degree in fulvic acids (FA) from different composts, and to reveal their roles after soil amending based on their excitation-emission matrices (EEM) of the fluorescence spectra and projection pursuit regression (PPR) analysis. Two peaks were detected in EEM spectra of FA from all composts, and three components were identified by the parallel factor analysis (PARAFAC) model. The assessment of the humification degree of FA using the ratios between the values of the percent fluorescence response in the visible and ultraviolet regions (PI,n /PII,n ) generally agreed with that using the distributions of FA components (C1, C2 and C3). The PPR considering the parameters (PI,n /PII,n , C1, C2 and C3) further ranked the composts with similar of FA, and the FA humification degree decreased in the order: GW, TSW, LW and SW > CM, MSW, and PM > MC and KW. The results showed that the compositions of FA were similar to each other in composts from different materials, but there were distinct differences in the humification degree of FA owing to the different distributions of each component in composts. Therefore, based on the redistribution of components, a method for regulating the humification degree of FA during composting was presented. Furthermore, the suitable soil application of composts with different humification degrees was also demonstrated. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Composting is defined as an economical and environmentfriendly biological process of aerobic thermophilic microbial degradation of wastes by populations of indigenous microorganisms, which can convert organic wastes into a soil amendment rich in humic substances and nutrients, mitigate groundwater contamination and reduce air pollution and greenhouse gas (GHG) emissions (He et al., 2011a; Yan et al., 2016; Zhang et al., 2016). Organic matter is partially transformed into more stable and complex macromolecules such as humic substances in the biological process of composting (Lashermes et al., 2012). Understanding the characteristic of the humic substances formed during composting is relevant because they constitute a stable fraction of carbon, thus regulating the carbon cycle and the release of nutrients, such as nitrogen, phosphorous and sulfur. After soil application, they play
∗ Corresponding author at: Northeast Agricultural University, College of Life Science, No. 59 Mucai Street Xiangfang District, Harbin 150030, China. Tel.: +86 451 55190413; Fax: +86 451 55190413. E-mail addresses: [email protected], [email protected] (Z. Wei). http://dx.doi.org/10.1016/j.ecolind.2016.08.051 1470-160X/© 2016 Elsevier Ltd. All rights reserved.
an important role in global carbon cycling and in the regulation of the mobility and fate of environmental contaminants and also have many positive benefits in creating a suitable medium for plant growth (Christl et al., 2005; Harrison, 2008). Over the years, a number of hypotheses have been presented on how humic matter is formed. Though there is not enough evidence to support the hypothesis that the de novo formation of humic polymers is quantitatively relevant for humus formation (Schmidt et al., 2011), the view relied on alkali and acid extraction methods from previous soil chemists has dominated for years, that is, fulvic acids (FA; soluble at all pH values) were a relatively more lively group constituent in humic substances when compared with humic acids (HA; soluble in alkaline media and insoluble in acidic media) (Ryan and Weber, 1982; Bai et al., 2008). Various parameters have been proposed to study the degree of humification such as humification index (HI), a ratio of peak A (fulvic acid-like substances) to peak C (humic acid-like) in Excitation emission matrix (EEM) fluorescence spectroscopy; fluorescence index (FI), the ratio of emission intensity at 450 nm and 500 nm at 370 nm excitation (McKnight et al., 2001; Ohno, 2002). Since composting implies the formation of some humic-like substances by microorganisms whose metabolism
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predominantly occurs in the water-soluble phase (Said-Pullicino et al., 2007; Bernal et al., 2009), a study of the degree of humification occurring in the water-extract FA may be useful for assessing compost. However, most reports focused on the characteristics of dissolved organic matter (DOM) during composting, and few studies have examined the humification degree in humic substances of different composts. FA contain characteristic structures such as aromatic rings with three to five substituents (mainly hydroxyl, methoxyl or aliphatic hydrocarbon groups with some aldehyde and keto functional groups also attached to some of the aromatic nuclei), aromatic–aliphatic ethers, carboxylic groups, sugars and amino acids. Traditionally, the fractions of fulvic acids were characterized by size exclusion chromatography, elemental analysis (C, H, N, S), as well as spectroscopic techniques, including ultraviolet visible (UV-VIS), Cross-Polarization Magic Angle Spinning Carbon-13 Nuclear Magnetic Resonance (CP-MAS 13C NMR), Fourier transform infrared spectroscopy (FT-IR), and fluorescence spectroscopy (Christl et al., 2005). Specifically, fluorescence spectroscopy is used as a non-destructive, simple, non-separative and accurate tool to quantify the humification and maturity during composting (Hur et al., 2009; Fernandez-Romero et al., 2016). The fluorescence characteristics of DOM have been extensively investigated owing to the technological advances in fluorescence spectroscopy, especially the development excitation – emission (EEMs) (Coble, 1996). Application of EEM as a tool for assessment of compost products is well documented, owing to its high sensitivity and simplicity (Yu et al., 2010a; Wu et al., 2012). The parameters used to assess the humification degree of humic substances include an intensity ratio between the fluorescence peaks at different wavelengths (Zsolnay et al., 1999), an area ratio between different fluorescence spectra regions in traditional fluorescence spectra (Kalbitz et al., 1999), and the percentage of fluorescence response (Pi,n ) calculated by fluorescence regional integration (FRI) in an excitation – emission matrix (EEM) fluorescence spectra (Chen et al., 2003). They also include the distribution of components identified by EEM fluorescence spectra combined with parallel factor analysis (EEM-PARAFAC) (Yu et al., 2010b; Markechova et al., 2014). Apart from the analysis methods of FRI and EEM-PARAFAC in fluorescence spectra, there was also a useful method based on second derivative synchronous fluorescence to characterize DOM (Yu et al., 2013). EEM is a powerful tool for determining DOM substances (Yu et al., 2010a). EEM offers several major advantages over single-scan methodologies such as providing new information regarding the fluorescence DOM composition of a sample (Coble et al., 1993). However, to conquer the difficulty in identifying individual fluorescence components in sample, simple and multivariate data analysis technique PARAFAC have been used (Stedmon et al., 2003). PARAFAC analysis can decompose fluorescence EEMs into independent groups of fluorescence components and provide a unique solution to the FA EEM dataset, and it is regarded as an important analytical tool to characterize the FA in composting (He et al., 2013). The use of fluorescence spectral techniques to characterize the same sample can generate a large number of fluorescence parameters, and the humification degree of FA could be affected by a combination of multiple fluorescence parameters, not necessarily by each measure individually. Therefore, an assessment method utilizing multiple fluorescence parameters would be necessary. Projection pursuit regression (PPR) is a nonlinear multivariate regression procedure proposed by Friedman and Stuetzle (1981). Its basic idea is to project high dimension to low dimensional space, and it tries to find the intrinsic structural information hidden in the high dimensional data. At present, it has been applied successfully to tackle some chemical problems (Ghasemi and Zolfonoun, 2013). The objectives of this study were (1) to obtain FA fluorescence characteristics from different composts; (2) to select fluorescence
parameters, which were suitable for estimating the humification degree in DOM; (3) to assess the humification degree of FA from different composts using EEM-PARAFAC and PPR; (4) to suggest suitable application methods of composts with different humification degrees. 2. Materials and methods 2.1. Sample collection and storage Nine trapezoidal piles of Green waste (GW), Kitchen waste (KW), Tomato stem waste (TSW), Chicken manure (CM), Straw waste (SW), Litter waste (LW), Municipal solid waste (MSW), Pig (Swine) manure (PM) and a co-compost (MC) mixed with biogas residue. All the composts were prepared by Shanghai Songjiang Composting Plant, and each composting pile contained approximately 2 t of raw material (1.5 m high with a 2 × 3 m base). The C/N was adjusted about 25 for each material by mixing sawdust at the initial stage of composting. The composting time was approximately 45 days according to the composting period of the plant. When the composting finished, approximately 3 kg of samples were collected from several sites of the compost pile and stored at 4 ◦ C for the analysis of FA. The samples for analysis were homogenized using the methods of coning and quartering (Bernabé et al., 2011). And all the samples for analyzing FA were carried out by triplicate. Details of the composting properties are described in Table S1. 2.2. Extraction of fulvic acid Compost samples (10 g) were mixed with 0.1 M (NaOH + Na4 P2 O7 ) with a solid to water ratio of 1:10 (w/v). The mixtures were shaken for 24 h with a rotational speed of 150 rpm at room temperature and centrifuged at 10,000 rpm for 15 min. The obtained supernatant was filtered through a 0.45 m membrane filter and then acidified to a pH of 1 with 6 M HCl. The mixtures were allowed to stand for 24 h at 4 ◦ C and again centrifuged at 10,000 rpm for 15 min. The obtained supernatant was passed through an XAD-8 macroporous resin column and an H+ -saturated cation exchange resin for further FA purification (He et al., 2011b). The stationary phases used for the FA purification were XAD-8 resin and 732 cation exchange resin, which have been described by He et al. (2011b). The mean final concentrations of FA in different composts were 116.04 ± 2.05 mg/L (GW), 148.04 ± 3.21 mg/L (KW), 168.51 ± 3.13 mg/L (TSW), 188.00 ± 4.30 mg/L (CM), 82.60 ± 1.51 mg/L (SW), 77.55 ± 1.95 mg/L (LW), 183.32 ± 2.54 mg/L (MSW), 156.13 ± 3.75 mg/L (PM) and 60.54 ± 0.85 mg/L (MC), respectively. 2.3. Fluorescence spectroscopy analysis Fluorescence spectroscopy was recorded using a Hitachi F7000 fluorescence spectrophotometer (Hitachi High Technologies, Japan) in a 1 cm clear quartz cuvette at room temperature (20 ± 2 ◦ C). The emission wavelength was recorded from 250 to 600 for 2 nm increments and excitation wavelength was recorded from 200 to 550 for 10 nm increments. The concentration of FA was diluted to the same level of 10 mg/L before the measurement to decrease the influence of varying FA concentrations among the compost samples in contribution to fluorescence intensities (Yu et al., 2009). The EEM spectra were recorded for the excitation spectra from 200 to 550 nm at intervals of 10 nm while the emission spectra ranged between 250 and 600 nm, with data saved for every 2 nm increments. The scan speed was set at 1200 nm min−1 . The fluorescence intensities were converted to Roman Unit (R.U.). Meanwhile, Milli-Q water blank EEMs were deducted from the
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Fig. 1. EEM fluorescence spectra of FA in different composts.
sample EEM to decrease the influence of the Rayleigh and Raman scattering.
3. Results and discussion 3.1. EEM fluorescence spectroscopy
2.4. Regional integration analysis Fluorescence regional integration, a quantitative technique that integrates the volume beneath an EEM, was developed to analyze EEMs. EEM was delineated into two excitation-emission regions based on fluorescence of model components, FA fractions. Volumetric integration under the EEM within each region, normalized to the projected excitation-emission area within that region, resulted in a normalized region-specific EEM volume (PI,n ). 2.5. PARAFAC analysis PARAFAC analysis was applied to the three-dimensional data array using MATLAB2010 with the DOM Fluor toolbox, and all EEM spectra data of each molecular weights (MW) fraction comprised a three-dimensional data array (27 samples × 41 Ex × 45 Em). The array was decomposed into three matrices: score, Ex loading, and Em loading matrices (Stedmon and Bro, 2008). The scores in the score matrix, which were expressed as Fmax values, were used to evaluate the concentration of the fluorescence components determined through EEM–PARAFAC analysis in accordance with previous reports. 2.6. Multivariate statistical analysis SPSS version 17.0 was used for significance test and Origin 8.0 was used to analyze the relationships among fluorescence parameters and draw the plots. Matlab R2010b was employed to perform PPR program using in-house-developed MATLAB software (PPR analysis). Furthermore, PARAFAC analysis was carried out in MATLAB with the DOM Fluor toolbox, following the procedure described by Stedmon and Bro (2008).
EEM fluorescence spectra could provide a large amount of information about the structure of FA. The EEM fluorescence spectra of FA are shown in Fig. 1. All of the EEM fluorescence spectra of FA exhibited two peaks at Ex/Em of 230–240/421–448 nm (peak a), 330–350/424–442 nm (peak b), which were related to FA area of the visible region and the FA area of the ultraviolet region, respectively. The differences in the intensities of fluorescence and the wavelengths of peaks of FA in different samples indicated that there were slight differences in the amount and distribution of components of FA from composts. Besides, as shown in Fig. 1 and Table S2, the intensities of peak a from different composts are all significantly higher than those of peak b. According to the previous research by Chen et al. (2003), the peaks in the region I represent for complex structure materials. Therefore, the complex structure components account for a large proportion of FA in all compost samples. According to a previous study by Chen et al. (2003), EEM fluorescence spectra of dissolved organic matter could be divided into five regions. However, five regions for FA may not be fully applicable because of the absence of protein regions or negligible portions in the EEM fluorescence spectra of FA (Fig. 1). To compare the humification correctly, the EEM fluorescence spectra of FA was divided into two regions. The percentage of fluorescence response (Pi,n ) of each region was calculated based on the regional integration of fluorescence (Chen et al., 2003). Region I in the visible region could be associated with the presence of high molecular weight fractions, while region II in the ultraviolet region may be attributed to simple structural components in FA (Senesi et al., 1991; Wei et al., 2014). Therefore, the ratio of PI,n /PII,n can be an indicator of the humification degree for FA. Moreover, as the composting progressed, organic matters reach stability through mineralization and humification
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process and the FRI values in long wavelength from mature composting present higher than that of fresh composting (Yu et al., 2011; He et al., 2013). Therefore, in this study, the higher ratio value of PI,n /PII,n represented a higher humification degree of composts. These percentages of PI,n /PII,n varied from 1.99 to 4.10 for all the samples, indicating that there were distinct differences in the humification degree for FA in these composts. Based on the value of PI,n /PII,n , the humification degree was the highest for GW (3.90), TSW (4.10), SW (3.76) and LW (3.94), and lower for MC (1.99) and KW (2.20), with intermediate values for CM (2.71), MSW (2.73) and PM (2.68). 3.2. PARAFAC analysis PARAFAC analysis, which can decompose EEMs into various individual fluorescent components (Andersen and Bro, 2003; Hunt and Ohno, 2007), was conducted to investigate the composition of FA from different composts. Three components were identified for FA from all samples (Fig. 2). Component 1 (C1) had a primary (and secondary) fluorescence peak at an excitation/emission wavelength of 240 (340) nm/437 nm. Component 2 (C2) exhibited a fluorescence peak at <200 (260) (400) nm/475 nm. Component 3 (C3) possessed a primary (and secondary) fluorescence peak at an excitation/emission wavelength of 240 (280) nm/410 nm (Fig. 2). Fluorescence component C1 was characterized as fulvic acid fluorophore group which was similar to the fluorescence spectra of anthraquinone2,6-disulfonate (AQDS) (Cory and McKnight, 2005; Stedmon and Markager, 2005). Component C2 was similar to the fulvic acid fluorophore group which was similar to the fluorescence spectra of 2,6- anthrahydroquinone disulphonate (AHDS) (Cory and McKnight, 2005; Murphy et al., 2008). Component C3 was characterized as humic materials similar to the fluorescence spectra of lawsone (Cory and McKnight, 2005; Murphy et al., 2008). Generally, according to the previous research, the increase of the molecular complexity and the structural condensation and polymerization of FA could be related with the increase of the wavelength of peak position for FA (Wei et al., 2007; He et al., 2013). Therefore, the humification degree of FA components would be C2 > C1 > C3. Besides, Table S3 provides the excitation and emission characteristics of the DOM components with identified and examples of matching components identified by other researchers. All the composting samples were collected to carry out the PARAFAC analysis, and the 3-component model was successfully validated in the data set. Although three individual components were determined for this dataset using the PARAFAC model, our results do not suggest that only three types of fluorophores were present in all samples or that all three components were present in the majority of the composting samples. Other fluorescent groups were certainly present, however, their influence was so weak that they could not be separated from the noise. Therefore, these three components could explain most of the variation. Variation in the Fmax values of components in FA is displayed in Fig. 3. There were significant differences in Fmax among components of FA from different composts (F = 37.13, p < 0.001), and the sequence was as follows: C1 (44.97% ± 4.83%) > C2 (36.94% ± 6.85%) > C3 (18.09% ± 8.26%). During the composting process, fresh organic matter was decomposed along with the formation of HA and FA (He et al., 2013). In this study, FA from different maturity composts were separated and the fluorescence components were all attributed to FA. Each fluorescence components present differently content in different composts. This may due to the variety of substance in the raw composting material. The majority of FA fluorescence could be described by a combination of C1 and C2, constituting over 80% of the total PARAFAC components in the Fmax values for all samples, except for MC and KW, in which the Fmax values of C3 were 32.26%,
Fig. 2. Components identified by EEM-PARAFAC analysis.
and 28.51%, respectively (Fig. 3a, b). The result suggests that the FA in the two samples would be associated with simple condensation and polymerization. Generally, as the total Fmax value of C1 and C2 with the peaks at a long wavelength for FA increases, the humification degree of FA increases. Therefore, the humification degree of FA was ranked as GW (93.60%), TSW (89.55%), LW (87.27%) and SW (84.45%) > PM (81.87%), CM (81.26%) and MSW (80.07%) > KW (71.49%), and MC (67.64%). Besides, according to the results of the values of PI,n /PII,n from different composts, the humification degree of FA was ranked as GW, TSW, LW, and SW > PM, CM and MSW > KW and MC (Fig. S1). Therefore, these two results, which represented for the FA humification degree of different composts were similar to each other. 3.3. Correlation analysis There were no significant correlations between C1 and the other two components (C2, C3), while the Fmax of C3 was negatively correlated with that of C2 (r2 = 0.610, p = 0.008) (Fig. 4a). We hypothesized that C3 could be a precursor of C2, and the high humification degree of FA was caused by the transition from C3 to C2 during composting. The PI,n /PII,n of regional integration in EEM
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Fig. 3. The box chart (a) and distributions (b) of Fmax in FA components from different composts.
Fig. 4. the correlations of C2 with C3 (a), PI,n /PII,n with C1(b) and C3 (c).
spectra was positively correlated with the Fmax of C1 (r2 = 0.578, p = 0.010) (Fig. 4b) and negatively correlated with the Fmax of C3 (r2 = 0.819, p = 0.000) (Fig. 4c). The results agreed with those of the assessment of the humification degree of FA, i.e., in EEM spectra, the humification degree of FA caused by the peak at long wavelength. However, there was no significant correlation between the PI,n /PII,n and the Fmax of C2 at the longest wavelength among FA components. One reason was that the wavelengths of peak a and peak b in the EEM spectra were similar to that of C1 and C3 as identified by PARAFAC analysis, and C2, with a small relative fluorescence intensity, was covered by peak a and peak b in the EEM spectra (Figs. 1 and 2). Another reason was that the PI,n /PII,n calculated by regional integration in the EEM spectra in this study only considered the differences in fluorescence intensities at the excitation wavelength, while the components based on the EEM-PARAFAC only involved the differences of fluorescence intensities at the emission wavelength. In the EEMs, there were two obvious fluorescence peaks. Actually, there were several fluorescence peaks covered in these two fluorescence peaks. While the technology of PARAFAC can separate fluorescence peaks from EEMs into individual component. The results of the relationships between fluorescence components C1, C3 and PI,n /PII,n suggest that the fluorescence components C1, C3 and PI,n /PII,n can reflect the humification degree of FA. FRI cannot represent for the fluorescence component C2. FRI analysis divided EEMs into two regions, and it
is more suitable for small sample size to characterize the humification degree of FA. PARAFAC can decompose EEMs into various individual fluorescent components. And some authors also indicated that EEM combined PARAFAC could be employed to trace the properties of composting-derived FA (Plazaa et al., 2007; Lv et al., 2014). Furthermore, PARAFAC analysis is more suitable for large sample size to characterize the humification degree of FA. Above all, regional integration agreed with PARAFAC for the assessment of the humification degree of FA with different spectral properties. For instance, the two analysis methods were all ranked by the assessment of the humification degree of FA as GW, TSW, LW and SW > PM, CM and MSW > KW and MC. However, the two analysis methods were all limited for similar spectral properties of FA. For instance, regional integration disagreed with the PARAFAC analysis for the assessment of the humification degree of FA derived from GW, TSW, LW and SW. Therefore, a multi-index evaluation for the humification degree of FA considering the regional integration and PARAFAC analysis is necessary. 3.4. PPR analysis The above analysis suggested that a multi-index evaluation could reveal more detailed humification characteristics of FA than each index individually. Therefore, an integrated tool utilizing multiple fluorescence parameters would be necessary. In this study,
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of FA, even in humic substances. For instance, the three components identified by EEM-PARAFAC (Fig. 3) and the peaks at similar wavelength (Fig. 2) indicated that the compositions of FA were similar to each other despite being composed of composts from different sources. The differences in the humification degree of FA were mainly caused by the distribution of each component for the composts. Therefore, composting with a mixture of different raw materials can regulate the humification degree of FA through the redistribution of components. Take for example Fig. 5; we can mix GW with KW in a certain proportion to decrease the humification degree of FA in GW, or increase that of FA in KW in a certain period of composting. In addition, multiple raw materials will benefit from the microbial diversity during composting owing to the multiple carbon sources, increasing composting efficiency.
3.6. Roles of composts with different humification degrees of FA in soil Fig. 5. Projection values of FA from different composts. Different colors of column represent for the significantly differences between the projection values of different composts (p < 0.05).
PPR was performed to rank the humification degree of FA for these composts using the data (Fmax values of C1, C2, C3, and PI,n /PII,n ). Moreover, the values of C1, C2 and PI,n /PII,n were positively correlated with the humification degree of FA, and the Fmax value of C3 was negatively correlated with the humification degree of FA. As shown in Fig. 5, the projection values of different composts present significantly different from each other. The higher projection values represent for the higher humification degree of FA. The results were consistent with those obtained with the Fmax values of C1, C2 and C3, and the values of PI,n /PII,n , respectively, suggesting that PPR could be as an integrated tool for the assessment of the humification degree of FA. Furthermore, the projection values also rank the humification degree of FA at each level. For instance, the humification degree in FA was GW > TSW and LW > SW at the highest level, CM > MSW > PM at the intermediate level, and KW > MC at the lowest level. The results indicated that the assessment of the humification degree of FA using a PPR model could distinguish the slight differences, which were not recognized by PI,n /PII,n or the individual distributions of the Fmax of FA components. 3.5. The relationship between humification degree of FA and composition of raw materials The above analysis shows that the humification degree of FA was affected by the composition of raw materials. According to the reports on the humification degree of DOM (Tan, 2014; Wei et al., 2014), a high humification degree of FA may be attributed to raw materials with a high distribution of macromolecular organic matter. For instance, cellulose was the primary component of the raw materials of GW, TSW, LW and SW, which resulted in the highest humification degree of FA in those compost samples. While the raw materials dominated by low molecular weight fractions would lead to a low humification degree of FA, such as in KW, which had high concentrations of protein and fat. The lowest humification degree of FA occurred in MC mixed with biogas residue, due to the low molecular weight organic acids in the biogas residue. During the biological process of composting, more stable and complex macromolecules (humic substances) would be formed by organic matter. Therefore, understanding the relationship between the fluorescent components of FA and the composition of raw materials is important for the regulation of the humification degree
It is known that composting is also a form of a humification process of humic substance. After amending, the FA from composts through the soil profile influence the cycling of nutrients and microbial activities (Esteves da Silva and Oliveira, 2002). FA also interact with a number of inorganic and organic pollutants because of the presence of oxygen-containing and organic aromatic functional groups in its constituents (Pemrinova et al., 2001). Generally, as the humification degree of FA increases, the bioavailability decreases. Therefore, when composts are land applied, composts can be used in different ways based on the humification degree of FA. Take for example Fig. 5, the compost with a low humification degree of FA (MC and KW) is suitable for increasing soil fertilizer because of the high bioavailability of FA. After amending the soil, FA in the compost can provide plants with nutrients as decomposition occurs. However, considering the effect of aromatic and humiclike components on binding heavy metals and organic pollutants (He et al., 2014; Peng et al., 2014), the FA with high humification degree in the compost could adsorb pollutants or form stable complexes with them. Besides, the strong metal binding sites in high humification degree of FA could result in the stable chelates of FA and metal, which are generally very resistant to microbial decomposition and difficult to absorb in organisms (low bioavailability) (Al-Reasi et al., 2013). The characteristics of FA with high humification degree predict potential protective impacts of composts on metal toxicity after applying the compost to the contaminated soil. Therefore, the compost with a high humification degree of FA (GW, TSW, LW and SW) seems more appropriate for the restoration of soils contaminated by metals or organic pollutants. For the FA (CM, MSW, and PM) with a medium humification degree in the compost, it would be better off used as a degenerated soil amendment. This FA with both labile and refractory fractions serves many roles in the soil, ranging from improving soil structure, increasing the water-holding capacity and infiltration through structural and porosity changes, improving nutrient conservation and availability and decreasing soil erosion (Weng et al., 2002). In addition, the application of FA with different humification degrees is also suitable for HA. Considering the aim of precise fertilization to meet the needs of different soils, we expect to carry out the further study to investigate the suitable amount and ratio of different composts with different humification degree as soil amendments. Generally, the amounts of composting products could be determined according to the aim and cost, such as 5% in agricultural soils for increasing soil fertilizer (approximately 7500 kg/ha); 10% in a degenerated soil to improve soil structural properties (approximately 15,000 kg/ha); 15% in the soils contaminated by metals or organic pollutants to restore the soils (approximately 22,500 kg/ha). They would pro-
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vide numerous essential nutrients for plants growth and have their special effects on different soils. 4. Conclusion Both the values of PI,n /PII,n and the distributions of the Fmax of C1, C2 and C3 indicated that the humification degree of FA was ranked as GW, TSW, LW and SW > PM, CM and MSW > KW and MC. The PPR analysis further ranked the samples with similar humification degrees compared to the assessment based on the values of PI,n /PII,n or the distributions of the Fmax of C1, C2 and C3. Though the compositions of FA were similar in composts from different sources, the differences in the humification degree of FA could be caused by the distribution of each component for the composts. Therefore, mixing different raw materials was suggested to regulate the humification degree of FA through the redistribution of components. Additionally, the roles of composts with different humification degrees of FA were demonstrated, that is, the composts with a low, medium and high humification degree of FA are suitable for increasing soil fertilizer, improving degenerated soils and the restoration of soils contaminated by metals or organic pollutants, respectively. Further study is needed to investigate the suitable amount and ratio of composts with different humification degrees as amendments to achieve the aim of precise fertilization based on the needs of different soils. Acknowledgments This work was financially supported by the National Natural Science Foundation of China (No. 51178090 and No. 51378097) and the National Key Technology R&D Program (No. 2012BAJ21B02-02). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ecolind.2016. 08.051. References Al-Reasi, H.A., Wood, C.M., Smith, D.S., 2013. Characterization of freshwater natural dissolved organic matter (DOM): mechanistic explanations for protective effects against metal toxicity and direct effects on organisms. Environ. Int. 59, 201–207. Andersen, C.M., Bro, R., 2003. Practical aspects of PARAFAC modeling of fluorescence excitation-emission data. J. Chemom. 17, 200–215. Bai, Y.C., Wu, F.C., Liu, C.Q., Guo, J.Y., Fu, P.Q., Li, W., Xing, B.S., 2008. Interaction between carbamazepine and humic substances: a fluorescence spectroscopy study. Environ. Toxicol. Chem. 27, 95–102. Bernabé, G.A., Almeida, S., Ribeiro, C.A., Crespi, M.S., 2011. Evaluation of organic molecules originated during composting process. J. Therm. Anal. Calorim. 106 (3), 773–778. Bernal, M.P., Alburquerque, J.A., Moral, R., 2009. Composting of animal manures and chemical criteria for compost maturity assessment. A review. Bioresour. Technol. 100 (22), 5444–5453. Chen, W., Westerhoff, P., Leenheer, J.A., Booksh, K., 2003. Fluorescence excitation–emission matrix regional integration to quantify spectra for dissolved organic matter. Environ. Sci. Technol. 37, 5701–5710. Christl, I., Metzger, A., Heidmann, L., Kretzschmar, R., 2005. Effect of humic and fulvic acid concentrations and ionic strength on copper and lead binding. Environ. Sci. Technol. 39, 5319–5326. Coble, P.G., 1996. Characterization of marine and terrestrial DOM in seawater using excitation-emission matrix spectroscopy. Mar. Chem. 51, 325–346. Coble, P.G., Mopper, K., Schultz, C.S., 1993. Fluorescence contouring analysis of DOC intercalibration experiment samples: a comparison of techniques. Mar. Chem. 47, 173–178. Cory, R.M., McKnight, D.M., 2005. Fluorescence spectroscopy reveals ubiquitous presence of oxidized and reduced quinones in dissolved organic matter. Environ. Sci. Technol. 39 (21), 8142–8149. Esteves da Silva, J.C., Oliveira, C.J., 2002. Metal ion complexation properties of fulvic acids extracted from composted sewage sludge as compared to a soil fulvic acid. Water Res. 36, 3404–3409.
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