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PARAFAC modeling of irradiation- and oxidation-induced changes in fluorescent dissolved organic matter extracted from poultry litter Kiranmayi P Mangalgiri, Stephen Andrew Timko, Michael Gonsior, and Lee Blaney Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b06589 • Publication Date (Web): 12 Jun 2017 Downloaded from http://pubs.acs.org on June 15, 2017
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Environmental Science & Technology
PARAFAC modeling of irradiation- and oxidation-induced changes in fluorescent dissolved organic matter extracted from poultry litter Kiranmayi P. Mangalgiri 1, Stephen A. Timko 2, Michael Gonsior 3, and Lee Blaney 1* 1:
University of Maryland Baltimore County Department of Chemical, Biochemical and Environmental Engineering 1000 Hilltop Circle, ECS 314 Baltimore, MD 21250 USA
2:
Kennedy/Jenks Consultants 1191 2nd Avenue, Suite 630 Seattle, WA 98101
3:
University of Maryland Center for Environmental Science Chesapeake Biological Laboratory 146 Williams Street, P.O. Box 38 Solomons, MD 20688
* Corresponding author: Lee Blaney, PhD University of Maryland Baltimore County Department of Chemical, Biochemical and Environmental Engineering 1000 Hilltop Circle, ECS 314 Baltimore, MD 21250 USA Tel: +1-410-455-8608 Fax: +1-410-455-1049 Email:
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TABLE OF CONTENTS GRAPHIC
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ABSTRACT
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Parallel factor analysis (PARAFAC) applied to fluorescence excitation emission matrices
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(EEMs) allows quantitative assessment of the composition of fluorescent dissolved organic
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matter (DOM). In this study, we fit a four-component EEM-PARAFAC model to characterize
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DOM extracted from poultry litter. The dataset included fluorescence EEMs from 291 untreated,
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irradiated (253.7 nm, 310 – 410 nm), and oxidized (UV-H2O2, ozone) poultry litter extracts. The
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four components were identified as microbial humic-, terrestrial humic-, tyrosine-, and
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tryptophan-like fluorescent signatures. The Tucker’s congruence coefficients for components
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from the global (i.e., aggregated sample set) model and local (i.e., single poultry litter source)
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models were greater than 0.99, suggesting that the global EEM-PARAFAC model may be
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suitable to study poultry litter DOM from individual sources. In general, the transformation
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trends of the four fluorescence components were comparable for all poultry litter sources tested.
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For irradiation at 253.7 nm, ozonation, and UV-H2O2 advanced oxidation, transformation of the
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humic-like components was slower than that of the tryptophan-like component. The opposite
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trend was observed for irradiation at 310 – 410 nm, due to differences in UV absorbance
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properties of components. Compared to the other EEM-PARAFAC components, the tyrosine-
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like component was fairly recalcitrant in irradiation and oxidation processes. This novel
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application of EEM-PARAFAC modeling provides insight into the composition and fate of
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agricultural DOM in natural and engineered systems.
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1. INTRODUCTION
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Parallel factor analysis (PARAFAC) is a mathematical tool that models the fluorescence
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excitation emission matrices (EEM) of dissolved organic matter (DOM) using a finite number of
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components 1-3. These components are described by their characteristic excitation and emission
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spectra, and are associated with a pool of organic molecules and/or moieties that contribute to the
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overall fluorescence signature of the bulk DOM matrix. EEM-PARAFAC models can be
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employed to study environmental or experimental samples using component scores that are
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analogous to concentrations, although these scores cannot be compared between different
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components due to differences in quantum yield; furthermore, solution pH and temperature also
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affect comparison of component scores 4. Regardless, changes in DOM fluorescence spectra can
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be described by component scores along a gradient corresponding to time, space, or extent of
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treatment.
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In the last decade, EEM-PARAFAC has been widely used to characterize the composition,
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biodegradability, and photolability of DOM in natural systems (e.g., rivers, oceans, lakes,
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wetlands, groundwater, soil, and sediments) 5-13 and to study the effects of hydrological events
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and biogeochemical cycles 14-16. DOM matrices from water and wastewater treatment plants
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have also been analyzed by EEM-PARAFAC to determine the fate of DOM through biological,
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physical, and chemical treatment processes, such as conventional activated sludge, filtration,
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coagulation, and disinfection 17-20. Recently, EEM-PARAFAC models have been used to
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describe DOM reactivity in bench-scale advanced oxidation processes, specifically, UV-TiO2,
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UV-Fenton, UV-chlorine, and UV-persulfate 21-24.
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The ability of EEM-PARAFAC to deconvolute DOM signatures has allowed for contaminant
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source tracking, which can be used to analyze the effects of anthropogenic activities on the
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environment. While several reports tie the DOM signatures of downstream natural systems to
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changes in upstream land use patterns 25-27 from industry, agriculture, and forestry, a limited
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number of models 28-30 have been developed using DOM derived from agricultural waste. Using
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an EEM-PARAFAC model constructed for DOM from plant chaff (e.g., oat, millet, soybean,
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corn, wheat, and canola) and animal biomass (i.e., dairy, swine, and poultry manure), Hunt and
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Ohno 28 reported that while decomposition of plant-based DOM showed similar behavior across
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species, degradation of animal-derived DOM was dependent on the type of animal manure. Yu
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et al. 29 developed an EEM-PARAFAC model for commercial compost generated from
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agricultural and industrial organic waste; however, the DOM sources were not separately
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assessed to determine agriculture- and industry-specific components. For these reasons, studies
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comprising DOM from specific animal manures are necessary to better understand the
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composition and fate of organic molecules in manure management processes.
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With the introduction of concentrated animal feeding operations in the United States (US) in the
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mid-20th century, five states (i.e., Alabama, Arkansas, Georgia, Mississippi, and North Carolina)
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account for 60% of the country’s total production 31 of broilers (chicken raised for consumption
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of meat). Poultry is the most widely available meat in the US 32 and the second most consumed
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meat worldwide 33. However, intensive poultry farming has been associated with the
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introduction of antibiotics, hormones, nutrients, and pathogens to the environment, ultimately
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affecting water quality 34. As DOM leaches from poultry litter, and affects the fate of other
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poultry litter-derived contaminants 35-37, an EEM-PARAFAC model to describe changes in DOM
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composition may offer additional insight into the fate and transport of other agricultural
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contaminants.
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The overall objective of this work was to characterize DOM in treated and untreated poultry
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litter-impacted water using EEM-PARAFAC. In this study, we investigated DOM
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transformation through UV irradiation at 253.7 nm, simulated sunlight photolysis at 310 – 410
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nm, UV-H2O2 advanced oxidation, and ozonation. Irradiation at 253.7 nm, advanced oxidation,
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and ozonation were performed to analyze changes in poultry litter-derived DOM fluorescence in
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engineered systems for agricultural waste management and treatment. These treatment processes
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are of increasing interest to the agricultural industry. UV irradiation (253.7 nm) and ozonation
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have been employed for disinfection and odor control 38-42. Adak et al. 36 proposed the UV-H2O2
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system for treatment of organoarsenicals, which are predominantly used in the poultry industry
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and present in poultry litter-impacted waters. Photolysis at 310 – 410 nm was chosen to simulate
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solar photodegradation, which occurs in storage lagoons, constructed wetlands, and surface water
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systems. Studying the wavelength-dependent phototransformation of DOM allows for
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comparison of UV-based engineered processes and sunlight photolysis, ultimately providing a
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better understanding of the reactivity of agricultural DOM in intentional waste management
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systems. As DOM significantly impacts the treatment efficiency of oxidation systems, EEM-
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PARAFAC modeling offers the ability to characterize compositional changes in the poultry
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litter-derived DOM matrix during UV-H2O2 and ozone treatment.
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2. EXPERIMENTAL
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2.1 Poultry Litter Extracts
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Poultry litter samples (i.e., PL1, PL2, and PL3) were acquired from three anonymous
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conventional and organic broiler operations in the Chesapeake Bay watershed following “crust
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out” of poultry houses. These operations produce poultry meat for consumption. During crust
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out, the top layer of poultry litter is collected, but the lower bedding material is left behind to be
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used by the next flock 43. The litter is then piled, but not actively composted. The time that litter
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spent in the pile before collection was designated as the litter age. At each farm, litter was
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collected from multiple points within a pile to obtain a representative sample.
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Upon receipt, the moisture content of poultry litter was determined by gravimetric methods. The
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poultry litter was then oven-dried for five days at 40 °C, homogenized, and sieved (1.19 mm).
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The total organic carbon (TOC) content of the poultry litter was measured with a Shimadzu TOC
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analyzer (TOC-5000A; Columbia, MD) equipped with a solids analysis module (SSM-5000A).
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Stock poultry litter extracts (stock-PLEs) were prepared by adding one gram of the processed
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litter to 25 mL of deionized water (DI; Neu-Ion; Windsor Mill, MD), based on the solids loading
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of a previously reported nutrient recovery process 44. The solutions were shaken at 250 rpm for
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40 minutes, centrifuged at 14,000 g, filtered with 1.2 µm glass fiber pre-filters (Millipore) and
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0.45 µm glass micro-fiber syringe filters (Whatman), and stored in the dark at -20 °C. The stock-
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PLEs were generated just before experimentation, and approximately one week before
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fluorescence analysis commenced. The dissolved organic carbon (DOC) content (see Table 1)
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was determined with a Shimadzu TOC analyzer (TOC-LCPH; Columbia, MD). The pH values
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2.2 Photodegradation and Oxidation Experiments
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A merry-go-round type photoreactor (Rayonet RPR600, Southern New England Ultraviolet Inc.;
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Branford, CT), equipped with eight exchangeable bulbs, was used for irradiation experiments.
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The effective photon flux, measured by ferrioxalate actinometry 45, was 1.22×10-5 Ein/L-s for the
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253.7 nm bulbs and 3.52×10-5 Ein/L-s for the 310 – 410 nm bulbs. Experimental solutions,
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consisting of 9.5 mL DI and 0.5 mL stock-PLE (i.e., 20× diluted stock-PLE, to match the DOC
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of agricultural runoff following manure application 46), were irradiated for 24 hours in quartz
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tubes. A 200 µL aliquot was extracted at 0, 6, 12, 18, and 24 hours.
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UV-H2O2 advanced oxidation was conducted using light at 253.7 nm. Hydrogen peroxide (30%
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H2O2) was purchased from Fisher Scientific (Pittsburgh, PA). Samples (10 mL) containing 9.5
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mL of DI and 0.5 mL of stock-PLE were irradiated for 90 minutes in the presence of a gradient
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of H2O2 concentrations, namely 0, 5, 25, and 50 mg/L. At 0, 15, 30, 60, and 90 min, 200 µL of
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the irradiated solution was withdrawn.
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A high-strength aqueous ozone solution was generated by bubbling ozone gas from a Del Ozone
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generator (LG-7; San Luis Obispo, CA) into DI as previously reported 47. The ozone
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concentration was approximately 12 mg O3/L, as determined by the indigo method 48. The high-
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strength aqueous ozone was added to 10 mL samples, which contained 0.5 mL stock-PLE, at
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doses of 0, 1, 2, 4, and 6 mg O3/L. Specific ozone doses were calculated as the mass of dosed
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ozone to the initial mass of organic carbon. Samples were allowed to react at room temperature
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in the dark for 20 hours, at which time a 200 µL aliquot was collected for analysis. Absorbance
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and fluorescence data were corrected for dilution caused by the addition of the high-strength
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ozone solution.
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For all experiments, the 200 µL sample aliquots were diluted with DI to a volume of 10 mL to
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limit inner-filter effects and prevent detector overload. All data were, therefore, collected and
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reported for samples with an effective dilution factor of 1000, with respect to the stock-PLEs.
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Below, the 1000× diluted stock-PLE solutions are labeled as “PLEs” for brevity. Solution pH
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was not adjusted; all samples were naturally buffered in the pH 6.7 ± 0.2 range. The irradiation
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and oxidation experiments were performed in triplicate, and all data are reported as mean ± 95%
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confidence interval.
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2.3 PARAFAC Modeling
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Fluorescence EEMs and UV-visible absorbance spectra (Figure 1) were recorded for the PLEs
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using a 1-cm quartz cuvette in an Aqualog fluorometer (Horiba Scientific; Edison, NJ). The
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excitation and emission wavelength ranges were 210 – 620 nm and 240 – 600 nm, respectively;
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these ranges were restricted to 240 – 520 nm for excitation and 240 – 600 nm for emission
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during PARAFAC analysis. In all cases, the wavelength step was 3 nm. Inner-filter corrections,
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blank corrections, and conversion to Raman Units (RU) using water peaks at an excitation
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wavelength of 350 nm (emission range 381 – 441 nm) were performed as described in Timko et
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al. 4. Best practices, as described in Murphy et al. 3, were used for preprocessing corrections and
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exploratory analyses.
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A “global” EEM-PARAFAC model was developed with the drEEM 1.0 toolbox 3 in MATLAB
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(MathWorks; Natick, MA) using 291 untreated and treated PLE solutions. The input data was
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for all poultry litter samples, and a four-component model was found to best describe the
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fluorescence patterns in the associated EEMs (see Text S1 and Figure S1 in the Supporting
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Information). The five-component model did not significantly reduce the residuals (see Figure
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S2 in the Supporting Information). A convergence criterion of 10-10 was used, and 50 iterations
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with random initialization were run to check model convergence and confirm the global
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minimum. The four-component EEM-PARAFAC model had a core consistency of greater than
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80% (see Table S3 in the Supporting Information) and acceptable residual errors (see Figure S2
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of the Supporting Information). The data was reverse-normalized at the end of the analysis, as
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per Murphy et al. 3. Rigorous validation tests were performed using six fluorescence data splits
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with alternate sample distributions, and the model was found to be robust as determined by split-
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half analysis.
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To ensure the suitability of the global EEM-PARAFAC model to study DOM from three
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different sources, local 3-13 component EEM-PARAFAC models were tested to examine the
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presence of potentially unique DOM characteristics in the individual poultry litter sources. The
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same standards and protocols were used for preprocessing and exploratory analysis of ‘global’
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and ‘local’ models. As with the global model, four-component models were found to best
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describe the fluorescence data of the individual PLEs. The local EEM-PARAFAC models were
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validated using best practices 3, and the excitation and emission loadings were compared to those
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of the global model in Figure 2b-e. The Tucker’s congruence coefficient was greater than 0.99
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for all components, suggesting that the global EEM-PARAFAC model can be used to analyze
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DOM changes resulting from irradiation and oxidation experiments for all poultry litter sources.
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The Fmax values (i.e., the component scores multiplied by the maximum fluorescence intensities)
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for the PLE solutions are reported in RU, and were used to compare the fluorescence of a single
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component across the treated and untreated PLEs.
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Insert Figure 1
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3. RESULTS AND DISCUSSION
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3.1 Poultry Litter Characterization
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As indicated in Table 1, poultry litter from the three commercial farms exhibited a comparable
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TOC content of approximately 30%, while the DOC for the stock-PLE solutions varied from 1.9
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to 4.2 g C/L. The specific UV absorbance (SUVA254), which is calculated as the UV absorbance
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at 254 nm (UV254) divided by the DOC concentration, suggested that PLE1 contained more
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aromatic moieties compared to PLE2 and PLE3. The E2/E3 ratios (i.e., the UV absorbance at
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250 nm divided by the absorbance at 365 nm) for PLE1, PLE2, and PLE3 were 6.2 (±1.2), 3.8
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(±1.3), and 5.3 (±0.2), respectively, suggesting that the water extractable DOM had dissimilar
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molecular weight distributions 49. A similar conclusion can be made from the spectral slope
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values calculated for 275 – 295 nm (S275-295) which ranged from 0.9 to 1.4×10-2. For context, a
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lower S275-295 and E2/E3 reflects that the DOM matrix has a higher average molecular weight 50.
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The apparently conflicting trends of molecular size and aromaticity from the UV-based
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parameters that are typically used to characterize surface water DOM requires further vetting
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with other analytical techniques to provide additional insight into agricultural DOM
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characterization. Below, we use EEM-PARAFAC to analyze DOM content and reactivity.
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Insert Table 2
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The fluorescence signatures in the EEMs (Figure 1) were tentatively characterized by Coble’s
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peak picking method and the descriptors used for regional analysis reported by Chen et al. 51
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(Table 2). The water content of the poultry litters varied with age. PL1 and PL2 were relatively
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fresh (i.e., 0-6 months) and, unsurprisingly, contained more water than PL3, which had been
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aged for 12 months in an unmanaged pile. The impacts of litter age on DOM composition were
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also apparent from the higher fluorescence intensity associated with soluble microbial products
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at excitation wavelengths greater than 250 nm and emission wavelengths less than 380 nm
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(Figure 1) in PLE1 and PLE2. The process of composting poultry litter involves elevated
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microbial activity and temperature, resulting in the breakdown of carbon sources, accompanied
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by the formation of humic-like fluorophores from protein-like molecular pools 52. Hence, the
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intensity of peaks corresponding to humic-like fluorescence is higher in PLE3 compared to those
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for PLE1 and PLE2. Similar changes in fluorescence signature have been reported in other
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composted organic matter 29. These fluorescence differences in poultry litter-derived DOM were
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further elucidated using EEM-PARAFAC.
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3.2 Global and Local PARAFAC Models
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Recent studies have demonstrated that fluorescence peaks in EEM datasets are a result of
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complex combinations of multiple fluorescent molecules 6, 25. These findings suggest that EEM-
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PARAFAC components are useful descriptors of fluorophores in DOM samples as these
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components facilitate deconvolution of the bulk fluorescence data. The excitation and emission
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patterns of the four components from the global EEM-PARAFAC model (Figure 2) were
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examined in the online OpenFluor 53 database and identified as microbial humic- 54, 55
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(Component 1 or C1), terrestrial humic- 56, 57 (Component 2 or C2), tyrosine- 18 (Component 3 or
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C3), and tryptophan-like 58 (Component 4 or C4) fluorophores, based on Tucker’s congruence
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coefficients greater than 0.97.
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Insert Figure 2
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The large spectral overlap (68 nm and 130 nm) in the excitation and emission loadings of C1 and
250
C2 is indicative of a complex DOM composition 3, 59; furthermore, the red shift of the
251
fluorophores is likely associated with higher aromaticity 60, 61. The sources of the fluorophores
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identified from the OpenFluor database closely matched those indicated by Coble’s peak-picking
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technique 62 and regional analysis descriptors 51 (see Table 2). The terrestrial humic-like
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component (C1) is one of the most frequently reported EEM-PARAFAC components in
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OpenFluor 53, particularly for surface water and wastewater. Previous studies 54, 55 have also
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reported the presence of the microbial humic-like fluorescence component (C2) in wastewater
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and marine environments, indicating that these fluorophores are autochthonous in nature. The
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C3 and C4 protein-like fluorophores are typically present at lower levels than humic substances
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in surface waters. For poultry manures, which exhibit a higher ratio of protein-like molecules to
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humic substances compared to surface waters, further description of the changes in the
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concentrations of these components during natural and engineered processes is important to fully
262
understand the fate of agricultural DOM.
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The differences in the fluorescence EEMs for the three DOM sources (Figure 1) suggest the
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presence of a variety of fluorophores. The relative abundance of each component in the
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untreated samples were similar for PLE1 and PLE2, but different for PLE3. For example, the
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relative abundance of humic-like C1 was about 30% in both PLE1 and PLE2, but much higher
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(44%) in PLE3. Similarly, C4 represented 43% and 50% of the total fluorescence intensity in 13 ACS Paragon Plus Environment
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untreated PLE1 and PLE2, but contributed only 27% of the total fluorescence for PLE3.
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Regardless of these differences, the local and global EEM-PARAFAC models exhibited a high
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degree of similarity (see Figure 2b-e). Furthermore, a comparison of the Fmax values for all
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components from the global model shows a high degree of correlation (R2 > 0.99) with
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components from the local models (see Figure S3 in the Supporting Information). For these
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reasons, the global model was used to analyze all experimental samples. Full excitation and
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emission loadings for the global fluorescence components are provided in Tables S1 and S2 of
275
the Supporting Information. The core consistency and explained variance of the global and local
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models are presented in Table S3 in the Supporting Information.
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3.3 Irradiation of Poultry Litter-Derived DOM
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EEMs showing the change in fluorescent DOM during irradiation are shown in Figure 3a-b for
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select treatment times. The complete suite of EEMs for irradiated PLE1, PLE2, and PLE3
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samples are shown in Figures S4 – S6 (see Supporting Information), respectively. For all PLE
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sources, irradiation at 253.7 nm and 310 – 410 nm resulted in an overall loss of fluorescence.
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The corresponding changes in DOC were less than 8% and 4% for the 253.7 and 310 – 410 nm
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treatments, respectively. The Fmax value was used to study the degradation of individual
284
fluorescence components. The degradation trends showed a rapid change for C1, C2, and C4
285
(Figure 4) in the first six hours of irradiation, corresponding to a fluence of 3.95×10-4 Ein/cm2 for
286
253.7 nm and 1.14×10-3 Ein/cm2 for 310 – 410 nm. For C3, the overall trend varied by
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wavelength; these trends are discussed in more detail below. The loss of fluorescence agrees
288
with previous studies of aquatic humic substances that have reported photobleaching (i.e., loss of
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UV absorbance) 63, 64. A similar loss in Fmax has also been reported for sunlight photolysis of
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Insert Figure 3
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Insert Figure 4
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The degradation kinetics varied with the light source due to wavelength-dependent absorbance
294
(Figure 2) and photoreactivity, as previously reported 21, 65. The reactivity trends encompassed
295
by the data in Figure 4 demonstrate that the fate of poultry litter DOM in natural systems (solar-
296
based irradiation) is markedly different than in treatment processes (irradiation with 253.7 nm).
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Although the higher photon flux at 310 – 410 nm partially accounts for the increased
298
degradation, a comparison of the Fmax loss for similar fluence at the two irradiation wavelengths
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highlights the role of the absorbance spectra of the fluorophores. For example, a fluence of
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1.19×10-3 Ein/cm2 at 253.7 nm results in 60.1% loss in Fmax for C1 in PLE3; the corresponding
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loss at 310 – 410 nm was greater (68.2%) due to the higher UV-A absorbance of C1. The
302
differences in characteristic absorbance spectra are also exhibited by the excitation loading of
303
C1: 0.125 at 253.7 nm and 0.208 at 315 nm (see Figure 2b). Hence, the excitation loading was
304
used to further examine the effects of irradiation on individual components. Degradation of C2
305
was similar at both irradiation wavelengths, reflecting the similar UV absorbance at 253.7 nm
306
and 310 – 410 nm (see Figure 2c). On the contrary, C4 absorbed more light at 253.7 nm (Figure
307
2e), resulting in faster degradation (see Figure 4g-h). The observations for C4 degradation at
308
310 – 410 nm are in agreement with previous literature suggesting that protein-like fluorophores
309
are less photolabile than humic acid-like molecules 21, 66.
310
Overall, the trends in the degradation of C1, C2, and C4 were similar for all three poultry litter
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sources. During irradiation, the component scores decreased quickly within the first six hours,
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nm, the Fmax values for C1, C2, and C4 in PLE1 were 40, 37, and 33%, respectively, of the initial
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values. C3 was an exception (see Figure 4e-f). The fluorescence signal associated with C3 was
315
fairly constant for PLE1 and PLE2 during irradiation at 253.7 nm, but increased for PLE3
316
initially, before plateauing near the levels observed for PLE1 and PLE2. PLE3 exhibited low
317
protein fluorescence prior to irradiation, suggesting that irradiation decreased the inherent
318
fluorescence quenching in the sample 67 (i.e., the loss of fluorescence of tryptophan due to the
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presence of tyrosine) 68 or generated fluorescent tyrosine-like species through unknown
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mechanisms due to photodegradation of other DOM molecules 69, 70. In sunlight photolysis, the
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Fmax for C3 increased for all three PLEs. These findings indicate that either the rate of C3
322
formation was greater for 310 – 410 nm or the rate of C3 degradation was faster at 253.7 nm.
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Due to the higher absorbance of C3 at 253.7 nm compared to 310 – 410 nm (Figure 2d), we
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attribute these trends to the higher rate of C3 photodegradation at 253.7 nm. Similar
325
wavelength-dependent photodegradation was reported by Phong and Hur 21 for a tryptophan-like
326
component.
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The photodegradation trends observed for C1-C4 at 253.7 nm and 310 – 410 nm are important in
328
understanding the fate of agricultural DOM. These findings suggest that the global EEM-
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PARAFAC model proposed above may be used to provide accurate estimates of the
330
photoreactivity of poultry litter-derived DOM in natural and engineered systems. Furthermore,
331
these trends may also extend to other organic contaminants present in agricultural waste.
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3.4 Oxidation of DOM from Poultry Litter
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The reactivity of DOM with several oxidants has been well documented in terms of bulk
334
parameters, such as DOC, SUVA254, and spectral slopes 71-73. In general, ozonation of DOM is a 16 ACS Paragon Plus Environment
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fast reaction that occurs at electron-rich groups 71 and generates smaller, more polar molecules 74.
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The ozone reaction rate constant with DOM is source dependent 75, indicating that standard
337
DOM surrogates cannot be used to predict the reactivity of DOM from wastewater or agricultural
338
sources. Liu et al. 76 reported the loss of UV254 and the formation of aldehydes for ozonated
339
surface waters and wastewaters. Furthermore, Li et al. 77 showed that changes in DOM
340
composition were directly associated with oxidant exposure (i.e., ∫[oxidant]dt) in advanced
341
oxidation processes. However, few studies 78 have described the degradation of EEM-
342
PARAFAC components as a function of ozone treatment.
343
Select fluorescence EEMs for ozone treatment of PLE3 are shown in Figure 3c; furthermore, the
344
EEMs for PLE1, PLE2, and PLE3 at all treatment levels are shown in Figures S4, S5, and S6,
345
respectively (see Supporting Information). Ozonation of the PLEs resulted in fluorescence loss
346
at relatively low specific ozone doses (i.e., < 100 mg O3 /g DOC). Minimal changes (i.e., less
347
than 3%) in DOC were observed for the ozone treatments. For most EEM-PARAFAC
348
components, an increase in O3 dose resulted in greater loss of fluorescence (see Figure 5). In
349
PLE1 and PLE2, the transformation of C4 was faster than that of C1, C2, and C3. This
350
observation corroborates previous studies reporting that ozone preferentially reacts with
351
molecules that have high electron density 79. For PLE1 and PLE2, C3 exhibited slow
352
degradation; furthermore, C3 levels in PLE3 increased slightly during ozone treatment,
353
indicating that while tyrosine degrades due to reaction with ozone 80 , the suite of molecules
354
demonstrating tyrosine-like fluorescence may behave differently.
355
Insert Figure 5
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356
Reaction of DOM with hydroxyl radicals generated by the UV-H2O2 system resulted in
357
significant fluorescence losses (see Figure 3d); however, changes in DOC concentration were
358
less than 3%. Previous literature has reported that UV-H2O2 process generates hydroxyl radicals
359
with an approximate yield of 1 mol HO• / mol H2O2 at 253.7 nm 81. Three H2O2 doses, namely
360
5, 25, and 50 mg/L, were employed in this study to study the effect of increasing HO• exposure.
361
The corresponding specific H2O2 doses (i.e., the mass of dosed H2O2 per mass of initial DOC)
362
are reported in the legend of Figure 6. Previous studies have shown that an increase in the H2O2
363
concentration results in greater transformation of organic molecules, although high H2O2
364
concentrations can result in HO• scavenging and no net benefit. For example, Adak et al. 36
365
showed that for a H2O2 dose of greater than 50 mg/L, no significant increase in transformation
366
was observed for the poultry feed additive, roxarsone.
367
Addition of H2O2 to the PLE resulted in an increase in the Fmax value for C3 prior to irradiation.
368
These observations may be associated with reaction of H2O2 with DOM or other dissolved
369
species to form C3-like fluorescent molecules. The impacts of UV-H2O2 treatment on
370
fluorescence in PLE1, PLE2, and PLE3 are shown for all three H2O2 doses after irradiation in
371
Figure S4 – S6 (see Supporting Information). For all poultry litter sources, the loss of
372
fluorescence at a fluence of 1.65×10-5 Ein/cm2 and an H2O2 dose of 50 mg/L (i.e., the highest
373
H2O2 dose and lowest irradiation time) was greater than the transformation at an H2O2 dose of 5
374
mg/L and fluence of 9.88×10-5 Ein/cm2 (i.e., the lowest H2O2 dose and highest irradiation time).
375
Accordingly, the overall loss of fluorescence was significantly lower for 253.7 nm irradiation
376
alone, even for a fluence that was two orders of magnitude greater. These observations highlight
377
the role of HO•-mediated reactions during transformation of DOM. Hydroxyl radicals are non-
378
selective oxidants with a high oxidation potential (2.7 eV) 82. Westerhoff et al. 71 found that the 18 ACS Paragon Plus Environment
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379
rate constant for reaction of DOM with HO• was dependent on molecular weight and
380
aromaticity. While a representative second-order rate constant for reaction of DOM with HO•
381
has been proposed 83, EEM-PARAFAC component-specific behavior has not been reported and
382
may be more representative, as it better encompasses the reactivity of different DOM
383
components.
384
For C1, C2, and C4, the transformation efficiency increased with H2O2 dose (Figure 6); however,
385
the extent of increase in efficiency varied between the components. For example, the
386
degradation of C4 over 90 minutes of irradiation was consistently high (> 88%) for all H2O2
387
doses and poultry litter sources. After 90 minutes of irradiation, the transformation of C1 and C2
388
ranged from 10 to 80%, depending on H2O2 dose and poultry litter source. The greater reactivity
389
of C4 compared to C1 and C2 is in agreement with previous studies reporting the degradation of
390
tryptophan- and humic-like components in hydroxyl radical-mediated photocatalysis 21. Like
391
irradiation with 253.7 nm in the absence of H2O2 (Figure 4e), the fluorescence intensity of C3
392
remained relatively stable throughout treatment regardless of the H2O2 dose, indicating that this
393
component was recalcitrant during UV-H2O2 advanced oxidation. The relative pseudo-stability
394
of this component is also noticeable in the full set of EEMs for the three poultry litter sources in
395
Figures S4 – S6 (see Supporting Information). For UV-H2O2 treatment (5 mg/L H2O2, 90
396
minutes of irradiation), the change in fluorescence associated with C1 was greatest for PLE3
397
(55%) and lowest for PLE1 (15%), suggesting that litter age, and the associated biochemical
398
processes, may influence the reactivity of the DOM matrix. Thus, the fluorescence signatures
399
associated with C1 in PLE1 and PLE3 may stem from similar fluorescent moieties present in
400
different molecular compositions, although no significant trends of component reactivity with
401
initial SUVA254 and E2/E3 were observed. 19 ACS Paragon Plus Environment
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Insert Figure 6
403
3.5 Environmental Significance
404
EEM-PARAFAC models provide a quantitative approach to study changes in fluorescent DOM
405
composition during natural and engineered processes. The global model developed here for
406
three poultry litter sources was found to be robust and suitable for analysis of the changes in four
407
fluorescence EEM-PARAFAC components during irradiation and oxidation. The excitation and
408
emission loadings of C1-C4 were used to identify the nature and source of fluorophores in
409
poultry litter. Here, we have validated an EEM-PARAFAC model for poultry litter-derived
410
DOM that satisfactorily describes the fluorescence patterns from three sources. Although the
411
number of litter sources used in this study is low, our model successfully captures the differences
412
in the fluorescent signatures associated with litter source, age, and treatment. The EEMs
413
highlight the similarity in DOM signatures originating from conventional and organic farms,
414
which may be associated with the dietary consistency for broilers and uniformity of waste
415
management practices. However, we note that poultry species and type (i.e., broiler, layer, etc.),
416
bedding material, environmental factors, climate, and waste management practices (i.e., active or
417
passive) may affect DOM composition; therefore, several factors affecting EEM-PARAFAC
418
components must be further evaluated to construct a more complete understanding of DOM
419
degradation in agricultural waste.
420
The EEM-PARAFAC model was successfully employed to identify changes in fluorescent DOM
421
during irradiation and oxidation processes relevant to four waste management strategies. These
422
results provide the first comparison of changes to fluorescence components in poultry litter-
423
derived DOM during abiotic transformation-based processes, and facilitate characterization of 20 ACS Paragon Plus Environment
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other animal manures using similar techniques. The results from this study indicate that
425
tryptophan-like protein fluorescence was fairly labile across the various treatments, whereas the
426
tyrosine-like fluorescence was recalcitrant for most treatments. As such, these two components
427
may be useful in benchmarking changes in DOM during treatment of agricultural waste,
428
although it should be noted that fluorescent DOM may not be representative of the total DOM 84.
429
While the UV-H2O2 system (at the highest H2O2 dose) performed best in this study, further
430
analysis is required to better understand the operating costs and energy demands of each system
431
for treatment of agricultural waste.
432
Our findings establish a groundwork for continued investigation into the fate of animal manure
433
fluorescence components during abiotic treatment. Additional studies should be performed to
434
comprehensively understand the fate of DOM in agricultural waste. Given the high nutrient
435
content in agricultural waste, specific changes in the dissolved organic nitrogen content are also
436
of interest; these measurements may provide additional insight to the protein-like fluorescence
437
components identified in this study. More specific identification of fluorescent DOM
438
components and better understanding of their reactivity in other treatment processes, including
439
composting, lagooning, and anaerobic digestion, will prove useful to continuing efforts to
440
manage agricultural waste and ensure environmental protection.
441
4. SUPPORTING INFORMATION
442
Analysis and validation of the EEM-PARAFAC model; representative EEMs for all treatments
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443
5. ACKNOWLEDGEMENTS
444
We thank four anonymous reviewers for their helpful suggestions. We gratefully acknowledge
445
funding from NSF CHE 1508090. This is contribution (xxxx, to be filled in after acceptance of
446
manuscript) of the University of Maryland Center for Environmental Science, Chesapeake
447
Biological Laboratory.
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6. REFERENCES
449
1.
450 451
Systems 1997, 38, (2), 149-171. 2.
452 453
3.
Murphy, K. R.; Stedmon, C. A.; Graeber, D.; Bro, R., Fluorescence spectroscopy and multi-way techniques. PARAFAC. Analytical Methods 2013, 5, (23), 6557-6566.
4.
456 457
Andersson, C. A.; Bro, R., The N-way Toolbox for MATLAB. Chemometrics and Intelligent Laboratory Systems 2000, 52, (1), 1-4.
454 455
Bro, R., PARAFAC. Tutorial and applications. Chemometrics and Intelligent Laboratory
Timko, S. A.; Gonsior, M.; Cooper, W. J., Influence of pH on fluorescent dissolved organic matter photo-degradation. Water Research 2015, 85, 266-274.
5.
Timko, S. A.; Romera-Castillo, C.; Jaffe, R.; Cooper, W. J., Photo-reactivity of natural
458
dissolved organic matter from fresh to marine waters in the Florida Everglades, USA.
459
Environmental Science: Process & Impacts 2014, 16, (4), 866-78.
460
6.
Yamashita, Y.; Jaffé, R.; Maie, N.; Tanoue, E., Assessing the dynamics of dissolved
461
organic matter (DOM) in coastal environments by excitation emission matrix fluorescence
462
and parallel factor analysis (EEM-PARAFAC). Limnology and Oceanography 2008, 53,
463
(5), 1900-1908.
464
7.
Murphy, K. R.; Stedmon, C. A.; Waite, T. D.; Ruiz, G. M., Distinguishing between
465
terrestrial and autochthonous organic matter sources in marine environments using
466
fluorescence spectroscopy. Marine Chemistry 2008, 108, (1), 40-58.
23 ACS Paragon Plus Environment
Environmental Science & Technology
467
8.
Page 24 of 43
Zhang, Y.; Yin, Y.; Feng, L.; Zhu, G.; Shi, Z.; Liu, X.; Zhang, Y., Characterizing
468
chromophoric dissolved organic matter in Lake Tianmuhu and its catchment basin using
469
excitation-emission matrix fluorescence and parallel factor analysis. Water Research 2011,
470
45, (16), 5110-5122.
471
9.
472 473
Yamashita, Y.; Tanoue, E., Production of bio-refractory fluorescent dissolved organic matter in the ocean interior. Nature Geoscience 2008, 1, (9), 579-582.
10.
Chen, M.; Price, R. M.; Yamashita, Y.; Jaffé, R., Comparative study of dissolved organic
474
matter from groundwater and surface water in the Florida coastal Everglades using multi-
475
dimensional spectrofluorometry combined with multivariate statistics. Applied
476
Geochemistry 2010, 25, (6), 872-880.
477
11.
Fellman, J. B.; D’Amore, D. V.; Hood, E.; Boone, R. D., Fluorescence characteristics and
478
biodegradability of dissolved organic matter in forest and wetland soils from coastal
479
temperate watersheds in southeast Alaska. Biogeochemistry 2008, 88, (2), 169-184.
480
12.
Banaitis, M. R.; Waldrip-Dail, H.; Diehl, M. S.; Holmes, B. C.; Hunt, J. F.; Lynch, R. P.;
481
Ohno, T., Investigating sorption-driven dissolved organic matter fractionation by
482
multidimensional fluorescence spectroscopy and PARAFAC. Journal of Colloid and
483
Interface Science 2006, 304, (1), 271-276.
484
13.
Santín, C.; Yamashita, Y.; Otero, X.; Alvarez, M.; Jaffé, R., Characterizing humic
485
substances from estuarine soils and sediments by excitation-emission matrix spectroscopy
486
and parallel factor analysis. Biogeochemistry 2009, 96, (1-3), 131-147.
24 ACS Paragon Plus Environment
Page 25 of 43
487
Environmental Science & Technology
14.
Mueller, K. K.; Fortin, C.; Campbell, P. G., Spatial variation in the optical properties of
488
dissolved organic matter (DOM) in lakes on the Canadian Precambrian shield and links to
489
watershed characteristics. Aquatic Geochemistry 2012, 18, (1), 21-44.
490
15.
Yamashita, Y.; Maie, N.; Briceño, H.; Jaffé, R., Optical characterization of dissolved
491
organic matter in tropical rivers of the Guayana Shield, Venezuela. Journal of Geophysical
492
Research: Biogeosciences 2010, 115, (G1).
493
16.
Jaffé, R.; Cawley, K. M.; Yamashita, Y., Applications of excitation emission matrix
494
fluorescence with parallel factor analysis (EEM-PARAFAC) in assessing environmental
495
dynamics of natural dissolved organic matter (DOM) in aquatic environments: A review. In
496
Advances in the physicochemical characterization of dissolved organic matter: Impact on
497
natural and engineered systems, Rosario-Ortiz, F., Ed. ACS Symposium Series, Americal
498
Chemical Society: Washington D.C., 2014; pp 27-73.
499
17.
Yang, L.; Hur, J.; Zhuang, W., Occurrence and behaviors of fluorescence EEM-PARAFAC
500
components in drinking water and wastewater treatment systems and their applications: A
501
review. Environmental Science and Pollution Research 2015, 22, (9), 6500-6510.
502
18.
Murphy, K. R.; Hambly, A.; Singh, S.; Henderson, R. K.; Baker, A.; Stuetz, R.; Khan, S. J.,
503
Organic Matter Fluorescence in Municipal Water Recycling Schemes: Toward a Unified
504
PARAFAC Model. Environmental Science & Technology 2011, 45, (7), 2909-2916.
505
19.
Sanchez, N. P.; Skeriotis, A. T.; Miller, C. M., Assessment of dissolved organic matter
506
fluorescence PARAFAC components before and after coagulation–filtration in a full scale
507
water treatment plant. Water Research 2013, 47, (4), 1679-1690.
25 ACS Paragon Plus Environment
Environmental Science & Technology
508
20.
Ishii, S. K.; Boyer, T. H., Behavior of reoccurring PARAFAC components in fluorescent
509
dissolved organic matter in natural and engineered systems: a critical review.
510
Environmental Science & Technology 2012, 46, (4), 2006-2017.
511
21.
Page 26 of 43
Phong, D. D.; Hur, J., Insight into photocatalytic degradation of dissolved organic matter in
512
UVA/TiO2 systems revealed by fluorescence EEM-PARAFAC. Water Research 2015, 87,
513
119-126.
514
22.
Jung, C.; Deng, Y.; Zhao, R.; Torrens, K., Chemical oxidation for mitigation of UV-
515
quenching substances (UVQS) from municipal landfill leachate: Fenton process versus
516
ozonation. Water Research 2016, 108, 260-270.
517
23.
Ballesteros, S. G.; Costante, M.; Vicente, R.; Mora, M.; Amat, A.; Arques, A.; Carlos, L.;
518
Einschlag, F. G., Humic-like substances from urban waste as auxiliaries for photo-Fenton
519
treatment: a fluorescence EEM-PARAFAC study. Photochemical & Photobiological
520
Sciences 2017, 16, (1), 38-45.
521
24.
Ye, Z.; Zhang, H.; Zhang, X.; Zhou, D., Treatment of landfill leachate using
522
electrochemically assisted UV/chlorine process: Effect of operating conditions, molecular
523
weight distribution and fluorescence EEM-PARAFAC analysis. Chemical Engineering
524
Journal 2016, 286, 508-516.
525
25.
Stedmon, C. A.; Markager, S., Resolving the variability in dissolved organic matter
526
fluorescence in a temperate estuary and its catchment using PARAFAC analysis.
527
Limnology and Oceanography 2005, 50, (2), 686-697.
26 ACS Paragon Plus Environment
Page 27 of 43
528
Environmental Science & Technology
26.
Williams, C. J.; Yamashita, Y.; Wilson, H. F.; Jaffé, R.; Xenopoulos, M. A., Unraveling
529
the role of land use and microbial activity in shaping dissolved organic matter
530
characteristics in stream ecosystems. Limnology and Oceanography 2010, 55, (3), 1159-
531
1171.
532
27.
Graeber, D.; Gelbrecht, J.; Pusch, M. T.; Anlanger, C.; von Schiller, D., Agriculture has
533
changed the amount and composition of dissolved organic matter in Central European
534
headwater streams. Science of the Total Environment 2012, 438, 435-446.
535
28.
Hunt, J. F.; Ohno, T., Characterization of fresh and decomposed dissolved organic matter
536
using excitation-emission matrix fluorescence spectroscopy and multiway analysis. Journal
537
of Agricultural and Food Chemistry 2007, 55, (6), 2121-2128.
538
29.
Yu, G.-H.; Luo, Y.-H.; Wu, M.-J.; Tang, Z.; Liu, D.-Y.; Yang, X.-M.; Shen, Q.-R.,
539
PARAFAC modeling of fluorescence excitation− emission spectra for rapid assessment of
540
compost maturity. Bioresource Technology 2010, 101, (21), 8244-8251.
541
30.
Guo, X.; He, X.; Zhang, H.; Deng, Y.; Chen, L.; Jiang, J., Characterization of dissolved
542
organic matter extracted from fermentation effluent of swine manure slurry using
543
spectroscopic techniques and parallel factor analysis (PARAFAC). Microchemical Journal
544
2012, 102, 115-122.
545 546
31.
2012 Census of Agriculture: Volume 1. Geographic Area Series. Part 51; AC-12-A-51; National Agricultural Statistics Service, USDA: Washington, D.C. , 2014.
27 ACS Paragon Plus Environment
Environmental Science & Technology
547
32.
Page 28 of 43
USDA Economic Research Service: Food availability (per capita) data system.
548
http://www.ers.usda.gov/data-products/food-availability-per-capita-data-system/ (Sep 01,
549
2016),
550
33.
551 552
Publications Ltd: London, 2003. 34. Risk management evaluation for concentrated animal feeding operations EPA/600/R-
553 554
04/042; National Risk Management Laboratory, US EPA: Cincinnati, 2004. 35.
555 556
Bruinsma, J., World Agriculture: Towards 2015/2030. An FAO perspective. Earthscan
Mangalgiri, K. P.; Adak, A.; Blaney, L., Organoarsenicals in poultry litter: Detection, fate, and toxicity. Environment International 2015, 75, 68-80.
36.
Adak, A.; Mangalgiri, K. P.; Lee, J.; Blaney, L., UV irradiation and UV-H2O2 advanced
557
oxidation of the roxarsone and nitarsone organoarsenicals. Water Research 2015, 70, 74-
558
85.
559
37.
Fu, Q.-L.; He, J.-Z.; Blaney, L.; Zhou, D.-M., Roxarsone binding to soil-derived dissolved
560
organic matter: Insights from multi-spectroscopic techniques. Chemosphere 2016, 155,
561
225-233.
562
38.
Wu, J. J.; Park, S.-h.; Hengemuehle, S. M.; Yokoyama, M. T.; Person, H. L.; Gerrish, J. B.;
563
Masten, S. J., The use of ozone to reduce the concentration of malodorous metabolites in
564
swine manure slurry. Journal of Agricultural Engineering Research 1999, 72, (4), 317-327.
28 ACS Paragon Plus Environment
Page 29 of 43
565
Environmental Science & Technology
39.
Macauley, J. J.; Qiang, Z.; Adams, C. D.; Surampalli, R.; Mormile, M. R., Disinfection of
566
swine wastewater using chlorine, ultraviolet light and ozone. Water Research 2006, 40,
567
(10), 2017-2026.
568
40.
Yetilmezsoy, K.; Sakar, S., Improvement of COD and color removal from UASB treated
569
poultry manure wastewater using Fenton's oxidation. Journal of Hazardous Materials
570
2008, 151, (2–3), 547-558.
571
41.
Bilotta, P.; Steinmetz, R. L. R.; Kunz, A.; Mores, R., Swine effluent post-treatment by
572
alkaline control and UV radiation combined for water reuse. Journal of Cleaner Production
573
2017, 140, (3), 1247-1254.
574
42.
575 576
Omer, A. R.; Walker, P. M., Treatment of swine slurry by an ozone treatment system to reduce odor. Journal of Environmental Protection 2011, 2, (7), 867-872.
43.
Shah, S.; Grabow, G.; Li, W. L.; Parsons, J. Poultry waste stockpiling methods:
577
Environmental impacts and their mitigation; AG-788W; North Carolina Cooperative
578
Extension: Raleigh, 2014.
579
44.
580 581
Szogi, A.; Vanotti, M.; Hunt, P., Phosphorus recovery from poultry litter. Transactions of the ASABE 2008, 51, (5), 1727-1734.
45.
Harris, G. D.; Dean Adams, V.; Moore, W. M.; Sorensen, D. L., Potassium ferrioxalate as
582
chemical actinometer in ultraviolet reactors. Journal of Environmental Engineering 1987,
583
113, (3), 612-627.
29 ACS Paragon Plus Environment
Environmental Science & Technology
584
46.
Royer, I.; Angers, D. A.; Chantigny, M. H.; Simard, R. R.; Cluis, D., Dissolved organic
585
carbon in runoff and tile-drain water under corn and forage fertilized with hog manure.
586
Journal of Environmental Quality 2007, 36, (3), 855-863.
587
47.
Page 30 of 43
Hopkins, Z. R.; Blaney, L., A novel approach to modeling the reaction kinetics of
588
tetracycline antibiotics with aqueous ozone. Science of the Total Environment 2014, 468–
589
469, 337-344.
590
48.
Clesceri, L. S.; Greenberg, A. E.; Trussell, R. R., Standard Methods for the Examination of
591
Water and Wastewater. 17 ed.; American Public Health Association, American Water
592
Works Association, Water Pollution Control Federation: Washington D.C., 1989.
593
49.
Helms, J. R.; Stubbins, A.; Ritchie, J. D.; Minor, E. C.; Kieber, D. J.; Mopper, K.,
594
Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and
595
photobleaching of chromophoric dissolved organic matter. Limnology and Oceanography
596
2008, 53, (3), 955-969.
597
50.
598 599
Guo, M.; Chorover, J., Transport and fractionation of dissolved organic matter in soil columns. Soil Science 2003, 168, (2), 108-118.
51.
Chen, W.; Westerhoff, P.; Leenheer, J. A.; Booksh, K., Fluorescence Excitation-Emission
600
Matrix Regional Integration to Quantify Spectra for Dissolved Organic Matter.
601
Environmental Science & Technology 2003, 37, (24), 5701-5710.
602 603
52.
Marhuenda-Egea, F.; Martínez-Sabater, E.; Jordá, J.; Moral, R.; Bustamante, M.; Paredes, C.; Pérez-Murcia, M., Dissolved organic matter fractions formed during composting of
30 ACS Paragon Plus Environment
Page 31 of 43
Environmental Science & Technology
604
winery and distillery residues: evaluation of the process by fluorescence excitation–
605
emission matrix. Chemosphere 2007, 68, (2), 301-309.
606
53.
Murphy, K. R.; Stedmon, C. A.; Wenig, P.; Bro, R., OpenFluor–an online spectral library
607
of auto-fluorescence by organic compounds in the environment. Analytical Methods 2014,
608
6, (3), 658-661.
609
54.
Cawley, K. M.; Butler, K. D.; Aiken, G. R.; Larsen, L. G.; Huntington, T. G.; McKnight,
610
D. M., Identifying fluorescent pulp mill effluent in the Gulf of Maine and its watershed.
611
Marine Pollution Bulletin 2012, 64, (8), 1678-1687.
612
55.
Catalá, T. S.; Reche, I.; Fuentes-Lema, A.; Romera-Castillo, C.; Nieto-Cid, M.; Ortega-
613
Retuerta, E.; Calvo, E.; Alvarez, M.; Marrasé, C.; Stedmon, C. A., Turnover time of
614
fluorescent dissolved organic matter in the dark global ocean. Nature Communications
615
2015, 6, 5986.
616
56.
Shutova, Y.; Baker, A.; Bridgeman, J.; Henderson, R. K., Spectroscopic characterisation of
617
dissolved organic matter changes in drinking water treatment: From PARAFAC analysis to
618
online monitoring wavelengths. Water Research 2014, 54, 159-169.
619
57.
Dainard, P. G.; Guéguen, C.; McDonald, N.; Williams, W. J., Photobleaching of
620
fluorescent dissolved organic matter in Beaufort Sea and North Atlantic Subtropical Gyre.
621
Marine Chemistry 2015, 177, 630-637.
622 623
58.
Murphy, K. R.; Bro, R.; Stedmon, C. A., Chemometric analysis of organic matter fluorescence. In Aquatic Organic Matter Fluorescence, Cambridge Environmental
31 ACS Paragon Plus Environment
Environmental Science & Technology
624
Chemistry Series, Coble, P.; Lead, J.; Baker, A.; Reynolds, D.; Spencer, R. G. M., Eds.
625
Cambridge University Press: Cambridge, 2014; pp 339-375.
626
59.
Page 32 of 43
Wei, J.; Han, L.; Song, J.; Chen, M., Evaluation of the interactions between water
627
extractable soil organic matter and metal cations (Cu (II), Eu (III)) using excitation-
628
emission matrix combined with parallel factor analysis. International Journal of Molecular
629
Sciences 2015, 16, (7), 14464-14476.
630
60.
Tang, S.; Wang, Z.; Wu, Z.; Zhou, Q., Role of dissolved organic matters (DOM) in
631
membrane fouling of membrane bioreactors for municipal wastewater treatment. Journal of
632
Hazardous Materials 2010, 178, (1), 377-384.
633
61.
634 635
organic matter fractions. Chemosphere 2003, 50, (5), 639-647. 62.
636 637
63.
642
Allard, B.; Boren, H.; Pettersson, C.; Zhang, G., Degradation of humic substances by UV irradiation. Environment International 1994, 20, (1), 97-101.
64.
640 641
Coble, P. G., Marine optical biogeochemistry: the chemistry of ocean color. Chemical Reviews 2007, 107, (2), 402-418.
638 639
Chen, J.; LeBoeuf, E. J.; Dai, S.; Gu, B., Fluorescence spectroscopic studies of natural
Backlund, P., Degradation of aquatic humic material by ultraviolet light. Chemosphere 1992, 25, (12), 1869-1878.
65.
Del Vecchio, R.; Blough, N. V., On the origin of the optical properties of humic substances. Environmental Science & Technology 2004, 38, (14), 3885-3891.
32 ACS Paragon Plus Environment
Page 33 of 43
643
Environmental Science & Technology
66.
Hur, J.; Jung, K.-Y.; Jung, Y. M., Characterization of spectral responses of humic
644
substances upon UV irradiation using two-dimensional correlation spectroscopy. Water
645
Research 2011, 45, (9), 2965-2974.
646
67.
Wang, Z.; Cao, J.; Meng, F., Interactions between protein-like and humic-like components
647
in dissolved organic matter revealed by fluorescence quenching. Water Research 2015, 68,
648
404-413.
649
68.
Aiken, G., Fluorescence and dissolved organic matter: A chemist's perspective. In Aquatic
650
Organic Matter Fluorescence, Coble, P. G.; Lead, J.; Baker, A.; Reynolds, D. M.; Spencer,
651
R. G. M., Eds. Cambridge University Press: New York, 2014.
652
69.
McEnroe, N. A.; Williams, C. J.; Xenopoulos, M. A.; Porcal, P.; Frost, P. C., Distinct
653
optical chemistry of dissolved organic matter in urban pond ecosystems. PLOS ONE 2013,
654
8, (11), e80334.
655
70.
Zhang, Y.; Liu, X.; Osburn, C. L.; Wang, M.; Qin, B.; Zhou, Y., Photobleaching response
656
of different sources of chromophoric dissolved organic matter exposed to natural solar
657
radiation using absorption and excitation–emission matrix spectra. PLOS ONE 2013, 8,
658
(10), e77515.
659
71.
Westerhoff, P.; Aiken, G.; Amy, G.; Debroux, J., Relationships between the structure of
660
natural organic matter and its reactivity towards molecular ozone and hydroxyl radicals.
661
Water Research 1999, 33, (10), 2265-2276.
33 ACS Paragon Plus Environment
Environmental Science & Technology
662
72. Nöthe, T.; Fahlenkamp, H.; Sonntag, C. v., Ozonation of wastewater: rate of ozone
663
consumption and hydroxyl radical yield. Environmental Science & Technology 2009, 43,
664
(15), 5990-5995.
665
Page 34 of 43
73.
Wenk, J.; Aeschbacher, M.; Salhi, E.; Canonica, S.; Von Gunten, U.; Sander, M., Chemical
666
oxidation of dissolved organic matter by chlorine dioxide, chlorine, and ozone: effects on
667
its optical and antioxidant properties. Environmental Science & Technology 2013, 47, (19),
668
11147-11156.
669
74.
670 671
organic matter (NOM) structure. Ozone: Science & Engineering 1999, 21, (6), 551-570. 75.
672 673
Westerhoff, P.; Debroux, J.; Aiken, G.; Amy, G., Ozone-induced changes in natural
Gottschalk, C.; Libra, J. A.; Saupe, A., Ozonation of water and waste water: A practical guide to understanding ozone and its applications. John Wiley & Sons: Hoboken, 2009.
76.
Liu, C.; Tang, X.; Kim, J.; Korshin, G. V., Formation of aldehydes and carboxylic acids in
674
ozonated surface water and wastewater: a clear relationship with fluorescence changes.
675
Chemosphere 2015, 125, 182-190.
676
77.
Li, W.; Nanaboina, V.; Zhou, Q.; Korshin, G. V., Effects of Fenton treatment on the
677
properties of effluent organic matter and their relationships with the degradation of
678
pharmaceuticals and personal care products. Water Research 2012, 46, (2), 403-412.
679
78.
Liu, C.; Li, P.; Tang, X.; Korshin, G. V., Ozonation effects on emerging micropollutants
680
and effluent organic matter in wastewater: characterization using changes of three-
681
dimensional HP-SEC and EEM fluorescence data. Environmental Science and Pollution
682
Research 2016, 23, (20), 20567-20579. 34 ACS Paragon Plus Environment
Page 35 of 43
683
Environmental Science & Technology
79.
684 685
Von Sonntag, C.; Von Gunten, U., Chemistry of ozone in water and wastewater treatment. IWA publishing: London, 2012.
80.
Pryor, W. A.; Giamalva, D. H.; Church, D. F., Kinetics of ozonation. 2. Amino acids and
686
model compounds in water and comparisons to rates in nonpolar solvents. Journal of the
687
American Chemical Society 1984, 106, (23), 7094-7100.
688
81.
689 690
Baxendale, J.; Wilson, J., The photolysis of hydrogen peroxide at high light intensities. Transactions of the Faraday Society 1957, 53, 344-356.
82.
Kommineni, S.; Zoeckler, J.; Stocking, A.; Liang, P. S.; Flores, A.; Rodriguez, R.; Browne,
691
T.; Roberts, P. R.; Brown, A. Advanced oxidation processes; NWRI-99-06; National Water
692
Research Institute: Fountain Valley, 2000.
693
83.
Appiani, E.; Page, S. E.; McNeill, K., On the use of hydroxyl radical kinetics to assess the
694
number-average molecular weight of dissolved organic matter. Environmental Science &
695
Technology 2014, 48, (20), 11794-11802.
696
84.
Rosario-Ortiz, F. L.; Korak, J. A., Oversimplification of Dissolved Organic Matter
697
Fluorescence Analysis: Potential Pitfalls of Current Methods. Environmental Science &
698
Technology 2017, 51, (2), 759-761.
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Environmental Science & Technology
699 700
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Table 1. Physicochemical characteristics of poultry litter samples and extracts. Data are reported as mean ± 95% confidence interval (n = 3). PL1
PL2
PL3
Farm type
Conventional, commercial
Organic, commercial
Organic, commercial
Litter age a
0-3
0-6
>12
Water content (% H2O) of
31.5 ± 0.4
45.7 ± 1.1
19.1 ± 1.5
TOC (% C) of poultry litter
31.8 ± 1.1
32.6 ± 0.6
29.3 ± 0.5
DOC of stock-PLE (g C/L)
1.9 ± 0.3
3.3 ± 0.1
4.2 ± 0.1
SUVA254 of PLE (L/(mg C m)) b
2.30 ± 0.40
1.10 ± 0.01
1.20 ± 0.04
E2/E3 of PLE c
6.2 ± 1.2
3.8 ± 1.3
5.3 ± 0.2
Spectral slope (S275-295) of PLE d
0.9 (± 0.1)×10-2
1.4 (±0.1)×10-2
1.2 (± 0.3)×10-2
Relative abundance (%) of C1 in untreated PLE
30.2
30.1
44.4
Relative abundance (%) of C2 in untreated PLE
20.9
15.4
28.8
Relative abundance (%) of C3 in untreated PLE
5.4
4.3
0.2
poultry litter
701 702 703 704
43.4 50.2 26.5 Relative abundance (%) of C4 in untreated PLE a approximate time that litter has been piled at the poultry farm b defined as the UV absorbance of sample at 254 nm normalized to DOC c determined as at the ratio of UV absorbance at 250 nm to that of 365 nm d calculated for the UV range of 275 – 295 nm
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Table 2.
a
Description of components in the global EEM-PARAFAC model for DOM extracted from poultry litter.
Component
Exmax (nm) a
Emmax (nm) b
Source from OpenFluor database 53
C1
240 (310) c
405
Microbial humic-like
C2
240 (365) c
470
Terrestrial humic-like
C3 C4
250 270
300 333
Tyrosine-like Tryptophan-like
Description from Chen et al. Soluble microbial product-like Humic acid-like Soluble microbial product-like Humic acid-like Fulvic acid-like Tyrosine-, protein-like Tryptophan-, protein-like Fulvic acid-like
51
Fluorescence peak association from Coble 62 (Exmax/Emmax) (nm/nm) M (300/390) A (260/450), C (340/440) B (270/306) T (270/340)
Maximum excitation wavelength Maximum emission wavelength c Secondary fluorescence peaks in parentheses b
706
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707 708 709 710
Figure 1. (a-c) Fluorescence EEMs and (d) UV-visible absorbance spectra for untreated PLEs (1000× dilution). The DOC concentrations for the PLE1, PLE2, and PLE3 data shown here were 1.87, 3.31, and 4.17 mg C/L, respectively.
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Figure 2. (a) Fluorescence fingerprints of the four components in the global EEM-PARAFAC model; (b-e) excitation (Ex, dashed line) and emission (Em, dashed and dotted lines) spectra for all four components in the global (black) and local models for PLE1 (blue), PLE2 (red), and PLE3 (green). The legend in (d) also applies to (b), (c), and (e). Note that the similarity of spectra from the global and local models reinforces the suitability of the global model.
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716 717 718 719 720 721 722 723
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Figure 3. Fluorescence EEMs for treated PLE3 for (row a) irradiation with 253.7 nm, (row b) photolysis at 310-410 nm, (row c) ozonation, and (row d) advanced oxidation by UV-H2O2. This figure shows the initial, first, and final samples for each treatment type. Full EEM datasets for treated PLE1 (Figure S4), treated PLE2 (Figure S5), and treated PLE3 (Figure S6) can be found in the Supporting Information.
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Figure 4. Loss of fluorescence for all components (rows a-d) for irradiation of the treated PLEs at 253.7 nm (solid symbols, left column) and 310 – 410 nm (open symbols, right column).
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728 729 730 731
Figure 5. Change in Fmax of C1, C2, C3, and C4 during ozonation for (a) PLE1, (b) PLE2, and (c) PLE3 as a function of the specific ozone dose (mg O3 added / g of initial DOC).
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732 733 734 735 736 737
Figure 6. Change in fluorescence intensity of Components 1 - 4 for all three DOM sources during UV-H2O2 treatment as a function of irradiation time and the specific H2O2 dose (corresponding to H2O2 concentrations of 5, 25, and 50 mg/L). Individual plots are shown for (a) C1 in PLE1, (b) C2 in PLE1, (c) C3 in PLE1, (d) C4 in PLE 1, (e) C1 in PLE2, (f) C2 in PLE2, (g) C3 in PLE2, (h) C4 in PLE2, (i) C1 in PLE3, (j) C2 in PLE3, (k) C3 in PLE3, and (l) C4 in PLE3. The legends in (d), (h), and (l) correspond to PLE1, PLE2, and PLE3 measurements, respectively. 43 ACS Paragon Plus Environment