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Characterization of Natural and Affected Environments
Land Use Controls on the Spatial Variability of Dissolved Black Carbon in a Subtropical Watershed Jesse Alan Roebuck, Michael Seidel, Thorsten Dittmar, and Rudolf Jaffe Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00190 • Publication Date (Web): 25 Jun 2018 Downloaded from http://pubs.acs.org on June 26, 2018
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Environmental Science & Technology
Land Use Controls on the Spatial Variability of Dissolved Black Carbon in a Subtropical Watershed J. Alan Roebuck, Jr.1, Michael Seidel2, Thorsten Dittmar2, Rudolf Jaffé*1 1
Southeast Environmental Research Center and Department of Chemistry and Biochemistry, Florida International University, Miami, FL 33179 2
Research Group for Marine Geochemistry, Institute for Chemistry and Biology of the Marine Environment (ICBM), University of Oldenburg, D-26129 Oldenburg, Germany
Correspondence author: Rudolf Jaffé e-mail:
[email protected] phone: 305-348-2456
Abstract
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Rivers export roughly 250 Pg of dissolved organic carbon (DOC) to coastal oceans. DOC
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exported from rivers can be a reflection of watershed dynamics, and changes in land use can lead
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to shifts in the molecular composition and reactivity of riverine DOC. About 10% of DOC
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exported from rivers is dissolved black carbon (DBC), a collection of polycondensed aromatic
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compounds derived from the incomplete combustion of biomass and fossil fuels. While DOC
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and DBC export are generally coupled, the effects of watershed land use on DBC quality are not
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well understood. In this study, DBC samples were collected throughout the Altamaha River
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watershed in Georgia, USA. DBC was characterized using the benzenepolycarboxylic acid
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method and Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS). DBC
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had a more polycondensed character in areas of the watershed with less anthropogenic
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disturbance. Furthermore, FTICR-MS revealed that DBC became enriched with a lower
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molecular weight, heteroatomic signature in response to higher anthropogenic activity. As global
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land cover continues to change, this study demonstrates on a localized scale that watershed land
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use can influence the export and composition of DBC, which may have further implications for
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global carbon and nutrient cycling.
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1. Introduction
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Pyrogenic carbon (PyC) is a carbonaceous residue of thermogenically altered organic
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compounds formed through incomplete combustion of biomass and from anthropogenic
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activities, such as fossil fuel combustion1. PyC is comprised of a heterogeneic collection of
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organic compounds ranging across a combustion continuum from small anhydrosugars formed at
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low temperatures (< 300°C) to highly condensed polycyclic aromatic compounds formed under
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higher temperature combustion conditions2-3, which is generally referred to as black carbon
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(BC)4. In comparison to bulk organic matter (OM), the highly condensed fraction of the BC
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spectrum is considered to be relatively recalcitrant and resistant to biological degradation5. Thus,
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BC is ubiquitous throughout both terrestrial and marine environments. However, while a
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majority of BC becomes incorporated and stored in soils and sediments over millennial time
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scales, a portion of this material can be mobilized and transported throughout the aquatic
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environment as dissolved BC (DBC)6-8. Each year, rivers export an average of 27 Tg DBC
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globally, which equates to about 10% of the total riverine dissolved organic carbon (DOC) flux,
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making rivers an important means for transport and biogeochemical cycling of DBC9.
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Rivers are intrinsically connected with the terrestrial environment and thus, the DOC and
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subsequent DBC exported from fluvial systems can be strongly reflective of watershed dynamics
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and the anthropogenic activities from within10. For instance, the majority of dissolved organic
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matter (DOM) exported from small headwater streams will be most reflective of local
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allochthonous inputs and may undergo further bio- and photo-chemical transformations during
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downstream transport11-13. However, elevated nutrient inputs from agricultural activity and
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heightened urbanization throughout a watershed have been directly linked to shifts in DOM
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quality and bioavailability leading to shifts in molecular composition that is more nitrogen rich
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and reflective of autochthonous in-stream activity14-16. Similar transformations are also observed
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for combustion derived material in which pyrogenic DOM exported to coastal oceans from
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agriculturally influenced watersheds is enriched in nitrogen functionality17.
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Contrary to bulk DOC, however, direct relationships between DBC export and
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composition with changes in watershed land use have yet to be determined. With charcoal and
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aerosols from wildfires being the most significant source of BC to the environment7, 18,
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watersheds with a high degree of burn activity in forested areas would be expected to yield
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higher exports of DBC. While some studies have suggested there is no direct correlation between
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watershed short-term fire history and DBC export19-20, watersheds will continue to export DBC
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even decades after a major burn event21. Furthermore, loss of natural landscapes as a result of
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increasing anthropogenic activity may result in fewer exchangeable BC reservoirs and thus, a
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decrease in the amount of DBC available to be mobilized in streams. However, literature reports
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also suggest an increase in DBC export due to the addition of biochars as soil amendments in
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agricultural areas22. With more than 40% of earth’s landmass now developed for agricultural
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purposes and with an ever-increasing urbanization to accommodate long term population
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growth23, a better understanding of changing DBC dynamics with respect to catchment land use
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and its effects on long term carbon cycling and river quality is of increasing importance.
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While numerous studies have assessed the influence of catchment land use on bulk DOC
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properties and export24-27, only little information is available on the effects on land use with
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respect to DBC10, 17, 22. This study aims to address this knowledge gap by characterizing DBC on
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a watershed scale and assessing shifts in DBC quality with respect to catchment land use by
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applying a combination of analytical methods. While no single method has been developed to
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quantitatively estimate all PyC constituents produced during combustion, the
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benzenepolycarboxylic acid (BPCA) method has provided successful quantitative and qualitative
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characterization of compositional information with respect to the highly condensed fraction of
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the PyC spectrum28. In addition, ultrahigh-resolution mass spectrometry techniques, in particular
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Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) has also been
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successfully used for the characterization of complex DOM mixtures, including DBC29, as it is
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capable of resolving thousands of individual molecular masses to which molecular formula are
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assigned30-31. These molecular formulae are mostly represented as compounds with carbon,
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hydrogen, and oxygen (C, H, & O) with some containing heteroatomic functionalities (nitrogen,
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N; sulfur, S, & phosphorus, P), and they can be further categorized into compound groups which
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best describe their degree of saturation, oxidation and aromaticity by using a modified
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aromaticity index (AImod)32-33.
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Together, we used the quantitative BPCA method along with the molecular
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characterization via FTICR-MS to characterize DBC throughout the Altamaha River, a large
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subtropical watershed located within the state of Georgia, southeastern USA. This watershed is
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characterized by varying degrees of natural land use, urbanization (Atlanta Metropolitan Area),
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and agriculture consisting mainly of poultry, beef, soy and hay production34. Because soil BC
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source and formation temperature influence DBC composition35, we hypothesized that DBC
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exported from natural landscapes would exhibit a more polycondensed signature that is most
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typically reflective of natural wildfire derived PyC. This is in contrast to anthropogenically
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impacted regions, where agricultural management practices result in lower temperature burns,
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and where the leachable fractions of sooty particles characteristic of urban dusts are depleted in
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highly condensed aromatic moieties36-37. DBC concentrations from the headwaters to river mouth
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were further assessed with regards to conservative mixing, in an effort to establish potential
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source variability in concert with changes in land cover. Additionally, in concurrence with
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Wagner et al.17, we hypothesized that the shifts in watershed land use may alter the molecular
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level DBC signature through incorporation of heteroatomic functionalities.
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2. Methods
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2.1 Site Description
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The Altamaha River is located entirely within the state of Georgia, USA draining ca.
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36,000 km2 (~25%) of the Georgian land mass, making it one of the largest drainage basins in
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the Eastern United States (Figure S1). Its two largest tributaries, the Ocmulgee River and Oconee
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River, each have their source in the Georgia Piedmonts and converge in the Southern Coastal
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Plains near Lumber City to form the Altamaha River. Together, these two tributaries contribute
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about 75% of the total water flow from the Altamaha River to the Atlantic Ocean. The Altamaha
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River exhibits an average water discharge of 400 m3/s and has an annual maximum in the early
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spring.
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Although the Altamaha River remains relatively undisturbed in comparison to other
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watersheds along the eastern seaboard, it was listed as an endangered river38 as increasing
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anthropogenic activities within the watershed are expected to contribute to augmenting
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eutrophication within its estuary. In a thirty-year period from 1970 to 2000, population doubled
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within the watershed from ca. 1.2 million to ca. 2.5 million people39. The most notable increase
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was within the Georgia Piedmont region, which was primarily due to the Atlanta Metropolitan
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Area and other urban developments, an arrangement counter to general patterns in which
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population densities are highest in coastal regions39. The Altamaha River drains a large portion
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of the urban Atlanta area and its suburbs primarily by means of the Ocmulgee River tributary,
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although a much smaller fraction is also drained within the Oconee River tributary. Agricultural
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land use is highest in the upper Altamaha River watershed and generally declines throughout the
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watershed. Primary agricultural activities throughout the watershed include poultry, beef, soy,
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and hay production34. The lower watershed consists primarily of natural forested areas and
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pristine wetlands with a much lower degree of anthropogenic activity.
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2.2 Sample Collection
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A total of 42 samples were collected primarily along the Oconee River tributary within
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the Altamaha River watershed. With an effort to avoid potential hydrological variations within
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this system, sampling occurred over a short four-day period between May 23, 2016 and May 27
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2016 (Figure S1) for this large watershed-scale study. Samples were also collected at the mouth
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of each of the other three main tributaries (Figure S1). These sites were selectively chosen to
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represent a wide array land use types throughout a gradient of small streams in the upper
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headwaters to larger rivers downstream. Of 42 sample locations, 19 were at USGS monitoring
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stations in which water discharge data was also collected. When possible, 1 L samples were
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collected from the riverbank directly into clean high-density polyethylene (HDPE) bottles.
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Bottles were pre-treated by soaking subsequently in 2 M HCl and 2 M NaOH each for 24 hours
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followed by rinsing with ultrapure water. Bottles were rinsed 3 times with sample water before
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final collection. Otherwise, samples were collected by dispensing a 5-gallon bucket over a bridge
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followed by transfer of water to clean HDPE bottles. The collection bucket was pre-rinsed at
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least three times with river water prior to each collection. Samples were stored on ice during
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transport back to the laboratory. Samples were filtered on the same day of collection (generally
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within 12 hours or less) through a 0.7 µm pre-combusted (500 ˚C, 5.5 hours) Whatman glass
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fiber filter (GFF). DOC was analyzed on filtered river samples using a Shimadzu TOC-V CSH
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total organic carbon analyzer upon acidification and purging to remove inorganic carbon. Quality
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control was monitored with TOC standards from ERA (Demand, WasteWarR, Lot#516, ERA)
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with recoveries of 100.3% of the certified value.
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DOC was extracted from river samples using a solid phase extraction technique
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previously described by Dittmar et al.40. Briefly, Agilent Bond Elut PPL cartridges (1 g) were
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conditioned consecutively with methanol and acidified ultrapure water (HCl , pH 2). The
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samples (~1L) were then gravity fed into the cartridge followed by rinsing again with acidified
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ultrapure water and drying under a stream of nitrogen gas. Samples were then eluted from the
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cartridge in methanol and stored at -20 ˚C until DBC and molecular analysis. The PPL extraction
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efficiency for this sample set was 73 ± 8%.
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2.3 Dissolved Black Carbon Analysis
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Quantification of DBC was carried out only on the 19 samples collected at USGS
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monitoring stations using the benzenepolycarboxylic (BPCA) method described by Dittmar28, in
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which the higher temperature polycondensed fraction of the pyrogenic carbon pool is defined
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based on the distribution of quantifiable molecular tracers after thermo-chemical oxidation of
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condensed aromatic units. For each sample, in triplicate, aliquots of methanol eluent containing
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ca. 0.2 mg DOC were dried under a stream of nitrogen gas in pre-combusted (500 ˚C for 5.5
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hours) glass ampoules. The dried samples were re-dissolved in 0.5 mL concentrated nitric acid
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and flame sealed within the glass ampoules. Samples were thermo-chemically oxidized at 160 ˚C
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for 6 hours with remaining nitric acid removed by a stream of nitrogen gas19.
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Thermo-chemical oxidation of DBC generates a collection tri-, tetra-, penta-, and hexa-
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substituted BPCAs (B3CA, B4CA, B5CA, and B6CA) whose relative abundance are related to
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the degree of DBC polycondensation41. The newly generated BPCAs were re-dissolved in
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mobile phase buffer A (4 mM tert-butyl ammonium bromide, 50 mM sodium acetate, 10%
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methanol). High performance liquid chromatography, coupled with a photodiode array detection
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(Surveyor, Thermo Scientific), was used to separate and quantify individual BPCAs. Separation
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was carried out on a Sunfire C18 reverse phase column (3.1 µm, 2.1 x 150 mm, Waters
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Corporation) using an elution gradient consisting of mobile phase buffer A, and mobile phase
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buffer B (100% methanol). Complete separation conditions are described by Dittmar28.
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Quantification of DBC was achieved based on individual BPCA concentrations using a
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conversion factor reported by Dittmar28. The average coefficient of variation for all triplicate
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analyses was less than 5%.
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2.4 Ultrahigh Resolution Mass Spectrometry
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The DOM methanol extracts for all 42 samples were diluted to a DOC concentration of
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ca.5 mg C/L in a methanol water mixture of 1:1 (v/v). The samples were analyzed as described
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in Seidel et al.42 with ultrahigh-resolution mass spectrometry using a solariX XR FTICR-MS
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(Bruker Daltonik GmbH, Bremen, Germany) connected to a 15 Tesla superconducting magnet.
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The diluted extracts were infused at a rate of 2 µL/min into the electrospray source (ESI; Apollo
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II ion source, Bruker Daltonik GmbH, Bremen, Germany) with the capillary voltage set to 4 kV
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in negative mode. 200 scans were accumulated in a mass window from 150 to 2000 Da and
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molecular formulae were assigned with the following restrictions: 12C1-1301H1-200O1-50 14N0-4S0-
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2P0-1
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to masses above the method detection limit after Riedel and Dittmar43. The employment of electrospray ionization in negative mode primarily ionizes polar
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constituents. While it is well understood there that there may be preferential ionization of various
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compound classes/functional groups that may limit the true representation of signal intensities to
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actual concentrations within the DOM pool, linearity of signal intensity among a series of
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dilutions has demonstrated the semi-quantitative character of FTICR-MS44. Reproducibility was
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tested by running replicate measurements of samples, by control measurements of procedural
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blanks and an in-house standard (SPE-DOM from ‘‘North Equatorial Pacific Intermediate
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Water’’) which was run regularly in between samples to control for instrument variability of the
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FT-ICR-MS44-45. Molecular masses that were detected in less than three samples were removed
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prior to further analysis. The samples were normalized to the sum of FTICR-MS signal
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intensities. The modified aromaticity index (AImod)32-33 and intensity-weighted molar ratios were
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calculated for each sample. Condensed aromatic compounds were operationally defined by an
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AImod ≥ 0.67 and having greater than or equal to 14 carbon atoms32-33. The elemental
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compositions of these compounds were represented by CHO, CHON, CHOS, CHOP, CHONS,
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CHONP, and CHOSP. Because the total number of CHOP, CHONS, CHONP and CHOSP
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represented on average less than 3% of the detected condensed aromatic molecular formulae, we
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limit this study to only include compounds categorized as CHO, CHON, or CHOS.
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2.5 Statistical Analysis
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A geographical information systems (GIS) IMG data file containing Georgia land cover
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information from the year 2008 was obtained from Georgia GIS Data Clearinghouse, initially
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provided by the National Resources Spatial Analysis Laboratory, University of Georgia. ArcMap
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version 10.3 was used to calculate land cover contributions and drainage area for each sampling
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location. The initial 13 different land cover types for this dataset were condensed to four for this
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study, which include the following: forested area, wetlands, agriculture, and urban land use
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(Figure S1). Land use at each site was calculated as a function of the entire upstream catchment
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area respective to each sampling location. Percent urban land use was log-transformed to achieve
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a normal distribution.
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Statistical analyses were performed using JMP version 12.0. The overall significance of a
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relationship between any two parameters was determined through linear correlations using
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Pearson’s product-moment correlation coefficient (r). Positive “r” values indicate a direct
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correlation whereas a negative “r” value indicates an inverse correlation. Correlations are
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considered significant for p < 0.05, but are also further highlighted when p < 0.01. Hierarchical
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Cluster Analysis was performed on the percent-normalized BPCA concentrations with Ward’s
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method by using the squared Euclidean distance to determine similarity in BPCA distribution
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among sampled rivers. Principal Component Analyses (PCA) were performed on the percent-
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normalized BPCA concentrations and on the mean centered normalized peak intensities for all
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identified DBC formula detected throughout the Altamaha River, respectively.
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3. Results and Discussion
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3.1 DBC Fluxes and Conservative Mixing along the Altamaha River Continuum
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DBC was measured at 19 active USGS monitoring stations throughout the Altamaha
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River watershed, primarily within the Oconee River sub-basin (Figure S1, Table S1). DBC
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concentrations varied significantly along the Altamaha River continuum ranging from 0.1 ppm
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up to 5.0 ppm with concentrations more than an order of magnitude higher in the lower
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watershed compared to the upper headwaters (Figure 1a). A BPCA ratio, defined as the relative
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proportion of B6CA and B5CA to B3CA and B4CA (section 2.3), was used to assess the
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composition of DBC where a higher ratio implies more polycondensed DBC35, 46. BPCA ratios
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ranged from < 0.2 to 1.3 while increasing along the river continuum (Figure 1b) suggesting a
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more polycondensed DBC signature in the lower watershed. Water discharge increased
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downstream, ranging from < 0.1 m3/s to 221 m3/s (Table S2), and was coupled with an increase
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in DBC flux, which ranged from < 1 mg/s to 48,000 mg/s (Table S2). However, two exceptions
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to this general downstream pattern are observed from within the Little Ocmulgee River and
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Ohoopee River (Figure S1), which are the two smaller sub-basins of the Altamaha River.
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Concurrent to their smaller drainage area are lower water discharges, which in turn lead to lower
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DBC fluxes when compared to the larger Oconee River sub-basin (Table S2). Nevertheless, the
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general increase in DBC fluxes along the river continuum coupled with the increasing BPCA
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ratios may suggest either of two possibilities. Regarding concentration, (a) there are considerable
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source changes throughout the Altamaha River watershed that may influence downstream export
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of DBC, and/or (b) that DBC is most strongly associated with the more refractory pool of DOC
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that has survived upstream mineralization processes and is becoming enriched downstream. With
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regards to composition (i.e. BPCA ratio change), (a) sources in the upper watershed might be
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more strongly influenced by urban DBC sources such as fossil fuels37, and/or (b) the less
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polycondensed fraction of the DBC is more reactive and selectively removed along the river
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continuum47.
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To further assess potential sources of DBC throughout the Altamaha River watershed, a
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DBC conservative mixing model was developed for the Altamaha River with slight modification
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from Marques et al.10 and DBC fluxes were compared with those expected from conservative
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mixing behavior (Figure 1c, 1d). We note this model was developed in part with extrapolated
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DBC and discharge data, as detailed in the Supporting Information, and is thus limited with
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respect to the assumption of linearity and the consistency of strong relationships between DBC
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and DOC as well as between discharge and drainage area. As presented in Figure 1c and 1d,
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DBC fluxes were generally consistent with conservative estimates suggesting that higher DBC
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concentrations (Figure 1a) observed in the mid-lower reaches of the Altamaha River compared to
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those upstream may result through conservative accumulation of DBC downstream as suggested
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above. This coupled with higher BPCA ratios (Figure 1b) might imply downstream source
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related shifts, where DBC with higher BPCA ratios accumulated downstream is enriched in
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wildfire derived DBC, compared to the DBC derived from fossil fuel combustion that may be
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expected from the highly populated urban areas upstream35, 37. This hypothesis is discussed in
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further detail in the next section. When comparing to other watersheds, the conservative behavior
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of DBC in the Altamaha River highlights the importance of unique watershed dynamics in
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transporting DBC from upper headwaters to coastal areas. For instance, in a similar study,
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Marques et al.10 attributed upstream sources of DBC in the Paraíba Do Sul River, Brazil, to old
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slash and burn practices in the region followed by a downstream sink of DBC due to
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photodegradation (as noted by shifts in BPCA distribution patterns). In comparison, the
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increasing BPCA ratios in the lower reaches of the Altamaha River watershed are concurrent to
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increasing downstream turbidity48 suggesting that photodegradation is not a substantial
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downstream sink for DBC in this system. Nonetheless, source related shifts in DBC accumulated
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in the downstream areas, as evident based on the higher BPCA ratios observed, is likely related
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to noticeable differences in land cover between the upper and lower watershed.
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3.2 Land Use Controls on DBC Concentration & Composition
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DBC concentrations and respective BPCA ratios were significantly correlated to changes
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in land use throughout the Altamaha River watershed (Table 1). However, DBC concentrations
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were most strongly correlated with bulk DOC concentrations (r = 0.98, p < 0.01) suggesting
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strong intermolecular associations between the respective DBC and DOC pools9. Thus, it is
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unclear if there is a direct relationship between DBC concentrations and changes in respective
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land cover, or rather an indirect relationship driven by changes in DOC concentrations with
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respect to land cover. However, the source related changes in DBC composition as noted by
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BPCA distributions would be expected when considering that there is major BC compositional
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variation observed with respect to source change and/or formation temperature2-3, 36.
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The upper portion of the Altamaha River watershed is the most anthropogenically
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impacted region within the basin (Figure S1) consisting of areas draining both the urban
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influences of the Atlanta Metropolitan Area as well as drainage areas from primarily agricultural
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and farming regions, which consist primarily of poultry and beef, corn, soy, and hay
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production34. This distinction between the upper and lower watershed with respect to DBC is
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highlighted with a cluster analysis performed using percent-normalized BPCA concentrations
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(Figure S3) that clearly shows clustering of samples between two groups that represent the upper
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and lower watershed. Because of the clear spatial differentiation in land use type throughout the
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watershed, the clustering of these samples provides clear indication that BPCA composition may
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be driven by watershed land cover and/or land use.
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Among the small rivers and streams sampled, the lowest DBC concentrations were
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observed in 3 rivers with the highest urban influence (Stations 26, 29, & 31, Tables S1 & S2),
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each collecting waters primarily from the Atlanta metropolitan region. These samples also had
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no detectable representation of penta- and hexa-substituted BPCAs (B5CA, B6CA in Table S2)
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suggesting that the DBC has a lower degree of polycondensed aromaticity. This overall general
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trend is still highlighted on watershed scale in which a strong inverse correlation is observed
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between urban land use with both DBC concentrations (r = -0.60, p < 0.01) and BPCA ratios (r =
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-0.63, p < 0.01). The low BPCA ratio, and in particular samples lacking representation of B5CA
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and B6CA, would suggest the DBC in samples with strong urban influence are mainly derived
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from anthropogenic sources. However, using BPCA ratios as a sole indicator of DBC source
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should be exercised with caution considering the potential effects of photodegradation on BPCA
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distributions49-50. Nonetheless, the low BPCA ratios in urban areas may be indicative of a source
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primarily derived from fossil fuel combustion37, 51. Deposition of aerosols can be sources of DBC
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to fluvial systems52 and traces of elemental carbon (i.e. BC) and polycyclic aromatic
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hydrocarbons (PAHs) are transported as part of the fine particulate matter (PM2.5) within the
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Atlanta area53. While soot particles formed from fossil fuel combustion represent a source of
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highly polycondensed BC36, the leachable fraction of this material contain primarily less
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polycondensed DBC. This is reflected by a predominately B3CA and B4CA signature37 and thus
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may explain the less polycondensed DBC signature observed as a function of land use in the
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Altamaha River watershed. The low BPCA ratio, in particular for samples previously mentioned
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as depleted in the more substituted BPCAs, could in part be driven by deposition of PAHs from
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the Atlanta region. While we did not directly measure PAH concentrations in these samples,
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nitric acid oxidation of PAHs generally yields a BPCA signature characterized by less
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substituted BPCAs (B3CA and B4CA)46, 54. As such, although it is difficult to differentiate
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between the two possible anthropogenic sources of BPCAs in urban areas (i.e leachable soot vs
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PAHs)37, 55 without further analyses56, our data suggests that anthropogenic activity clearly
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contributes to the less polycondensed DBC signature observed in urban areas of the Altamaha
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River watershed.
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The low aromaticity DBC signature was not limited to urban land use. In fact, the BPCA
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ratio was also inversely correlated with agricultural land cover (r = -0.52, p < 0.05) suggesting
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that in general, anthropogenically impacted areas are represented by a less polycondensed DBC
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signature. The lower BPCA ratios in agricultural areas though may come as a surprise
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considering the common practice of burning agricultural croplands and use of PyC as soil
339
amendments57. Between 8 and 11% of global fires can be attributed to agricultural practices and
340
charcoal can represent between 10 and 35% of U.S. agricultural soils58-59. Furthermore, the
341
release of DBC is enhanced when biochars are added to soils for agricultural purpose22.
342
However, more polycondensed BC and increasing biochar aromaticity has repeatedly been
343
observed to increase as a function of charring temperature35. Because biochar production and
344
farm management burning are most favored at lower temperatures60, the formation of less
345
polycondensed BC (and therefore subsequent DBC) is likely more notable in agricultural areas,
346
which may explain the observed inverse relationship between BPCA ratios and agricultural land
347
cover (r = -0.52, p < 0.05) within the Altamaha River watershed.
348 349
The anthropogenic influences in the Oconee River sub-basin of the Altamaha River watershed are reduced downstream with natural forest and wetlands prevailing as the dominant
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land cover. Downstream samples (below Lake Sinclair, Figure S1) average about 68% natural
351
land cover in comparison to upstream samples, which have a much higher anthropogenic
352
influence (~50% with some samples >80%, Table S1). DBC concentrations increased
353
considerably in downstream samples and were coupled with an increase in the BPCA ratio,
354
suggesting a downstream source of a more polycondensed DBC pool (Table S1 and S2). BPCA
355
ratios were positively correlated with natural forest area (r = 0.58, p < 0.05) suggesting a
356
predominately wildfire derived DBC source from forested areas. Roughly a million acres of
357
Georgia forests are burned yearly for forest management purposes61, and a 50-year survey of fire
358
history dating up to the year 2007 suggests the state experiences an average between 8,000 and
359
12,000 small wildfires annually62. The extensive annual burning of Georgia forests would
360
suggest a considerable source of DBC in watersheds throughout the state, which likely includes
361
sources of DBC to the Altamaha River as well. The higher temperature wildfire derived burning
362
of forested biomass leads to the formation of more polycondensed BC as noted due to an
363
enrichment of B5CA and B6CA formation upon thermal oxidation35 further supporting the
364
observed positive correlation of BPCA ratios with forest area coverage (r = 0.58, p < 0.05)
365
within the Altamaha River.
366
The observed increases in DBC and BPCA ratio with increasing natural land cover was
367
not limited to forested area as wetlands were also very strongly correlated with more
368
polycondensed DBC (r = 0.87, p < 0.01). This association is further highlighted with a principal
369
component analysis where a clear separation of BPCAs was observed along principal component
370
1 (PC1) in which the more substituted BPCAs fell negatively along PC1 and the least substituted
371
BPCAs falling positively along PC1 (Figure 2). Wetland cover was both inversely and strongly
372
correlated to PC1 (r = -0.80, p < 0.01) further confirming the association between wetlands and
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the more polycondensed DBC. This observation could be explained by frequent burning of
374
wetlands in the Southeastern USA that leave behind charcoal rich soils63, which may lead to
375
leaching of more polycondensed DBC into fluvial systems over long time scales. The export of
376
DBC from large sub-tropical wetlands has been previously noted where there are sources of BC
377
from wetland wildfires during periods of drought64. Wetlands in the Altamaha River watershed
378
however would not be considered nearly as a large-scale (as the Florida Everglades for example),
379
but are rather integrated throughout the lower watershed primarily within the riparian areas of the
380
Oconee River and Altamaha River. These riparian wetlands areas are further surrounded by
381
natural forest areas, which also experience frequent burning activity61. Charcoal may be easily
382
mobilized by runoff65-66; and due to the waterlogged nature of wetlands, the frequent burning in
383
surrounding forested areas may also lead to the accumulation and aging of BC within the
384
wetland soils, inducing the release and transport of more polycondensed DBC throughout the
385
Altamaha River64, 67.
386
3.3 Land Use Controls on Molecular Composition of DBC
387
Using FTICR-MS, we identified a total of 16,477 molecular formulae among all samples
388
collected throughout the Altamaha River, of which 1,668 contained a combustion
389
derived/polycondensed aromatic signature (DBC, A.I. ≥ 0.67, C ≥15)29, 32-33. Most individual
390
samples contained between 6,500 and 9,500 individual molecular formulae with DBC
391
representing ca. 400 to 700 (ca. 5 to 10%) of the molecular formulae identified in a given sample
392
(Table S3). The intensity-weighted percent of DBC molecular formulae detected in each sample
393
were also highly correlated to individual BPCA concentrations (normalized to DOC; B3CA: r =
394
0.92; B4CA: r = 0.93; B5CA: r = 0.87; B6CA: r = 0.77; p < 0.01 in all cases). Although FTICR-
395
MS is not considered a fully quantitative technique, the correlations between the polycyclic
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aromatic compounds with individual BPCA components observed in this study, as well as
397
others42, 68, clearly indicates that FTICR-MS is of strong semi-quantitative character and supports
398
the hypothesis that a fraction of DOM compounds detected by FTICR-MS are of thermogenic
399
origin. 69-7071In the Altamaha River, an average of about 43% of the polycondensed aromatic
400
molecular formulae were characterized as CHO compounds, while the other 57% contain CHO
401
and one or more heteroatoms (Table S3) such as nitrogen or sulfur, which is more commonly
402
referred to as dissolved black nitrogen (DBN)69-70 and dissolved black sulfur (DBS)71,
403
respectively.
404
Changes in watershed land use can have considerable impacts on the molecular
405
composition of organic matter transported through river systems. For instance, increasing
406
cropland has been routinely linked to higher nitrogen inputs into local rivers, which leads to a
407
higher proportion of low molecular weight, nitrogen-containing DOM that is characteristic of
408
autochthonous DOM production15-16, 72-73. A recent study found that in 10 large global river
409
systems, the pyrogenic DOM signature is enriched in nitrogen for watersheds most impacted
410
with agricultural activities, indicating that agricultural burning practices may enhance the
411
production of charcoal containing nitrogen and may enhance the export of DBN17. Molecular
412
structures containing nitrogen and sulfur have also been linked to urbanization through high
413
loads in wastewater74 and septic influenced aquatic systems75.
414
In order to elucidate the impacts of land use on the molecular composition and export of
415
DBC on a smaller, localized watershed scale, principal component analysis was performed on
416
the intensity-mean centered DBC molecular formulae (Figure 3). PCA loading and score plots
417
are presented in Figure 3a and 3b, respectively with principal component 1 (PC1) representing
418
45.1% of explained variation and principal component 2 (PC2) explaining 10.2% of the
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explained variation. As shown in Figure 3b, a clear separation in elemental composition of DBC
420
compounds was observed along both PC1 and PC2. CHO-DBC compounds cluster
421
predominately around negative PC1 whereas heteroatomic DBC cluster more positively with
422
PC1. This is further evident with a strong positive correlation between PC1 and intensity
423
weighted DBN (Nw-dbc, r = 0.62 , p < 0.01). Clustering of pyrogenic DOM based on heteroatom
424
composition has been previously reported in world rivers and found to be directly correlated to
425
changes in watershed land use17. For the Altamaha River, PC1 was negatively correlated to
426
wetland (r = -0.67, p < 0.01, Figure 3c) and forest area (r = -0.38, p < 0.05) but positively
427
correlated to urban land cover (r = 0.39, p < 0.05) indicating an enrichment in DBN with
428
anthropogenic activity. These correlations in general support global trends reported by Wagner et
429
al.17, but on a smaller watershed scale, in that anthropogenic activity enhances the heteroatomic
430
DBC signature in fluvial systems. In agreement with the observed correlations of PC1 with
431
‘natural’ (negative PC1) vs. urban (positive PC1) land use, PC1 was also correlated with the
432
m/zw-dbc (Figure 3d, r = -0.64, p < 0.01), O/Cw-dbc (r = -0.36, p < 0.05), and H/Cw-dbc
433
(r = 0.85, p < 0.01). This agrees with the expectation that DBC exported from natural land covers
434
is higher in average molecular weight. This is also consistent with our previous results using
435
BPCA ratios that indicate a more polycondensed DBC signature from natural land covers
436
compared to a less polycondensed DBC signature in more the anthropogenically impacted areas
437
of the watershed. Furthermore, this pattern suggests that DBN exported from anthropogenically
438
impacted areas is also generally lower in average molecular weight in comparison to their CHO
439
only counterparts. This hypothesis is further supported by a strong inverse relationship between
440
m/zw-dbc and Nw-dbc (r = -0.76, p < 0.01).
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The positive relationship between PC1 with both urban land use and Nw-dbc may be an
442
indication that nitrogen in the pyrogenic DOM pool may be in part fossil fuel combustion
443
derived. Evidence to support this hypothesis has been reported by Yang et al.76 who have shown
444
the release nitrogen containing PAHs from coal combustion. Thus, we hypothesize that similar
445
mechanisms driving the inclusion of nitrogen into PAHs would be similar for the more
446
condensed aromatic fraction of the PyC spectrum as described in this study. The relationship of
447
DBN with land use has also been linked to agricultural practices in comparison to urbanization17.
448
While PC1 was not directly correlated to agricultural land cover, a positive correlation between
449
Nw-dbc and agriculture (r = 0.42, p < 0.01) further suggests a link between DBN export and
450
agricultural activity. In general, nitrogen inputs from agricultural areas have typically been
451
associated with enhanced production of low molecular weight DOM derived from instream
452
autochthonous sources15-16. However, for pyrogenic OM, nitrogen has been shown to become
453
incorporated into charred material through surface reactions and cyclization77-78 during burning
454
activity where it may be leached as DBN69-70. As previously discussed, charring temperature can
455
significantly influence pyrogenic OM composition35, and thus the low temperature burning for
456
agricultural management may enhance the production and leaching of low molecular weight
457
DBN in comparison to higher temperature, wildfire derived char.
458
Heteroatomic DBC is not limited to DBN as preliminary evidence by FTICR-MS has
459
been reported suggesting the existence of condensed aromatic compounds in aquatic systems that
460
contain some degree of sulfur functionality71. The presence of DBS is evident throughout the
461
Altamaha River as roughly 28% of the identified condensed aromatic compounds contain at least
462
one sulfur atom (Table S3). However, the intensity-weighted average of DBS (Sw-dbc) is much
463
lower in comparison to Nw-dbc (Table S3) suggesting the relative abundance of these DBS
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compounds in fluvial systems is quite low in comparison to DBN compounds. In the PCA
465
presented in Figure 3b, DBS molecular formulae cluster positively along PC1 similar to DBN,
466
but also cluster more positively along PC2. In fact, PC2 is positively correlated with both Sw-dbc
467
(Figure 3e, r = 0.69, p < 0.01) and agricultural land cover (Figure 3f, r = 0.43, p < 0.01)
468
suggesting sulfur from agricultural sources may become incorporated into the DBC pool within a
469
watershed. Studies within the agricultural areas of the Florida Everglades suggests that DOM
470
becomes enriched in sulfur moieties in areas where there is increased sulfate enrichment, with
471
DBS accounting for a small fraction of the detected sulfur containing compounds71, 79.
472
Mechanisms for addition of sulfur within the DBC pool are currently unknown. A strong inverse
473
relationship between PC2 and O/Cw-dbc (r = -0.85, p < 0.01) suggests that DBS is associated with
474
less oxygenated DBC and in a more reduced state. This would support a hypothesis of abiotic
475
sulfurization in low oxygen and reducing environments, which has been previously observed for
476
bulk DOM in sulfide rich conditions such as marine hydrothermal systems80 and sulfidic
477
intertidal flat sediments42. As aerosols may also contribute to BC deposition in anthropogenically
478
impacted watersheds18, 53, contributions of DBC and potentially DBS may in part originate from
479
use of diesel fuels from farming equipment; however, this hypothesis is speculative and would
480
require further investigation. It is also not unreasonable to hypothesize that sulfur can be directly
481
incorporated into charred materials through fire activity similar to that of nitrogen77. However,
482
evidence to support this hypothesis is currently not available and would also require further
483
investigation. Regardless, the link between DBS and agricultural land cover in the Altamaha
484
River suggests the existence of an important, but still unrecognized mechanism for integration of
485
sulfur functionality within the condensed aromatic spectrum. The incorporation of these
486
compounds into aquatic systems may have further unrecognized biogeochemical implications in
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relation to carbon, nitrogen, and sulfur cycling and their influence on global climate change,
488
which warrants further investigation.
489
3.4 Environmental Implications and Future Directions
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We show in this study that compositional shifts in DBC, implying variations in source
491
and quality, are directly impacted by watershed land use. As the population and agricultural
492
activities continue to increase in the watershed, long-term shifts in the molecular composition
493
and potentially the reactivity of DBC is to be expected. The long-term consequence for these
494
changes are not well understood, but shifts in DBC quality throughout fluvial systems and export
495
to coastal oceans could have important impacts on both carbon and nutrient cycling, and may
496
have further implications for on-going global climate change trends.
497
It is important to note that while the BPCA method and FTICR-MS cover a span of
498
analytical windows in characterizing DBC (polycondensed fractions via defined markers and
499
molecular fingerprinting), future studies should continue to expand upon the controls of land use
500
over the entire pyrogenic carbon spectrum, while recognizing that other fractions of this
501
continuum may still need to be analytically defined. Additional studies should also continue to
502
focus on the effects of land use with respect to DBC quality in large watersheds while further
503
incorporating other environmental drivers that may influence DBC composition such as
504
climatology, wildfire history, and river biogeochemistry. Furthermore, hydrological controls on
505
DBC export have been previously observed in fluvial systems20-21, 81. However, temporal
506
variability and hydrological controls on DBC quality and export with respect to land use have yet
507
to be determined and warrant further study.
508 509
5. Supporting Information
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Figure S1 is a map displaying the locations of each sampling location. Figure S2 is a map
511
displaying land cover throughout the Altamaha River watershed. Figure S3 represents a cluster
512
analysis using relative BPCA distributions. Table S1 summarizes sample collection and land use
513
data. Table S2 provides DOC, DBC, BPCA and flux information. Table S3 summarizes
514
molecular parameters for the polycondensed aromatic compounds detected with FTICR-MS.
515 516
6. Acknowledgments
517
The authors greatly appreciate the contributions from Nicolas Jaffé regarding the GIS processing
518
needed to assemble the land-use data for this study. Many thanks to Drs. Patricia Medeiros and
519
Aron Stubbins at the University of Georgia for providing lab space for sample processing during
520
the field work. This research was funded through the George Barley Endowment (to RJ). This is
521
contribution number XXX from the Southeast Environmental Research Center at FIU.
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1. Goldberg, E. D., Black Carbon in the Environment: Properties and Distribution. 1 ed.; John Wiley & Sons Inc: New York, 1985.
526 527
2. Masiello, C. A., New directions in black carbon organic geochemistry. Marine Chemistry 2004, 92 (1–4), 201-213.
528 529
3. Wagner, S.; Jaffé, R.; Stubbins, A., Dissolved black carbon in aquatic ecosystems. Limnology and Oceanography Letters 2018, 0 (0), doi: 10.1002/lol2.10076.
530 531 532
4. Preston, C. M.; Schmidt, M. W. I., Black (pyrogenic) carbon: a synthesis of current knowledge and uncertainties with special consideration of boreal regions. Biogeosciences 2006, 3 (4), 397-420.
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5. Kuzyakov, Y.; Bogomolova, I.; Glaser, B., Biochar stability in soil: Decomposition during eight years and transformation as assessed by compound-specific 14C analysis. Soil Biology and Biochemistry 2014, 70, 229-236.
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6. Hockaday, W. C.; Grannas, A. M.; Kim, S.; Hatcher, P. G., Direct molecular evidence for the degradation and mobility of black carbon in soils from ultrahigh-resolution mass spectral analysis of dissolved organic matter from a fire-impacted forest soil. Organic Geochemistry 2006, 37 (4), 501-510.
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7. Santín, C.; Doerr, S. H.; Kane, E. S.; Masiello, C. A.; Ohlson, M.; de la Rosa, J. M.; Preston, C. M.; Dittmar, T., Towards a global assessment of pyrogenic carbon from vegetation fires. Global Change Biology 2016, 22 (1), 76-91.
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9. Jaffé, R.; Ding, Y.; Niggemann, J.; Vähätalo, A. V.; Stubbins, A.; Spencer, R. G. M.; Campbell, J.; Dittmar, T., Global charcoal mobilization from soils via dissolution and riverine transport to the oceans. Science 2013, 340 (6130), 345-347.
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50. Wagner, S.; Jaffé, R., Effect of photodegradation on molecular size distribution and quality of dissolved black carbon. Organic Geochemistry 2015, 86, 1-4.
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51. Khan, A. L.; Jaffé, R.; Ding, Y.; McKnight, D. M., Dissolved black carbon in Antarctic lakes: Chemical signatures of past and present sources. Geophysical Research Letters 2016, 43 (11), 5750-5757.
672 673 674 675
52. Mari, X.; Van, T. C.; Guinot, B.; Brune, J.; Lefebvre, J.-P.; Raimbault, P.; Dittmar, T.; Niggemann, J., Seasonal dynamics of atmospheric and river inputs of black carbon, and impacts on biogeochemical cycles in Halong Bay, Vietnam. Elementa Science of the Anthropocene 2017, 75, doi: 10.1525/elementa.255.
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53. Li, Z.; Porter, E. N.; Sjödin, A.; Needham, L. L.; Lee, S.; Russell, A. G.; Mulholland, J. A., Characterization of PM2.5-bound polycyclic aromatic hydrocarbons in Atlanta—Seasonal variations at urban, suburban, and rural ambient air monitoring sites. Atmospheric Environment 2009, 43 (27), 4187-4193.
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54. Wiedemeier, D. B.; Brodowski, S.; Wiesenberg, G. L. B., Pyrogenic molecular markers: Linking PAH with BPCA analysis. Chemosphere 2015, 119, 432-437.
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55. Abdel-Shafy, H. I.; Mansour, M. S. M., A review on polycyclic aromatic hydrocarbons: Source, environmental impact, effect on human health and remediation. Egyptian Journal of Petroleum 2016, 25 (1), 107-123.
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56. Hanke, U. M.; Reddy, C. M.; Braun, A. L. L.; Coppola, A. I.; Haghipour, N.; McIntyre, C. P.; Wacker, L.; Xu, L.; McNichol, A. P.; Abiven, S.; Schmidt, M. W. I.; Eglinton, T. I., What on Earth have we been burning? Deciphering Sedimentary Records of Pyrogenic Carbon. Environmental Science & Technology 2017, 51 (21), 12972-12980.
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57. Woolf, D.; E., A. J.; Street-Perrott, F. A.; Lehmann, J.; Josheph, S., Sustainable biochar to mitigate global climate change. Nat Commun 2010, 1 (56), doi: 10.1038/ncomms1053.
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58. Skjemstad, J. O.; Reicosky, D. C.; Wilts, A. R.; McGowan, J. A., Charcoal carbon in U.S. agricultural soils. Soil Science Society of America Journal 2002, 66 (4), 1249-1255.
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59. Korontzi, S.; McCarty, J.; Loboda, T.; Kumar, S.; Justice, C., Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data. Global Biogeochemical Cycles 2006, 20 (2), doi: 10.1029/2005GB002529.
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60. McHenry, M. P., Agricultural bio-char production, renewable energy generation and farm carbon sequestration in Western Australia: Certainty, uncertainty and risk. Agriculture, Ecosystems & Environment 2009, 129 (1), 1-7.
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61. Tian, D.; Wang, Y.; Bergin, M.; Hu, Y.; Liu, Y.; Russell, A. G., Air quality impacts from prescribed forest fires under different management practices. Environmental Science & Technology 2008, 42 (8), 2767-2772.
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62. Georgia Forestry Commission., The Histroic 2007 georgia Wildfires: Learning from the past – Planning for the future; 2007.
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63. Rollins, M. S.; Cohen, A. D.; Durig, J. R., Effects of fires on the chemical and petrographic composition of peat in the Snuggedy Swamp, South Carolina. International Journal of Coal Geology 1993, 22 (2), 101-117.
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64. Ding, Y.; Cawley, K. M.; da Cunha, C. N.; Jaffé, R., Environmental dynamics of dissolved black carbon in wetlands. Biogeochemistry 2014, 119 (1), 259-273.
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65. Pyle, L. A.; Magee, K. L.; Gallagher, M. E.; Hockaday, W. C.; Masiello, C. A., Shortterm changes in physical and chemical properties of soil charcoal support enhanced landscape mobility. Journal of Geophysical Research: Biogeosciences 2017, 122 (11), 3098-3107.
712 713 714 715
66. Cotrufo, M. F.; Boot, C. M.; Kampf, S.; Nelson, P. A.; Brogan , D. J.; Covino, T.; Haddix, M. L.; MacDonald, L. H.; Rathburn, S.; Ryan‐Bukett, S.; Schmeer, S.; Hall, E., Redistribution of pyrogenic carbon from hillslopes to stream corridors following a large montane wildfire. Global Biogeochemical Cycles 2016, 30 (9), 1348-1355.
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67. Abiven, S.; Hengartner, P.; Schneider, M. P. W.; Singh, N.; Schmidt, M. W. I., Pyrogenic carbon soluble fraction is larger and more aromatic in aged charcoal than in fresh charcoal. Soil Biology and Biochemistry 2011, 43 (7), 1615-1617.
719 720 721 722
68. Seidel, M.; Beck, M.; Greskowiak, J.; Riedel, T.; Waska, H.; Suryaputra, I. N. A.; Schnetger, B.; Niggemann, J.; Simon, M.; Dittmar, T., Benthic-pelagic coupling of nutrients and dissolved organic matter composition in an intertidal sandy beach. Marine Chemistry 2015, 176, 150-163.
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69. Ding, Y.; Watanabe, A.; Jaffé, R., Dissolved black nitrogen (DBN) in freshwater environments. Organic Geochemistry 2014, 68, 1-4.
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70. Wagner, S.; Dittmar, T.; Jaffé, R., Molecular characterization of dissolved black nitrogen via electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Organic Geochemistry 2015, 79, 21-30.
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71. Hertkorn, N.; Harir, M.; Cawley, K. M.; Schmitt-Kopplin, P.; Jaffé, R., Molecular characterization of dissolved organic matter from subtropical wetlands: a comparative study through the analysis of optical properties, NMR and FTICR/MS. Biogeosciences 2016, 13 (8), 2257-2277.
732 733 734
72. Carpenter, S. R.; Caraco, N. F.; Correll, D. L.; Howarth, R. W.; Sharpley, A. N.; Smith, V. H., Nonpoint Pollution of Surface Waters with Phosphorus and Nitrogen. Ecological Applications 1998, 8 (3), 559-568.
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73. Mattsson, T.; Kortelainen, P.; Laubel, A.; Evans, D.; Pujo-Pay, M.; Räike, A.; Conan, P., Export of dissolved organic matter in relation to land use along a European climatic gradient. Science of The Total Environment 2009, 407 (6), 1967-1976.
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74. Gonsior, M.; Zwartjes, M.; Cooper, W. J.; Song, W.; Ishida, K. P.; Tseng, L. Y.; Jeung, M. K.; Rosso, D.; Hertkorn, N.; Schmitt-Kopplin, P., Molecular characterization of effluent organic matter identified by ultrahigh resolution mass spectrometry. Water Research 2011, 45 (9), 2943-2953.
742 743 744
75. Arnold, W. A.; Longnecker, K.; Kroeger, K. D.; Kujawinski, E. B., Molecular signature of organic nitrogen in septic-impacted groundwater. Environmental Science: Processes & Impacts 2014, 16 (10), 2400-2407.
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76. Yang, X.; Liu, S.; Xu, Y.; Liu, Y.; Chen, L.; Tang, N.; Hayakawa, K., Emission factors of polycyclic and nitro-polycyclic aromatic hydrocarbons from residential combustion of coal and crop residue pellets. Environmental Pollution 2017, 231 (Part 2), 1265-1273.
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77. Knicker, H., How does fire affect the nature and stability of soil organic nitrogen and carbon? A review. Biogeochemistry 2007, 85 (1), 91-118.
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78. Knicker, H.; González-Vila, F. J.; Polvillo, O.; González, J. A.; Almendros, G., Fireinduced transformation of C- and N- forms in different organic soil fractions from a Dystric Cambisol under a Mediterranean pine forest (Pinus pinaster). Soil Biology and Biochemistry 2005, 37 (4), 701-718.
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79. Poulin, B. A.; Ryan, J. N.; Nagy, K. L.; Stubbins, A.; Dittmar, T.; Orem, W.; Krabbenhoft, D. P.; Aiken, G. R., Spatial dependence of reduced sulfur in Everglades dissolved organic matter controlled by sulfate enrichment. Environmental Science & Technology 2017, 51 (7), 3630-3639.
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80. Gomez-Saez, G. V.; Niggemann, J.; Dittmar, T.; Pohlabeln, A. M.; Lang, S. Q.; Noowong, A.; Pichler, T.; Wörmer, L.; Bühring, S. I., Molecular evidence for abiotic sulfurization of dissolved organic matter in marine shallow hydrothermal systems. Geochimica et Cosmochimica Acta 2016, 190 (Supplement C), 35-52.
762 763 764 765
81. Myers-Pigg, A. N.; Louchouarn, P.; Teisserenc, R., Flux of dissolved and particulate lowtemperature pyrogenic carbon from two high-latitude rivers across the spring freshet hydrograph. Frontiers in Marine Science 2017, 4 (38), doi: 10.3389/fmars.2017.00038.
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8. Figures Captions
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Figure 1: Spatial distribution of (a) DBC and (b) DBC composition (BPCA ratio) within the
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Altamaha River. Smoothing lines (grey) were added to follow general changes in data from the
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upper watershed to the coastal region. (c) DBC fluxes within the Altamaha River in comparison
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to conservative estimates where a DBC flux > conservative estimates indicates a source of DBC
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and a DBC flux < conservative estimates indicates a DBC sink. (d) The conservative mixing
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model displayed in 1c, however only showing the expanded scale between 380 and 250 km from
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the coastal region
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Figure 2: Principal Component Analysis using the relative BPCA distributions including (a)
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BPCA loadings and sample score plots, and (b) a strong inverse linear correlation between PC1
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and wetland land cover. Samples are color coded according to their clusters (S. Figure 1).
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Figure 3: A principal component (PC) analysis of the intensity mean-centered DBC molecular
780
formulae as determined by FTICR-MS analysis. (a) Loading plots displaying sample locations in
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PC space. (b) Score plot representing the distribution of molecular formulae in PC space with
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each highlighted in accordance with molecular composition. Graphs (c) and (d) represent linear
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correlations of PC1 with percent wetland cover and intensity weighted m/z, respectively. Graphs
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(e) and (f) represent linear correlations of PC2 with intensity weighted sulfur and percent
785
agriculture, respectively.
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Table 1: Significant (p < 0.01, p < 0.05) linear correlations as represented by the Pearson
788
correlation coefficient (r) between land use variables with DBC concentration and composition
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(BPCA and FT-ICR/MS). A (*) indicates statistical analysis for samples only characterized by
790
the BPCA method. A (-) indicates correlations were not significant.
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9. Figures and Tables
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Figure 1:
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Figure 2:
a
b
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Figure 3:
a
b CHO
c
d
e
f
CHON
CHOS
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Table 1 Urban Forested
Agriculture
Wetland
*DBC
-0.60
-
-
0.87
*BPCA
-0.63
0.58
-0.52
0.81
m/zw
-
-
-0.39
0.61
Nw
-
-0.40
0.42
-0.51
Sw
-
-
-
-
O/Cw
-
-
-0.39
-
H/Cw
0.35
-0.36
0.35
-0.67
800
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84x47mm (150 x 150 DPI)
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