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hydrochloric acid (J.T. Baker ULTREX II grade) and sparged overnight. (~10±2h) with clean, low-CO2 air to remove ambient dissolved inorganic carbon (DIC).
Author's personal copy Marine Chemistry 118 (2010) 11–21

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Marine Chemistry j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / m a r c h e m

Carbon dioxide and carbon monoxide photoproduction quantum yields in the Delaware Estuary Emily M. White a,1, David J. Kieber a,⁎, Jane Sherrard b,2, William L. Miller b,3, Kenneth Mopper c a b c

Department of Chemistry, State University of New York, College of Environmental Science and Forestry, 1 Forestry Drive, Syracuse, NY 13210, USA Department of Oceanography, Dalhousie University, 1355 Oxford Street, Halifax, Nova Scotia, Canada B3H 4J1 Department of Chemistry and Biochemistry, Old Dominion University, 4541 Hampton Boulevard, Norfolk, VA 23529, USA

a r t i c l e

i n f o

Article history: Received 14 April 2009 Received in revised form 1 October 2009 Accepted 7 October 2009 Available online 14 October 2009 Keywords: Dissolved organic matter Photochemistry Carbon dioxide Carbon monoxide Delaware Estuary

a b s t r a c t Photochemical mineralization of dissolved organic matter (DOM) plays an important role in the cycling of carbon in estuarine systems. A key to modeling this process is knowledge of apparent quantum yields (AQYs) for the photochemical products. Here we determined spectral AQYs for carbon dioxide (CO2) and carbon monoxide (CO), the main products of DOM photomineralization, along the main axis of the Delaware Estuary. Apparent quantum yields for CO2 photoproduction were determined shipboard using a multi-spectral irradiation system. Carbon monoxide AQYs were determined in stored samples by employing a narrow band spectral irradiation system. A single AQY spectrum described carbon dioxide photochemical production within the estuary whereas CO AQY spectra varied with salinity, suggesting different precursors and mechanisms for the production of these two species. CO2 AQYs were used along with shipboard measurements of DOM absorbance and solar irradiance to calculate photoproduction rates. Calculated CO2 photoproduction rates agreed with directly measured rates (2 to 4 μM CO2 d− 1) within experimental error, supporting the further development and use of AQYs to calculate regional-scale photochemical fluxes. © 2009 Elsevier B.V. All rights reserved.

1. Introduction The photochemical degradation of dissolved organic matter (DOM) plays a significant role in the cycling of carbon in natural waters (for review see Mopper and Kieber, 2000). This is due in part to the formation of biologically labile organic compounds as well as the photomineralization of DOM to carbon dioxide (CO2) and carbon monoxide (CO), the two main carbon photoproducts identified in natural waters. Photochemistry is of particular importance in estuaries where large inputs of terrestrial organic carbon (0.25 Pg dissolved organic carbon yr− 1, Hedges et al., 1997) are processed during transport to the ocean. Globally, the estuarine CO2 and CO

⁎ Corresponding author. Tel.: +1 315 470 6951; fax: +1 315 470 6858. E-mail addresses: [email protected] (E.M. White), [email protected] (D.J. Kieber), [email protected] (J. Sherrard), [email protected] (W.L. Miller), [email protected] (K. Mopper). 1 Present Address: United States Environmental Protection Agency, National Exposure Research Laboratory, Ecosystems Research Division, 960 College Station Road, Athens, GA 30605, USA. 2 Present Address: Hill Laboratories, 1 Clyde Street, Private Bag 3205, Hamilton 3240, New Zealand. 3 Present Address: Department of Marine Sciences, University of Georgia, Athens, GA 30602, USA. 0304-4203/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.marchem.2009.10.001

photoproduction flux is ~ 0.04 Pg C yr− 1 or ~17% of riverine dissolved organic carbon (Stubbins, 2001). Despite the biogeochemical significance of this process, few studies have examined the photoproduction of CO2 and CO in estuarine systems (Stubbins, 2001; Skalski, 2006; Zhang et al., 2006). Recent work has focused on the determination of apparent quantum yield (AQY) spectra for the photochemical production of CO (Stubbins et al., 2006; Zhang et al., 2006; Ziolkowski and Miller, 2007) and CO2 (Bélanger et al., 2006; Skalski, 2006; Johannessen et al., 2007), where the AQY is defined as the moles of CO or CO2 formed per mole of photons absorbed by chromophoric DOM (CDOM). Apparent quantum yields are important because they are used to calculate photochemical rates in large-scale photochemical flux models (Fichot, 2004). In this study, AQY spectra were determined along the main axis of the Delaware Estuary during late June and early July 2002. A shipboard polychromatic irradiation system was employed to determine CO2 AQY in freshly collected water samples. Several samples were transported to Syracuse, New York for determination of CO AQY using a monochromatic irradiation system. Rates of CO2 photoproduction were also determined directly during the cruise by exposure of filter-sterilized estuarine samples to solar radiation in a deckboard incubator. The AQYcalculated CO2 production rates were then evaluated by comparison to directly measured production rates. CO2 and CO photoproduction rates are important indicators of the chemical reactivity of CDOM as it transits

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through the Delaware Estuary. Details highlighting the importance of these processes are presented elsewhere (White, 2007). 2. Materials and methods 2.1. Sample collection Hydrographic stations were sampled in the Delaware Estuary (Fig. 1) from the R/V Endeavor between 25 June and 04 July 2002 (EN372). A Sea-Bird Electronics (SBE) 911plus CTD with attached 10 L GO-FLO bottles (General Oceanics) was used to collect samples and determine bulk water characteristics. Surface water samples (1.5 to 3 m) were gravity-filtered in-line from the GO-FLO bottles into glass Qorpak bottles using silicone tubing and a pre-cleaned Whatman 0.2 μm POLYCAP AS/HD high-flow capsule filter. Capsule filters and glassware were cleaned as described in White et al. (2008) using 18.2 MΩ cm high purity laboratory water (Barnstead NANOpure system). 2.2. CDOM absorption spectra Ultraviolet–visible absorbance spectra were determined from 200 to 800 nm with 0.2 μm-filtered samples, using a Perkin-Elmer Lambda 18 scanning spectrophotometer with a 10 cm long cylindrical cuvette. Spectra were referenced against NANOpure water and baseline corrected by adjusting the absorbance (Aλ) to zero between 700 and 800 nm (Blough et al., 1993). Measured Aλ were used to calculate absorption coefficients (i.e., aλ = 2.303(Aλ/l) where l is the pathlength in m). 2.3. Sample pretreatment To determine CO2 photoproduction rates and CO2 AQYs, 0.2 μmfiltered samples were acidified to pH 3 to 4 with concentrated hydrochloric acid (J.T. Baker ULTREX II grade) and sparged overnight (~10 ± 2 h) with clean, low-CO2 air to remove ambient dissolved inorganic carbon (DIC). The low-CO2 air (b1 ppm CO2) was obtained from zero air using a FTIR Purge Gas Generator (Parker Hannifin model 75–45) with in-line activated carbon and ascarite columns.

Sparged samples were adjusted back to the initial pH by addition of concentrated sodium hydroxide, prepared by dissolving sodium hydroxide pellets (Aldrich, 99.99%) in acidified, low-dissolved inorganic carbon (DIC) NANOwater. The DIC concentration was typically b0.5 μM in the samples following this pretreatment (White et al., 2008). Water samples were 0.2 μm-filtered for CO studies using the same procedure outlined for CO2 samples, and were stored in the dark at 4 °C until analysis in the home laboratory (within a year of sample collection). Samples were warmed to room temperature and re-filtered by vacuum through a 0.2 μm Nylon filter (Micron Separations Inc.) and sparged with CO-free air for at least 3 h before use, reducing background CO to ≤0.1 nM. Control experiments indicated that sparging did not affect CO photoproduction rates. Additionally, routine work in our laboratory has shown only small changes in CDOM absorption (b10%) as a result of prolonged sample storage (e.g., 1 yr). For example, a330 for the salinity = 13 sample increased by only 0.2 m− 1 (from 4.2 to 4.4 m− 1) after storage in the dark at 4 °C for a year. Therefore it was assumed that sample storage did not significantly affect measured CO photoproduction rates, as these rates have been found to be directly related to CDOM absorption (Valentine and Zepp, 1993; Miller and Zepp, 1995; Zuo and Jones, 1995). 2.4. Shipboard CO2 photoproduction rates Following sample pretreatment, the resulting low-DIC samples were pneumatically transferred to gas-tight quartz tubes (~90 mL, ~2 cm pathlength) for determination of CO2 photoproduction rates. For details regarding the quartz tube design and experimental protocols see White et al. (2008). Tubes were placed on the ship's deck in a ~3 cm deep circulating fresh water bath (27 to 32 °C). Samples were exposed to solar radiation for 5 to 8 h starting between 9:00 and 11:00 local time; dark controls were wrapped in aluminum foil. At least triplicates of each treatment were irradiated simultaneously for each sample. Dark production (presumably due to diffusion of atmospheric CO2 into the quartz tubes) was b 0.2 μM. During shipboard irradiations, a deck mounted Optronics OL754 spectroradiometer with a cosine collector (calibrated with an Optronics OL752-150 irradiance standard) was used to continuously record the solar irradiance at 1 nm intervals from 290 to 600 nm, with an average scan time of 15 min. The total light dose integrated between 290 to 600 nm ranged from 17.5 to 27.0 mol quanta m− 2 for CO2 photoproduction experiments. To account for differences in light exposure and convert production to daily rates, measured photoproduction rates were normalized to the average daily (i.e., sunrise to sunset) light exposure from 310 to 350 nm (1.2 mol quanta m− 2). This wavelength range was selected because it corresponds to the main solar bandwidth for CO2 photoproduction in natural waters (White, 2007). Carbon dioxide concentrations were determined in the quartz tubes according to the method outlined in White et al. (2008). Samples and standards were analyzed in triplicate and introduced into the instrument either pneumatically or with a gas-tight syringe. Aqueous sodium carbonate (J.T. Baker, ACS Reagent) standards (1 to 15 μM) were prepared by dilution in low-DIC NANOwater and gave a coefficient of variation of ≤1.0%. The detection limit, defined as three times the standard deviation of the low-DIC seawater blank, was approximately 0.2 µM. 2.5. AQY for carbon dioxide photoproduction

Fig. 1. Map of Delaware Estuary with locations (and salinities) of the stations sampled during the EN372 cruise (25 June to 04 July 2002).

Apparent quantum yields for CO2 photoproduction were determined during the EN372 cruise according to the multispectral procedure outlined in Johannessen and Miller (2001). Briefly, fifteen cylindrical quartz cells (10 cm pathlength, 28 mL volume, Spectrocell) were filled with pretreated low-DIC sample and capped with Teflon-

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faced silicon septa (National Scientific Company). Cells were filled vertically from the bottom with no headspace and flushed with sample before closing to reduce atmospheric contamination. Cells were aligned vertically in a black, temperature-regulated aluminum block holder (held at 20 ± 0.5 °C), and irradiated for 8 to 12 h in a Suntest CPS multispectral irradiation enclosure fitted with a 1.5 kW Hereaus xenon lamp. Schott cutoff filters, positioned above the quartz cells, modified the spectral irradiance incident on each sample. Eight different long pass filters were used to cutoff short wavelength radiation, with 50% transmission at the following wavelengths: 280, 295, 305, 320, 335, 380, 425 and 480 nm. In most experiments, matched filters were used for duplicate irradiations for all light treatments except for the 335 and 480 nm cutoff filters where only one filter was used. Dark controls were placed in an aluminum block and the incoming radiation was blocked. A single dark cell was processed for each water sample, and typical dark values were ~2 μM CO2. The irradiance was measured under each filter with a second Optronics OL754 spectroradiometer fitted with a fiber optic cable and Teflon diffuser (calibrated with an Optronics OL752-150 irradiance standard). The spectral output of several of the filters is shown in Johannessen and Miller (2001). Carbon dioxide concentrations were determined in irradiated samples and controls (White et al., 2008) to determine CO2 production rates (dCO2/dt) and calculate wavelength-dependent AQYs: dCO2 = ∫ϕðλÞQ a ðλÞdλ dt ∫ϕðλÞdλ =

dCO2 1 ∫ dλ Q a ðλÞ dt

ð1Þ ð2Þ

where ϕ(λ) is the wavelength-dependent AQY and Qa(λ) is moles of photons absorbed by CDOM at each wavelength per volume of sample per second, corrected for inner filter effects as described by Hu et al. (2002):   SA −aðλÞl Q a ðλÞ = EðλÞð1−e Þ V

ðm1 + m2 ðλ−290ÞÞ

ϕðλÞ = e

Energy) fitted with a 5 cm thermostated cell holder. Pretreated CO samples were transferred to a rectangular quartz cell (5 cm pathlength, 25.4 mL volume, Spectrocell) and sealed with a screw top cap, lined with a Teflon-faced silicon septum. To reduce the surface area of the exposed septum, a cap drilled with two small 1.6 mm holes near the center was used rather than a typical “open” septum cap. To further prevent atmospheric exchange, the cell was filled from the bottom and overfilled with ~50 mL of sample before closing. Samples were irradiated at 20 °C with continuous stirring. Irradiation times varied from 5 min to 13 h and covered a wavelength range from 290 to 490 nm at 10 nm intervals below 430 nm and 20 nm at longer wavelengths. Irradiation bandwidths were 10 nm below 400 nm and 20 nm at ≥400 nm. CO production was linear over the irradiation period and no photobleaching was observed. Dark controls (samples with a foil plate between the light inlet and cuvette) were subtracted from irradiated samples and NANOpure water blanks were also examined; these samples showed b1 nM increase in CO when incubated for 12 h, which was well below the amount of CO produced in any of the light-exposed samples. After a sample was irradiated it was transferred from the quartz cell to a 10 mL MICRO-MATE luer glass tip syringe (Popper & Sons, Inc.) and analyzed according to Xie et al. (2002). The CO in each injected sample was quantified by headspace analysis using a modified Trace Analytical RGA-3 reduction gas analyzer. Once CO was quantified in the headspace, it was used to calculate the CO concentration in the water sample (Xie et al., 2002). The detection limit, defined as three times the standard deviation of the CO-free water blank, was approximately 0.05 nM. Measured CO concentrations were used to determine photoproduction rates (dCO/dt), which were used in turn to calculate wavelength dependent AQY (ϕ(λ)) for CO photoproduction:

ϕðλÞ =

ð3Þ

E(λ) is the wavelength-dependent irradiance (mol quanta m− 2 s− 1 nm − 1 ), a(λ) is the wavelength-dependent CDOM absorption coefficient (m− 1), l is the pathlength (m), SA is the cross section of the irradiated area (m2), and V is the sample volume (m3). Spectral AQYs were computed using a modified statistical curve fitting method, as described in Johannessen and Miller (2001), based on the work of Rundel (1983) and Cullen and Neale (1994). An in-house MATLAB program was used to iteratively fit CO2 production rates, spectral absorption coefficients, and spectral irradiance data to an exponential equation for AQY: ð4Þ

where m1 and m2 are best-fit parameters. All CO2 production data were used in the statistical fit for each estuarine sample that was examined; the number of data points ranged from 35–57 (Table 1), which included replicate analysis of samples from fourteen irradiation cells and in some cases duplicate irradiation experiments. The best-fit AQY spectra were used to model CO2 production rates for each light treatment by using the sample absorbance spectra and spectral irradiance to evaluate the robustness of the modeled fit. 2.6. AQY for carbon monoxide photoproduction Apparent quantum yields for CO photoproduction were determined as a function of wavelength employing the monochromatic irradiation system described in Kieber et al. (1996). This system consisted of a 1 kW xenon lamp, a high intensity quarter meter grating monochromator (GM 252), and a sample chamber (Spectral

13

ðdCO = dtÞV FðλÞð1−e−aðλÞl Þ

ð5Þ

The potassium ferrioxalate (PF) chemical actinometer (Hatchard and Parker, 1956) was used to measure the radiant flux in the irradiated cell (F(λ)) according to the method of Murov et al. (1993); the PF chemical actinometer was used for CO AQY studies because it allowed for the determination of the light flux in the irradiation cell, accounting for variations in cell geometry. Pure solid PF was prepared from potassium oxalate (Acros, ACS reagent) and ferric chloride (Mallinckrodt Chemical, Inc.) as described by Hatchard and Parker (1956). The PF actinometer solution (in 0.05 M HCl) was irradiated for 5 to 10 min at a concentration of 6 mM (for λ ≤ 430 nm) or 0.15 M (for λ ≥ 440 nm). All irradiations were done in triplicate; monochromator settings and the quartz cell were identical to those used for the spectral CO photoproduction experiments. Photochemical production of Fe2+ in the actinometer solution was quantified spectrophotometrically as its 1,10-phenanthroline complex. The radiant flux (F(λ), mol quanta s− 1) was calculated from the following equation: 2 +

FðλÞ =

½Fe

V = ϕPF ðλÞt 1−10−APF ðλÞ

ð6Þ

where [Fe2+] is the concentration of photoproduced Fe2+ (M, corrected for dilution during analysis), V is the volume of sample irradiated (L), ϕPF(λ) is the quantum yield for the production of Fe2+ from PF (taken from Murov et al., 1993), t is the irradiation time (s), and APF(λ) is the absorbance of the PF solution in the quartz cell (5 cm pathlength). Radiant fluxes ranged from 0.210 × 10− 8 to 1.74 × 10− 8 mol quanta s− 1.

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Table 1 Station salinity (S), date sampled (in 2002), location (latitude and longitude), absorption coefficients at 350 nm (a350), and CO2 apparent quantum yield fit parameters, m1 and m2, for the equation: ϕ(λ) = e −(m1 + m2 (λ − 290)). Salinity

Date

Latitude (°N)

Longitude (°W)

a350 (m− 1)

m1

0.1 3 10 13 19 21 Pooledb

28 Jun 30 Jun 26 Jun 29 Jun 25 Jun 1 Jul

39.85 39.50 39.34 39.25 39.11 39.11

75.34 75.56 75.42 75.32 75.21 75.20

5.4 4.2 3.6a 3.2 2.5 2.3

6.4 7.2 7.4 7.0 6.9 7.1 7.1

m2 (± 0.1) (± 0.2) (± 0.3) (± 0.3) (± 0.2) (± 0.2) (± 0.1)

0.019 0.028 0.025 0.034 0.036 0.027 0.030

(± 0.001) (± 0.004) (± 0.005) (± 0.006) (± 0.004) (± 0.004) (± 0.002)

r2

n

0.99 0.69 0.90 0.93 0.95 0.94 0.92

55 38 50 38 57 35 218

Values in parentheses are 95% confidence intervals for the best-fit spectra. Values of r 2 indicate the agreement between CO2 production rates measured with the Suntest multispectral irradiation system and production rates predicted from the modeled AQY spectra (see Johannessen and Miller (2001) for details); n denotes the number of measurements (including replicate irradiations and dark controls, all analyzed in triplicate). Corresponding spectra are shown in Fig. 2. a Data interpolated from samples with similar salinities. b Pooled spectrum for Delaware Estuary (excluding S = 0.1 sample).

3. Results and discussion 3.1. CO2 AQY spectra Apparent quantum yield spectra for CO2 photoproduction are presented in Fig. 2A, with the corresponding fit parameters (m1 and m2) given in Table 1. The agreement between rates measured in the different cutoff filter exposures and rates predicted from AQY spectra was very good in all cases (r2 = 0.90 to 0.99), except for the salinity (S) = 3 sample (r2 = 0.69). Although not evaluated in our AQY experiments, loss of CDOM absorbance (i.e., photochemical fading) likely occurred in irradiations employing the short wavelength cutoff filters. Using photochemical fading coefficients determined for these samples in another study, the maximum fading for our most colored sample (S = 0.1) under the short wavelength cutoff filter is approximately 15% (Cedric Fichot, personal communication). By not accounting for fading, our Qa values are overestimated, resulting in an underestimation of AQYs as well as an unknown error in the AQY spectral slope (i.e., m1 and m2) due to the wavelength dependence of photobleaching. Using a simple spectral model that compares calculated CO2 production using the measured irradiance under our 280 nm cutoff filter, a CDOM spectrum from our S = 0.1 sample that is unfaded and “numerically faded” by 15% at each wavelength, and our AQY spectrum for this sample, we estimate that the error in the AQY determined without accounting for this degree of fading is less than 10%.

Quantum yield spectra for stations in the Delaware Estuary with S N 0.1 (Fig. 2A) were not statistically different (i.e., the 95% confidence intervals of the fitting parameters for the individual spectra overlapped; Table 1). By comparison, the AQY spectrum for the lowest salinity, riverine sample (S = 0.1) was significantly higher (with smaller values of m1 and m2). As such, CO2 was produced with a much higher photochemical efficiency by DOM at the lowest salinity station compared to the rest of the estuary. This higher efficiency was likely due to some components of DOM originating from the Delaware River that were rapidly removed from the estuary during transport. The distribution of CDOM (a350) along the salinity gradient, which showed a large decrease below S = 1 (Fig. 2B), provides evidence of rapid removal of CDOM at low salinity. Since there was no significant difference observed in the photochemical efficiency of CDOM to produce CO2 throughout the estuary, except for S = 0.1, a pooled AQY spectrum (r2 = 0.92) was calculated by applying a single exponential fit to all CO2 production and irradiance data at S N 0.1. The AQY spectrum was nearly constant throughout the estuary, indicating that dilution of terrestrialderived CDOM during estuarine transport reduced the quantity of CO2 precursors without significantly changing CDOM quality. Pooled AQYs for CO2 photoproduction in the Delaware Estuary were compared to values reported for other estuarine, inshore, and fresh waters (Fig. 3A). Published values varied by roughly one to two orders of magnitude. For example, AQY at 350 nm ranged from 5.7 × 10− 5 in a fjord system (Johannessen et al., 2007) to 2.0 × 10− 3 in a coastal river

Fig. 2. (A) Apparent quantum yield spectra for the photochemical production of CO2 in six samples collected along the salinity (S) gradient in the Delaware Estuary. Fit parameters for these spectra are given in Table 1. (B) Distribution of absorption coefficient at 350 nm (a350) as a function of salinity.

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15

Fig. 3. Comparison of our CO2 AQY spectra with published values from other studies of (A) estuarine (S06, Skalski, 2006; J07, Johannessen et al., 2007; B06, Bélanger et al., 2006), inshore (J01, Johannessen and Miller, 2001), and fresh waters (G98, Gao and Zepp, 1998; V00, Vähätalo et al., 2000) and (B) coastal (B06, Bélanger et al., 2006; J01, Johannessen and Miller, 2001) and open ocean waters (J01, Johannessen and Miller, 2001). Sample details, equations, and where appropriate, fit parameters for these spectra are given in Table 2. Our CO2 AQY data are presented as two spectra, S = 0.1 (solid line) and a pooled spectrum from all other data obtained in the Delaware Estuary (dotted line).

(Gao and Zepp, 1998). The S = 0.1 and pooled spectra fall within this range, with values of 5.6 × 10− 4 and 1.3 × 10− 4 at 350 nm, respectively. Our pooled Delaware Estuary CO2 AQY spectrum is similar in magnitude but lower than the pooled inshore spectrum presented by Johannessen and Miller (2001). Corresponding CO2 rates calculated with Johannessen and Miller's inshore AQY spectrum are on average twice those calculated with our pooled Delaware Estuary spectrum, although fitting parameters are within the 80% CI of those of the inshore spectrum. While few studies have been conducted with coastal and open ocean waters, most published spectra fall within this same range (Fig. 3B). When considered as a whole, the dataset of published CO2 AQY values show a great deal of variability and no clear trend with water type (e.g., CO2 AQY did not systematically increase or decrease with decreasing CDOM absorbance) or temperature. In addition to comparing AQY at individual wavelengths, AQY curves were evaluated by comparing fitting parameters and “best-fit” equations from the literature (Table 2). Our “best-fit” parameters (m1 and m2) are directly comparable with other studies that employed the same exponential equation to model data. Clear differences in fitting parameter values are seen, especially for m2 which varied by an order of magnitude. However, the mechanistic significance of these variations is not known and will require an understanding of the underlying molecular basis of CO2 photoproduction from CDOM, which is currently lacking. These differences likely represent changes

in CO2-producing mechanisms and/or CDOM-specific chromophores that alter the absorption of radiation relative to CO2 photoproduction. Although CO2 AQY spectra are generally assumed to be exponential and an exponential fit captures much of the observed variability in the AQY spectra, a purely exponential function may not always provide the best fit of CO2 AQY spectra. Indeed, there are no chemical or physical principles that would indicate a priori that AQY spectra should fit an exponential function. Exponential fitting is based on experimental evidence that the shape of AQY spectra are strongly influenced by the corresponding absorption spectra, which generally decrease exponentially with increasing wavelength. Bélanger et al. (2006) found that a quasi-exponential model using three fitting parameters gave a better fit to their experimental data compared to a two parameter exponential fit, thus resulting in a different spectral shape. More work is needed to evaluate these differences, especially at longer wavelengths where the largest uncertainty in AQYs exits due to the combination of vanishingly small absorbance values, characteristic of “blue” oligotrophic waters, and lower energy photons available for photochemistry. 3.2. CO AQY spectra Apparent quantum yield spectra for CO photoproduction are shown in Fig. 4 and the corresponding AQY values are given in Table 3. Carbon monoxide AQY decreased with increasing salinity across the entire

Table 2 Equations and sample details, including irradiation temperatures, for CO2 apparent quantum yield spectra given in the literature. Study site Medway Harbour Estuary Saanich Inlet Mackenzie Estuary Inshore Admundsen Gulf Coastal Open Ocean Humic Lake

Salinity

T (°C)

Equation −(m1 + m2(λ − 290))

m1

m2

r2

Reference

0.96

Skalski (2006) (S06) Skalski (2006) (S06) Johannessen et al. (2007) (J07) Bélanger et al. (2006) (B06)

ϕ(λ) = e ϕ(λ) = e −(m1 + m2(λ − 290)) ϕ(λ) = e −(m1 + m2(λ − 290)) ϕ(λ) = (4.9 × 10− 6)e(352/(λ − 224))

5.8 (± 0.2) 5.0–8.5 7.2

0.021 (± 0.003) 0.004–0.03 0.04

0.92

8

25 25 18 0

S b 31 31 31 – 35 35

27 0 27 27

ϕ(λ) = e−(m1 + m2(λ − 290)) ϕ(λ) = (6.7 × 10− 8)e(1538/(λ − 111)) ϕ(λ) = e −(m1 + m2(λ − 290)) ϕ(λ) = e −(m1 + m2(λ − 290)) ϕ(λ) = 7.52 × 10(− 0.0122λ)

7 (±1)

0.03 (± 0.03)

0.83

6 (±1) 5.5 (± 0.7)

0.01 (± 0.02) 0.009 (± 0.008)

0.82 0.93

14 0 – 35

Johannessen and Miller (2001) (J01) Bélanger et al. (2006) (B06) Johannessen and Miller (2001) (J01) Johannessen and Miller (2001) (J01) Vähätalo et al. (2000) (V00)

Apparent quantum yield fit parameters, m1 and m2, and r 2 values are included for data fit to ϕ(λ) = e−(m1 + m2(λ − 290)); values in parentheses are 95% confidence intervals for m1 and m2. Fit parameter data for our Delaware Estuary samples are given in Table 1. The corresponding spectra are shown in Fig. 3.

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Fig. 4. Apparent quantum yield spectra for the photochemical production of CO in samples collected along the salinity gradient in the Delaware Estuary. AQY data were obtained at individual wavelengths using a monochromatic light source. Error bars indicate the standard deviation from analysis of replicate samples.

wavelength range, except at 290 and 300 nm where AQYs for S= 13 and S = 21 were not significantly different. In agreement with our CO2 data, CO was produced with a higher photochemical efficiency at the S = 0.1 station where the DOM pool is comprised of riverine material. However, unlike CO2, differences in CO AQY were observed between the higher salinity samples (Fig. 5). For example, the AQY at 330 nm decreased by nearly 30% from 3.2 ×10− 5 at S =13 to 2.3 × 10− 5 at S = 21. Zhang et al. (2006) observed a similar general trend of decreasing CO AQY with increasing salinity in the St. Lawrence Estuary system as did Xie et al. (2009) in the Mackenzie River Estuary (Fig. 6A). In agreement with these findings, CO AQYs were linearly related to a330 (r2 =0.99). In contrast to CO, we found no significant trend in CO2 AQY at 330 nm. Values ranged from 2.2 ×10− 4 to 2.8× 10− 4 between S =3 and S = 21 (n= 5), with an average AQY of 2.4 ×10− 4. The difference in salinity trends for CO2 and CO suggest different source functions for photoproduced CO2 and CO. CDOM behaved conservatively throughout most of the estuary and if riverine CDOM were simply diluted along the estuarine gradient, AQYs

Table 3 Apparent quantum yields for CO photoproduction (mol CO mol quanta− 1) determined using a monochromatic irradiation system. λ (nm)

290 ± 5 300 ± 5 310 ± 5 320 ± 5 330 ± 5 340 ± 5 350 ± 5 360 ± 5 370 ± 5 380 ± 5 390 ± 5 400 ± 10 410 ± 10 420 ± 10 430 ± 10 450 ± 10 470 ± 10 490 ± 10

Apparent Quantum Yield (×10− 5) S = 0.1

S = 13

S = 21

32 (± 3) 19.4 (± 0.6) 16.2 (± 0.8) 11.2 (± 0.1) 7.8 (± 0.5) 4.1 (± 0.01) 3.6 (± 0.4) 3.6 (± 0.3) 2.2 (± 0.5) 2.1 (± 0.2) 1.9 (± 0.06)

12 9 7.1 4.6 3.2 2.3 1.6 1.2 0.89 0.63 0.64 0.28 0.34

12.3 (± 0.9) 8.0 (± 0.8) 5.6 (± 0.4) 3.5 (± 0.6) 2.3 (± 0.3) 1.3 (± 0.1) 1.0 (± 0.1) 0.73 (± 0.09) 0.52 (± 0.08) 0.34 (± 0.07)

2.4 (± 0.2)

(± 1) (± 1) (± 0.4) (± 0.3) (± 0.2) (± 0.2) (± 0.2) (± 0.1) (± 0.07) (± 0.09) (± 0.06) (± 0.02) (± 0.01)

0.19 (± 0.02) 0.12 (± 0.01)

2.2 (± 0.02) 2.3 2.2 (± 0.1) 2.6 (± 0.1)

0.25 (± 0.02) 0.20 (± 0.02)

Values in parentheses are standard deviations based on duplicate sample analyses. Corresponding spectra are shown in Fig. 4. Data were fit with simple exponential functions as presented in Table 4.

Fig. 5. Comparison of CO2 (circles) and CO (squares) apparent quantum yields at 330 nm along the estuarine salinity gradient. Error bars represent the standard deviation determined by propagation of error from the analysis of replicate samples for CO AQY. An error of ±20% was used for CO2 AQY.

would remain constant with respect to salinity (as was observed for CO2) because photoproduction is proportional to CDOM absorption. However, the decrease in CO AQY that we observed with increasing salinity indicates that the rate of CO photoproduction dropped off more rapidly than CDOM absorption. This suggests that there is preferential removal of terrestrial CO precursors during mixing, relative to the chromophores that control the overall CDOM absorbance and CO2 photoproduction. It is also possible that the decrease in CO AQY with increasing salinity reflects the presence of less photoreactive, autochthonous, marine-derived DOM. Ionic strength or pH related changes in DOM conformation or complexation (Minor et al. 2006) may have also contributed to the observed trend in CO AQY. Our CO AQY spectra for the Delaware Estuary were comparable to published spectra from other estuarine and fresh water studies (Fig. 6A, Table 4). Using 350 nm as an example, CO AQYs ranged from 1.5 × 10− 5 in the Gulf outside the St. Lawrence Estuary (Zhang et al., 2006) to 6.8 × 10− 5 in a coastal river (Gao and Zepp, 1998), compared to 1.0 × 10− 5 to 3.6 × 10− 5 in the Delaware Estuary. Our fresh water Delaware CO AQYs are among the highest values reported and are comparable to values found in other rivers (Valentine and Zepp, 1993; Gao and Zepp, 1998) and the Tyne Estuary (Stubbins, 2001). The S = 13 sample closely matched that seen in the Tamar (Stubbins, 2001), St. Lawrence (Zhang et al., 2006), and Mackenzie (Xie et al., 2009) estuaries. The CO AQY for the S = 21 sample (near the mouth of the Delaware Estuary) was lower than published AQYs from other estuaries, and showed better agreement with coastal and open ocean samples (Zafiriou et al., 2003; Stubbins et al., 2006; Zhang et al., 2006; Ziolkowski and Miller, 2007) (Fig. 6B). Differences in CO AQY discussed above and in Table 4 are likely not due to temperature. Zhang et al. (2006) reported that CO AQYs were temperature dependent in the St. Lawrence Estuary. For comparison, the AQYs of Zhang et al. (2006) and Xie et al. (2009) were temperature corrected to match our experimental conditions (i.e., 20 °C) (Fig. 6A). Adjusting the data of Zhang et al. (2006) from 24 to 20 °C, resulted in a 5 to 10% decrease in AQYs at 350 nm (e.g., AQY decreased from 2.7 × 10− 5 to 2.4 × 10− 5 for the zero salinity St. Lawrence Estuary sample). Given the lower experimental temperatures (−0.5 to 18 °C) of Xie et al. (2009), temperature correction increased AQYs by 5 to 80% at 350 nm (e.g., AQY increased from 2.1 × 10− 5 to 2.2 × 10− 5 for the Mackenzie River sample with a salinity of 0.1). The CO AQYs in the low salinity region of these two estuaries were still lower than we observed in the Delaware Estuary at the same temperature (3.6× 10− 5 at 350 nm).

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Fig. 6. Comparison of Delaware Estuary CO AQY spectra with published values from other studies of (A) estuarine (solid lines, Xie et al., 2009; dotted lines, Zhang et al., 2006; open triangles, Stubbins, 2001) and fresh waters (open squares, Gao and Zepp, 1998; open circles, Valentine and Zepp, 1993) and (B) coastal and open ocean waters (solid lines, Ziolkowski and Miller, 2007; dotted line, Zafiriou et al., 2003; dashed line, Stubbins et al., 2006; dashed-dotted line, Zhang et al., 2006). Our Delaware Estuary data are denoted by filled circles (S = 0.1), filled triangles (S = 13), and filled squares (S = 21). Sample details and equations (of plotted lines) from the literature are given in Table 4. For purposes of comparison, AQY spectra in Xie et al. (2009) and Zhang et al. (2006) were corrected to 20 °C according to the temperature relationship of Zhang et al. (2006).

Thus, even after accounting for this temperature difference, there are spectral differences in CO AQYs; albeit the applicability of this temperature-AQY relationship (Zhang et al., 2006) to other waters including the Mackenzie River is unknown.

3.3. AQY spectral shape Apparent quantum yield spectra showed that the photochemical efficiency of CO2 and CO production were highest for UV-B radiation (280 to 320 nm) and decreased exponentially with increasing wavelength (Figs. 2A and 4). This spectral dependence has been observed previously for both CO2 and CO (e.g., Gao and Zepp, 1998), as

well as for other CDOM photooxidation products (e.g., hydrogen peroxide, Andrews et al., 2000). Our CO2 AQY spectra were generated by fitting an exponential equation to CO2 production data, as has been done in a number of other studies (e.g., Vähätalo et al., 2000; Johannessen and Miller, 2001; Johannessen et al., 2007). All of these studies employed simultaneous polychromatic irradiations of multiple samples to determine AQY for CO2 photoproduction. This high irradiation flux, relatively short irradiation method can overcome some difficulties associated with the determination of monochromatic CO2 AQY (e.g., lower production rates, longer irradiation times), especially in relatively low DOM marine waters where these problems become exacerbated. Measurement of AQY using monochromatic irradiations

Table 4 Equations and sample details, including irradiation temperature, for CO apparent quantum yield spectra given in the literature. Study site

Sample

T (°C)

Equation

Reference

Delaware Estuary

S = 0.1

20

this study

S = 13

20

S = 21

20

SL, S = 0 SL, S = 5 SL, S = 25 SL, S = 30 MR, S = 0.1 MR, S = 2 MR, S = 8 MR, S = 26 Coastal Coastal

24 24 24 24 18 13 12 9 20 20

ϕ(λ = 290 − 370) = 9.25 e(− 0.036λ), r 2 = 0.99 ϕ(λ = 370 − 490) = 0.22 × 10− 4 ϕ(λ = 290 − 410) = 1.03 e(− 0.031λ), r 2 = 0.99 ϕ(λ = 410 − 450) = 0.0010 e(− 0.014λ), r 2 = 0.99 ϕ(λ = 290 − 380) = 20.2 e(− 0.041λ), r 2 = 1.00 ϕ(λ = 380 − 420) = 0.08 e(− 0.026λ), r 2 = 1.00 ϕ(λ) = 4.00 × 10− 10 e(4894.5/(λ + 90.37)) ϕ(λ) = 6.74 × 10− 11 e(7332.9/(λ + 205.5)) ϕ(λ) = 6.20 × 10− 11 e(5901.4/(λ + 119.2)) ϕ(λ) = 8.77 × 10− 11 e(4854.9/(λ + 53.97)) ϕ(λ) = 9.00 × 10− 8 e(1233.5/(λ − 123.79)) ϕ(λ) = 7.78 × 10− 8 e(1215.4/(λ − 126.29)) ϕ(λ) = 4.60 × 10− 8 e(1436.5/(λ − 106.53)) ϕ(λ) = 3.28 × 10− 9 e(2509.7/(λ − 46.31)) ϕ(λ) = e −(9.035 + 0.036(λ − 290)) ϕ(λ) = e(−(9.134 + 0.0425(λ − 290))) + e(−(11.316 + 0.0142(λ − 290)))

Open ocean Open ocean

20 5–30

ϕ(λ) = e(−(9.688 + 0.0513(λ − 290))) + e(−(11.507 + 0.0131(λ − 290))) ϕ(λ b 360) = 5.78 × 10− 6 e(− 0.050(λ − 360)) − 6.99 × 10− 7 ϕ(λ N 360) = 5.24 × 10− 6 e(− 0.0229(λ − 360)) ϕ(λ b 345) = 2.70 × 1023 × λ − 11.2 ϕ(λ N 345) = 2.75 × 109 × λ − 5.65 ϕ(λ) = 3.40 × 10− 11 e(4690/(λ + 22.10))

Ziolkowski and Miller (2007) (Z07) Zafiriou et al. (2003) (Z03)

St. Lawrence Estuary (SL)

Mackenzie River Estuary (MR)

Damariscotta Estuary Gulf of Maine and NW Atlantic Sargasso Sea Pacific Atlantic Meridional Transect Atlantic Ocean off Cabot Strait

Open ocean Open ocean

Corresponding spectra are shown in Fig. 6.

24

Zhang et al. (2006) (Z06)

Xie et al. (2009) (X09)

Ziolkowski and Miller (2007) (Z07) Ziolkowski and Miller (2007) (Z07)

Stubbins et al. (2006) (S06) Zhang et al. (2006) (Z06)

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over relatively narrow bandwidths has been limited to a single study focused on high CDOM fresh waters (Gao and Zepp, 1998). The polychromatic approach, however, has its own limitations. Key among them is the necessity of assuming a priori a specific mathematical equation to describe the AQY spectral shape that best fits the observed rate data. To date, CO2 AQY spectral data are generally adequately fit by a simple exponential function and investigation into the use of other functions (e.g., bi-exponentials, polynomials, exponential-linear combinations, etc.) has not resulted in significantly better r2 values (Johannessen and Miller, 2001). Larger AQY data sets for CO2 photoproduction with increased wavelength resolution may support a more robust fitting treatment in the future. As an independent test of the use of an exponential function to describe the CO2 AQY, we directly compared predicted wavelengthintegrated sunlight production rates of CO2 (using our CO2 AQY spectra) to CO2 photochemical production rates measured in deck incubations with the same water. Results of this study, discussed in detail in Section 3.5, showed that predicted and measured rates were not statistically different to the level of our analytical capabilities. This indicates that a simple exponential function for AQY is appropriate for use in estimating the photochemical production of CO2 in the Delaware Estuary, but by no means precludes the need for further intercomparison studies as an independent check of the robustness of the exponential fit in other aquatic environments. Unlike CO2, CO AQY spectra were obtained using relatively narrow bandwidth monochromatic irradiations. Therefore, it was possible to determine how well data were described by an exponential fit. Log transformed CO AQY spectra were linear across the entire wavelength range for the S = 13 (r2 = 0.97) and S = 21 (r2 = 0.99) samples as expected for an exponential fit. However, the S = 0.1 sample clearly was not adequately described by a single exponential fit (r2 = 0.49). For this low salinity sample, the AQY remained constant (at a value of ~0.22× 10− 4) at wavelengths between 370 and 490 nm (Fig. 4), rather than dropping off as seen in the AQY spectra for higher salinity samples. Closer inspection of the S = 13 data showed a similar, but subtle leveling off at long wavelengths. Data from the higher salinity samples were better described by fitting with two exponential functions (i.e., separately fitting two wavelength regions). Similar findings have been reported for open ocean CO AQY spectra (Kettle, 1994; Zafiriou et al., 2003; Stubbins et al., 2006). Ziolkowski and Miller (2007) adopted a “two-part aggregate” exponential approach to fit CO data obtained from multi-spectral irradiations. A quasi-exponential fit was used for multispectral irradiation data in the St. Lawrence (Zhang et al., 2006) and Mackenzie River (Xie et al., 2009) estuaries. While CO and CO2 AQY spectra in the Delaware Estuary were generally well described by an exponential function, comparison of fitting parameters, rate and AQY ratios indicated fundamental differences. For the purpose of direct comparison to CO2 AQY spectra, CO AQY data were fit to Eq. (4) (note that a single exponential function was used to compare our CO AQY to published CO AQY spectra, Table 4). Values of m1 for CO were 8.07, 9.03 and 9.01 for S = 0.1, 13 and 21, respectively, which were approximately 20% higher on average than m1 for CO2 (Table 1). In both cases, m1 was lowest for the low salinity sample (S = 0.1), while there was no difference in m1 values for the higher salinity samples (Tables 1 and 4). While differences were noted for m1, m2 values for CO (range 0.03 to 0.04) were essentially the same as observed for CO2 (Table 1, range: 0.02 to 0.04), indicating a similar spectral shape. 3.4. Action spectra When discussing spectral AQYs, it is important to consider the relevant wavelength regions for photochemical production of CO2 and CO in natural waters. While AQY (Figs. 2A and 4) and sample absorption (Fig. 7A) were highest in the UV-B, CO2 and CO photoproduction primarily occurred at longer wavelengths due to the increased photon

flux for solar radiation at longer wavelengths in the UV-A (Fig. 7B). Action spectra for CO2 (Fig. 7C) and CO (Fig. 7D) were obtained by calculating the predicted spectral production according to Eq. (1) from the sample absorption, solar irradiance, and AQY. In general, action spectra for CO2 and CO were similar with a non Gaussian shape, a maximum in the vicinity of 330 nm and a long production tail in the visible. The shape of the CO2 (Fig. 7C) and CO (Fig. 7D) action spectra are very similar to that of the inshore CO2 spectrum of Johannessen (2000) and the CO spectra of Ziolkowski (2000) and Zhang et al. (2006). The main difference between Delaware Estuary spectra was that the spectral production was substantially higher for CO2 compared to CO. The area under the action spectrum curve was calculated for CO2 and CO to determine the total daily production and the % contribution of the different spectral regions to total daily photoproduction rates. Total CO2 production rates were 7.2, 1.6, and 2.1 µM d− 1 for the S = 0.1, S = 13, and S = 21 samples, respectively. The spectral contributions for the three different samples were nearly the same, with ~80% of the total production in the UV-A (320 to 400 nm) and ~20% in the UV-B (290 to 320 nm). A small amount of production (b5%) was also observed between 400 and 600 nm (Fig. 7C). In contrast, CO exhibited changes in AQY along the salinity gradient (Fig. 4) that resulted in some spectral differences in action spectra (Fig. 7D). UV-A accounted for 60, 73 and 70% of CO production, while UV-B was responsible for 18, 22, and 28% in the S = 0.1, S = 13 and S = 21 samples, respectively. Total CO production rates were 1.2, 0.3, and 0.1 µM d− 1 for the S = 0.1, S = 13, and S = 21 samples, respectively. The main difference between CO spectra was seen in the visible portion of the solar spectrum where ~20% of the total production was observed between 400 and 490 nm in the 0.1 salinity sample compared to b5% in the higher salinity samples. Despite these spectral differences, the maximum production of both CO2 and CO occurred at ~330 nm with 50 to 80% of the total production observed between 310 and 350 nm. This similarity points to the importance of variations in the solar spectrum (i.e., ozone levels and cloud cover) for controlling photochemical spectral responses, as the action spectrum for many photochemical species is dominated by this spectral region (e.g., Blough, 2001). Other factors such as phytoplankton and particulate material will also contribute to the total light absorption and must be considered when extrapolating AQYs to the water column to predict photochemical production rates (Bélanger et al. 2008). 3.5. Accuracy of CO2 AQY predictions Predicted rates of photochemical CO2 production calculated from Eq. (1), employing the appropriate quantum yields, sample absorption spectra, and solar irradiance spectra, were compared to measured shipboard rates. The predicted CO2 production rate was highest at the low salinity station (15 ± 6 μM d− 1) compared to all other stations where the predicted rate average was ~2 μM d− 1 (Fig. 8A). Predicted rates showed excellent agreement with measured rates at all salinities, except for S = 0.1. In this lowest salinity sample, the predicted rate was a factor of four higher than the observed rate (3.8± 0.1 μM d− 1), possibly due to an overestimation of AQY or to an underestimation of the measured rate at this salinity. An underestimation of the measured rate is possible, since the rate at S = 0.1 was expected to be much higher than the rate determined at S = 3 and not nearly the same as was observed (see Fig. 8A). It is more difficult to ascertain if AQY and corresponding rates were overestimated in the S = 0.1 sample. However, several lines of evidence suggest that S = 0.1 AQY should be high including down estuary trends in CDOM (Fig. 2B) and CO photoproduction (Fig. 5). If the S = 0.1 sample contained a low concentration of a photochemically active compound with a very high AQY for CO2 production, it would contribute disproportionally to CO2 production relative to the CDOM spectrum, explaining the generally higher CO2 production for this sample with a disproportionately smaller increase in CDOM absorption. Because the AQY irradiations intentionally used a greater integrated UV

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Fig. 7. (A) Absorption coefficient spectra, (B) time-integrated solar irradiance, and daily (C) CO2 and (D) CO photoproduction rates as a function of wavelength at three stations in the Delaware Estuary. The solar irradiance was measured from 9:30 to 17:00 local time on 26 Jun 2002 (at 38.8° N). Integrating the area under the curve from 290 to 600 nm gives a total daily irradiance of 27.0 mol quanta m− 2 (1.2 mol quanta m− 2 from 310 to 350 nm). Photoproduction rates were calculated using this irradiance spectrum and AQY spectra (shown in Figs. 2A and 4) to predict the expected production rate at each wavelength (according to Eq. (1)). The action spectra presented in (D) were modeled by fitting the CO AQY data (denoted by circles) with the equations given in Table 3.

Fig. 8. (A) Predicted (filled diamonds) and measured (open diamonds) daily CO2 photoproduction rates as a function of salinity and (B) correlation between predicted and measured daily CO2 photoproduction rates. Predicted CO2 production rates were calculated from individual AQY spectra. Error bars represent the standard deviation determined by propagation of error from the analysis of replicate samples for measured CO2 photoproduction while an overall error of ±40% was used for predicted production. The dashed line in panel B represents a 1:1 ratio between measured and predicted photoproduction rates. The solid line is a linear regression of the data, excluding the low salinity sample (open triangle) (Slope = 0.9 ± 0.2, y-intercept = − 0.1 ± 0.5, r 2 = 0.81), and the dotted lines denote the 95% confidence interval. Predicted and measured rates were not significantly different, based on a paired Student t-test (p b 0.05).

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photon flux (to maximize CO2 analytical precision) than was present in the deck incubations (by roughly a factor of two), it is possible that the AQY experiments captured a much greater contribution to the CO2 production by this efficient chromophore(s) than did the deck incubations. The slope of the regression between the predicted and observed production, excluding the S = 0.1 sample, was not significantly different from one (slopepooled = 0.9 ± 0.2) and the y-intercept (−0.1 ± 0.5) was not significantly different from zero. This indicates that neither the possible disparity in CO2 production due to UV irradiance differences between the AQY and deck incubations nor the underestimation of AQY due to fading created a significant systematic error in our ability to determine AQY spectra appropriate for modeling results from the deck incubations. Comparison of predicted and measured rates demonstrated that apparent quantum yield spectra accurately predicted CO2 photoproduction rates in the Delaware Estuary, since the modeled CO2 production rates agreed with measured rates within ±10%, which is within the error of using a statistical curve fitting method to determine AQYs. Errors inherent in the use of multispectrally determined AQYs to estimate in situ rates include a combination of CO2 analysis, irradiance, and CDOM spectral measurement errors, as well as uncertainties associated with the solar irradiance used to drive the production model (Johannessen and Miller, 2001). The average error associated with directly measured photoproduction rates is ± 10%, due to errors associated with sampling and CO2 analysis (White et al., 2008). 3.6. Comparison of CO2 and CO AQY Most CO2:CO photoproduction ratios reported in the literature are based on studies of terrestrially influenced waters (Miller and Zepp, 1995; Miller and Moran, 1997; Gao and Zepp, 1998) with an average ratio of about 15 to 20, although some variability has been observed. Miller and Zepp (1995) measured ratios ranging from 17 in the Mississippi River Plume to 65 in Sapelo Island Marsh water. They also observed that this ratio decreased with irradiation time. Ratios for humic substances isolated from Sapelo Island Marsh water ranged from 6 to 25 (Miller and Moran, 1997). Johannessen (2000) used CO2 and CO AQY spectra from the literature to calculate CO2:CO photoproduction ratios for inshore, coastal, and open ocean waters of 2, 15, and 63, respectively. This variability suggests that a single ratio may not reasonably describe the relative photoproduction rates of these two compounds in natural waters. The mechanisms involved in the formation of CO2 and CO are not well understood, but likely reflect the contribution of multiple processes. The participation of carboxyl and carbonyl groups have been recognized (Miles and Brezonik, 1981; Redden, 1983; Gao and Zepp, 1998; Pos et al., 1998) and a relationship between DOM aromaticity and CO photoproduction has been identified (Vähätalo et al. 1999; Xie et al. 2004; Stubbins et al., 2008) although contradictory evidence exists (e.g., Zhang et al. 2006). While more mechanistic studies are needed, our work suggests that CO2 and CO photoproduction likely arise from different pathways, even though respective AQY spectra are similar reflecting similar wavelength dependences for both products. Variations in AQY ratios at single wavelengths indicated differences between CO2 and CO photoproduction in samples collected at different salinities along the estuarine gradient. For example, the AQY ratio for CO2:CO at 300 nm was 4, 6, and 9 for S = 0.1, 13, and 21, respectively, while ratios at 350 nm were 8, 6, and 18. Differences in AQY spectral slopes (vide supra) and ratios for CO2 and CO photoproduction at individual wavelengths are consistent with the involvement of fundamentally different mechanisms and chromophores in the formation of these two photoproducts. Ratios for the rates of CO2:CO photoproduction (from broadband irradiation) also showed a change in the estuary, with low values at the low salinity stations (5 at S = 0.1 and 6 at S = 13) and a higher value (15) at

S = 21. These low salinity ratios are lower than the reported, average ratios of 15 to 20 (Miller and Zepp, 1995; Miller and Moran, 1997; Gao and Zepp, 1998) but show good agreement with ratios of 7 to 12 reported for Mackenzie Estuary samples (Xie et al., 2009). The general trend of increasing CO2:CO ratios with salinity is consistent with the observed trends in AQYs in the Delaware Estuary. Carbon monoxide AQYs decreased with increasing salinity while CO2 AQYs did not change significantly. Therefore, changes in the CO2:CO ratio were controlled by the CO AQY spectra (Fig. 5). Our ratios reflect not only a decrease in the photochemical efficiency of CDOM to produce CO along the estuarine gradient, but also subtle differences in CDOM character (in the lower versus upper estuary) that influenced the wavelength dependence of CO photoproduction (i.e., changes in both absolute CO AQYs and CO AQY spectral slopes). Such differences were not observed in CO2 AQYs or bulk CDOM (i.e., a350). 4. Conclusions The action spectra for the photochemical production of CO2 and CO were quite similar in their spectral shape in the Delaware Estuary owing to the importance of CDOM absorbance and the incident light field in controlling the shape of the action spectra. However, similarities among the action spectra belie an important difference. The efficiency of riverine CDOM to produce CO2 was not affected by transport through the Delaware Estuary, whereas the chromophores involved in CO productions were preferentially depleted. The later finding strongly suggests that different precursors and mechanisms were involved in the production of these two compounds. Apparent quantum yield spectra accurately predicted measured CO2 production rates in the Delaware Estuary, supporting the further development and use of quantum yields to calculate regional-scale photochemical fluxes. Further work is needed to establish whether the spectra presented in this study are appropriate for other inshore coastal systems in order to improve the accuracy of photochemical flux models. Additional studies are also warranted to evaluate whether AQYs determined in filtered samples can predict in situ production rates, particularly in cases where CDOM does not control the UV light field (e.g., high detrital, inorganic particulate, or chlorophyll environments). Acknowledgments We thank the captain and crew of the R/V Endeavor for their support of this project. We also thank Dr. Oliver Zafiriou for use of his CO analyzer and Dr. Kazuhiko Takeda for advice regarding the CO experiments, George Westby for measuring sample absorbance spectra, Andrew Davis for acquisition of spectroradiometer data during the R/V Endeavor cruise, and Dr. Aron Stubbins and two anonymous reviewers for critically evaluating this document. This study was supported by the National Science Foundation Chemical Oceanography Program (OCE-0196220 and OCE-0096426 to KM; OCE-0096413 to DJK), the Office of Naval Research Optical and Biological Oceanography Program (N000140610219 to WLM), and the Canadian National Science and Engineering Council (C-SOLAS Network to WLM). Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation. This work was also supported by NASA Headquarters under the Earth System Science Fellowship Grant (NGT5-30431, EMW). References Andrews, S.S., Caron, S., Zafiriou, O.C., 2000. Photochemical oxygen consumption in marine waters: a major sink for colored dissolved organic matter? Limnolology and Oceangraphy 45, 267–277. Bélanger, S., Babin, M., Larouche, P., 2008. An empirical ocean color algorithm for estimating the contribution of chromophoric dissolved organic matter to total light absorption in optically complex waters. Journal of Geophysical Research 113, C04027. doi:10.1029/2007JC004436.

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