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Inherent optical properties of the ocean: retrieval of the absorption coefficient of chromophoric dissolved organic matter from airborne laser spectral fluorescence measurements Frank E. Hoge, Anthony Vodacek, Robert N. Swift, James K. Yungel, and Neil V. Blough

The absorption coefficient of chromophoric dissolved organic matter 1CDOM2 at 355 nm has been retrieved from airborne laser-induced and water Raman-normalized CDOM fluorescence. Four combined airborne and ship field experiments have demonstrated that 112 the airborne CDOM fluorescence-to--water Raman ratio is linearly related to concurrent quinine-sulfate-standardized CDOM shipboard fluorescence measurements over a wide range of water masses 1coastal to blue water2; 122 the vicarious calibration of the airborne fluorosensor in units traceable to a fluorescence standard can be established and then maintained over an extended time period by tungsten lamp calibration; 132 the vicariously calibrated airborne CDOM fluorescence-to-water Raman ratio can be directly applied to previously developed shipboard fluorescence-to-absorption algorithms to retrieve CDOM absorption; and 142 the retrieval is not significantly affected by long-path multiple scattering, differences in attenuation at the excitation and emission wavelengths, or measurement in the 180° backscatter configuration. Airborne CDOM absorption measurements will find immediate application to 1a2 forward and inverse modeling of oceanic water-leaving radiance and 1b2 validation of satellite-retrieved products such as CDOM absorption.

1.

Introduction

Dissolved organic carbon 1DOC2 originates as marine and terrestrial biologic degradation products and is the largest pool of organic matter in the ocean.1 A variable portion of the total DOC pool is chromophoric dissolved organic matter 1CDOM2 that is measurable in situ by absorption2,3 and fluorescence.4 To date, remote measurement of CDOM has been limited to laser-induced fluorescence.5 Knowledge of the absorption coefficient of CDOM is crucial to studying several facets of carbon dynamics

F. E. Hoge is with the NASA Goddard Space Flight Center, Wallops Island Flight Facility, Wallops Island, Virginia 23337. A. Vodachek is with the Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742. R. N. Swift and J. K. Yungel are with the EG&G Washington Analytical Services Center, Inc., Wallops Flight Facility, Wallops Island, Virginia 23337. N. V. Blough is with the Department of Chemistry and Biochemistry, University of Maryland. Received 11 October 1994; revised manuscript received 8 May 1995. 0003-6935@95@307032-07$06.00@0. r 1995 Optical Society of America. 7032

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in surface waters. The absorption of CDOM affects the photosynthetically available radiation available to phytoplankton6 and interferes with satellite detection and measurement of phytoplankton pigments by means of ocean-color-inversion methods.2 CDOM absorption also affects the penetration of biologically harmful UV radiation,7 the photochemical production of reactive oxygen species,8 low-molecular-weight compounds,9 and trace gases.10–12 Recent research has established that it is possible to retrieve CDOM absorption coefficients from fluorescence measurements, which can be acquired without filtration and with greater sensitivity than absorption.4,13,14 This methodology has perhaps its greatest potential when employed with an airborne lidar. Airborne platforms can provide a scale of measurement in time and space that complements data obtained from a ship or a satellite. The feasibility of this retrieval methodology is supported by observations that CDOM fluorescence quantum yields fall within a narrow range over wide areas of the ocean,14 despite wide variation in DOC-specific absorption.15 Use of an appropriate fluorescence standard has been crucial to establishing the range of variation of

the CDOM fluorescence quantum yield in different aquatic environments over time. We use a procedure that incorporates the commonly used fluorescence standard, quinine sulfate,16 with an internal standard, the water Raman signal.4 Incorporation of the water Raman signal into the standardization process was prompted by our interest in comparing laboratory and in situ measurements of fluorescence with airborne lidar measurements, which rely on the water Raman signal to account for variation in the water-column attenuation and other parameters.17 Because normalization of fluorescence to the water Raman signal produces a unitless quantity, radiometric calibration of a laser fluorosensor is not strictly necessary. However, it is critical to correct for the spectral response of the detection system if the fluorescence and the Raman signal are determined at different wavelengths. In theory, normalization of fluorescence to the integrated water Raman signal should produce a 1:1 relation between data collected by any two spectrofluorometers. However, deviation from a 1:1 relation is typical and is due to the sensitivity of the Raman and fluorescence signals to uncorrected instrument polarization conditions, differences in the excitation and emission bandpasses used, and the angular orientation of the emission detector with respect to the excitation beam. Thus it is necessary to use a fluorescence standard to compare data from different in situ, laboratory, or airborne instruments. A direct implementation of a quinine sulfate standardization for a laser fluorosensor is difficult because the instrument is configured to stimulate and detect fluorescence and water Raman backscatter in an optically thick medium at a distance. Our approach to standardizing CDOM fluorescence data, such as that collected by NASA’s Airborne Oceanographic Lidar 1AOL2 was to use a vicarious calibration in which surface-water samples were collected concurrently with laser fluorosensor overflights. This was a straightforward process in which surface-station fluorescence was standardized against quinine sulfate and then regressed against the airborne data collected at or near the station site to yield a calibration factor for transformation of laser fluorosensor data to standard fluorescence units. Once the AOL data are in fluorescence units, a global or site-specific algorithm4 can be applied to retrieve the absorption coefficient. In our research we were able to show that a stable linear relation existed between surface-station data and airborne data collected with the AOL for four experiments conducted over a two-year period in the Gulf of Mexico, Monterey Bay, and the Middle Atlantic Bight. By combining the calibration factor with a previously defined algorithm for determining CDOM absorption from fluorescence,4 a remote measurement of CDOM absorption was made. The algorithm used was a refined version of the Middle Atlantic Bight algorithm given by Hoge et al.,4 using additional data from four cruises in the Middle Atlan-

tic Bight.

The updated algorithm is

aCDOM13552 5 0.232 3 Fn13552 1 0.049,

R2 5 0.94,

n 5 143, standard error 5 0.083,

112

where aCDOM13552 is the CDOM absorption coefficient at the excitation wavelength. Fn13552 is the ratio of the maximum CDOM fluorescence signal at 450 nm as normalized by the 404-nm water Raman spectral line height resulting from 355-nm excitation, relative to that of quinine sulfate standard solution examined under the same experimental conditions.4 Fn13552 is in normalized fluorescence units 1n.f.u.2, where a 0.01-mg L21 solution of quinine sulfate in 0.1 N H2SO4 is defined as having a fluorescence intensity of 10 n.f.u. Values of the CDOM absorption may be obtained at other wavelengths by using models of the well-known exponential decrease of the absorption with increasing wavelength.18 2.

Sample Handling and Instrumentation

Surface sampling and concurrent AOL overflights were performed in three coastal areas of the United States during 1992, 1993, and 1994. Samples were collected on 11 and 12 May 1992 from the mouth of Tampa Bay to the Loop Current in the Gulf of Mexico, 4 and 5 September 1992 in Monterey Bay, and 24 August 1993 and 25 and 26 April 1994 in the Middle Atlantic Bight 1from the mouth of Delaware Bay to the Sargasso Sea2. The locations of the surface stations corresponding in time and space to the aircraft overflights and the relevant portions of the flight lines are shown in Fig. 1. All samples were held in acid-washed amber glass or similar-type bottles and refrigerated until they were warmed to room temperature for the fluorescence and absorption determinations. Spectral absorption of samples 1filtered with 0.2-µm Baxter nylon or 0.2-µm Supor filters2 was determined with an HP 8451A, HP 8452, or Perkin Elmer Lambda 2 spectrophotometer with the method described by Blough et al.3 Absorbance was determined for samples in 5- or 10-cm fused-silica cells with Milli-Q water as the blank. Spectral absorbance A1l2 was transformed to spectral absorption coefficients aCDOM1l2 with the formula aCDOM1l2 5 2.303 3 A1l2@l, where l is the cell path length. Corrected fluorescence spectra resulting from 355-nm excitation were obtained with a Perkin Elmer LS 50, SLM SPF500C, or SLM AB2 spectrofluormeter. Samples were held in 1-cm fused-silica cells, and Milli-Q water was the blank. Spectra were normalized to the water Raman signal and standardized against quinine sulfate, as detailed in Hoge et al.4 The AOL and its ancillary remote-sensing systems were flown on a Goddard Space Flight Center P-3B aircraft. Details of the AOL instrumentation have been discussed in other papers dealing with various oceanographic applications.19–21 Below we discuss only the features of the system that are pertinent to understanding the calibration procedure. 20 October 1995 @ Vol. 34, No. 30 @ APPLIED OPTICS

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Fig. 1. Locations of the representative ship stations 1symbols2 and airborne flight lines 1solid lines2 at the three study sites. For clarity, not all the stations used in the calibration are plotted.

The excitation source used for measurement of CDOM fluorescence was a 10 pulse@s frequencytripled Nd:YAG laser 1355 nm2. The AOL spectral fluorescence detection system consists of a transmission grating that disperses the spectrum to 32 contiguous light guides; each light guide directs the received photons to 1 of 32 photomultiplier tubes 1PMT’s2. The analog output from each PMT was digitized over a 40-ns period beginning just before the arrival of the laser pulse at the water surface, thus integrating the signal from the upper ,4.5 m of the water column. 7034

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The spectral range covered is 353 to 713 nm, with a nominal resolution of ,11.25 nm per channel. Wavelength calibration was set before each mission by using the 589.3-nm line from a sodium lamp to provide equal signal levels in channels 21 and 22 of the spectrometer. The wavelength dispersion of the spectrometer is linear. The spectral response of the detection system was calibrated by viewing an integrating sphere with a known spectral output.22 During the sphere-calibration procedure, the PMT voltages were individually adjusted under computer control to match the system response to the known spectrum of the sphere. The calibration sphere was again viewed following each mission as a final check of the drift in the system response. Because the large 10.75-m-diameter2 sphere can only be used during ground-based calibration, a set of LED’s located within the AOL spectrometer is used in a procedure to transfer and maintain calibration during airborne missions. In this procedure, which is conducted immediately following ground calibration with the illuminating sphere, the precisely controlled output from the LED’s is used to illuminate all 32 of the PMT’s. The signal levels from the PMT’s are then recorded as a reference file. During the subsequent airborne mission the LED’s are viewed by the PMT’s at various elapsed time intervals. During postmission data processing the output from the individual PMT’s recorded during these in-mission calibration procedures are used along with the reference file to adjust for small drifts in sensitivity. During postflight data processing the 10 pulses@s airborne spectral data were block averaged over 1 or 2 s to reduce the volume of data as well as to increase the signal to noise. 1The aircraft crosses ,135 m of the ocean surface in 1 s.2 The data processing also included adjustment for system drift with the LED data and a dark-current subtraction. The CDOM fluorescence contribution to the channel centered on 404 nm 1containing the bulk of the water-Raman signal2 was removed by subtracting 0.6 times the peak CDOM fluorescence signal in the channel at 450 nm from the peak signal in the 404-nm channel. The factor 0.6 was derived from 178 laboratory spectral measurements for which the ratio of CDOM fluorescence at 404 nm to that at 450 nm was determined. These 178 laboratory determinations of seawatersample fluorescence were taken from seven separate field studies. Fluorescence values in all other channels were normalized to the water Raman signal. The CDOM spectral fluorescence F1l2 normalized to the water Raman signal R1l2 is F1l2@R1l2, a unitless quantity. The 355-nm induced CDOM fluorescence maximum is at 450 nm, and the water Raman maximum is at 404 nm so that the F@R ratio is specifically defined herein as F14502@R14042. 3.

Results

Figure 2 presents a test of the effect of filtration on the fluorescence of samples from the Middle Atlantic Bight and Monterey Bay. This test used sample

Fig. 2. Comparison of fluorescence from filtered and unfiltered samples taken in Monterey Bay and near Cape Hatteras. The Cape Hatteras region was sampled on 6 May 1992, and the data were analyzed with the same protocol used for the other sites.

handling and analysis procedures identical to those used for the calibration samples. The unfiltered samples yield essentially the same fluorescence as the filtered samples. Representative airborne laser-fluorosensor and laboratory fluorescence-emission spectra are given in Fig. 3. The raw airborne fluorescence spectra are shown in Fig. 3A, and the same spectra normalized by the water Raman peak height are given in Fig. 3B. The airborne data are 1- or 2-s averages from the

point of closest approach of the flight line to the surface stations. The spectrum having the highest fluorescence is from the Tampa Bay mouth region, and the lowest-fluorescence sample was from the blue water near the end of the flight line 1but not in the loop current2. The intermediate fluorescence spectrum was taken from a location between the two previous spectra. The calibration artifact in the airborne spectrum at ,530 nm is caused by a filter that is used to reject scatter from a second 1532-nm2 laser that is concurrently used to obtain phytoplankton pigment fluorescence spectra on an alternating-pulse basis.5 Surface-station samples taken near the same locations as the airborne spectra yielded the fluorescence spectra shown in Figs. 3C and 3D. Notice that the airborne spectral variability 1see Fig. 3A2 is dominated by the water Raman signal and not the CDOM fluorescence. In contrast the surface samples 1Fig. 3C2 analyzed in a 1-cm path-length cuvette show the water Raman signal 1sitting upon the broad CDOM fluorescence band2 to be essentially constant for varying amounts of CDOM. After water Raman normalization the airborne and surface sample data 1see Figs. 3B and 3D2 are comparable. Figure 4 presents a scatter plot of surface-station fluorescence Fn 1in quinine standardized fluorescence units2 and airborne laser-fluorosensor F@R values. The data pairs are restricted to those observations for which the distance between the closest approach of the flight line to the surface station was no more than

Fig. 3. Examples of CDOM fluorescence determined with an airborne laser fluorosensor and a laboratory spectrofluorometer for waters of the Gulf of Mexico. The laboratory spectra were from filtered samples. A, Raw airborne fluorescence-emission spectra induced by a 355-nm laser. The calibration artifact at ,530 nm is caused by a filter used to reject on-wavelength radiation from a 532-nm laser used to stimulate phytoplankton fluorescence concurrently. B, Same as A, except normalized by the peak water Raman signal at 404 nm. C, Raw laboratory fluorescence-emission spectra of surface samples. D, Same as C, except normalized by the peak water Raman signal at 404 nm. 20 October 1995 @ Vol. 34, No. 30 @ APPLIED OPTICS

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dots are laboratory spectrophotometer determinations of the surface-station absorption coefficient. The stations plotted in Figs. 5A, 5B, and 5D are the same stations from which the fluorescence data were used in the development of the AOL calibration factor. The airborne absorption coefficient was retrieved by multiplying the AOL’s F@R by 5.62 and then applying the Middle Atlantic Bight CDOM fluorescence-toabsorption retrieval algorithm 3Eq. 1124. 4.

Fig. 4. Airborne F14502@R14042 values plotted against laboratory quinine-sulfate-standardized CDOM fluorescence, Fn13552, for the Gulf of Mexico, Monterey Bay, and April 1994 Middle Atlantic Bight studies. This represents the vicarious calibration of the airborne data.

1 km, and the temporal separation between the aircraft and surface-station sampling was no more than 12 hrs. The solid line is the least-squares regression. The slope of the regression line, 5.62, defines the vicarious calibration of the AOL and thus can be used to transform airborne F@R values to Fn values. Figures 5A–5D are profiles of the CDOM absorption coefficient at 355 nm retrieved from the airborne F@R data obtained in the Gulf of Mexico, Monterey Bay, and August 1993 and April 1994 Middle Atlantic Bight experiments, respectively 1solid curves2. The

Discussion

A 1:1 correlation was observed between the fluorescence of filtered and unfiltered samples following short-term refrigeration. This result has also been obtained during other laboratory tests of filtered and unfiltered samples. This strongly suggests that the airborne F@R is not influenced by the particulates and, therefore, satisfactorily represents the dissolved portion of the organic matter. The laboratory and AOL spectra are very similar, both in spectral shape and relative magnitude 1Figs. 3A and 3B2. The spectra acquired from the Gulf of Mexico 1Fig. 3A2 show the precision with which airborne measurements can be made. The more variable portions of the spectra in Fig. 3B from Monterey Bay and the Middle Atlantic Bight are from systematic variation in channel sensitivity, not laserreceiver noise. This response arises from small deviations from a normal-incidence angle at the focal plane and is now being corrected with hardware modifications. These spectra further illustrate that fluores-

Fig. 5. CDOM absorption coefficient, aCDOM13552, retrieved from the AOL CDOM F@R by combining the calibration factor, 5.62, and Eq. 112 1curves2. The laboratory determination of the CDOM absorption from surface stations is also shown 1symbols2. A, Gulf of Mexico; B, Monterey Bay 1this figure is plotted in units of kilometers because the flight track was not linear2; C, Middle Atlantic Bight, August 1993; D, Middle Atlantic Bight, April 1994. 7036

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cence in the observed wavelength range is not discernibly affected by the presence or absence of particles, because the filtered laboratory spectra are very similar to the AOL data. The laboratory and AOL data also compared well despite considerable differences between the airborne and laboratory instrumentation and the handling of stray light in each instrument. Laboratory data analysis used a blank subtraction to remove the effects of stray excitation light, whereas the airborne fluorosensor uses Wratten filters to reject stray light within the spectrometer. Perhaps most important, there is no observable distortion of the AOL data because of the spectral dependence of attenuation in the water column. This further validates the Raman-normalization procedure and diminishes the effects of spectral differences at the two emission wavelengths, as can be seen in equation 8 of Bristow et al.17 Figure 4 shows good agreement 1R2 5 0.972 between the remotely sensed F@R and surface-station Fn values. The linearity of the relation between F@R and Fn further suggests that errors due to the spectral dependence of the attenuation of seawater, phytoplankton, or CDOM must be small. The surface stations encompass chlorophyll concentrations ranging from ,0.1 to ,3 mg m23 and CDOM absorption coefficients between ,0.1 and 1 m21. Thus the Raman normalization was valid for field conditions ranging from coastal to blue waters. More important, for purposes of developing a calibration, the AOL spectral response is shown to be reasonably stable and repeatable. Some of the scatter in Fig. 4 is due to the differences in space and time between the ship and the aircraft sampling. This can be a serious practical limitation to a vicarious calibration and becomes more of a problem near shore, where tidal movement and high concentration gradients make coincident measurements more difficult. We do not have a good set of ship and aircraft data for more turbid water conditions, so we cannot extend these results into the Delaware Bay, for example. Should future studies of more turbid waters reveal distinct spectral attenuation effects, these effects can be mitigated by selecting CDOM fluorescence wavelengths closer to or at the water Raman band.17 The profiles 1Fig. 52 of the CDOM absorption coefficient inferred from the AOL data match well with the surface-station determinations of absorption. The August 1993 Middle Atlantic Bight data are an independent test of the calibration and algorithm, with no apparent measurement bias. However, the airborne estimation of absorption in the Gulf of Mexico 1Fig. 5A2 is consistently higher than the surfacestation data. This overestimation may occur because we are applying an algorithm based on a fluorescence quantum yield for the Middle Atlantic Bight that is known to be slightly lower than that determined for Gulf of Mexico waters.4 When the site-specific retrieval algorithm for the Gulf of Mexico is used, the surface station and airborne data coincide more closely.

Another major source of error in the algorithm is inaccuracy in the absorption coefficients, which can be determined to no better than approximately 60.05 m21 with a commercial spectrophotometer and a 10-cm cell. Thus almost half the standard error in the aircraft determination of absorption may be traceable to the laboratory measurements. The use of scatterinsensitive long-path instrumentation such as the reflecting-tube absorption meter23 or the integratingcavity absorption meter24,25 have the potential to reduce the standard error in the airborne retrieval algorithm. As more field experiments are performed the calibration and retrieval algorithms will continue to be refined. In addition, a redesign of the AOL optical system is underway. Briefly, the original light guides will be replaced with optical fibers and the light path simplified, with an increase in throughput and reductions in cross-channel scatter. Thus another vicarious calibration will be required. Regardless, the calibrated fluorescence protocol is generally applicable to any fluorosensor, and the results reported here can be compared with those obtained after the redesign and with those given by other researchers who used a quinine sulfate standardization. We thank Diane Wickland and Frank MullerKarger of NASA Headquarters for their support of the flight programs and Ken Carder 1University of South Florida2 for the invitation to participate in the Tampa Bay Experiment. Christina Fair 1Scripps Institution of Oceanography2 collected the samples from the Gulf of Mexico. Ship support for the Monterey Bay cruises was provided by the Monterey Bay Aquarium Research Institute 1Peter Brewer2, and the Middle Atlantic Bight cruises were supported by the U.S. Office of Naval Research 1N. V. Blough, Chief Scientist2. Additional support was provided by the NASA EOS Interdisciplinary Program. This work was done while A. Vodacek was a National Research Council resident research associate at NASA. References 1. J. I. Hedges and J. Farrington, ‘‘Comments from the editors on the Suzuki statement,’’ Mar. Chem. 41, 289–290 119932. 2. K. L. Carder, S. K. Hawes, K. A. Baker, R. C. Smith, R. G. Steward, and B. G. Mitchell, ‘‘Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products,’’ J. Geophys. Res. 96, 20599–20611 119912. 3. N. V. Blough, O. C. Zafiriou, and J. Bonilla, ‘‘Optical absorption spectra of waters from the Orinoco River outflow: terrestrial input of colored organic matter to the Caribbean,’’ J. Geophys. Res. 98, 2271–2278 119932. 4. F. E. Hoge, A. Vodacek, and N. V. Blough, ‘‘Inherent optical properties of the ocean: retrieval of the absorption coefficient of chromophoric dissolved organic matter from fluorescence measurements,’’ Limnol. Oceanogr. 38, 1394–1402 119932. 5. F. E. Hoge, R. N. Swift, J. K. Yungel, and A. Vodacek, ‘‘Fluorescence of dissolved organic matter: a comparison of North Pacific and North Atlantic Oceans during April 1991,’’ J. Geophys. Res. 98, 22779–22787 119932. 6. R. A. del Giorgio and R. H. Peters, ‘‘Patterns in planktonic P:R ratios in lakes: influence of lake trophy and dissolved organic carbon,’’ Limnol. Oceanogr. 39, 772–787 119942. 20 October 1995 @ Vol. 34, No. 30 @ APPLIED OPTICS

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7. N. V. Blough and R. G. Zepp, eds., Effects of Solar Ultraviolet Radiation on Biogeochemical Dynamics in Aquatic Environments, Tech. Rep. WHOI-90-09 1Woods Hole Oceanographic Institution, Woods Hole, Mass., 19902. 8. N. V. Blough and R. G. Zepp, ‘‘Reactive oxygen species 1ROS2 in natural waters,’’ in Reactive Oxygen Species in Chemistry, C. S. Foote and J. S. Valentine, eds. 1Chapman and Hall, London, 19952, pp. 280–333. 9. D. J. Kieber, J. McDaniel, and K. Mopper, ‘‘Photochemical source of biological substrates in seawater: implication for carbon cycling,’’ Nature 341, 637–639 119892. 10. M. O. Andreae and R. J. Ferek, ‘‘Photochemical production of carbonyl sulfide in seawater and its emission to the atmosphere,’’ Global Biogeochem. Cycles 6, 175–183 119922. 11. R. H. Gammon and K. C. Kelly, ‘‘Photochemical production of carbon monoxide in surface waters of the Pacific and Indian Oceans,’’ in Effects of Solar Ultraviolet Radiation on Biogeochemical Dynamics in Aquatic Environments, N. V. Blough and R. G. Zepp, eds., Tech. Rep. WHOI-90-09 1Woods Hole Oceanographic Institution, Woods Hole, Mass., 19902, pp. 58–60. 12. R. L. Valentine and R. G. Zepp, ‘‘Formation of carbon monoxide from the photodegradation of terrestrial dissolved organic carbon in natural waters,’’ Environ. Sci. Technol. 27, 409–412 119932. 13. G. M. Ferrari and S. Tassan, ‘‘On the accuracy of determining light absorption by ‘yellow substance’ through measurements of induced fluorescence,’’ Limnol. Oceanogr. 36, 777–786 119912. 14. S. A. Green and N. V. Blough, ‘‘Optical absorption and fluorescence properties of chromophoric dissolved organic matter in natural waters,’’ Limnol. Oceanogr. 39, 1903–1916 119942. 15. A. Vodacek, F. E. Hoge, R. N. Swift, J. K. Yungel, E. T. Peltzer, and N. V. Blough, ‘‘The use of in situ and airborne fluorescence measurements to determine UV absorption coefficients and DOC concentrations in surface waters,’’ Limnol. Oceanogr. 40, 411–415 119952. 16. R. A. Velapoldi and K. D. Mielenz, Standard Reference Materi-

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