Autumn Photoproduction of Carbon Monoxide in Jiaozhou Bay, China

REN Chunyan, YANG Guipeng, and LU Xiaolan

1) Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao 266100, P. R. China

2)College of Chemistry and Pharmaceutical Sciences, Qingdao Agricultural University, Qingdao 266109, P. R. China

Autumn Photoproduction of Carbon Monoxide in Jiaozhou Bay, China

REN Chunyan1,2), YANG Guipeng1),*, and LU Xiaolan1)

1) Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao 266100, P. R. China

2)College of Chemistry and Pharmaceutical Sciences, Qingdao Agricultural University, Qingdao 266109, P. R. China

Carbon monoxide (CO) plays a significant role in global warming and atmospheric chemistry. Global oceans are net natural sources of atmospheric CO. CO at surface ocean is primarily produced from the photochemical degradation of chromophoric dissolved organic matter (CDOM). In this study, the effects of photobleaching, temperature and the origin (terrestrial or marine) of CDOM on the apparent quantum yields (AQY) of CO were studied for seawater samples collected from Jiaozhou Bay. Our results demonstrat that photobleaching, temperature and the origin of CDOM strongly affected the efficiency of CO photoproduction. The concentration, absorbance and fluorescence of CDOM exponentially decreased with increasing light dose. Terrestrial riverine organic matter could be more prone to photodegradation than the marine algae-derived one. The relationships between CO AQY and the dissolved organic carbon-specific absorption coefficient at 254 nm for the photobleaching study were nonlinear, whereas those of the original samples were strongly linear. This suggests that: 1) terrestrial riverine CDOM was more efficient than marine algae-derived CDOM for CO photoproduction; 2) aromatic and olefinic moieties of the CDOM pool were affected more strongly by degradation processes than by aliphatic ones. Water temperature and the origin of CDOM strongly affected the efficiency of CO photoproduction. The photoproduction rate of CO in autumn was estimated to be 31.98 μmol m-2d-1and the total DOC photomineralization was equivalent to 3.25% - 6.35% of primary production in Jiaozhou Bay. Our results indicate that CO photochemistry in coastal areas is important for oceanic carbon cycle.

carbon monoxide; photoproduction; apparent quantum yield; photobleaching; CDOM

1 Introduction

As the second largest product of chromophoric dissolved organic matter (CDOM) photolysis, carbon monoxide (CO) in surface seawater has been broadly observed over the last several decades (Conradet al., 1982; Mopperet al., 1991; Zafiriouet al., 2003; Stubbinset al., 2006). CO is primarily produced from CDOM photolysis (Zuoet al., 1995; Zafiriouet al., 2003) and lost to microbial processes (Zafiriouet al., 2003; Xieet al., 2005), sea-to-air gas exchange (Conradet al., 1982; Stubbinset al., 2006) and vertical mixing (Johnson and Bates, 1996; Kettle, 2005). These chemical, biological and physical interactions lead to complex spatial and temporal distributions of sea surface CO. CO is also a key proxy to evaluate the photoproduction of dissolved inorganic carbon (DIC), biolabile carbon and nitrogen compounds because of their difficulty to measure (Miller, 1995, 2002; Mopper, 2000). CO apparent quantum yield (AQY) data have been reported for a number of samples including those from high carbon waters (Zhang and Xie, 2011; Yanget al., 2011; Gao and Zepp, 1998; Valentine and Zepp, 1993), sea ice (Songet al., 2011) and open-ocean waters (Zafiriouet al., 2003; Stubbinset al., 2006). The AQY spectra reported on near-coastal waters were higher than those on Sargasso Sea waters and blue waters, suggesting that terrestrial CDOM might exhibit different efficiency and be more efficient at producing CO than marine CDOM. However, there are still many gaps in our understanding of the influencing factors on CO production and the coastal photoproduction of CO. In this study, we collected several different water samples from Jiaozhou Bay, China to examine the factors controlling CO photoproduction, such as photobleaching and temperature. Furthermore, the total amount of CO photoproduction in Jiaozhou Bay in autumn was calculated.

2 Materials and Methods

2.1 Study Area

Jiaozhou Bay is the largest semi-enclosed bay on the western part of the Shandong Peninsula, China (Fig.1).

Fig.1 Locations of the sampling stations in Jiaozhou Bay, China.

The bay is surrounded by the city of Qingdao with an area of about 390 km2and a mean water depth of about 7 m. The bay mouth is narrow, only about 2.5 km wide and connects with the South Yellow Sea. The water exchange rate between the bay and the open sea is high, being 7%, and the half of exchange period is 5 d (Liu, 1992). More than 10 small rivers enter the bay, the largest being Dagu River and the rest including Haipo River, Licun River, Loushan River and so on. Most of these rivers pass through the urban areas of Qingdao, which causes Jiaozhou Bay greatly influenced by human activities, such as wastewater discharge from domestic, industrial, agricultural and marine-cultural activities (Shen, 2001).

2.2 Sample Collection and Pretreatment

Cruise was conducted in Jiaozhou Bay on November 11, 2008, and the sampling locations are shown in Fig.1. At each location, surface seawater samples (2 m deep) were collected using 12 L Niskin bottles. After collection, samples were filtered through 0.45 μm and 0.2 μm polyethersulfone membranes (Pall, USA). The filtered water was transferred in the dark into acid-cleaned clear glass bottles, stored in darkness at 4℃, and brought back to the laboratory. Samples were re-filtered with 0.2 μm polyethersulfone membranes (Pall, USA) immediately before irradiation.

The filtered water samples, placed in clean glass bottles covered with a quartz plate, kept at 15℃, were irradiated with a SUNTEST CPS solar simulator (Atlas, Germany) equipped with a Xelon lamp. The output of the Xe-lamp was adjusted to 765W m-2and determined with an ILT-900R UV-VIS spectroradiometer (International Light Technologies, USA). Irradiation times varied from 4 h to 240 h to obtain various photobleaching degree samples, whose contents of dissolved organic matter (DOM) were all different from that of the original samples.

2.3 Analytical Methods

Before irradiation, water samples were stripped with CO-free air to decrease CO concentration of the samples and then determined for the determination of the initial concentration. Then seawater samples were transferred into gastight quartz cells and placed into the SUNTEST CPS solar simulator to be irradiated with the temperature of water-bath controlled at 15℃. The SUNTEST CPS solar simulator was modified with eight long-pass cut-off filters (280, 295, 305, 320, 345, 395, 435 and 495 nm, numbers being nominal 50% transmission cutoff wavelength) to obtain different solar wave bands and determined with an ILT-900R UV-VIS spectroradiometer. Right after irradiation, water samples were transferred into 50 mL glass acid-cleaned syringes fitted with threeway Nylon valves and analyzed with TA 3000 gas analyzer (Ametek, USA) (Luet al., 2010). CO concentration (CCO) was calculated according to Xieet al. (2002).

Absorbance spectra were measured from 200 to 800 nm at 1 nm increment in quartz cell against Milli-Q water reference using an UV-2550 UV-VIS spectrometer (Shimadzu). A baseline correction was applied by subtracting the absorbance value which was an average over a 5-nm interval around 685 nm from all the spectral values (Babinet al., 2003). This spectral range around 685 nm was chosen because of the negligible CDOM absorption and the very small temperature and salinity effects on water absorption (Pegauet al., 1997). Then absorption coefficients (a) (m-1) were calculated as (Lohet al., 2004):

whereAis the absorbance, andLis the path length (m).

Dissolved organic carbon (DOC) was measured using a TOC-5000A carbon analyzer (Shimadzu) calibrated with potassium biphthalate. The relative standard deviation was less than 2%.

Excitation-Emission Matrix Spectra (EEMs) of the organic matter was measured in 1-cm quartz cell against Milli-Q water reference using F-4500 fluorescent spectrometer (Hitachi). The excitation and emission ranges were both from 200 to 500 nm and the increments were both 5 nm.

Apparent quantum yield (AQY(λ)) is traditionally defined as the ratio of the number of molecules transformed via one reaction pathway to the number of photons absorbed by the reactant at a given wavelength. So AQY was here defined as follows:

A Matlab-coded iterative curve-fit method was employed to derive AQY(λ) (Johannessen and Miller, 2001). Zhang’s (2006) recommendation was adopted to calculate AQY as follows:

wherem1,m2andm3are fitting parameters. This functionhas been demonstrated to perform generally better (Xie and Gosselin, 2005).

CO production rate in the irradiation cell could be predicted by the equation below:

whereQab(λ) is photons absorbed by CDOM at a specific wavelength.

Then χ2error could be calculated as:

wherePiis the measured CO production rate. The fit parameters (m1,m2andm3) were derived by changing them iteratively from their initial estimates until the χ2error was minimized.

3 Results and Discussion

3.1 Influence of Light Dose on the Contents of CDOM

There are 7 types of peaks of fluorescent DOM in seawater, and the major 3 types and their peak positions are listed in Table 1. Peaks A, S and T are humic-like and protein-like peaks, which are the primary components of CDOM (Coble, 1996; Parlantiet al., 2000). Several organic compound EEMs of different photobleaching degrees for Licun estuary samples are shown in Fig.2. Peak A can be clearly observed at Ex/Em being 250/470 nm of non-photobleached sample (photobleaching time is zero), whose fluorescent value is very high and covers up peak S at 235/370 nm and peak T at 280/350 nm on the whole. After some period of photobleaching, peak S and peak T were very obvious with the disappearing of peak A in other EEMs. At the same time, emission wavelengths of peak S and peak T decreased from 370 nm to 355 nm and from 350 nm to 325 nm, respectively, but excitation wavelength remained the same. The fluorescent values of peaks A, S and T were significantly decreased with the photobleaching time. After the long time of photobleaching (236 h), humic-like substances were mostly degraded (the fluorescent value of peak A was only 7.56% of the original value), but a large amount of protein-like substances remained (the fluorescent values of peak S and peak T were 37.87% and 55.02% of the original value, respectively). It has been reported that humic substances could mostly be photodegraded by sunlight into a variety of photoproducts including low-molecular-weight organic compounds, which could be separated into three main categories: 1) aliphatic mono-and dibasic acids; 2) ketoacids; 3) aromatic hydroxy carboxylic acids and aldehydes (Kieber and Mopper, 1987; Kieberet al., 1990; Wetzelet al., 1995; Nina Corinet al., 1996) and inorganic compounds such as CO, DIC and carbonyl sulfide (COS), but the degradation of protein-like substances was much smaller (Andreae and Ferek, 1992; Miller and Zepp, 1995; Moran and Zepp, 1997). Our investigations testified this point.

Fig.2 EEMs of different photobleaching degrees in the samples from B5 station (photobleaching times are 0, 4, 64, 120, 173 and 236 h, respectively).

Table 1 Major fluorescent types of dissolved organic matter in seawater

Absorption coefficient at 350 nm (a350) and the fluorescent value of peak A (IF(A)) are the proxy of the content of CDOM, to some extent, because these optical parameters are directly related to the concentration and photoreactivity of DOM (Zuo and Jones, 1997). The influence of light dose ona350and IF(A) in the photobleaching of CDOM were investigated.

The influence of light dose ona350and fluorescent peak A are shown in Fig.3. It can be seen from Fig.3 that botha350and IF(A) exponentially decreased with the increasing light dose in all 5 different samples. During the first 4 hours of photobleaching, botha350and IF(A) sharply declined. Thereafter,a350and IF(A) decreased slowly. During long time photobleaching,a350and IF(A) remained approximately constant. This suggests that a significant amount of the DOM, especially more hydrophilic moieties of the DOM, was degraded at the beginning of photobleaching, and the residual organic matter after long time photobleaching should be some refractory organic substances (Brinkmannet al., 2003).

Fig.3 The influence of light dose on a350and fluorescent peak A.

Among different samples, the extents of degredation were different. During long time photobleaching, most of the organic matter was degraded in the samples from B5, D4 and B1 stations. However, quite a number of organic matters remained in the water after long time photobleaching with samples from C3 and E3. This was mainly due to their different sources of CDOM. Terrestrial organic matter has a greater aromaticity than marine DOMand may be more prone to photodegradation, so most of them could be degraded after long time photobleaching as discussed by Moran and Hodson (1994). In contrast, the pool of marine algae-derived DOM was relatively resistant against natural UV radiation and not so readily photo-oxidized (Thomas and Lara, 1995). For samples from B5, D4 and B1 stations (Fig.4), almost all organic matter was from terrestrial riverine import, so most of them could be degraded. For samples from C3 and E3 stations, most of the organic matter was of marine origin and only a small part was of terrestrial origin, so there were still many organic compounds left during long time photobleaching (Zhanget al., 2002).

Fig.4 The relationship between CO AQY and water temperature of B5 and D4 samples.

3.2 Temperature Dependence

To assess the effect of temperature on CO photoproduction, the original samples from B5 and D4 were irradiated at four temperatures: 5, 10, 15 and 20℃, and the AQY–temperature relationship is shown in Fig.5. We can see that the relationship followed the linear Arrehenius behavior. The activation energy for samples from stations B5 and D4 were 19.15 and 13.59 kJ mol-1, respectively, both being smaller than 20 kJ mol-1. For an increase per 10 K, the AQY increased by about 35% and 22%, respectively, which are accordant with Zhang (2006), but much lower than van’t Hoff rule’s coefficient. However, the temperature dependence of AQY demonstrated that secondary photoreactions were involved in the CO production. This viewpoint is supported by the fact that aromatics without the carbonyl group are the dominant CO precursors (Hubbard, 2006). However, the possibility of CO production through primary photoreaction may still exist. That is mainly because some simple carbonyl compounds such as formaldehyde and acetaldehyde can be produced by photoreaction in natural seawater (Kieber, 1990) and decomposed to CO by the solar UV spectrum.

Fig.5 Effects of photobleaching on the CO AQY as illustrated by f330.

3.3 Photobleaching Dependence

The wavelength peak of CO production is about 330 nm, so the fraction of the originala330(f330) was chosen to describe the photoleaching degree of water samples (Zhanget al., 2006). The dependence of AQY on CDOM photobleaching is depicted as plots of AQYvsf330(Fig.5). The dose dependence varied widely among different samples and at different stages of photobleaching. AQY for estuary samples (stations B5, D4 and B1) decreased dramatically at first, continued to decline thereafter at gradually reducing rates, and eventually became approximately constant. Station C3 in the bay center and station E3 in the bay mouth exhibited a similar pattern, but the initial decrease in AQY was much smaller.

The dissolved organic carbon-specific absorption coefficient at 254 nm (SUVA254, defined asa254divided by DOC, with a unit of L m-1(mg C)-1) was an indicator of the aromatic carbon content of DOM (Weishaaret al., 2003). The dependence of AQY on SUVA254was also examined (Fig.6). Similar to the AQYvsf330pattern, the AQY-SUVA254relationship observed for the photobleaching study was nonlinear, which was different from strong linear correlation found for the original samples (Fig.7). At the beginning of photobleaching, AQY decreased sharply in the B5, D4 and B1 samples, which represented the conditions of Licun estuary, Haipo estuary and Dagu estuary, respectively. In contrast to these three sets of samples, AQY also decreased but not so sharply in the samples from C3 (the bay center) and E3 (the bay mouth). However, SUVA254did not decline rapidly like AQY, suggesting that reactive CO precursors contained aromatic moieties, but the aromatic rings were not destroyed during the initial process (Zhanget al., 2006). Thereafter, the AQY decreased slowly with the decrease of SUVA254. During more than 120 hours’photobleaching, AQY eventually became relatively constant, but SUVA254continued to decline. These observations showed that: 1) there should be two classes of CO producers: terrestrial riverine CDOM and marine algaederived CDOM, terrestrial CDOM being more reactive than the other in the photoproduction of CO; 2) Aromatic and olefinic moieties of the CDOM pool were affected more strongly by degradation processes than by aliphaticones (Mopper and Kieber, 2000).

Fig.6 Effects of photobleaching on the CO AQY as illustrated by SUVA254.

Fig.7 The relationship between AQY and SUVA254of the original samples.

3.4 CO Photoproduction

AQYs were significantly correlated with SUVA254of all original samples (Fig.7), suggesting that aromatic and olefinic moieties of the CDOM pool strongly affected AQY relative to aliphatic ones. Stubbins (2008) has demonstrated that many specific aromatic compounds are efficient CO producers. As terrestrial DOM (samples such as those from B5 and D4 stations) usually contain more aromatic compounds than marine algae-derived one (samples such as the others) (see Table 2), AQYs of the former two samples were much higher than those of the others.

AQY spectra for CO photoproduction are presented in Fig.8. By comparison, the AQY spectrum of the samples collected from station B5 was significantly higher in magnitude, indicating that CO was produced with a much higher photochemical efficiency in the sample compared with the other samples from the bay. This higher efficiency was likely due to the higher value of SUVA254(Table 2). Since no statistical difference was observed in the photochemical efficiency of CDOM to produce CO for stations throughout the bay (most of the three fitting parameters (m1,m2andm3) were close in value), a pooled AQY spectrum was calculated by applying a single exponential fit to all CO production.

The pooled AQY spectra of Jiaozhou Bay samples, together with the average freshwater (Valentine and Zepp, 1993), and for the East China Sea (ECS) and the Yellow Sea (YS) (Yanget al., 2011) and average Pacific blue water (Zafiriouet al., 2003), are displayed in Fig.8. Across the whole UV-visible regimes, the AQY of freshwater was the highest, those of Jiaozhou Bay and the ECS and YS samples were intermediate, and the blue water had the lowest value. This indicates that the contribution of continental shelves and coastal regions to the global oceanic photoproduction of CO might not be neglected. However, the differences of these AQY values diminished with decreasing wavelength. As the samples from station B5 had lower salinity (S = 23.451) and thus containedmore terrestrial CDOM (SUVA254= 6.44 L m-1(mg C)-1) than those from station E3, the CO spectrum with station B5 was much closer to that with freshwater area. These observations suggest that the two precursors of CDOM (terrestrial and marine derived CDOM) had different efficiencies to produce CO and the terrestrial CDOM was more prone to photolysis than the marine algae-derived one. Our result also showed the presence of multiple CO precursors that were less selectively photolyzed by UV-B radiation than by UV-A and visible radiations.

Fig.8 Comparison of AQY spectra for Jiaozhou Bay in this study with previously published AQY spectra. The AQY spectrum for average freshwater is from Valentine and Zepp (1993), the ECS and YS from Yang et al. (2011) and those for average Pacific blue water from Zafiriou et al. (2003).

Table 2 Physical and chemical parameters of the water samples

CO photoproduction rates over all the relevant wavelength range (280 - 600 nm) were calculated as (Zafiriouet al., 2003; Xieet al., 2009):

where irradiance is global spectral solar irradiance; attenuation factors 1 is correction for the reflection of light by clouds, derived from UV reflectivity (Ecket al., 1995), the average value in Jiaozhou Bay in autumn being 0.70; attenuation factors 2 is the transmittance at the air-sea interface, the value being about 0.94, a mean of all of the Fresnel reflectivity (Liu, 2009);αCDOMandαTotalare the CDOM and the sum of the absorption coefficients of CDOM, particles and seawater in the water column; AQYCOis the AQY of CO at each wavelength between 280 and 600 nm.

The Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS2 model) (Gueymard, 2001), which covers a full range of photochemically active radiation (280 - 4000 nm) and with a spectral resolution of at least 0.5 nm, was used to calculate the CO photoproduction rates. This model has been validated over the North Atlantic Ocean by Stubbinset al. (2006), who found that the model could accurately and precisely predict variations of irradiance between 280 - 450 nm; but above 450 nm, the model overestimated irradiance by about 10%. Using SMARTS2 irradiance and the CDOM-based AQYCOspectrum as described above, the CO photoproduction rate in Jiaozhou Bay in autumn was calculated to be 31.98 μmol m-2d-1.

3.5 Implications for Coastal Carbon Cycle

CO is the second abundant inorganic carbon product after DIC, whose photoproductive amount can be used to estimate the total photomineralization of DOC. Using the ratios of DIC to CO photoproduction of 10-20 (Day and Faloona, 2009; Whiteet al., 2010) and the ratio of DIC photoproduction to the photochemical release of biolabile organic carbon of approximately 1 (Milleret al., 2002), the total photomineralization of DOC in Jiaozhou Bay was estimated to be 8.06 - 15.73 mg C m-2d-1. Assuming the primary production of the bay in autumn to be 247.81 mg C m-2d-1(Sunet al., 1995), DOC photomineralization is equivalent to 3.25%-6.35% of primary production in Jiaozhou Bay. This estimate is higher than the previous estimate of photochemical DOC mineralization in the coastal area of the northern California upwelling system (2.5%; Day and Faloona, 2009). Our result provides the evidence that the photolytic mineralization of dissolved organic matter should be regarded as a noteworthy component of the regional carbon cycle in the Jiaozhou Bay ecosystem.

4 Conclusion

Our findings have several implications for assessing the importance of photochemical formation of CO and carbon cycling in sea water. First, our study demonstrates that DOM, especially humic-like substances, could be significantly degraded by long time photobleaching in surface seawater, which could further affect the cycling of carbon and other reactive elements in marine ecosystems. Second, our results strongly suggest that long time photobleaching could significantly influence the photoproduction of CO, especially in near-coastal and continental shelf areas whose organic matters are mostly from terrestrial riverine origin. Finally, based on the CO photoproduction rate calculated for Jiaozhou Bay, the total DOC photomineralization is estimated to be 8.06-15.73 mg C m-2d-1, equivalent to 3.25%-6.35% of primary production in Jiaozhou Bay. This result suggests that photochemistry of CO may be an important component in the carbon cycling of this studied system. Further studies should be designated to identify the seasonal variation of CO photoproduction and pay more attention to coastal areas to evaluate the global total CO photoproduction.

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (No. 40976043), the Science and Technology Key Project of Shandong Province (2006GG2205024), the Changjiang Scholars Program, Ministry of Education of China, the Taishan Scholars Program of Shandong Province, and the Scholar Foundation of Qingdao Agricultural University (631102).

Andreae, M. O., and Ferek., R. J., 1992. Photochemical production of carbonyl sulfide in seawater and its emission to the atmosphere. Global Biogeochemical Cycles, 6: 175-183.

Babin, M., Stramski, D., Ferrari, G. M., Claustre, H., Bricaud, A., Obolensky, G., and Hoepffner, N., 2003. Variations in the light absorption coefficients of phytoplankton, nonalgal particles and dissolved organic matter in coastal waters around Europe. Journal of Geophysical Research, 108 (C7), DOI 10.1029/2001jc000882.

Brinkmann, T., Horsch, P., Sartorius, D., and Frimmel., F. H., 2003. Photoformation of low-molecular-weight organic acids from brown water dissolved organic matter. Environmental Science and Technology, 37: 4190-4198.

Coble, P. G., 1996. Characterization of marine and terrestrial DOM in seawater using excitation-emission matrix spectroscopy. Marine Chemistry, 51: 325-346.

Conrad, R., Seiler, W., Bunse, G., and Giehl, H., 1982. Carbon Monoxide in seawater (Atlantic Ocean). Journal of Geophysical Research, 87 (C11): 8839-8852.

Corin, N., Backlund, P., and Kulovaara, M., 1996. Degradation products formed during UV-irradiation of humic waters. Chemosphere, 33 (2): 245-255.

Day, D. A., and Faloona, I., 2009. Carbon monoxide and chromophoric dissolved organic matter cycles in the shelf waters of the northern California upwelling system. Journal of Geophysical Research, 114 (C01006), DOI: 10.1029/2007JC004 590.

Eck, T. F., Bhartia, P. K., and Kerr, J. B., 1995. Satellite estimation of spectral UVB irradiance using TOMS derived total ozone and UV reflectivity, Geophysical Research Letters, 22: 611-614.

Gao, H., and Zepp, R. G., 1998. Factors influencing photoreactions of dissolved organic matter in a coastal river of the southeastern United States. Environmental Science and Technology, 32: 2940-2946.

Johnson, J. E., and Bates, T. S., 1996. Sources and sinks of carbon monoxide in the mixed layer of tropical South Pacific Ocean. Global Biogeochemical Cycles, 10 (2): 347-359.

Kettle, A. J., 2005. Diurnal cycling of carbon monoxide (CO) in the upper ocean near Bermuda. Ocean Modelling, 8: 337-367. Kieber, D. J., and Mopper., K., 1987. Photochemical formation of glyoxylic and pyruvic acids in seawater. Marine Chemistry, 21: 135-149.

Kieber, D. J., McDaniel, J., and Mopper, K., 1989. Photochemical source of biological substrates in sea water: Implications for carbon cycling. Nature, 341: 637-639.

Kieber, D. J., Zhou, X., and Mopper, K., 1990. Formation of carbonyl compounds from UV-induced photodegradation of humic substances in natural waters: Fates of riverine carbon in the sea. Limnology and Oceanography, 35: 1503-1515.

Liu, R. Y., 1992. Characteristics of physical environmental of Jiaozhou Bay. Ecology and Biological Resources of Jiaozhou Bay. Science Press, Beijing, 25-30 (in Chinese).

Liu, Y. G., 2009. Satellite Oceanography. Higher Education Press, Beijing, 171pp.

Lu, X. L., Yang, G. P., Wang, X. M., Wang, W. L., and Ren, C. Y., 2010. Determination of carbon monoxide in seawater by headspace analysis. Chinese Journal of Analytical Chemiatry, 38 (3): 352-356, DOI: 10.3724/SP.J.1096.2010.00352.

Miller, W. L., Moran, M. A., Sheldon, W. M., Zepp, R. G., and Opsahl, S., 2002. Determination of apparent quantum yield spectra for the formation of biologically labile photoproducts. Limnology and Oceanography, 47: 343-352.

Miller, W. L., and Zepp, R. G., 1995. Photochemical production of dissolved inorganic carbon from terrestrial organic-matters significance to the oceanic organic-carbon cycle. Geophysical Research Letters, 22: 417-420.

Mopper, K., and Kieber, D. J., 2000. Marine Photochemistry and its Impact on Carbon Cycling. The Effects of UV Radiation in the Marine Environment. Cambridge University Press, Cambridge, 101-129.

Mopper, K., Zhou, X. L., Kieber, R. J., Sikorski, D. J., and Jones, R. D., 1991. Photochemical degradation of dissolved organic carbon and its impact on the oceanic carbon cycle. Nature, 353 (6339): 60-62.

Moran, M. A., and Hodson, R. E., 1994. Support of bacterioplankton production by dissolved humic substances from three marine environments. Marine Ecology Progress Series, 110: 241-247.

Moran, M., and Zepp, R., 1997. Role of photoreactions in the formation of biologically labile compounds from dissolved organic matter. Limnology and Oceanography, 42 (6): 1307-1316.

賈承造：在推進能源綠色低碳轉(zhuǎn)型的國際背景下，我國遵循十九大提出的“兩步走”戰(zhàn)略，努力實現(xiàn)社會主義現(xiàn)代化，大力推進生態(tài)文明建設(shè)，建設(shè)美麗中國，我國的天然氣發(fā)展迎來了難得的歷史機遇。預(yù)期我國天然氣仍會保持快速發(fā)展。而推動天然氣發(fā)展首先需要加快天然氣產(chǎn)供儲銷體系建設(shè)。

Nelson, N. B., Siegel, D. A., and Michaels, A. F., 1998. Seasonal dynamics of colored dissolved organic material in the Sargasso Sea. Deep-Sea Research I, 45 (6): 931-957.

Parlanti, P., Worz, K., Geoffroy, L., and Lamotte, M., 2000. Dissolved organic matter fluorescence spectroscopy as a tool of estimate biological activity in a coastal zone submitted to anthropogenic inputs. Organic Geochemistry, 31: 1765-1781.

Pegau, W. S., Deric, G., and Zaneveld, J. R. V., 1997. Absorption and attenuation of visible and near-infrared light in water: Dependence on temperature and salinity. Applied Optics, 36 (24): 6035-6046.

Shen, Z. L., 2001. Historical changes in nutrient structure and its influence on phytoplankton composition in Jiaozhou Bay. Estuarine, Coastal and Shelf Science, 52: 211-224.

Song, G., Xie, H., Aubry, C., Zhang, Y., Gosselin, M., Mundy, C. J., Philippe, B., and Papakyriakou, T. N., 2011. Spatiotemporal variations of dissolved organic carbon and carbon monoxide in first-year sea ice in the western Canadian Arctic. Journal of Geophysical Research, 116 (C00G05), DOI: 10.1029/ 2010JC 006867.

Stubbins, A., Uher, G., Law, C. S., Mopper, K., Robinson, C., and Upstill-Goddard, R. C., 2006. Open-ocean carbon monoxide. Deep-sea Research II, 53: 1695-1705.

Stubbins, A., Hubbard, V., Uher, G., Law, C. S., Upstill-Goddard, R. C., Aiken, G. R., and Mopper, K., 2008. Relating carbon monoxide photoproduction to dissolved organic matter functionality. Environmental Science and Technology, 42: 3271-3276.

Thomas, D. N., and Lara, R. J., 1995. Photodegradation of algal derived dissolved organic carbon. Marine Ecology Progress Series, 116: 309-310.

Valentine, R. L., and Zepp, R. G., 1993. Formation of carbon monoxide from the photodegradation of terrestrial dissolved organic carbon in natural waters. Environmental Science and Technology, 27 (2): 409-412.

Wetzel, R. G., Hatcher, P. G., and Bianchi, T. S., 1995. Natural photolysis by ultraviolet irradiance of recalcitrant dissolved organic matter to simple substrates for rapid bacterial metabolism. Limnology and Oceanography, 40: 1369-1380.

White, E. M., Kieber, D. J., Sherrard, J., Miller, W. L., and Mopper, K., 2010. Carbon dioxide and carbon monoxide photoproduction quantum yields in the Delaware Estuary. Marine Chemistry, 118: 11-21.

Wiesenburg, D. A., and Guinasso, N. L., 1979. Equilibrium solubilities of methane, carbon monoxide, and hydrogen in water and sea water. Journal of Chemical and Engineering Data, 24: 356-360.

Xie, H., Andrews, S. S., Martin, W. R., Miller, J., Ziolkowski, L., Taylor, C. D., and Zafiriou, O. C., 2002. Validated methods for sampling and headspace analysis of carbon monoxide in seawater. Marine Chemistry, 77: 93-108.

Xie, H., Zafiriou, O. C., Umile, T. P., and Kieber, J., 2005. Biological consumption of carbon monoxide in Delaware Bay, NW Atlantic and Beaufort Sea. Marine Ecology Progress Series, 290: 1-14.

Xie, H., Belanger, S., Demers, S., and Papakyriakou, T. N., 2009. Photobiogeochemical cycling of carbon monoxide in the southeastern Beaufort Sea in spring and autumn. Limnol-ogy and Oceanography, 54 (1): 234-249.

Yang, G. P., Ren, C. Y., Lu, X. L., Liu, C. Y., and Ding, H. B., 2011. Distribution, flux and photoproduction of carbon monoxide in the East China Sea and the Yellow Sea in spring. Journal of Geophysical Research, 116 (C02001), DOI: 10. 1029/2010JC 006300.

Zafiriou, O. C., Andrews, S. S., and Wang, W., 2003. Concordant estimates of oceanic carbon monoxide source and sink processes in the Pacific yield a balanced global ‘blue-water’CO budget. Global Biogeochemical Cycles, 17 (1): 1015, DOI: 10.1029/2001gb001638.

Zepp, R. G., and Cline, D. M., 1977. Rates of direct photolysis in aquatic environments. Environmental Science and Technology, 11: 359-366.

Zhang, X. Q., Wu, Y. S., Zhang, S. K., and Wu, L. Y., 2002. The distribution on fluorescence intensity of yellow substance in Jiaozhou Bay. Journal of Remote Sensing, 6 (3): 229-232.

Zhang, Y., and Xie, H., 2011. The sources and sinks of carbon monoxide in the St. Lawrence estuarine system. Deep-Sea Research II, DOI:10.1016/j.dsr2.2011.09.003.

Zhang, Y., Xie, H., and Chen, G. H., 2006. Factors affecting the efficiency of carbon monoxide photoproduction in the St. Lawrence estuarine system (Canada). Environmental Science and Technology, 40: 7771-7777.

Zuo, Y., and Jones, R. D., 1995. Formation of carbon monoxide by photolysis of dissolved marine organic material and its significance in the carbon cycling of the ocean. Naturwissenschaften, 82 (10): 472-474.

Zuo, Y., and Jones, R. D., 1997. Photochemistry of natural dissolved organic matter in lake and wetland waters-production of carbon monoxide. Water Research, 31 (4): 850-858.

(Edited by Ji Dechun)

(Received December 16, 2012; revised March 3, 2013; accepted May 18, 2013)

? Ocean University of China, Science Press and Springer-Verlag Berlin Heidelberg 2014

* Corresponding author. Tel: 0086-532-66782657

E-mail: gpyang@ouc.edu.cn