Relationships between atmospheric organic compounds and air-mass exposure to marine biology

Arnold, S. R.; Spracklen, D. V.; Gebhardt, S.; Custer, Thomas; Williams, Jonathan; Peeken, Ilka; Alvain, Séverine

doi:10.1071/en09144

Cited by 38 publications

(44 citation statements)

References 66 publications

(77 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We found a weak positive correlation between the AMS organics and fluorometer measurements for the VOCALS campaign (r = 0.35), but no relationship for OOMPH. Recent work demonstrated the importance of accounting for the air mass history when analyzing the variability in atmospheric tracers (Arnold et al, 2010). We found a marginal improvement in correlation between the organics and chlorophyll-a, when the latter was averaged over 2-day back-trajectories.…”

Section: Resultsmentioning

confidence: 71%

“…Alvain et al (2005) has identified the major dominant phytoplankton functional types from SeaWiFS measurements. The degree of correlation between atmospheric tracers and exposure to chlorophyll-a has been shown to be dependent on these types (Arnold et al, 2010). Recent work by Fuentes et al (2010) has further shown that the relationship between chlorophyll-a and organic mass fraction in aerosols are expected to be very complex, as seawater OM production by marine biota depends on conditions in the algal blooms, including nutrient availability, temperature and lifespan of algal cells.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Investigating organic aerosol loading in the remote marine environment

et al. 2011

Self Cite

View full text Add to dashboard Cite

Abstract. Aerosol loading in the marine environment is investigated using aerosol composition measurements from several research ship campaigns (ICEALOT, MAP, RHaMBLe, VOCALS and OOMPH), observations of total AOD column from satellite (MODIS) and ship-based instruments (Maritime Aerosol Network, MAN), and a global chemical transport model (GEOS-Chem). This work represents the most comprehensive evaluation of oceanic OM emission inventories to date, by employing aerosol composition measurements obtained from campaigns with wide spatial and temporal coverage. The model underestimates AOD over the remote ocean on average by 0.02 (21 %), compared to satellite observations, but provides an unbiased simulation of ground-based Maritime Aerosol Network (MAN) observations. Comparison with cruise data demonstrates that the GEOS-Chem simulation of marine sulfate, with the mean observed values ranging between 0.22 µg m −3 and 1.34 µg m −3 , is generally unbiased, however surface organic matter (OM) concentrations, with the mean observed concentrations between 0.07 µg m −3 and 0.77 µg m −3 , are underestimated by a factor of 2-5 for the standard model run. Addition of a sub-micron marine OM source of approximately 9 TgC yr −1 brings the model into agreement with the ship-based measurements, however this additional OM source does not exCorrespondence to: K. Lapina (klapina@atmos.colostate.edu) plain the model underestimate of marine AOD. The model underestimate of marine AOD is therefore likely the result of a combination of satellite retrieval bias and a missing marine aerosol source (which exhibits a different spatial pattern than existing aerosol in the model).

show abstract

Section: Resultsmentioning

confidence: 71%

Section: Resultsmentioning

confidence: 99%

Investigating organic aerosol loading in the remote marine environment

et al. 2011

Self Cite

View full text Add to dashboard Cite

show abstract

“…The PHYSAT approach relies on the identification of specific signatures in the normalized water leaving radiance (nLw) spectra measured by an ocean color sensor (Alvain et al, , 2008, thereby enabling the identification of nanoeukaryotes, haptophytes (a major component of the nanoflagellates), Synechococcuslike cyanobacteria, diatoms, Prochlorococcus, Phaeocystis-like phytoplankton, and coccolithophorids. The PHYSAT method has been successfully validated with phytoplankton in situ data and extensively used by many authors (e.g., Bopp et al, 2005;Arnold et al, 2010;D'Ovidio et al, 2010;Gorgues et al, 2010;Masotti et al, 2010Masotti et al, , 2011Alvain et al, 2012Alvain et al, , 2013Belviso et al, 2012;Demarcq et al, 2012;De Monte et al, 2013;Hashioka et al, 2013;Ben Mustapha et al, 2014;Thyssen et al, 2015). Navarro et al (2014) later proposed a regionalized version of the algorithm for the Mediterranean Sea (Figure 1), the PHYSAT-Med, using the MODIS era (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) for identification of nanoeukaryotes, Prochlorococcus, Synechococcus-like cyanobacteria and diatoms, which was compared with more than 3,000 high-performance liquid chromatography (HPLC) in situ measurements (see Table 3 in Navarro et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Reproduction of Spatio-Temporal Patterns of Major Mediterranean Phytoplankton Groups from Remote Sensing OC-CCI Data

et al. 2017

View full text Add to dashboard Cite

During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT-Med, was developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows the detection from ocean color images of the dominant Mediterranean phytoplankton groups, namely nanoeukaryotes, Prochlorococcus, Synechococcus, diatoms, coccolithophorids, and Phaeocystis-like phytoplankton. Here, we present a new version of PHYSAT-Med applied to the Ocean Colour-Climate Change Initiative (OC-CCI) database. The OC-CCI database consists of a multi-sensor, global ocean-color product that merges observations from four different sensors. This retuned version presents improvements with respect to the previous version, as it increases the temporal range (since 1998), decreases the cloud cover, improves the bias correction and a validation exercise was performed in the NW Mediterranean Sea. In particular, the PHYSAT-Med version has been used here to analyse the annual cycles of the major phytoplankton groups in the Mediterranean Sea. Wavelet analyses were used to explore the spatial variability in dominance both in the time and frequency domains in several Mediterranean sub-regions, such as the Alboran Sea, Ligurian Sea, Northern Adriatic Sea, and Levantine basin. Results extended the interpretation of previously detected patterns, indicating the dominance of Synechococcus-like vs. prochlorophytes throughout the year at the basin level, and the predominance of nanoeukaryotes during the winter months. The method successfully reproduced the diatom blooms normally detected in the basin during the spring season (March to April), especially in the Adriatic Sea. According to our results, the PHYSAT-Med OC-CCI algorithm represents a useful tool for the spatio-temporal monitoring of dominant phytoplankton groups in Mediterranean surface waters. The successful applications of other regional ocean color algorithms to the OC-CCI database will give rise to extended time series of phytoplankton functional types, with promising applications to the study of long-term oceanographic trends in a global change context.

show abstract

“…[]). Laboratory and field data exist, linking very short‐lived iodocarbons and phytoplankton activity [ Smythe‐Wright et al ., ; Hill and Manley , ; Arnold et al ., ; Brownell et al ., ; Lai et al ., ]. However, there is increasing evidence that biological sources of iodine precursors are not the most significant [ Garland and Curtis , ; Reeser et al ., ; Martino et al ., ; Sakamoto et al ., ; Mahajan et al ., ].…”

Section: Introductionmentioning

confidence: 99%

Iodine chemistry in the eastern Pacific marine boundary layer

et al. 2013

View full text Add to dashboard Cite

[1] Observations of gas-phase iodine species were made during a field campaign in the eastern Pacific marine boundary layer (MBL). The Climate and Halogen Reactivity Tropical Experiment (CHARLEX) in the Galápagos Islands, running from September 2010 to present, is the first long-term ground-based study of trace gases in this region. Observations of gas-phase iodine species were made using long-path differential optical absorption spectroscopy (LP-DOAS), multi-axis DOAS (MAX-DOAS), and resonance and off-resonance fluorescence by lamp excitation (ROFLEX). These measurements were supported by ancillary measurements of ozone, nitrogen oxides, and meteorological variables. Selective halocarbon and ultrafine aerosol concentration measurements were also made. MAX-DOAS observations of iodine monoxide (IO) display a weak seasonal variation. The maximum differential slant column density was 3.8 Â 10 13 molecule cm À2 (detection limit~7 Â 10 12 molecule cm À2 ). The seasonal variation of reactive iodine IO x (= I + IO) is stronger, peaking at 1.6 pptv during the warm season (February-April). This suggests a dependence of the iodine sources on the annual cycle in sea surface temperature, although perturbations by changes in ocean surface iodide concentration and solar radiation are also possible. An observed negative correlation of IO x with chlorophyll-a indicates a predominance of abiotic sources. The low IO mixing ratios measured (below the LP-DOAS detection limit of 0.9 pptv) are not consistent with satellite observations if IO is confined to the MBL. The IO x loading is consistent with the observed absence of strong ozone depletion and nucleation events, indicating a small impact of iodine chemistry on these climatically relevant factors in the eastern Pacific MBL.

show abstract

Relationships between atmospheric organic compounds and air-mass exposure to marine biology

Cited by 38 publications

References 66 publications

Investigating organic aerosol loading in the remote marine environment

Investigating organic aerosol loading in the remote marine environment

Reproduction of Spatio-Temporal Patterns of Major Mediterranean Phytoplankton Groups from Remote Sensing OC-CCI Data

Iodine chemistry in the eastern Pacific marine boundary layer

Contact Info

Product

Resources

About