Can simple models predict large-scale surface ocean isoprene concentrations?

Abstract

Abstract. We use isoprene and related field measurements from three different ocean data sets together with remotely sensed satellite data to model global marine isoprene emissions. We show that using monthly mean satellite-derived chl a concentrations to parameterize isoprene with a constant chl a normalized isoprene production rate underpredicts the measured oceanic isoprene concentration by a mean factor of 19 ± 12. Improving the model by using phytoplankton functional type dependent production values and by decreasing the bacterial degradation rate of isoprene in the water column results in only a slight underestimation (factor 1.7 ± 1.2). We calculate global isoprene emissions of 0.21 Tg C for 2014 using this improved model, which is twice the value calculated using the original model. Nonetheless, the sea-to-air fluxes have to be at least 1 order of magnitude higher to account for measured atmospheric isoprene mixing ratios. These findings suggest that there is at least one missing oceanic source of isoprene and, possibly, other unknown factors in the ocean or atmosphere influencing the atmospheric values. The discrepancy between calculated fluxes and atmospheric observations must be reconciled in order to fully understand the importance of marine-derived isoprene as a precursor to remote marine boundary layer particle formation.

Marine isoprene production and consumption in the mixed layer of the surface ocean – a field study over two oceanic regions

“…We neglected the loss rates of isoprene due to biological degradation and physical mixing because they are low compared to k CHEM and k AS (Palmer and Shaw, 2005;Booge et al, 2016), meaning that the resulting P need value can be seen as a minimum needed production rate.…”

“…Isoprene production rates of different PFTs were determined in laboratory phytoplankton culture experiments (see a collection of literature values: Table 2 in Booge et al, 2016) and were used here to calculate isoprene production from measured PFTs in the field. These literature studies showed that isoprene production rates are light dependent, with increasing production rates at higher light levels (Shaw et al, 2003;Gantt et al, 2009;Bonsang et al, 2010;Meskhidze et al, 2015).…”

“…Marine-derived isoprene emissions only account for a few percent of the total emissions and are suggested, based on model studies, to be generally lower than 1 Tg C yr −1 (Palmer and Shaw, 2005;Arnold et al, 2009;Gantt et al, 2009;Booge et al, 2016). Some model studies suggest that these low emissions are not enough to control the formation of SOAs over the ocean (Spracklen et al, 2008;Arnold et al, 2009;Gantt et al, 2009;Anttila et al, 2010;Myriokefalitakis et al, 2010).…”

“…However, this link is not consistent enough on global scales to predict marine isoprene concentrations using chl a (Table 1). Laboratory studies with different monocultures illustrate that the isoprene production rate varies widely depending on the phytoplankton functional type (PFT) (Booge et al, 2016, and references therein). In addition, environmental parameters, such as temperature and light, have been shown to influence isoprene production (Shaw et al, 2003;Exton et al, 2013;Meskhidze et al, 2015).…”

Obtaining Phytoplankton Diversity from Ocean Color: A Scientific Roadmap for Future Development

“…In addition, satellite PG data were used to assess globally particulate organic carbon export (Mouw et al, 2016), for detection of regional HAB events (e.g., Kurekin et al, 2014), the estimation of recruitment of juvenile fish (Trzcinski et al, 2013) and for inferring globally oceanic emissions of volatile organic compounds (Arnold et al, 2009;Booge et al, 2016).…”