Net ecosystem fluxes of isoprene over tropical South America inferred from Global Ozone Monitoring Experiment (GOME) observations of HCHO columns

Abstract

[1] We estimate isoprene emissions over tropical South America during 1997-2001 using column measurements of formaldehyde (HCHO) from the Global Ozone Monitoring Experiment (GOME) satellite instrument, the GEOS-Chem chemistry transport model, and the MEGAN (Model of Emissions of Gases and Aerosols from Nature) bottom-up isoprene inventory. GEOS-Chem is qualitatively consistent with in situ ground-based and aircraft concentration profiles of isoprene and HCHO, and GOME HCHO column data (r = 0.41; bias = +35%), but has less skill in reproducing wet season observations. Observed variability of GOME HCHO columns over South America is determined largely by isoprene and biomass burning. We find that the column contributions from other biogenic volatile organic compounds (VOC) are typically smaller than the column fitting uncertainty. HCHO columns influenced by biomass burning are removed using Along Track Scanning Radiometer (ATSR) firecounts and GOME NO 2 columns. We find that South America can be split into eastern and western regions, with fires concentrated over the eastern region. A monthly mean linear transfer function, determined by GEOS-Chem, is used to infer isoprene emissions from observed HCHO columns. The seasonal variation of GOME isoprene emissions over the western region is broadly consistent with MEGAN (r = 0.41; bias = À25%), with largest isoprene emissions during the dry season when the observed variability is consistent with knowledge of temperature dependence. During the wet season, other unknown factors play a significant role in determining observed variability.

The formaldehyde budget as seen by a global-scale multi-constraint and multi-species inversion system

“…Over region South American Tropical, instead of peaking at 4.2 TgHCHO in August only like the prior, the posterior estimates peak at 2 TgHCHO in April (wet season) and at 2.1 TgHCHO in September (dry season). Interestingly, this posterior seasonal cycle agrees well with the in-situ tower measurements of isoprene, also showing two peaks, made for year 2002 at Tapajos National Forest in Brazil (Barkley et al, 2008, their Fig. 8).…”

“…The largest discrepancies are found over the tropical regions, and particularly over South America and Indonesia. This has already been pointed out by Barkley et al (2008), who found higher model HCHO columns (using the GEOS-Chem chemistry-transport model and the MEGAN inventory for NMVOC emissions) than GOME HCHO measurements. HCHO concentrations are mainly driven by NMVOC emissions and the uncertainties associated with these NMVOC emissions (e.g.…”

“…HCHO concentrations are mainly driven by NMVOC emissions and the uncertainties associated with these NMVOC emissions (e.g. in the GEIA inventory, or in Model of Emissions of Gases and Aerosols MEGAN) are large (Barkley et al, 2008). These uncertainties result from errors in emission factors, and from incorrect or incomplete parameterizations of activity factors.…”

“…These uncertainties result from errors in emission factors, and from incorrect or incomplete parameterizations of activity factors. For example, tropical rainforest emission in the GEIA inventory are based on ambient isoprene concentration measurements from a single study (Zimmerman et al, 1988;Barkley et al, 2008), which could explain the notable differences in terms of magnitude over tropical regions. In tropical regions, except Indonesia, our prior does not reproduce the observed seasonal cycle, particularly over South America and Africa.…”

“…Even though uncertainties remain large for the HCHO satellite retrievals, past studies have demonstrated the usefulness of HCHO column data (determined in near-UV wavelengths 310-365 nm) from the Global Ozone Monitoring Experiment (GOME) (Abbot et al, 2003;Palmer et al, 2006Palmer et al, , 2007Fu et al, 2007;Barkley et al, 2008), from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) (Stavrakou et al, 2009) and from the Ozone Monitoring Instrument (OMI) (Millet et al, 2008;Marais et al, 2012) to constrain NMVOC emissions, the latter having the highest spatial resolution of these 3 instruments.…”