A Large Underestimate of Formic Acid from Tropical Fires: Constraints from Space-Borne Measurements.

Formic acid (HCOOH) is one of the most abundant carboxylic acids and a dominant source of atmospheric acidity. Recent work indicates a major gap in the HCOOH budget, with atmospheric concentrations much larger than expected from known sources. Here, we employ recent space-based observations from the Tropospheric Emission Spectrometer with the GEOS-Chem atmospheric model to better quantify the HCOOH source from biomass burning, and assess whether fire emissions can help close the large budget gap for this species. The space-based data reveal a severe model HCOOH underestimate most prominent over tropical burning regions, suggesting a major missing source of organic acids from fires. We develop an approach for inferring the fractional fire contribution to ambient HCOOH and find, based on measurements over Africa, that pyrogenic HCOOH:CO enhancement ratios are much higher than expected from direct emissions alone, revealing substantial secondary organic acid production in fire plumes. Current models strongly underestimate (by 10 ± 5 times) the total primary and secondary HCOOH source from African fires. If a 10-fold bias were to extend to fires in other regions, biomass burning could produce 14 Tg/a of HCOOH in the tropics or 16 Tg/a worldwide. However, even such an increase would only represent 15-20% of the total required HCOOH source, implying the existence of other larger missing sources.

HCOOH measurements from space: TES retrieval algorithm and observed global distribution.

Presented is a detailed description of the TES (Tropospheric Emission Spectrometer)-Aura satellite formic acid (HCOOH) retrieval algorithm and initial results quantifying the global distribution of tropospheric HCOOH. The retrieval strategy, including the optimal estimation methodology, spectral microwindows, a priori constraints, and initial guess information, are provided. A comprehensive error and sensitivity analysis is performed in order to characterize the retrieval performance, degrees of freedom for signal, vertical resolution, and limits of detection. These results show that the TES HCOOH retrievals (i) typically provide at best 1.0 pieces of information; (ii) have the most vertical sensitivity in the range from 900 to 600 hPa with ~2 km vertical resolution; (iii) require at least 0.5 ppbv (parts per billion by volume) of HCOOH for detection if thermal contrast is greater than 5 K, and higher concentrations as thermal contrast decreases; and (iv) based on an ensemble of simulated retrievals, are unbiased with a standard deviation of ±0.4 ppbv. The relative spatial distribution of tropospheric HCOOH derived from TES and its associated seasonality are broadly correlated with predictions from a state-of-the-science chemical transport model (GEOS-Chem CTM). However, TES HCOOH is generally higher than is predicted by GEOS-Chem, and this is in agreement with recent work pointing to a large missing source of atmospheric HCOOH. The model bias is especially pronounced in summertime and over biomass burning regions, implicating biogenic emissions and fires as key sources of the missing atmospheric HCOOH in the model.

Quantifying global terrestrial methanol emissions using observations from the TES satellite sensor.

We employ new global space-based measurements of atmospheric methanol from the Tropospheric Emission Spectrometer (TES) with the adjoint of the GEOS-Chem chemical transport model to quantify terrestrial emissions of methanol to the atmosphere. Biogenic methanol emissions in the model are based on version 2.1 of the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1), using leaf area data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and GEOS-5 assimilated meteorological fields. We first carry out a pseudo observation test to validate the overall approach, and find that the TES sampling density is sufficient to accurately quantify regional- to continental-scale methanol emissions using this method. A global inversion of two years of TES data yields an optimized annual global surface flux of 122 Tg yr-1 (including biogenic, pyrogenic, and anthropogenic sources), an increase of 60 % from the a priori global flux of 76 Tg yr-1. Global terrestrial methanol emissions are thus nearly 25 % those of isoprene (~540 Tg yr-1), and are comparable to the combined emissions of all anthropogenic volatile organic compounds (~100-200 Tg yr-1). Our a posteriori terrestrial methanol source leads to a strong improvement of the simulation relative to an ensemble of airborne observations, and corroborates two other recent top-down estimates (114-120 Tg yr-1) derived using in situ and space-based measurements. Inversions testing the sensitivity of optimized fluxes to model errors in OH, dry deposition, and oceanic uptake of methanol, as well as to the assumed a priori constraint, lead to global fluxes ranging from 118 to 126 Tg yr-1. The TES data imply a relatively modest revision of model emissions over most of the tropics, but a significant upward revision in midlatitudes, particularly over Europe and North America. We interpret the inversion results in terms of specific source types using the methanol : CO correlations measured by TES, and find that biogenic emissions are overestimated relative to biomass burning and anthropogenic emissions in central Africa and southeastern China, while they are underestimated in regions such as Brazil and the US. Based on our optimized emissions, methanol accounts for > 25 % of the photochemical source of CO and HCHO over many parts of the northern extratropics during springtime, and contributes ~6 % of the global secondary source of those compounds annually.

Methanol from TES global observations: retrieval algorithm and seasonal and spatial variability.

We present a detailed description of the TES methanol (CH3OH) retrieval algorithm, along with initial global results showing the seasonal and spatial distribution of methanol in the lower troposphere. The full development of the TES methanol retrieval is described, including microwindow selection, error analysis, and the utilization of a priori and initial guess information provided by the GEOS-Chem chemical transport model. Retrieval simulations and a sensitivity analysis using the developed retrieval strategy show that TES: (i) generally provides less than 1.0 piece of information, (ii) is sensitive in the lower troposphere with peak sensitivity typically occurring between ~900-700 hPa (~1-3 km) at a vertical resolution of ~5 km, (iii) has a limit of detectability between 0.5 and 1.0 ppbv Representative Volume Mixing Ratio (RVMR) depending on the atmospheric conditions, corresponding roughly to a profile with a maximum concentration of at least 1 to 2 ppbv, and (iv) in a simulation environment has a mean bias of 0.16 ppbv with a standard deviation of 0.34 ppbv. Applying the newly derived TES retrieval globally and comparing the results with corresponding GEOS-Chem output, we find generally consistent large-scale patterns between the two. However, TES often reveals higher methanol concentrations than simulated in the Northern Hemisphere spring, summer and fall. In the Southern Hemisphere, the TES methanol observations indicate a model overestimate over the bulk of South America from December through July, and a model underestimate during the biomass burning season.

Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions.

Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1-2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index <1.2) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of both the IASI and TES measurements.