Which processes drive observed variations of HCHO columns over India?

Abstract

Abstract. We interpret HCHO column variations observed by the Ozone Monitoring Instrument (OMI), aboard the NASA Aura satellite, over India during 2014 using the GEOS-Chem atmospheric chemistry and transport model. We use a nested version of the model with a spatial resolution of approximately 25 km. HCHO columns are related to local emissions of volatile organic compounds (VOCs) with a spatial smearing that increases with the VOC lifetime. Over India, HCHO has bio-5 genic, pyrogenic, and anthropogenic VOC sources. Using a 0-D photochemistry model, we find that isoprene has the largest molar yield of HCHO that is typically realized within a few hours. We find that forested regions that neighbours major urban conurbations are exposed to high levels of nitrogen oxides. This results in depleted hydroxyl radical concentrations and a delay in the production of HCHO from isoprene oxidation. We find that propene is the only anthropogenic VOC emitted 10 in major Indian cities that produces HCHO at a comparable (slower) rate to isoprene. The GEOSChem model reproduces the broadscale annual mean HCHO column distribution observed by OMI (r=0.6), which is dominated by a distinctive meridional gradient in the northern half of the country, and by localized regions of high columns that coincide with forests. Major discrepancies are over the Indo-Gangetic Plain and Delhi. We find that the model has more skill at reproducing observations

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“…These findings are consistent with earlier work by Mahajan et al () and Surl et al (). Mahajan et al () compared HCHO column measurements from multiple satellite instruments with model predictions over India that were derived (as here) using RETRO and MEGAN VOC emissions.…”

“…Relative to the 2008–2015 period, the year 2009 OMI HCHO columns are fairly typical in the annual mean, unusually low in October, and unusually high in December. These interannual differences, partly reflecting meteorological variability associated with monsoon withdrawal (Surl et al, ), could play a role in the lower biogenic scale factor derived here for SON (relative to the other seasons) and the higher derived biogenic scale factor for DJF.…”

“…The SON period also marks the transition from wet‐to‐dry seasonal conditions across much of India. Previous studies over Amazonia (Barkley et al, ; Myneni et al, ) and India (Surl et al, ) imply a significant role for leaf flushing during the wet‐to‐dry transition, with impacts on isoprene emissions. Indeed, LAI reductions are seen over parts of India during the monsoon, with a subsequent post‐monsoonal increase (Figure S4).…”

“…On that basis the authors concluded that the model VOC emissions must be too high. Surl et al () compared OMI HCHO columns over India with GEOS‐Chem model predictions for year 2014. Aggregated over the region as a whole, their modeled columns were higher than the observations throughout much of the year, with the smallest disparity during winter—also qualitatively consistent with the downward total VOC emission adjustments derived here.…”

“…In a multi‐year analysis, Mahajan et al () also found the largest model HCHO overestimate during SON. However, Surl et al () showed that the seasonal cycle of HCHO columns over India varies significantly from year to year. Relative to the 2008–2015 period, the year 2009 OMI HCHO columns are fairly typical in the annual mean, unusually low in October, and unusually high in December.…”