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1.
Environ Pollut ; 252(Pt A): 256-269, 2019 Sep.
Article in English | MEDLINE | ID: mdl-31153030

ABSTRACT

We investigate the distribution of volatile organic compounds (VOCs) over Indian subcontinent during a winter month of January 2011 combining the regional model WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) with ground- and space-based observations and chemical reanalysis. WRF-Chem simulated VOCs are found to be comparable with ground-based observations over contrasting environments of the Indian subcontinent. WRF-Chem results reveal the elevated levels of VOCs (e. g. propane) over the Indo-Gangetic Plain (16 ppbv), followed by the Northeast region (9.1 ppbv) in comparison with other parts of the Indian subcontinent (1.3-8.2 ppbv). Higher relative abundances of propane (27-31%) and ethane (13-17%) are simulated across the Indian subcontinent. WRF-Chem simulated formaldehyde and glyoxal show the western coast, Eastern India and the Indo-Gangetic Plain as the regional hotspots, in a qualitative agreement with the MACC (Monitoring Atmospheric Composition and Climate) reanalysis and satellite-based observations. Lower values of RGF (ratio of glyoxal to formaldehyde <0.04) suggest dominant influences of the anthropogenic emissions on the distribution of VOCs over Indian subcontinent, except the northeastern region where higher RGF (∼0.06) indicates the role of biogenic emissions, in addition to anthropogenic emissions. Analysis of HCHO/NO2 ratio shows a NOx-limited ozone production over India, with a NOx-to-VOC transition regime over central India and IGP. The study highlights a need to initiate in situ observations of VOCs over regional hotspots (Northeast, Central India, and the western coast) based on WRF-Chem results, where different satellite-based observations differ significantly.


Subject(s)
Air Pollutants/analysis , Computer Simulation , Environmental Monitoring/methods , Ozone/analysis , Satellite Imagery , Volatile Organic Compounds/analysis , Climate , Ethane/analysis , Forecasting , Formaldehyde/analysis , Glyoxal/analysis , India , Propane/analysis , Seasons , Weather
2.
J Environ Sci (China) ; 71: 108-118, 2018 Sep.
Article in English | MEDLINE | ID: mdl-30195669

ABSTRACT

Currently, modeling studies tend to significantly underestimate observed space-based glyoxal (CHOCHO) vertical column densities (VCDs), implying the existence of missing sources of glyoxal. Several recent studies suggest that the emissions of aromatic compounds and molar yields of glyoxal in the chemical mechanisms may both be underestimated, which can affect the simulated glyoxal concentrations. In this study, the influences of these two factors on glyoxal amounts over China were investigated using the RAMS-CMAQ modeling system for January and July 2014. Four sensitivity simulations were performed, and the results were compared to satellite observations. These results demonstrated significant impacts on glyoxal concentrations from these two factors. In case 1, where the emissions of aromatic compounds were increased three-fold, improvements to glyoxal VCDs were seen in high anthropogenic emissions regions. In case 2, where molar yields of glyoxal from isoprene were increased five-fold, the resulted concentrations in July were 3-5-fold higher, achieving closer agreement between the modeled and measured glyoxal VCDs. The combined changes from both cases 1 and 2 were applied in case 3, and the model succeeded in further reducing the underestimations of glyoxal VCDs. However, the results over most of the regions with pronounced anthropogenic emissions were still underestimated. So the molar yields of glyoxal from anthropogenic precursors were considered in case 4. With these additional mole yield changes (a two-fold increase), the improved concentrations agreed better with the measurements in regions of the lower reaches of the Yangtze River and Yellow River in January but not in July.


Subject(s)
Air Pollutants/analysis , Air Pollution/statistics & numerical data , Environmental Monitoring/methods , Glyoxal/analysis , Models, Chemical
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