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Saikawa_2017_Environ._Res._Lett._12_065002.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/78085 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/78085 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/78085 archive 5 disk0/00/01/46/63 2017-06-13 07:47:36 2021-08-27 17:29:06 2017-06-13 07:47:36 article show Saikawa E. 8207 Trail M. Zhong M. Wu Q. Young C.L. Janssens-Maenhout G. Klimont Z. 1473 0000-0003-2630-198X Wagner F. 1789 0000-0003-3429-2374 Kurokawa J. Nagpure A.S. Gurjar B.R. pub prog_air prog_mag Greenhouse gas and air pollutant precursor emissions have been increasing rapidly in India. Large uncertainties exist in emissions inventories and quantification of their uncertainties is essential for better understanding of the linkages among emissions and air quality, climate, and health. We use Monte Carlo methods to assess the uncertainties of the existing carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission estimates from four source sectors for India. We also assess differences in the existing emissions estimates within the nine subnational regions. We find large uncertainties, higher than the current estimates for all species other than CO, when all the existing emissions estimates are combined. We further assess the impact of these differences in emissions on air quality using a chemical transport model. More efforts are needed to constrain emissions, especially in the Indo-Gangetic Plain, where not only the emissions differences are high but also the simulated concentrations using different inventories. Our study highlights the importance of constraining SO2, NOx, and NH3 emissions for secondary PM concentrations. 2017 published IOP Publishing 10.1088/1748-9326/aa6cb4 1548 159 321 public Environmental Research Letters 12 6 065002 TRUE 1748-9326 FALSE no info:eu-repo/semantics/article