Gridded anthropogenic emissions inventory and atmospheric transport of carbonyl sulfide in the U.S.

Abstract

Carbonyl sulfide (COS or OCS), the most abundant sulfur‐containing gas in the troposphere, has recently emerged as a potentially important atmospheric tracer for the carbon cycle. Atmospheric inverse modeling studies may be able to use existing tower, airborne, and satellite observations of COS to infer information about photosynthesis. However, such analysis relies on gridded anthropogenic COS source estimates that are largely based on industry activity data from over three decades ago. Here we use updated emission factor data and industry activity data to develop a gridded inventory with a 0.1° resolution for the U.S. domain. The inventory includes the primary anthropogenic COS sources including direct emissions from the coal and aluminum industries as well as indirect sources from industrial carbon disulfide emissions. Compared to the previously published inventory, we found that the total anthropogenic source (direct and indirect) is 47% smaller. Using this new gridded inventory to drive the Sulfur Transport and Deposition Model/Weather Research and Forecasting atmospheric transport model, we found that the anthropogenic contribution to COS variation in the troposphere is small relative to the biosphere influence, which is encouraging for carbon cycle applications in this region. Additional anthropogenic sectors with highly uncertain emission factors require further field measurements.

Biomass Burning Unlikely to Account for Missing Source of Carbonyl Sulfide

“…Observed atmospheric surface mixing ratios from global and hemispheric averages of NOAA air monitoring sites (Montzka et al, ), as well as annually averaged tropospheric mixing ratios from Jungfraujoch (Lejeune et al, ), show a moderate decline in the 1990s followed by similarly moderate growth in the 2000s (both approximately 1% year −1 ), with relatively little interannual variation. These time trends have been attributed to trends in the anthropogenic inventory, driven by a decline in residential coal in the early 1990s and the decline and growth of the rayon industry from 1990 onward (Campbell et al, ; Du et al, ; Zumkehr et al, , ).…”

Reviews and Syntheses: Carbonyl Sulfide as a Multi-scale Tracer for Carbon and Water Cycles

“…Anthropogenic sources have been used to interpret changes in atmospheric OCS observations in space and time Zumkehr et al, 2017). These sources include direct emissions of OCS as well as indirect sources caused by anthropogenic emissions of CS 2 .…”

“…The dominant 15 anthropogenic source is from rayon production , while other large anthropogenic sources include coal combustion, aluminum smelting, pigment production, shipping, tire wear, vehicle emissions, and coke production Chin and Davis, 1993;Lee and Brimblecombe, 2016;Watts, 2000). Temporally and spatially explicit inventories have been created for use in OCS atmospheric transport models Zumkehr et al, 2017). 20…”

“…While OCS observations show promise as an independent GPP tracer, there are smaller terrestrial OCS sources and sinks from soils 5 Kettle et al, 2002;Maseyk et al, 2014;Ogée et al, 2016;Sun et al, 2015; and industrial activities Kettle et al, 2002;Zumkehr et al, 2017) that must be considered (see Sect. 2).…”

High-resolution spatiotemporal patterns of China’s FFCO2 emissions under the impact of LUCC from 2000 to 2015

“…One approach to quantify and reduce the uncertainties (Janardanan et al 2016) associated with estimated emissions is homogeneously and optimally integrating all available observations together with prior information. Liu et al (2017) combined surface measurements with satellite data into a regional highresolution atmospheric transport model (Kort et al 2012, Zumkehr et al 2017 for central and southern Europe, revealing the spatiotemporal patterns of the FFCO 2 signal and additional changes in the variability in atmospheric CO 2 associated with FFCO 2 emissions. A new airborne method (Wecht et al 2014, Mitchell et al 2015 has been applied to quantify localized surface emissions at spatial scales of~1000 m, with an error less than 10% accounting for smaller-scale turbulent dispersion (Conley et al 2017).…”