Remotely sensed and surface measurement- derived mass-conserving inversion of daily NO_<i>x</i> emissions and inferred combustion technologies in energy-rich northern China

Abstract

This work presents a new model-free inversion estimation framework (MFIEF) using daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 columns and observed fluxes from the continuous emission monitoring system (CEMS) to quantify 3 years of daily scale emissions of NOx at 0.05∘×0.05∘ over Shanxi Province, a major world-wide energy-producing and energy-consuming region. The NOx emissions, day-to-day variability, and uncertainty on a climatological basis are computed to be 1.86, 1.03, and 1.05 Tg yr−1 respectively. The highest emissions are concentrated in the lower Fen River valley, which accounts for 25 % of the area, 53 % of the NOx emissions, and 72 % of CEMS sources. Two major forcing factors (10th to 90th percentile) are horizontal transport distance per day (63–508 km) and lifetime of NOx (7.1–18.1 h). Both of these values are consistent with NOx emissions to both the surface layer and the free troposphere. The third forcing factor, the ratio of NOx/NO2, on a pixel-to-pixel basis, is demonstrated to correlate with the combustion temperature and energy efficiency of large energy consuming sources. Specifically, thermal power plants, cement, and iron and steel companies have a relatively high NOx/NO2 ratio, while coking, industrial boilers, and aluminum oxide factories show a relatively lower ratio. Variance maximization is applied to daily TROPOMI NO2 columns, which facilitates identification of three orthogonal and statistically significant modes of variability, and successfully attributes them both spatially and temporally to (a) this work's computed emissions, (b) remotely sensed TROPOMI ultraviolet aerosol index (UVAI), and (c) computed transport based on TROPOMI NO2.