Abstract
We present a new method to infer nitrogen oxides (NOx) emissions and lifetimes based on tropospheric nitrogen dioxide (NO2) observations together with reanalysis wind fields for cities located in polluted backgrounds. Since the accuracy of the method is difficult to assess due to lack of “true values” that can be used as a benchmark, we apply the method to synthetic NO2 observations derived from the NASA-Unified Weather Research and Forecasting (NU-WRF) model at a high horizontal spatial resolution of 4 km × 4 km for cities over the continental US. We compare the inferred emissions and lifetimes with the values given by the NU-WRF model to evaluate the method. The method is applicable to 26 US cities. The derived results are generally in good agreement with the values given by the model, with the relative differences of 2 % ± 17 % (mean ± standard deviation) and 15 % ± 25 % for lifetimes and emissions, respectively. Our investigation suggests that the use of wind data prior to satellite overpass time improves the performance of the method. The correlation coefficients between inferred and NU-WRF lifetimes increase from 0.56 to 0.79 and for emissions increase from 0.88 to 0.96 when comparing results based on wind fields sampled simultaneously with satellite observations and averaged over 9 hours data prior to satellite observations, respectively. We estimate that uncertainties in NOx lifetime and emissions arising from the method are approximately 15 % and 20 %, respectively, for typical (US) cities. We expect this new method to be applicable to NO2 observations from the TROPOspheric Monitoring Instrument (TROPOMI) and geostationary satellites, such as Geostationary Environment Monitoring Spectrometer (GEMS) or the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument, to estimate urban NOx emissions and lifetimes globally.
Highlights
Nitrogen oxides (NOx), consisting of nitrogen dioxide (NO2) and nitric oxide (NO), are important atmospheric trace gases that actively participate in the formation of tropospheric ozone and secondary aerosols and have a significant effect on human health and climate (Seinfeld and Pandis, 2006)
In this work we developed a Chemical transport models (CTMs)-independent approach, MISATEAM, to infer NOx lifetimes and emissions from satellite NO2 observations
MISATEAM improves upon Liu et al (2016b) by advancing the fitting function to reduce the number of parameters and to provide estimations of NOx lifetimes and emissions simultaneously
Summary
Nitrogen oxides (NOx), consisting of nitrogen dioxide (NO2) and nitric oxide (NO), are important atmospheric trace gases that actively participate in the formation of tropospheric ozone and secondary aerosols and have a significant effect on human health and climate (Seinfeld and Pandis, 2006). Chemical transport models (CTMs) were initially employed to use NO2 measured from space as a constraint to improve NOx emission inventories based on mass balance (e.g., Martin et al, 2003; Kim et al, 2009; Lamsal et al, 2011) Techniques such as the four-dimensional variational (4D-Var) method (e.g., Henze et al, 2007, 2009), extended Kalman filter (e.g., Ding et al, 2017), ensemble Kalman filter (e.g., Miyazaki et al, 2017), and hybrid mass balance/4D-Var (e.g., Qu et al, 2019) have been used to improve emissions estimates within CTMs. Several studies have inferred emissions independent of CTMs (e.g., Beirle et al, 2011; Liu et al, 2017; Laughner and Cohen, 2019). On the basis of previous approaches (Beirle et al, 2011; Liu et al, 2016b), we develop a new CTM-independent approach for inferring NOx lifetimes and emissions for cities with polluted backgrounds and complex spatial distribution of interfering emissions.
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