2023
DOI: 10.1016/j.rse.2023.113720
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Model-free daily inversion of NOx emissions using TROPOMI (MCMFE-NOx) and its uncertainty: Declining regulated emissions and growth of new sources

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Cited by 15 publications
(8 citation statements)
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“…This combination led us to determine that the 80th percentile was optimal for subsequent use. Interestingly, using the 80% range of data for EOF1 leads to a map which is highly correlated with known urban, energy extractive, and industrial regions in Xinjiang, Lanzhou, Xi'an, and the Northwestern Energy Triangle found in and between Ningxia, Yulin, and Baotao 70,71 .…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…This combination led us to determine that the 80th percentile was optimal for subsequent use. Interestingly, using the 80% range of data for EOF1 leads to a map which is highly correlated with known urban, energy extractive, and industrial regions in Xinjiang, Lanzhou, Xi'an, and the Northwestern Energy Triangle found in and between Ningxia, Yulin, and Baotao 70,71 .…”
Section: Resultsmentioning
confidence: 99%
“…Mie models can approximate various optical properties of aerosols, accounting for the extinction, scattering, absorption, to approximate the mixing state, size, and implied composition of aerosols 71 . This work focuses on using SSA observations as the basis to constrain the MIE model.…”
Section: Mie Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…TROPOMI and GOSAT have both been shown to be data-rich at times (Butz et al, 2012;Hu et al, 2018;Jacob et al, 2016), but severely limited at other times (Butz et al, 2012;Kuze et al, 2009). Even when these satellites have sufficient data to compute emissions from other species, frequently CH4 cannot be computed (Li et al, 2023;Qin et al, 2023b) due to insufficient signal strength, and uncertainties which are both non-understood and mis-constrained (Povey and Grainger, 2015).…”
Section: Introductionmentioning
confidence: 99%
“…The uncertainties inherent in current aerosol emission databases are particularly pronounced for absorbing aerosols such as biomass burning and dust, which is a focus of the present research. Some literature (Cohen and Wang, 2014;Qin et al, 2023) suggests that the emission values of these absorbing aerosols (Wang et al, 2021) derived from remote sensing (referred to as "top-down" approaches) can be significantly higher, ranging from 2 to 4 times, compared to the "bottom-up" methodologies that are predominantly adopted by entities such as the IPCC and in many modeling studies. In particular, the findings of these top-down methodologies align more consistently with data from sun photometer (e.g., AERONET) (Burton et al, 2012) and lidar networks.…”
Section: Introductionmentioning
confidence: 99%