Data for "Quantifying the Missing Half of Daily NOx Emissions over South, Southeast and East Asia"

Fig_1_Mask_ROI.mat is the area mask and the standard deviation of OMI NO2 over the ROI.
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Fig_2_PC_EOF.mat is the EOF map and PC time series of the first 4 mode of OMI NO2 dataset.<br>

Fig_3_EOF_PC_4_Typical_Urban_And_BB.mat s the 2 typical EOF map and extreme time series extracted for Urban areas and BB areas, respectively.<br>

Fig_4_typical_daily_NOx_estimation.mat is 4 typical daily NOx emission in this paper.
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Fig_5_NOx_Mean_Ratio_4_Estimation_EI.mat is the mean and ratio of Mean to standard deviation of NOx estimation and the existing emission inventories(FINN+EDGAR, both in EOF and Mask regions).
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Fig_6_Timeseries_of_NOx_Est_EOF_Mask_4_Urban_BB.mat is the time series of NOx estimation, NOx emission inventory over EOF region and NOx emission inventory over mask region in Fig.1 for Urban and BB areas.<br>

Fig_7_NOx_Estimation_PDF_Geolocation_4_LCT_types.mat is the NOx estimation and geolocation distribution of 3 land cover types.
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Fig_8_NOx_Estimation_Comparison_4_Sensitivity_Runs.mat is the differences between Base+40%/Base-40% and Base, plus the time series comparisons of the three runs (Base+40%, Base-40% and Base) in both Urban and BB areas.<br>

Sup_Fig_1_NO2_mean_ROI.mat is the mean of OMI NO2 over the ROI.<br>

Sup_Fig_2_Lai_ROI.mat is the land cover types of MODIS over the ROI.<br>

Sup_Fig_3_EOF_PC_4_SouthernCSA.mat s 3 typical EOF map and extreme time series extracted for Southern Continental Southeast Asia.<br>

noxEst_year_2016.mat is the estimated NOx dataset for 2016 within this work.
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estimateGridCoefEmission.m is the core MATLAB code used to fit the coefficients with Least Square Method and estimate the emission with bootstrap method.
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Demo.zip is one example to help test the core code of this work.