Additional file 1 of Artificial intelligence for improving Nitrogen Dioxide forecasting of Abu Dhabi environment agency ground-based stations
Creators: name: AlShehhi, Aamna
name: Welsch, Roy
Publisher: name: figshare
Year: 2024
Subjects: subject: Artificial Intelligence and Image Processing
subject: FOS: Computer and information sciences

description: Additional file 1: Table S1: Missing Value Percentages in the 20 UAE monitoring stations. Figure S1. Station 1 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S2: Station 2 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S3: Station 3 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements.Figure S4: Station 4 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S5: Station 5 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S6: Station 6 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S7: Station 7 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S8: Station 8 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S9: Station 9 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S10: Station 10 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S11: Station 11 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements.Figure S12: Station 12 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S13: Station 14 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S14: Station 15 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S15: Station 16 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S16: Station 17 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S17: Station 18 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S18: Station 19 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements. Figure S19: Station 20 NO2 concentration: A)Missing values distribution: The missing regions are highlighted. B) Missing values imputation: visualization of missing value replacements