Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems
Air quality monitoring systems differ in composition and accuracy of observations and their temporal and spatial coverage. A monitoring system’s performance can be assessed by evaluating the accuracy of the emission sources identified by its data. In the considered inverse modeling approach, a sourc...
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| Vydáno v: | Atmosphere Ročník 12; číslo 12; s. 1697 |
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| Jazyk: | angličtina |
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Basel
MDPI AG
01.12.2021
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| ISSN: | 2073-4433, 2073-4433 |
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| Abstract | Air quality monitoring systems differ in composition and accuracy of observations and their temporal and spatial coverage. A monitoring system’s performance can be assessed by evaluating the accuracy of the emission sources identified by its data. In the considered inverse modeling approach, a source identification problem is transformed to a quasi-linear operator equation with the sensitivity operator. The sensitivity operator is composed of the sensitivity functions evaluated on the adjoint ensemble members. The members correspond to the measurement data element aggregates. Such ensemble construction allows working in a unified way with heterogeneous measurement data in a single-operator equation. The quasi-linear structure of the resulting operator equation allows both solving and predicting solutions of the inverse problem. Numerical experiments for the Baikal region scenario were carried out to compare different types of inverse problem solution accuracy estimates. In the considered scenario, the projection to the orthogonal complement of the sensitivity operator’s kernel allowed predicting the source identification results with the best accuracy compared to the other estimate types. Our contribution is the development and testing of a sensitivity-operator-based set of tools for analyzing heterogeneous air quality monitoring systems. We propose them for assessing and optimizing observational systems and experiments. |
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| AbstractList | Air quality monitoring systems differ in composition and accuracy of observations and their temporal and spatial coverage. A monitoring system’s performance can be assessed by evaluating the accuracy of the emission sources identified by its data. In the considered inverse modeling approach, a source identification problem is transformed to a quasi-linear operator equation with the sensitivity operator. The sensitivity operator is composed of the sensitivity functions evaluated on the adjoint ensemble members. The members correspond to the measurement data element aggregates. Such ensemble construction allows working in a unified way with heterogeneous measurement data in a single-operator equation. The quasi-linear structure of the resulting operator equation allows both solving and predicting solutions of the inverse problem. Numerical experiments for the Baikal region scenario were carried out to compare different types of inverse problem solution accuracy estimates. In the considered scenario, the projection to the orthogonal complement of the sensitivity operator’s kernel allowed predicting the source identification results with the best accuracy compared to the other estimate types. Our contribution is the development and testing of a sensitivity-operator-based set of tools for analyzing heterogeneous air quality monitoring systems. We propose them for assessing and optimizing observational systems and experiments. |
| Author | Penenko, Alexey Gochakov, Alexander Konopleva, Viktoriia Penenko, Vladimir Pyanova, Elza Tsvetova, Elena |
| Author_xml | – sequence: 1 givenname: Alexey orcidid: 0000-0002-1729-3343 surname: Penenko fullname: Penenko, Alexey – sequence: 2 givenname: Vladimir orcidid: 0000-0002-1646-7743 surname: Penenko fullname: Penenko, Vladimir – sequence: 3 givenname: Elena orcidid: 0000-0003-1947-9560 surname: Tsvetova fullname: Tsvetova, Elena – sequence: 4 givenname: Alexander orcidid: 0000-0001-9909-9730 surname: Gochakov fullname: Gochakov, Alexander – sequence: 5 givenname: Elza orcidid: 0000-0002-9505-9448 surname: Pyanova fullname: Pyanova, Elza – sequence: 6 givenname: Viktoriia surname: Konopleva fullname: Konopleva, Viktoriia |
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| Cites_doi | 10.3390/atmos11111230 10.3390/atmos9010008 10.1134/S0021894419020202 10.3390/su13041686 10.1002/wcc.535 10.1038/s41598-018-25153-w 10.3390/atmos11111215 10.1016/j.envsoft.2010.01.006 10.3390/atmos12070807 10.1016/j.atmosenv.2021.118366 10.3390/atmos10080470 10.1016/j.scs.2020.102190 10.1002/qj.3471 10.1515/jiip.1995.3.2.131 10.1145/3326162 10.1088/1755-1315/611/1/012032 10.1093/acprof:oso/9780198723844.003.0022 10.3390/atmos12050595 10.1111/j.1600-0870.1986.tb00459.x 10.3390/atmos12101348 10.3934/ipi.2020035 10.1016/S1352-2310(97)00480-9 10.5194/acp-5-249-2005 10.5194/amt-14-6057-2021 10.3390/s18124363 10.3390/atmos11121289 10.3390/atmos12121542 10.1175/BAMS-D-18-0013.1 10.1088/0266-5611/29/3/035009 10.1016/j.atmosenv.2017.02.011 10.3390/atmos12101357 10.3389/fenvs.2018.00085 10.1134/S1024856020060056 10.1007/s10874-015-9326-0 10.3390/atmos11030244 10.5194/npg-22-15-2015 10.1175/MWR-D-10-05013.1 10.1016/j.scs.2020.102239 10.1002/2014MS000385 10.5194/amt-13-4601-2020 10.1002/2015JD024110 10.1002/2017JD026825 10.5194/gmd-12-3687-2019 10.1002/9781118033210 10.5194/acp-3-2111-2003 10.1134/S1995423920020068 10.1007/978-94-009-1740-8 10.3390/atmos10120739 10.3390/atmos12030374 10.1142/S021972001940002X 10.1016/j.cpc.2015.10.008 10.1137/1.9780898717761 10.1029/98JD02398 10.1134/S1024856019040067 10.1002/wat2.1528 10.1088/1742-6596/1715/1/012072 10.1016/j.cviu.2020.103134 10.3390/atmos12020179 10.5194/amt-14-7297-2021 10.1088/1361-6560/ab9066 10.1134/S1995423919010051 10.1016/j.jes.2021.01.011 10.1134/S1875372811020119 10.4209/aaqr.210121 10.1016/j.atmosenv.2009.07.011 10.1016/j.atmosenv.2008.02.065 10.17537/2016.11.426 10.5194/acp-15-7703-2015 10.3390/w13192636 10.3390/rs13112219 10.1007/s10666-015-9445-7 10.1016/j.atmosenv.2015.09.030 |
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| References | Araki (ref_8) 2015; 122 ref_50 Abida (ref_5) 2008; 42 Elbern (ref_32) 2007; 7 Penenko (ref_40) 2019; 12 Grigorieva (ref_64) 2011; 32 Desyatkov (ref_18) 1999; 12 ref_14 Dimet (ref_55) 1986; 38A ref_58 ref_57 ref_12 ref_54 ref_51 Carrassi (ref_25) 2018; 9 Penenko (ref_3) 1985; 11 ref_16 ref_15 Penenko (ref_90) 2016; 11 Cheverda (ref_91) 1995; 3 Koh (ref_87) 2021; 203 Nguyen (ref_31) 2021; 253 Liu (ref_77) 2021; 14 Penenko (ref_53) 1976; 11 Penenko (ref_92) 2020; 13 ref_61 Issartel (ref_19) 2003; 3 ref_60 Markakis (ref_34) 2015; 15 Mijling (ref_30) 2020; 13 Brown (ref_66) 2021; 8 ref_69 ref_68 ref_67 Dimet (ref_52) 2015; 22 ref_63 Kim (ref_75) 2020; 101 Keats (ref_7) 2010; 25 Hauglustaine (ref_81) 1998; 103 Voronina (ref_73) 2014; 11 Judd (ref_74) 2018; 6 ref_29 ref_28 Mamonov (ref_20) 2013; 29 ref_26 Silver (ref_27) 2015; 73 Saunier (ref_6) 2009; 43 Baldauf (ref_82) 2011; 139 Naumann (ref_85) 2019; 45 Ngae (ref_9) 2019; 145 Marchuk (ref_49) 1964; 5 ref_72 ref_71 Holnicki (ref_35) 2015; 20 ref_70 Penenko (ref_42) 2019; 17 Akhtimankina (ref_65) 2013; 6 Penenko (ref_41) 2020; 14 ref_36 Plyusnin (ref_59) 2021; 152 ref_79 ref_78 Huang (ref_33) 2021; 21 Mettig (ref_76) 2021; 14 Bieringer (ref_23) 2017; 156 Penenko (ref_86) 2021; 1715 Zhang (ref_88) 2020; 65 Popovicheva (ref_62) 2021; 107 Cao (ref_11) 2020; 59 Khodzher (ref_44) 2019; 32 ref_38 ref_37 Kouichi (ref_10) 2019; 12 deSouza (ref_13) 2020; 60 ref_83 ref_80 ref_46 Antokhin (ref_45) 2018; 123 ref_89 Turbelin (ref_21) 2014; 6 Penenko (ref_39) 2019; 60 ref_1 Kumar (ref_22) 2015; 120 Issartel (ref_56) 2005; 5 ref_2 Pudykiewicz (ref_17) 1998; 32 Vlasenko (ref_84) 2016; 199 Bocquet (ref_24) 2014; 14 ref_48 Penenko (ref_4) 1986; 21 Penenko (ref_43) 2020; 611 Arshinov (ref_47) 2020; 33 |
| References_xml | – ident: ref_60 doi: 10.3390/atmos11111230 – volume: 14 start-page: 32233 year: 2014 ident: ref_24 article-title: Data assimilation in atmospheric chemistry models: Current status and future prospects for coupled chemistry meteorology models publication-title: Atmos. Chem. Phys. Discuss. – ident: ref_28 doi: 10.3390/atmos9010008 – volume: 60 start-page: 392 year: 2019 ident: ref_39 article-title: Methods for Studying the Sensitivity of Air Quality Models and Inverse Problems of Geophysical Hydrothermodynamics publication-title: J. Appl. Mech. Tech. Phys. doi: 10.1134/S0021894419020202 – ident: ref_80 – ident: ref_15 doi: 10.3390/su13041686 – volume: 9 start-page: e535 year: 2018 ident: ref_25 article-title: Data assimilation in the geosciences: An overview of methods, issues, and perspectives publication-title: Wiley Interdiscip. Rev. Clim. Chang. doi: 10.1002/wcc.535 – volume: 152 start-page: 202 year: 2021 ident: ref_59 article-title: Baikal region in the UNESCO “Man and Biocphere” Programme publication-title: Probl. Geogr. – ident: ref_89 doi: 10.1038/s41598-018-25153-w – ident: ref_12 doi: 10.3390/atmos11111215 – volume: 25 start-page: 1000 year: 2010 ident: ref_7 article-title: Information-driven receptor placement for contaminant source determination publication-title: Environ. Model. Softw. doi: 10.1016/j.envsoft.2010.01.006 – ident: ref_16 – ident: ref_69 doi: 10.3390/atmos12070807 – volume: 253 start-page: 118366 year: 2021 ident: ref_31 article-title: Data assimilation methods for urban air quality at the local scale publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2021.118366 – ident: ref_67 doi: 10.3390/atmos10080470 – volume: 59 start-page: 102190 year: 2020 ident: ref_11 article-title: Sensor deployment strategy using cluster analysis of Fuzzy C-Means Algorithm: Towards online control of indoor environment’s safety and health publication-title: Sustain. Cities Soc. doi: 10.1016/j.scs.2020.102190 – volume: 145 start-page: 967 year: 2019 ident: ref_9 article-title: Optimization of an urban monitoring network for emergency response applications: An approach for characterizing the source of hazardous releases publication-title: Q. J. R. Meteorol. Soc. doi: 10.1002/qj.3471 – volume: 3 start-page: 131 year: 1995 ident: ref_91 article-title: R-pseudoinverses for compact operators in Hilbert spaces: Existence and stability publication-title: J. Inverse Ill-Posed Probl. doi: 10.1515/jiip.1995.3.2.131 – ident: ref_1 – volume: 45 start-page: 1 year: 2019 ident: ref_85 article-title: Adjoint Code Design Patterns publication-title: ACM Trans. Math. Softw. doi: 10.1145/3326162 – volume: 611 start-page: 012032 year: 2020 ident: ref_43 article-title: Algorithms based on sensitivity operators for analyzing and solving inverse modeling problems of transport and transformation of atmospheric pollutants publication-title: IOP Conf. Ser. Earth Environ. Sci. doi: 10.1088/1755-1315/611/1/012032 – volume: 11 start-page: 532 year: 2014 ident: ref_73 article-title: Some properties of the inverse operator for a tsunami source recovery publication-title: Sib. Elektron. Mat. Izv. – ident: ref_26 doi: 10.1093/acprof:oso/9780198723844.003.0022 – ident: ref_58 – ident: ref_14 doi: 10.3390/atmos12050595 – volume: 38A start-page: 97 year: 1986 ident: ref_55 article-title: Variational algorithms for analysis and assimilation of meteorological observations: Theoretical aspects publication-title: Tellus doi: 10.1111/j.1600-0870.1986.tb00459.x – ident: ref_71 doi: 10.3390/atmos12101348 – volume: 14 start-page: 757 year: 2020 ident: ref_41 article-title: Convergence analysis of the adjoint ensemble method in inverse source problems for advection-diffusion-reaction models with image-type measurements publication-title: Inverse Probl. Imaging doi: 10.3934/ipi.2020035 – volume: 7 start-page: 1725 year: 2007 ident: ref_32 article-title: Emission rate and chemical state estimation by 4-dimensional variational inversion publication-title: Atmos. Chem. Phys. Discuss. – volume: 6 start-page: 3 year: 2013 ident: ref_65 article-title: Zagryaznenie atmosfernogo vozduha promyshlennymi predpriyatiyami g. Irkutska publication-title: IZVESTIYA Irkutsk. Gos. Univ. – volume: 32 start-page: 3039 year: 1998 ident: ref_17 article-title: Application of adjoint tracer transport equations for evaluating source parameters publication-title: Atmos. Environ. doi: 10.1016/S1352-2310(97)00480-9 – ident: ref_48 – volume: 5 start-page: 249 year: 2005 ident: ref_56 article-title: Emergence of a tracer source from air concentration measurements, a new strategy for linear assimilation publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-5-249-2005 – volume: 14 start-page: 6057 year: 2021 ident: ref_76 article-title: Ozone profile retrieval from nadir TROPOMI measurements in the UV range publication-title: Atmos. Meas. Tech. doi: 10.5194/amt-14-6057-2021 – ident: ref_46 doi: 10.3390/s18124363 – volume: 5 start-page: 675 year: 1964 ident: ref_49 article-title: Formulation of some converse problems publication-title: Sov. Math. Dokl. – ident: ref_29 doi: 10.3390/atmos11121289 – ident: ref_61 doi: 10.3390/atmos12121542 – volume: 101 start-page: E1 year: 2020 ident: ref_75 article-title: New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) publication-title: Bull. Am. Meteorol. Soc. doi: 10.1175/BAMS-D-18-0013.1 – volume: 29 start-page: 035009 year: 2013 ident: ref_20 article-title: Point source identification in nonlinear advection-diffusion-reaction systems publication-title: Inverse Probl. doi: 10.1088/0266-5611/29/3/035009 – volume: 156 start-page: 102 year: 2017 ident: ref_23 article-title: Paradigms and commonalities in atmospheric source term estimation methods publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2017.02.011 – ident: ref_70 doi: 10.3390/atmos12101357 – volume: 6 start-page: 1 year: 2018 ident: ref_74 article-title: The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles publication-title: Front. Environ. Sci. doi: 10.3389/fenvs.2018.00085 – volume: 33 start-page: 661 year: 2020 ident: ref_47 article-title: Study of the Spatial Distributions of CO2 and CH4 in the Surface Air Layer over Western Siberia Using a Mobile Platform publication-title: Atmos. Ocean. Opt. doi: 10.1134/S1024856020060056 – volume: 11 start-page: 10 year: 1985 ident: ref_3 article-title: Planning an experiment for determining the position and strength of a pollution source publication-title: Sov. Meteorol. Hydrol. – volume: 73 start-page: 261 year: 2015 ident: ref_27 article-title: Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: System description and verification publication-title: J. Atmos. Chem. doi: 10.1007/s10874-015-9326-0 – ident: ref_38 doi: 10.3390/atmos11030244 – volume: 22 start-page: 15 year: 2015 ident: ref_52 article-title: Toward the assimilation of images publication-title: Nonlinear Process. Geophys. doi: 10.5194/npg-22-15-2015 – volume: 139 start-page: 3887 year: 2011 ident: ref_82 article-title: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities publication-title: Mon. Weather. Rev. doi: 10.1175/MWR-D-10-05013.1 – volume: 60 start-page: 102239 year: 2020 ident: ref_13 article-title: Air quality monitoring using mobile low-cost sensors mounted on trash-trucks: Methods development and lessons learned publication-title: Sustain. Cities Soc. doi: 10.1016/j.scs.2020.102239 – volume: 6 start-page: 1244 year: 2014 ident: ref_21 article-title: Reconstructing source terms from atmospheric concentration measurements: Optimality analysis of an inversion technique publication-title: J. Adv. Model. Earth Syst. doi: 10.1002/2014MS000385 – volume: 13 start-page: 4601 year: 2020 ident: ref_30 article-title: High-resolution mapping of urban air quality with heterogeneous observations: A new methodology and its application to Amsterdam publication-title: Atmos. Meas. Tech. doi: 10.5194/amt-13-4601-2020 – volume: 120 start-page: 12589 year: 2015 ident: ref_22 article-title: Reconstruction of an atmospheric tracer source in an urban-like environment publication-title: J. Geophys. Res. Atmos. doi: 10.1002/2015JD024110 – volume: 123 start-page: 2285 year: 2018 ident: ref_45 article-title: Distribution of Trace Gases and Aerosols in the Troposphere Over Siberia during Wildfires of Summer 2012 publication-title: J. Geophys. Res. Atmos. doi: 10.1002/2017JD026825 – volume: 11 start-page: 3 year: 1976 ident: ref_53 article-title: A variational initialization method for the fields of the meteorological elements publication-title: Engl. Transl. Sov. Meteorol. Hydrol. – volume: 12 start-page: 3687 year: 2019 ident: ref_10 article-title: An optimization for reducing the size of an existing urban-like monitoring network for retrieving an unknown point source emission publication-title: Geosci. Model Dev. doi: 10.5194/gmd-12-3687-2019 – ident: ref_51 doi: 10.1002/9781118033210 – volume: 3 start-page: 2111 year: 2003 ident: ref_19 article-title: Rebuilding sources of linear tracers after atmospheric concentration measurements publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-3-2111-2003 – volume: 13 start-page: 152 year: 2020 ident: ref_92 article-title: Source Identification for the Smoluchowski Equation Using an Ensemble of Adjoint Equation Solutions publication-title: Numer. Anal. Appl. doi: 10.1134/S1995423920020068 – ident: ref_72 doi: 10.1007/978-94-009-1740-8 – ident: ref_68 doi: 10.3390/atmos10120739 – volume: 21 start-page: 705 year: 1986 ident: ref_4 article-title: Design of an experiment for the Pollution Source Power Estimation problem publication-title: Izv. Atmos. Ocean. Phys. – ident: ref_37 doi: 10.3390/atmos12030374 – volume: 17 start-page: 1940002 year: 2019 ident: ref_42 article-title: Numerical algorithm for morphogen synthesis region identification with indirect image-type measurement data publication-title: J. Bioinform. Comput. Biol. doi: 10.1142/S021972001940002X – volume: 199 start-page: 22 year: 2016 ident: ref_84 article-title: The efficiency of geophysical adjoint codes generated by automatic differentiation tools publication-title: Comput. Phys. Commun. doi: 10.1016/j.cpc.2015.10.008 – ident: ref_79 – ident: ref_83 doi: 10.1137/1.9780898717761 – ident: ref_50 – volume: 12 start-page: 130 year: 1999 ident: ref_18 article-title: Determination of some characteristics of an aerosol pollution source by solving the inverse problem of pollutant spread in the atmosphere publication-title: Atmos. Ocean. Opt. – ident: ref_54 – ident: ref_2 – volume: 103 start-page: 28291 year: 1998 ident: ref_81 article-title: MOZART, a global chemical transport model for ozone and related chemical tracers: 2. Model results and evaluation publication-title: J. Geophys. Res. Atmos. doi: 10.1029/98JD02398 – volume: 32 start-page: 434 year: 2019 ident: ref_44 article-title: Ship-Based Studies of Aerosol-Gas Admixtures over Lake Baikal Basin in Summer 2018 publication-title: Atmos. Ocean. Opt. doi: 10.1134/S1024856019040067 – volume: 8 start-page: e1528 year: 2021 ident: ref_66 article-title: Human impact and ecosystemic health at Lake Baikal publication-title: WIREs Water doi: 10.1002/wat2.1528 – volume: 1715 start-page: 012072 year: 2021 ident: ref_86 article-title: Parallel speedup analysis of an adjoint ensemble-based source identification algorithm publication-title: J. Phys. Conf. Ser. doi: 10.1088/1742-6596/1715/1/012072 – volume: 203 start-page: 103134 year: 2021 ident: ref_87 article-title: Single-image deblurring with neural networks: A comparative survey publication-title: Comput. Vis. Image Underst. doi: 10.1016/j.cviu.2020.103134 – ident: ref_36 doi: 10.3390/atmos12020179 – volume: 14 start-page: 7297 year: 2021 ident: ref_77 article-title: An improved TROPOMI tropospheric NO2 research product over Europe publication-title: Atmos. Meas. Tech. doi: 10.5194/amt-14-7297-2021 – volume: 65 start-page: 155010 year: 2020 ident: ref_88 article-title: Artifact removal using a hybrid-domain convolutional neural network for limited-angle computed tomography imaging publication-title: Phys. Med. Biol. doi: 10.1088/1361-6560/ab9066 – volume: 12 start-page: 51 year: 2019 ident: ref_40 article-title: A Newton-Kantorovich Method in Inverse Source Problems for Production-Destruction Models with Time Series-Type Measurement Data publication-title: Numer. Anal. Appl. doi: 10.1134/S1995423919010051 – volume: 107 start-page: 49 year: 2021 ident: ref_62 article-title: Industrial and wildfire aerosol pollution over world heritage Lake Baikal publication-title: J. Environ. Sci. doi: 10.1016/j.jes.2021.01.011 – volume: 32 start-page: 166 year: 2011 ident: ref_64 article-title: Big business in socio-economic development of cities in the Baikal region publication-title: Geogr. Nat. Resour. doi: 10.1134/S1875372811020119 – volume: 21 start-page: 210121 year: 2021 ident: ref_33 article-title: Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events publication-title: Aerosol Air Qual. Res. doi: 10.4209/aaqr.210121 – volume: 43 start-page: 4940 year: 2009 ident: ref_6 article-title: Model reduction via principal component truncation for the optimal design of atmospheric monitoring networks publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2009.07.011 – volume: 42 start-page: 5205 year: 2008 ident: ref_5 article-title: Design of a monitoring network over France in case of a radiological accidental release publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2008.02.065 – volume: 11 start-page: 426 year: 2016 ident: ref_90 article-title: Numerical Algorithms for Diffusion Coefficient Identification in Problems of Tissue Engineering publication-title: Math. Biol. Bioinform. doi: 10.17537/2016.11.426 – volume: 15 start-page: 7703 year: 2015 ident: ref_34 article-title: Climate-forced air-quality modeling at the urban scale: Sensitivity to model resolution, emissions and meteorology publication-title: Atmos. Chem. Phys. doi: 10.5194/acp-15-7703-2015 – ident: ref_57 – ident: ref_63 doi: 10.3390/w13192636 – ident: ref_78 doi: 10.3390/rs13112219 – volume: 20 start-page: 583 year: 2015 ident: ref_35 article-title: Emission Data Uncertainty in Urban Air Quality Modeling—Case Study publication-title: Environ. Model. Assess. doi: 10.1007/s10666-015-9445-7 – volume: 122 start-page: 22 year: 2015 ident: ref_8 article-title: Optimization of air monitoring networks using chemical transport model and search algorithm publication-title: Atmos. Environ. doi: 10.1016/j.atmosenv.2015.09.030 |
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| SubjectTerms | Accuracy Air Air monitoring Air pollution Air quality Algorithms Data assimilation Decision making Emission analysis emission source identification Forecasting Identification inverse problem Inverse problems Linear operators Measurement Monitoring systems Numerical experiments Sensitivity analysis sensitivity operator transport and transformation of impurities |
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| Title | Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems |
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