Geospatial applicability optics of the TROPOspheric monitoring instrument (TROPOMI) on a global scale: An overview
Alcindo Neckel, Emanuelle Goellner, Marcos L.S. Oliveira, Paloma Carollo Toscan, Alana Urio, Guilherme Peterle Schmitz, Giana Mores, Brian William Bodah, Eduardo Nuno Borges Pereira
Geoscience Frontiers ›› 2025, Vol. 16 ›› Issue (2) : 102008.
Geospatial applicability optics of the TROPOspheric monitoring instrument (TROPOMI) on a global scale: An overview
Studies arising from literature reviews are important as they facilitate specific understanding about the use of the Sentinel-5P satellite developed by the European Space Agency (ESA) to detect the concentration levels of atmospheric pollutants on a global scale. The objective of this literature review is to analyze the application of the geospatial optics of the Sentinel-5P satellite; coupled with the Tropospheric Monitoring Instrument (TROPOMI) in the detection of NO2 and CO over the period beginning in May 2018 and lasting through May 2024. This was accomplished using manuscripts published in the ScienceDirect databases. The study employed the rigorous Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, using the specific search term ‘sentinel TROPOMI satellite’, which yielded 555 results published between 2018 and 2024. Subsequently, 274 manuscripts were selected, and 85 were classified for analysis after a concise review. The Content Analysis Method (CAM) was used to understand the absolute frequency, with the use of the MAXQDA software (version 24.2.0) in this analysis. The purpose of using TROPOMI in the 85 manuscripts analyzed is significant. The manuscripts studied focused on air quality monitoring (30.1%), COVID-19 impact detection (24.3%), assessment of pollution sources (23.3%), support for decision makers (13.6%) and the development of methods and tools (8.7%). In this context, 38.5% of the examined studies focused on Asia, followed Europe (29.2%), North and South America (25.1%) and Africa (7.3%). TROPOMI data makes it possible to contribute to creating future government public policies on both the local and global scale.
Geoscience / Sentinel-5P satellite / TROPOMI / Atmospheric pollution / NO2 and CO / Global detections
J.A. Adame, I. Gutiérrez-Álvarez, J.P.B. Raya, M. Yela. Ground-based and OMI-TROPOMI NO2 measurements at El Arenosillo observatory: Unexpected upward trends. Environ. Pollut., 264 (2020), Article 114771,
CrossRef
Google scholar
|
S. Agrawal, P. Oza, R. Kakkar, S. Tanwar, V. Jetani, J. Undhad, A. Singh. Analysis and recommendation system-based on PRISMA checklist to write systematic review. Asses. Writing, 61 (2024), Article 100866,
CrossRef
Google scholar
|
N. Ahmad, R.F. Aghdam, I. Butt, A. Naveed. Citation-based systematic literature review of energy-growth nexus: an overview of the field and content analysis of the top 50 influential papers. Energy Econ., 86 (2020), Article 104642,
CrossRef
Google scholar
|
S.S. Al-Alola, I.I. Alkadi, H.M. Alogayell, S.M. Mohamed, I.Y. Ismail. Air quality estimation using remote sensing and GIS-spatial technologies along Al-Shamal train pathway, Al-Qurayyat City in Saudi Arabia. Environ. Sustain. Ind., 15 (2022), Article 100184,
CrossRef
Google scholar
|
L.G. Amorin-Woods, B.L. Woods, B.L. Mullings, D. Vindigni, B.E. Losco. Future Research by the Australian Chiropractic Profession: analysis of comments and suggestions from a nationwide survey of academics and practitioners. J. Manip. Physiol. Ther., 46 (1) (2023), pp. 1-16,
CrossRef
Google scholar
|
N. Amoroso, R. Cilli, T. Maggipinto, A. Monaco, S. Tangaro, R. Bellotti. Satellite data and machine learning reveal a significant correlation between NO2 and COVID-19 mortality. Environ. Res., 204 (2022), Article 111970,
CrossRef
Google scholar
|
S. Athul, J. Kuttippurath, V.K. Patel. Changes in global NO2 pollution by shipping during the COVID-19 lockdown: implication for sustainable marine operations. J. Hazard. Mater., 481 (2025), Article 136482,
CrossRef
Google scholar
|
S. Azad, M. Ghandehari. Emissions of nitrogen dioxide in the northeast U.S. during the 2020 COVID-19 lockdown. J. Environ. Manage., 312 (2022), Article 114902,
CrossRef
Google scholar
|
K. Baek, J. Bak, J.H. Kim, S.S. Park, D.P. Haffner, W. Lee. Validation of geostationary environment monitoring spectrometer (GEMS), TROPOspheric monitoring instrument (TROPOMI), and Ozone Mapping and Profiler Suite Nadir Mapper (OMPS) using pandora measurements during GEMS Map of Air Pollution (GMAP) field campaign. Atmos. Environ., 120408 (2024),
CrossRef
Google scholar
|
S. Bar, B.R. Parida, S.P. Mandal, A.C. Pandey, N. Kumar, B. Mishra. Impacts of partial to complete COVID-19 lockdown on NO2 and PM2.5 levels in major urban cities of Europe and USA. Cities, 117 (2021), Article 103308,
CrossRef
Google scholar
|
B.W. Bodah, A. Neckel, L.S. Maculan, C.B. Milanes, C. Korcelski, O. Ramírez, J.F. Mendez-Espinosa, E.T. Bodah, M.L. Oliveira. Sentinel-5P TROPOMI satellite application for NO2 and CO studies aiming at environmental valuation. J. Clean. Prod., 357 (2022), Article 131960,
CrossRef
Google scholar
|
M. Campanelli, A.M. Iannarelli, G. Mevi, S. Casadio, H. Diémoz, S. Finardi, A. Dinoi, E. Castelli, A. Di Sarra, A. Di Bernardino, G. Casasanta, C. Bassani, A.M. Siani, M. Cacciani, F. Barnaba, L. Di Liberto, S. Argentini. A wide-ranging investigation of the COVID-19 lockdown effects on the atmospheric composition in various Italian urban sites (AER – LOCUS). Urban Clim., 39 (2021), Article 100954,
CrossRef
Google scholar
|
Y. Chen, C.C. Chou, C. Liu, S. Chi, M. Chuang. Evaluation of the nitrogen oxide emission inventory with TROPOMI observations. Atmos. Environ., 298 (2023), Article 119639,
CrossRef
Google scholar
|
X. Chen, J. Wang, X. Xu, M. Zhou, H. Zhang, L.C. Garcia, P.R. Colarco, S.J. Janz, J. Yorks, M. McGill, J.S. Reid, M. De Graaf, S. Kondragunta. First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: algorithm development and application for surface particulate matter estimates. Remote Sens. Environ., 265 (2021), Article 112674,
CrossRef
Google scholar
|
Z. Chen, Y. Zhu, F. Pu, W. Tian. A study on basic research priorities and development suggestions for the digital transformation of air traffic management. Aeros. Traffic Safe (2024),
CrossRef
Google scholar
|
Copernicus Sentinel-5P (processed by ESA), 2021. TROPOMI Level 1B Irradiance products. Version 02. European Space Agency. https://doi.org/10.5270/S5P-mhtbru8. (Accessed 20 May 2024).
|
J. Dong, X. Cai, L. Tian, F. Chen, Q. Xu, T. Li, X. Chen. Satellite-based estimates of daily NO2 exposure in urban agglomerations of China and application to spatio-temporal characteristics of hotspots. Atmos. Environ., 293 (2023), Article 119453,
CrossRef
Google scholar
|
T. Drosoglou, M. Koukouli, I. Raptis, S. Kazadzis, A. Pseftogkas, K. Eleftheratos, C.S. Zerefos. Nitrogen dioxide spatiotemporal variations in the complex urban environment of Athens, Greece. Atmos. Environ., 314 (2023), Article 120115,
CrossRef
Google scholar
|
S. Du, S. Chen, S. Cheng, J. He, C. Liu, L. Lian, C. Zhang, D. Zhao, N. Yin, Y. Guan. Data-driven approach for air pollutant concentrations forecasting: a window-based multi-output GBRT approach. Atmos. Res., 307 (2024), Article 107459,
CrossRef
Google scholar
|
M. Eke, F. Cingiroglu, B. Kaynak. Investigation of 2021 wildfire impacts on air quality in southwestern Turkey. Atmos. Environ., 120445 (2024),
CrossRef
Google scholar
|
M. Faisal, L.M. Jaelani. Spatio-temporal analysis of nitrogen dioxide (NO2) from Sentinel-5P imageries using Google Earth Engine changes during the COVID-19 social restriction policy in Jakarta. Nat. Hazards Res., 3 (2) (2023), pp. 344-352,
CrossRef
Google scholar
|
M. Filonchyk, M.P. Peterson. NO2 emissions from oil refineries in the Mississippi Delta. Sci. Total Environ., 898 (2023), Article 165569,
CrossRef
Google scholar
|
J. Fu, D. Tang, M.L. Grieneisen, F. Yang, J. Yang, G. Wu, Q. Wang, Y. Zhan. A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: application to NO2 pollution hotspot identification. Atmos. Environ., 302 (2023), Article 119756,
CrossRef
Google scholar
|
M. Ghahremanloo, Y. Lops, Y. Choi, S. Mousavinezhad. Impact of the COVID-19 outbreak on air pollution levels in East Asia. Sci. Total Environ., 754 (2021), Article 142226,
CrossRef
Google scholar
|
F. Ghasempour, A. Şekertekin, Ş.H. Kutoğlu. Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing. J. Clean. Prod., 319 (2021), Article 128599,
CrossRef
Google scholar
|
I.A. Girach, N. Tripathi, P.R. Nair, L.K. Sahu, N. Ojha. O3 and CO in the South Asian outflow over the Bay of Bengal: impact of monsoonal dynamics and chemistry. Atmos. Environ., 233 (2020), Article 117610,
CrossRef
Google scholar
|
J. Godłowska, M.J. Hajto, B. Łapeta, K. Kaszowski. The attempt to estimate annual variability of NOx emission in Poland using Sentinel-5P/TROPOMI data. Atmos. Environ., 294 (2023), Article 119482,
CrossRef
Google scholar
|
D.L. Goldberg, M. Tao, G.H. Kerr, S. Ma, D. Tong, A.M. Fiore, A.F. Dickens, Z. Adelman, S.C. Anenberg. Evaluating the spatial patterns of U.S. urban NOx emissions using TROPOMI NO2. Remote Sens. Environ., 300 (2024), Article 113917,
CrossRef
Google scholar
|
T.C. Guetterman, T.G. James. A software feature for mixed methods analysis: the MAXQDA Interactive Quote Matrix. Methods Psychol., 8 (2023), Article 100116,
CrossRef
Google scholar
|
B.M. Hashim, S.K. Al-Naseri, A. Al-Maliki, N. Al-Ansari. Impact of COVID-19 lockdown on NO2, O3, PM2.5 and PM10 concentrations and assessing air quality changes in Baghdad, Iraq. Sci. Total Environ., 754 (2021), Article 141978,
CrossRef
Google scholar
|
J. Helbach, F. Hoffmann, D. Pieper, K. Allers. Reporting according to the preferred reporting items for systematic reviews and meta-analyses for abstracts (PRISMA-A) depends on abstract length. J. Clin. Epidemiol., 154 (2023), pp. 167-177,
CrossRef
Google scholar
|
J. Hoare, S. Garnett, L. Baur, N. Lister, H. Jebeile. A novel method to determine a custom sample size for image-based instagram content analysis. Curr. Dev. Nutr., 6 (2022), p. 768,
CrossRef
Google scholar
|
M. Hu, K. Bai, K. Li, Z. Zheng, Y. Sun, L. Shao, R. Li, C. Liu. Improving machine-learned surface NO2 concentration mapping models with domain knowledge from data science perspective to. Atmos. Environ., 322 (2024), p. 120372,
CrossRef
Google scholar
|
G. Huang, K. Sun. Non-negligible impacts of clean air regulations on the reduction of tropospheric NO2 over East China during the COVID-19 pandemic observed by OMI and TROPOMI. Sci. Total Environ., 745 (2020), Article 141023,
CrossRef
Google scholar
|
I. Ialongo, H. Cтeпaнoвa, J. Hakkarainen, H. Virta, D. Gritsenko. Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia. Atmos. Environ., 11 (2021), Article 100114,
CrossRef
Google scholar
|
K.M.A. Islam, M.S.G. Adnan, K.E. Zannat, A. Dewan. Spatiotemporal dynamics of NO2 concentration with linear mixed models: a Bangladesh case study. Phys. Chem. Earth (Pt A,B,C), 126 (2022), Article 103119,
CrossRef
Google scholar
|
D. Kaloni, Y.H. Lee, S. Dev. Air quality in the New Delhi metropolis under COVID-19 lockdown. Syst. Soft Comput., 4 (2022), Article 200035,
CrossRef
Google scholar
|
Y. Kang, H. Choi, J. Im, S. Park, M. Shin, C. Song, S. Kim. Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia. Environ. Pollut., 288 (2021), Article 117711,
CrossRef
Google scholar
|
T. Karppinen, A. Sundström, H. Lindqvist, J. Hatakka, J. Tamminen. Satellite-based assessment of national carbon monoxide concentrations for air quality reporting in Finland. Remote Sens. Appl.: Soc. Environ., 33 (2024), Article 101120,
CrossRef
Google scholar
|
A.E. Kenawy, J.I. López-Moreno, M.F. McCabe, F. Domínguez-Castro, D. Peña-Angulo, I.M. Gaber, A.S. Alqasemi, K.M.A. Kindi, T. Al-Awadhi, S.M. Robaa, N.A. Nasiri, S.M. Vicente-Serrano. The impact of COVID-19 lockdowns on surface urban heat island changes and air-quality improvements across 21 major cities in the Middle East. Environ. Pollut., 288 (2021), Article 117802,
CrossRef
Google scholar
|
M. Kganyago, K. Govender, L. Shikwambana, V. Sivakumar. Study on blazing wildfires at the outeniqua pass in South Africa during the october/november 2018 period. Remote Sens. Appl., 21 (2021), Article 100464,
CrossRef
Google scholar
|
M. Kim, D. Brunner, G. Kuhlmann. Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning. Remote Sens. Environ., 264 (2021), Article 112573,
CrossRef
Google scholar
|
K.D. Kovács, I. Haidu. Effect of anti-COVID-19 measures on atmospheric pollutants correlated with the economies of medium-sized cities in 10 urban areas of grand Est Region, France. Sustain. Cities Soc., 74 (2021), Article 103173,
CrossRef
Google scholar
|
K.D. Kovács, I. Haidu. Modeling NO2 air pollution variation during and after COVID-19-regulation using principal component analysis of satellite imagery. Environ. Pollut., 342 (2024), Article 122973,
CrossRef
Google scholar
|
S. Kumari, A.C. Yadav, M. Saharia, S. Dev. Spatio-temporal analysis of air quality and its relationship with COVID-19 lockdown over Dublin. Remote Sens. Appl.: Soc. Environ., 28 (2022), Article 100835,
CrossRef
Google scholar
|
S. Kurchaba, J. Van Vliet, F.J. Verbeek, C.J. Veenman. Anomalous NO2 emitting ship detection with TROPOMI satellite data and machine learning. Remote Sens. Environ., 297 (2023), Article 113761,
CrossRef
Google scholar
|
S. Kurchaba, A. Sokolovsky, J. Van Vliet, F.J. Verbeek, C.J. Veenman. Sensitivity analysis for the detection of NO2 plumes from seagoing ships using TROPOMI data. Remote Sens. Environ., 304 (2024), Article 114041,
CrossRef
Google scholar
|
S. Lama, S. Houweling, K.F. Boersma, I. Aben, H.D. Van Der Gon, M. Krol. The impact of COVID-19 lockdowns on urban photochemistry as inferred from TROPOMI. Atmos. Environ., 312 (2023), Article 120042,
CrossRef
Google scholar
|
M.M. Laughlin, J.D. Bakker, D.J. Churchill, M.J. Gregory, T. DeMeo, E.C. Alvarado, B.J. Harvey. Trends in forest structure restoration need over three decades with increasing wildfire activity in the interior Pacific Northwest US. For. Ecol. Manag., 527 (2023), Article 120607,
CrossRef
Google scholar
|
H.J. Lee, Y. Liu, R.B. Chatfield. Neighborhood-scale ambient NO2 concentrations using TROPOMI NO2 data: applications for spatially comprehensive exposure assessment. Sci. Total Environ., 857 (2023), Article 159342,
CrossRef
Google scholar
|
H.J. Lee, T. Kuwayama, M. FitzGibbon. Simultaneous decreases in NO2 levels and disparities in California during the COVID-19 pandemic. Atmos. Environ., 318 (2024), Article 120214,
CrossRef
Google scholar
|
R. Lei, S. Feng, Y. Xu, S. Tran, M. Ramonet, M. Grutter, A. Garcia, M. Campos-Pineda, T. Lauvaux. Reconciliation of asynchronous satellite-based NO2 and XCO2 enhancements with mesoscale modeling over two urban landscapes. Remote Sens. Environ., 281 (2022), Article 113241,
CrossRef
Google scholar
|
P.W.da.L. Leite, C.C.O. De Almeida Silva, L.D. Moro, B.W. Bodah, G. De Vargas Mores, D. Piccinato, A. Engel, M. Santosh, A. Neckel. Space Syntax at expression of Science on user flows in open and closed spaces aimed at achieving the sustainable development goal: a review. Architecture, 4 (1) (2024), pp. 170-187,
CrossRef
Google scholar
|
K. Li, K. Bai, P. Jiao, H. Chen, H. He, L. Shao, Y. Sun, Z. Zheng, R. Li, N. Chang. Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data. Remote Sens. Environ., 304 (2024), Article 114039,
CrossRef
Google scholar
|
P. Lin, Y. Tian, T. Borsdorff, Z. Li, J. Landgraf, H. Wu, J. Xue, D. Ding, H. Ye, Y. Zhu, C. Liu. TROPOMI unravels transboundary transport pathways of atmospheric carbon monoxide in Tibetan Plateau. Sci. Total Environ., 952 (2024), Article 175942,
CrossRef
Google scholar
|
T. Liu, B. Flückiger, K. De Hoogh. A comparison of statistical and machine-learning approaches for spatiotemporal modeling of nitrogen dioxide across Switzerland. Atmos. Pollut. Res., 13 (12) (2022), Article 101611,
CrossRef
Google scholar
|
S. Long, X. Wei, F. Zhang, R. Zhang, J. Xu, K. Wu, Q. Li, W. Li. Estimating daily ground-level NO2 concentrations over China based on TROPOMI observations and machine learning approach. Atmos. Environ., 289 (2022), Article 119310,
CrossRef
Google scholar
|
M. Lü, O. Schmitz, K. De Hoogh, K. Qin, D. Karssenberg. Evaluation of different methods and data sources to optimise modelling of NO2 at a global scale. Environ. Int., 142 (2020), Article 105856,
CrossRef
Google scholar
|
L. Luo, X. Wang, H. Guo. Transitioning from remote sensing archaeology to space archaeology: towards a paradigm shift. Remote Sens. Environ., 308 (2024), Article 114200,
CrossRef
Google scholar
|
K. Madkour. Monitoring the impacts of COVID-19 pandemic on climate change and the environment on Egypt using Sentinel-5P Images, and the Carbon footprint methodology. Egypt. J. Remote Sens. Space Sci., 25 (1) (2022), pp. 205-219,
CrossRef
Google scholar
|
K. Mahmud, B. Mitra, M.S. Uddin, A.E. Hridoy, Y.A. Aina, I.R. Abubakar, S.M. Rahman, M.L. Tan, M.M. Rahman. Temporal assessment of air quality in major cities in Nigeria using satellite data. Atmos. Environ., 20 (2023), Article 100227,
CrossRef
Google scholar
|
N.N. Maltare, S. Vahora, K. Jani. Seasonal analysis of meteorological parameters and air pollutant concentrations in Kolkata: an evaluation of their relationship. J. Clean. Prod., 436 (2024), Article 140514,
CrossRef
Google scholar
|
S. Mancin, M. Sguanci, D. Andreoli, F. Soekeland, G. Anastasi, M. Piredda, M.G. De Marinis. Systematic review of clinical practice guidelines and systematic reviews: a method for conducting comprehensive analysis. MethodsX, 12 (2024), Article 102532,
CrossRef
Google scholar
|
K. Mehmood, Y. Bao, G.P. Petropoulos, R. Abbas, M. Abrar, A. Mustafa, A. Soban, S. Saud, M. Ahmad, I. Hussain, S. Fahad. Investigating connections between COVID-19 pandemic, air pollution and community interventions for Pakistan employing geoinformation technologies. Chemosphere, 272 (2021), Article 129809,
CrossRef
Google scholar
|
D. Mejía, H. Alvarez, R. Žalakevičiūtė, D. Mcancela, C. Sanchez, S. Bonilla. Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador. Remote Sens. Appl.: Soc. Environ., 31 (2023), Article 100990,
CrossRef
Google scholar
|
J.F. Méndez-Espinosa, N.Y. Rojas, J.L.Y. Vargas, J.E. Pachón, L.C.B. Cerón, O. Ramírez. Air quality variations in Northern South America during the COVID-19 lockdown. Sci. Total Environ., 749 (2020), Article 141621,
CrossRef
Google scholar
|
M. Mofijur, I.R. Fattah, A. Alam, A.B.M.S. Islam, H.C. Ong, S. Rahman, G. Najafi, S.F. Ahmed, M.A. Uddin, T. Mahlia. Impact of COVID-19 on the social, economic, environmental and energy domains: lessons learnt from a global pandemic. Sustain. Prod. Consum., 26 (2021), pp. 343-359,
CrossRef
Google scholar
|
S. Muhammad, X. Long, M. Salman. COVID-19 pandemic and environmental pollution: a blessing in disguise?. Sci. Total Environ., 728 (2020), Article 138820,
CrossRef
Google scholar
|
I. Müller, T. Erbertseder, H. Taubenböck. Tropospheric NO2: explorative analyses of spatial variability and impact factors. Remote Sens. Environ., 270 (2022), Article 112839,
CrossRef
Google scholar
|
H.R. Naqvi, G. Mutreja, A. Shakeel, K.P. Singh, K. Abbas, D.F. Naqvi, A.A. Chaudhary, M.A. Siddiqui, A.S. Gautam, S. Gautam, A.R. Naqvi. Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California. Gondwana Res., 114 (2023), pp. 30-39,
CrossRef
Google scholar
|
A. Neckel, M.L. Oliveira, L.S. Maculan, B.W. Bodah, A.C. Gonçalves, L.F. Silva. Air pollution in central European capital (Budapest) via self-made passive samplers and Sentinel-3B SYN satellite images. Urban Clim., 47 (2023), Article 101384,
CrossRef
Google scholar
|
M.L. Oliveira, A. Neckel, D. Pinto, L.S. Maculan, G.L. Dotto, L.F. Silva. The impact of air pollutants on the degradation of two historic buildings in Bordeaux, France. Urban Clim., 39 (2021), Article 100927,
CrossRef
Google scholar
|
H. Pacheco, S. Díaz-López, E.J.J. Castro, H. Pacheco, W. Méndez, E. Zamora-Ledezma. NO2 levels after the COVID-19 lockdown in Ecuador: a trade-off between environment and human health. Urban Clim., 34 (2020), Article 100674,
CrossRef
Google scholar
|
G. Plant, E.A. Kort, L.T. Murray, J.D. Maasakkers, I. Aben. Evaluating urban methane emissions from space using TROPOMI methane and carbon monoxide observations. Remote Sens. Environ., 268 (2022), Article 112756,
CrossRef
Google scholar
|
M. Pommier. Estimations of NOx emissions, NO2 lifetime and their temporal variation over three British urbanised regions in 2019 using TROPOMI NO2 observations. Environ. Sci., 3 (2) (2023), pp. 408-421,
CrossRef
Google scholar
|
B.K. Prahani, I.A. Rizki, N. Suprapto, I. Irwanto, M.A. Kurtuluş. Mapping research on scientific creativity: a bibliometric review of the literature in the last 20 years. Think. Ski. Creat., 52 (2024), Article 101495,
CrossRef
Google scholar
|
S. Prakash, M. Goswami, Y.D.I. Khan, S. Nautiyal. Environmental impact of COVID-19 led lockdown: a satellite data-based assessment of air quality in Indian megacities. Urban Clim., 38 (2021), Article 100900,
CrossRef
Google scholar
|
P. Prunet, O. Lezeaux, C. Camy-Peyret, H. Thevenon. Analysis of the NO2 tropospheric product from S5P TROPOMI for monitoring pollution at city scale. City Environ. Interact., 8 (2020), Article 100051,
CrossRef
Google scholar
|
P. Purwanto, I.S. Astuti, F. Rohman, K.S.B. Utomo, Y.E. Aldianto. Assessment of the dynamics of urban surface temperatures and air pollution related to COVID-19 in a densely populated City environment in East Java. Ecol. Inform., 71 (2022), Article 101809,
CrossRef
Google scholar
|
S. Raum, F. Rawlings-Sanaei. WCM: a web content‐based method of stakeholder analysis. MethodsX, 9 (2022), Article 101635,
CrossRef
Google scholar
|
P. Rawat, M. Naja, M.C. Rajwar, H. Irie, C. Lerot, M. Kumar, S. Lal. Long-term observations of NO2, SO2, HCHO, and CHOCHO over the Himalayan foothills: insights from MAX-DOAS, TROPOMI, and GOME-2. Atmos. Environ., 336 (2024), Article 120746,
CrossRef
Google scholar
|
A. Ribeiro, L. Madureira, R. Carvalho. Citizens’ deliberation on solutions to fight urban household food waste and nexus with growing urban gardens: the case of Porto Metropolitan area in Portugal. Clean. Responsible Consum., 13 (2024), Article 100188,
CrossRef
Google scholar
|
A.P. Rudke, J.A. Martins, R. Hallak, L.D. Martins, D.S. De Almeida, A. Beal, E.D. De Freitas, M. Andrade, P. Koutrakis, T.T.A. Albuquerque. Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: a case study during the COVID-19 outbreak. Remote Sens. Environ., 289 (2023), Article 113514,
CrossRef
Google scholar
|
Ü.A. Şahin, B. Kaynak. Questioning whether there was a short-term interaction between the 6 February 2023 earthquakes and air quality parameters in Türkiye. Chemosphere, 347 (2024), Article 140616,
CrossRef
Google scholar
|
D.de Santis, S. Amici, C. Milesi, D. Muroni, A. Romanino, C. Casari, V. Cannas, F. Del Frate. Tracking air quality trends and vehicle traffic dynamics at urban scale using satellite and ground data before and after the COVID-19 outbreak. Sci. Total Environ., 899 (2023), Article 165464,
CrossRef
Google scholar
|
M. Savenets, V. Osadchyi, K.M. Komisar, N. Zhemera, A. Oreshchenko. Remotely visible impacts on air quality after a year-round full-scale Russian invasion of Ukraine. Atmos. Pollut. Res., 14 (11) (2023), Article 101912,
CrossRef
Google scholar
|
G.K. Saw, S. Dey, H. Kaushal, K. Lal. Tracking NO2 emission from thermal power plants in North India using TROPOMI data. Atmos. Environ., 259 (2021), Article 118514,
CrossRef
Google scholar
|
N. Shahrokhi, P.J. Rayner, J.D. Silver, S. Thomas. Urban-scale variational flux inversion for CO Using TROPOMI total-column retrievals: a case study of Tehran. Atmos. Environ., 311 (2023), Article 120009,
CrossRef
Google scholar
|
N. Shahrokhishahraki, P. Rayner, J.D. Silver, S. Thomas, R. Schofield. High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data. Atmos. Environ., 270 (2022), Article 118881,
CrossRef
Google scholar
|
C. Shi, Z. Zhang, S. Xiong, W. Chen, W. Zhang, Q. Zhang, X. Wang. Harmonizing atmospheric ozone column concentrations over the Tibetan Plateau from 2005 to 2022 using OMI and Sentinel-5P TROPOMI: a deep learning approach. Int. J. Appl. Earth Obs. Geoinf., 129 (2024), Article 103808,
CrossRef
Google scholar
|
L. Shikwambana, P. Mhangara, N. Mbatha. Trend analysis and first time observations of sulphur dioxide and nitrogen dioxide in South Africa using TROPOMI/Sentinel-5 P data. Int. J. Appl. Earth Obs. Geoinf., 91 (2020), Article 102130,
CrossRef
Google scholar
|
A. Shukla, C. Bansal, S. Badhe, M. Ranjan, R. Chandra. An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis. J. Nat. Lang. Process., 4 (2023), Article 100025,
CrossRef
Google scholar
|
C. Sohrabi, T. Franchi, G. Mathew, A. Kerwan, M. Nicola, M. Griffin, M. Agha, R. Agha. PRISMA 2020 statement: what’s new and the importance of reporting guidelines. Int. J. Surg., 88 (2021), Article 105918,
CrossRef
Google scholar
|
S. Sorooshian. The Sustainable development goals of the united nations: a comparative midterm research review. J. Clean. Prod., 453 (2024), Article 142272,
CrossRef
Google scholar
|
D. Stratoulias, N. Nuthammachot. Air quality development during the COVID-19 pandemic over a medium-sized urban area in Thailand. Sci. Total Environ., 746 (2020), Article 141320,
CrossRef
Google scholar
|
G. Suthar, S. Singh, N. Kaul, S. Khandelwal. Analyzing methane emissions in five Indian cities using TROPOMI data from sentinel-5 precursor satellite. Urban Clim., 58 (2024), Article 102174,
CrossRef
Google scholar
|
S. Tariq, H. Nawaz, U. Mehmood, Z.U. Haq, U.K. Pata, M. Murshed. Remote sensing of air pollution due to forest fires and dust storm over Balochistan (Pakistan). Atmos. Pollut. Res., 14 (2) (2023), Article 101674,
CrossRef
Google scholar
|
M. Tzortziou, C.P. Loughner, D.L. Goldberg, L. Judd, D. Nauth, C.F. Kwong, T. Lin, A. Cede, N. Abuhassan. Intimately tracking NO2 pollution over the New York City - Long Island Sound land-water continuum: an integration of shipboard, airborne, satellite observations, and models. Sci. Total Environ., 897 (2023), Article 165144,
CrossRef
Google scholar
|
M. Urrutia-Pereira, G. Guidos-Fogelbach, D. Solé. Climate changes, air pollution and allergic diseases in childhood and adolescence. J. Pediatr., 98 (2022), pp. S47-S54,
CrossRef
Google scholar
|
G. Varga, A. Csávics, J. Szeberényi, F. Gresina. Non-uniform tropospheric NO2 level changes in European Union caused by governmental COVID-19 restrictions and geography. City Environ. Interact., 22 (2024), Article 100145,
CrossRef
Google scholar
|
H. Virta, I. Ialongo, M.E. Szeląg, H. Eskes. Estimating surface-level nitrogen dioxide concentrations from Sentinel-5P/TROPOMI observations in Finland. Atmos. Environ., 312 (2023), Article 119989,
CrossRef
Google scholar
|
M.I. Volke, R.A. Del Río, C.A. Ulloa-Tesser. Impact of mobility restrictions on NO2 concentrations in key Latin American cities during the first wave of the COVID-19 pandemic. Urban Clim., 48 (2023), Article 101412,
CrossRef
Google scholar
|
I.F.S. Wahyuningrum, N.G. Humaira, M.A. Budihardjo, I.S. Arumdani, A.S. Puspita, A.N. Annisa, A.M. Sari, H.G. Djajadikerta. Environmental sustainability disclosure in Asian countries: bibliometric and content analysis. J. Clean. Prod., 411 (2023), Article 137195,
CrossRef
Google scholar
|
Q. Wang, M. Su. A preliminary assessment of the impact of COVID-19 on environment - A case study of China. Sci. Total Environ., 728 (2020), Article 138915,
CrossRef
Google scholar
|
World Health Organization (WHO), 2024. Air pollution causes 7 million premature deaths every year, UN warns. https://www.who.int/news/item/25-03-2014-7-million-premature-deaths-annually-linked-to-air-pollution (Accessed 12 June 2024).
|
S. Wu, B. Huang, J. Wang, L. He, Z. Wang, Z. Yan, X.Q. Lao, F. Zhang, R. Liu, Z. Du. Spatiotemporal mapping and assessment of daily ground NO2 concentrations in China using high-resolution TROPOMI retrievals. Environ. Pollut., 273 (2021), Article 116456,
CrossRef
Google scholar
|
T. Wu, T. Yue, P. Yang, Y. Jia. Notable efficacy of Shugan Jieyu capsule in treating adult with post-stroke depression: a PRISMA-compliant meta-analysis of randomized controlled trials. J. Ethnopharmacol., 294 (2022), Article 115367,
CrossRef
Google scholar
|
K. Wyche, M. Nichols, H. Parfitt, P. Beckett, D. Gregg, K. Smallbone, P.S. Monks. Changes in ambient air quality and atmospheric composition and reactivity in the South East of the UK as a result of the COVID-19 lockdown. Sci. Total Environ., 755 (2021), Article 142526,
CrossRef
Google scholar
|
G. Yumnam, Y. Gyanendra, C.I. Singh. A systematic bibliometric review of the global research dynamics of United Nations Sustainable Development Goals 2030. Sustain. Futures, 7 (2024), Article 100192,
CrossRef
Google scholar
|
Y. Zhang, X. Man, S. Zhang, L. Liu, F. Kong, T. Feng, R. Liu. Ground-based MAX-DOAS observations of formaldehyde and glyoxal in Xishuangbanna, China. J. Environ. Sci., 152 (2025), pp. 328-339,
CrossRef
Google scholar
|
G. Zhang, G. Qiao, Z. Mao. The order characteristics of daily life space in Chinese urban communities a case of Ningbo green axis sports park. Heliyon, 10 (13) (2024), Article e33548,
CrossRef
Google scholar
|
F. Zhao, C. Liu, Z. Cai, X. Liu, J. Bak, J. Kim, Q. Hu, C. Xia, C. Zhang, Y. Sun, W. Wang, J. Liu. Ozone profile retrievals from TROPOMI: implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China. Sci. Total Environ., 764 (2021), Article 142886,
CrossRef
Google scholar
|
Z. Zhao, Y. Lu, Y. Zhan, Y. Cheng, F. Yang, J.R. Brook, K. He. Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals. Sci. Total Environ., 904 (2023), Article 166693,
CrossRef
Google scholar
|
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