Abstract
The main objective of this study is to analyze hazardous elements in nanoparticles (NPs) (smaller than 100 nm) and ultrafine particles (smaller than 1 µm) in Porto Alegre City, southern Brazil using a self-made passive sampler and Sentinel-3B SYN satellite images in 32 collection points. The Aerosol Optical Thickness proportion (T550) identification was conducted using images of the Sentinel-3B SYN satellite at 634 points sampled in 2019, 2020, 2021, and 2022. Focused ion beam scanning electron microscopy analyses were performed to identify chemical elements present in NPs and ultrafine particles, followed by single-stage cascade impactor to be processed by high-resolution transmission electron microscopy. This process was coupled with energy-dispersive X-ray spectroscopy and later analysis via secondary ion mass spectrometry. Data was acquired from Sentinel-3B SYN images, normalized to a standard mean of 0.83 µg/mg, at moderate spatial resolution (260 m), and modeled in the Sentinel Application Platform (SNAP) software v.8.0. Statistical matrix data was generated in the JASP software (Jeffreys’s Amazing Statistics Program) v.0.14.1.0 followed by a K-means cluster analysis. The results demonstrate the presence of between 1 and 100 nm particles of the following chemical elements: Si, Al, K, Mg, P, and Ti. Many people go through these areas daily and may inhale or absorb these elements that can harm human health. In the Sentinel-3B SYN satellite images, the sum of squares in cluster 6 is 168,265 and in cluster 7 a total of 21,583. The use of images from the Sentinel-3B SYN satellite to obtain T550 levels is of great importance as it reveals that atmospheric pollution can move through air currents contaminating large areas on a global scale.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aarzoo N, Nidhi N, Samim M (2022) Palladium nanoparticles as emerging pollutants from motor vehicles: an in-depth review on distribution, uptake and toxicological effects in occupational and living environment. Sci Total Environ 823:153787. https://doi.org/10.1016/j.scitotenv.2022.153787
Abdillah SF, Wang YF (2023) Ambient ultrafine particle (PM0.1): sources, characteristics, measurements and exposure implications on human health. Environ Res 218:115061. https://doi.org/10.1016/j.envres.2022.115061
Akhbarizadeh R, Dobaradaran S, Torkmahalleh MA, Saeedi R, Aibaghi R, Ghasemi F (2021) Suspended fine particulate matter (PM2.5), microplastics (MPs), and polycyclic aromatic hydrocarbons (PAHs) in air: their possible relationships and health implications. Environ Res 192:110339. https://doi.org/10.1016/j.envres.2020.110339
Alderton D (2021) X-Ray diffraction (XRD). Encycl Geol 520–531. https://doi.org/10.1016/b978-0-08-102908-4.00178-8
Alencar W, Da Silva JAP, De Oliveira F, Ghosh A, Vasconcelos DFP, Da Silva JAP, De Freitas CM, De Moura T, Rufino F, Freire P (2022) Vibrational spectroscopy, X-ray diffraction and EDS applied to reveal the fossilization pathways of fossil shells from the Jandaíra Formation, Upper Cretaceous Northeast Brazil. Vib Spectrosc 123:103430. https://doi.org/10.1016/j.vibspec.2022.103430
ARL (NOAA Air Resources Laboratory) (2023) Real-time Environmental Applications and Display sYstem. https://www.ready.noaa.gov/index.php. (Accessed 27 November 2023)
Balch WM, Mitchell C (2023) Remote sensing algorithms for particulate inorganic carbon (PIC) and the global cycle of PIC. Earth-Sci Rev 239:104363. https://doi.org/10.1016/j.earscirev.2023.104363
Ballikaya P, Marshall J, Cherubini P (2022) Can tree-ring chemistry be used to monitor atmospheric nanoparticle contamination over time? Atmos Environ 268:118781. https://doi.org/10.1016/j.atmosenv.2021.118781
Bartholdi JJ, Goldsman P (2004) The vertex-adjacency dual of a triangulated irregular network has a Hamiltonian cycle. Oper Res Lett 32(4):304–308. https://doi.org/10.1016/j.orl.2003.11.005
Batool F, Hennig C (2021) Clustering with the average silhouette width. Comput Stat Data Anal 158:107190. https://doi.org/10.1016/j.csda.2021.107190
Bodah BW, Neckel A, Maculan LS, Milanes CB, Korcelski C, Ramírez O, Mendez-Espinosa JF, Bodah ET, Oliveira ML (2022) Sentinel-5P TROPOMI satellite application for NO2 and CO studies aiming at environmental valuation. J Clean Prod 357:131960. https://doi.org/10.1016/j.jclepro.2022.131960
Borrego C, Monteiro A, Ferreira J, Moraes M, Carvalho A, Ribeiro I, Miranda A, Moreira D (2010) Modelling the photochemical pollution over the metropolitan area of Porto Alegre, Brazil. Atmos Environ 44(3):370–380. https://doi.org/10.1016/j.atmosenv.2009.10.027
Brunner N, Mayrpeter G, Kühleitner M (2022) Parameter estimation of the Solow-Swan fundamental differential equation. Heliyon 8(10):e10816. https://doi.org/10.1016/j.heliyon.2022.e10816
Cappelletti D, Petroselli C, Mateos D, Herreras M, Ferrero L, Losi N, Gregorič A, Frangipani C, La Porta G, Lonardi M, Chernov D, Dekhtyareva A (2022) Vertical profiles of black carbon and nanoparticles pollutants measured by a tethered balloon in Longyearbyen (Svalbard islands). Atmos Environ 290:119373. https://doi.org/10.1016/j.atmosenv.2022.119373
Che W, Zhang Y, Lin C, Fung YH, Fung JCH, Lau AK (2022) Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data. J Environ Sci 125:513–523. https://doi.org/10.1016/j.jes.2022.02.041
Dal Moro L, Maculan LS, Neckel A, De Vargas Mores G, Pivoto D, Bodah ET, Bodah BW, Oliveira ML (2021) Geotechnologies applied to the analysis of buildings involved in the production of poultry and swine to the integrated food safety system and environment. J Environ Chem Eng 9(6):106475. https://doi.org/10.1016/j.jece.2021.106475
ESA (European Space Agency) (2023a) SENTINEL-3 OLCI introduction. https://sentinels.copernicus.eu/fr/web/sentinel/user-guides/sentinel-3-olci. (Accessed 28 January 2023)
ESA (European Space Agency) (2023b) SENTINEL-3 OLCI Resolutions. https://sentinels.copernicus.eu/fr/web/sentinel/user-guides/sentinel-3-olci/resolutions. (Accessed 29 January 2023)
ESA (European Space Agency) (2023c) SENTINEL-3 OLCI Level-2 Water Product Type. https://sentinels.copernicus.eu/fr/web/sentinel/user-guides/sentinel-3-olci/product-types/level-2-water. (Accessed 30 January 2023)
Guleria RP, Chand K (2020) Emerging patterns in global and regional aerosol characteristics: a study based on satellite remote sensors. J Atmos Sol-Terr Phys 197:105177. https://doi.org/10.1016/j.jastp.2019.105177
Hamdan AM, Lubis SS, Nazla CT, Jaswita D, Maulida Z, Munandar A, Hamdi H, Ardiansyah R, Khairuzzaman H (2023) Magnetic susceptibilities of suspended sediment and microplastic abundance in a tropical volcanic estuary. Reg Stud Mar Sci 61:102927. https://doi.org/10.1016/j.rsma.2023.102927
Herrera LK, Videla HA (2009) Surface analysis and materials characterization for the study of biodeterioration and weathering effects on cultural property. Int Biodeterior 63(7):813–822. https://doi.org/10.1016/j.ibiod.2009.05.002
Huaji Z, Bai J, Wang Y, Ren J, Yang X, Jiao L (2023) Deep radio signal clustering with interpretability analysis based on saliency map. Digit Commun Netw 19:1–16. https://doi.org/10.1016/j.dcan.2023.01.010
IBGE. Brazilian Institute of Geography and Statistics (2023) Cities and states of Brazil. Demographic Data. https://cidades.ibge.gov.br/. (Accessed 1 March 2023)
INMET. National Institute of Meteorology (2023) Annual historical data. https://portal.inmet.gov.br/dadoshistoricos. (Accessed 15 March 2023)
INPE. Center for Weather Forecasting and Climate Studies (2022) Monthly and seasonal evolution of rain. In: <http://clima1.cptec.inpe.br/evolucao/pt>. (Accessed 26 March 2022)
Jia H, Wang G, Tang W, Song D, Wang X, Hong J, Zhang Z (2020) An optimized approach using cryofixation for high-resolution 3D analysis by FIB-SEM. J Struct Biol 212(1):107600. https://doi.org/10.1016/j.jsb.2020.107600
Kariyam N, Abdurakhman N, Effendie AR (2023) A medoid-based deviation ratio index to determine the number of clusters in a dataset. MethodsX 102084. https://doi.org/10.1016/j.mex.2023.102084
Ketzel M, Frohn LM, Christensen JH, Brandt J, Massling A, Andersen CT, Im U, Jensen SS, Khan J, Nielsen O, Plejdrup MS, Manders A, Van Der Gon HD, Kumar PS, Raaschou-Nielsen O (2021) Modelling ultrafine particle number concentrations at address resolution in Denmark from 1979 to 2018 - Part 2: Local and street scale modelling and evaluation. Atmos Environ 264:118633. https://doi.org/10.1016/j.atmosenv.2021.118633
Kumar P, Skouloudis AN, Bell M, Viana M, Carotta MC, Biskos G, Morawska L (2016) Real-time sensors for indoor air monitoring and challenges ahead in deploying them to urban buildings. Sci Total Environ 560–561:150–159. https://doi.org/10.1016/j.scitotenv.2016.04.032
Kumar P, Zavala-Reyes JC, Kalaiarasan G, Abubakar-Waziri H, Young G, Mudway I, Dilliway C, Lakhdar R, Mumby S, Kłosowski M, Pain C, Adcock IM, Watson JS, Sephton MA, Chung KF, Porter AE (2022) Characteristics of fine and ultrafine aerosols in the London underground. Sci Total Environ 858:159315. https://doi.org/10.1016/j.scitotenv.2022.159315
Leong W, Kelani R, Ahmad Z (2020) Prediction of air pollution index (API) using support vector machine (SVM). J Environ Chem Eng 8(3):103208. https://doi.org/10.1016/j.jece.2019.103208
Li W (2023) The effect of China’s driving restrictions on air pollution: the role of a policy announcement without a stated expiration. Resour Energy Econ 72:101360. https://doi.org/10.1016/j.reseneeco.2023.101360
Li H, Yang Z, Yan W (2022) An improved AIC onset-time picking method based on regression convolutional neural network. Mech Syst Signal Process 171:108867. https://doi.org/10.1016/j.ymssp.2022.108867
Liang Y, Gui K, Che H, Li L, Zheng Y, Zhang X, Zhang X, Zhang P, Zhang X (2023) Changes in aerosol loading before, during and after the COVID-19 pandemic outbreak in China: effects of anthropogenic and natural aerosol. Sci Total Environ 857:159435. https://doi.org/10.1016/j.scitotenv.2022.159435
Lu S, Hao X, Liu D, Wang Q, Zhang W, Liu P, Zhang R, Yu S, Pan R, Wu M, Yonemochi S, Wang Q (2016) Mineralogical characterization of ambient fine/ultrafine particles emitted from Xuanwei C1 coal combustion. Atmos Res 169:17–23. https://doi.org/10.1016/j.atmosres.2015.09.020
Mandal J, Patel PP (2021) Gauging the effects of the COVID-19 pandemic lockdowns on atmospheric pollution content in select countries. Remote Sens Appl: Soc Environ 23:100551. https://doi.org/10.1016/j.rsase.2021.100551
Marcella S, Apicella B, Secondo A, Palestra F, Opromolla G, Ciardi R, Tedeschi V, Ferrara AL, Apicella B, Galdiero MR, Cristinziano L, Modestino L, Spadaro G, Fiorelli A, Loffredo S (2022) Size-based effects of anthropogenic ultrafine particles on activation of human lung macrophages. Environ Int 166:107395. https://doi.org/10.1016/j.envint.2022.107395
Marmett B, Pires Dorneles G, Böek Carvalho R, Peres A, Roosevelt Torres Romão P, BarcosNunes R, Ramos Rhoden C (2021) Air pollution concentration and period of the day modulates inhalation of PM2.5 during moderate - and high-intensity interval exercise. Environ Res 194:110528. https://doi.org/10.1016/j.envres.2020.110528
Maroni D, Cardoso GT, Neckel A, Maculan LS, Oliveira MLS, Bodah ET, Bodah BW, Santosh M (2021) Land surface temperature and vegetation index as a proxy to microclimate. J Environ Chem Eng 9(4):105796. https://doi.org/10.1016/j.jece.2021.105796
Martinello KD, Hower JC, Pinto DCGA, Schnorr CE, Dotto GL, Ramos CG (2022) Artisanal ceramic factories using wood combustion: a nanoparticles and human health study. Geosci Front 13(1):101151. https://doi.org/10.1016/j.gsf.2021.101151
Mehrjou A, Hosseini R, Araabi BN (2016) Improved Bayesian information criterion for mixture model selection. Pattern Recognit Lett 69:22–27. https://doi.org/10.1016/j.patrec.2015.10.004
Morillas H, Marcaida I, Maguregui M, Upasen S, Gallego-Cartagena E, Madariaga JM (2019) Identification of metals and metalloids as hazardous elements in PM2.5 and PM10 collected in a coastal environment affected by diffuse contamination. J Clean Prod 226:369–378. https://doi.org/10.1016/j.jclepro.2019.04.063
Naghizadeh A, Metaxas DN (2020) Condensed silhouette: an optimized filtering process for cluster selection in K-means. Procedia Comput Sci 176:205–214. https://doi.org/10.1016/j.procs.2020.08.022
Neckel A, Oliveira ML, Maculan LS, Bodah BW, Gonçalves AC, Silva LF (2023) Air pollution in central European capital (Budapest) via self-made passive samplers and Sentinel-3B SYN satellite images. Urban Clim 47:101384. https://doi.org/10.1016/j.uclim.2022.101384
Novo R, Marocco P, Giorgi G, Lanzini A, Santarelli M, Mattiazzo G (2022) Planning the decarbonisation of energy systems: the importance of applying time series clustering to long-term models. Energy Convers Manag: X 15:100274. https://doi.org/10.1016/j.ecmx.2022.100274
Oliveira ML, Neckel A, Pinto DCGA, Maculan LS, Zanchett MRD, Silva LF (2021) Air pollutants and their degradation of a historic building in the largest metropolitan area in Latin America. Chemosphere 277:130286. https://doi.org/10.1016/j.chemosphere.2021.130286
Peng C, Deng C, Lei T, Zheng J, Zhao J, Wang D, Wu Z, Wang L, Chen Y, Liu M, Jiang J, Ye A, Ge M, Wang W (2023) Measurement of atmospheric nanoparticles: bridging the gap between gas-phase molecules and larger particles. J Environ Sci 123:183–202. https://doi.org/10.1016/j.jes.2022.03.006
Perrotti TC, De Freitas NC, Alzamora M, Sanchez DR, Carvalho NM (2019) Green iron nanoparticles supported on amino-functionalized silica for removal of the dye methyl orange. J Environ Chem Eng 7(4):103237. https://doi.org/10.1016/j.jece.2019.103237
Pryshchepa O, Buszewski B (2020) Silver nanoparticles: synthesis, investigation techniques, and properties. Adv Colloid Interface Sci 284:102246. https://doi.org/10.1016/j.cis.2020.102246
Putra YC, Wijayanto AW, Chulafak GA (2022) Oil palm trees detection and counting on Microsoft Bing Maps Very High Resolution (VHR) satellite imagery and Unmanned Aerial Vehicles (UAV) data using image processing thresholding approach. Ecol Inform 72:101878. https://doi.org/10.1016/j.ecoinf.2022.101878
Quevedo CP, Jiménez-Millán J, Cifuentes GR, Jiménez-Espinosa R (2020) Clay mineral transformations in anthropic organic matter-rich sediments under saline water environment. Effect on the detrital mineral assemblages in the Upper Chicamocha River Basin. Colombia. Appl Clay Sci 196:105776. https://doi.org/10.1016/j.clay.2020.105776
Qv H, Ma T, Tong X, Huang X, Ma Z, Feng J (2022) Clustering by centroid drift and boundary shrinkage. Pattern Recognit 129:108745. https://doi.org/10.1016/j.patcog.2022.108745
Racoviteanu A, Manley WF, Arnaud Y, Williams M (2007) Evaluating digital elevation models for glaciologic applications: an example from Nevado Coropuna, Peruvian Andes. Glob Planet Chang 59(1–4):110–125. https://doi.org/10.1016/j.gloplacha.2006.11.036
Rohra H, Pipal AS, Satsangi P, Taneja A (2022) Revisiting the atmospheric particles: connecting lines and changing paradigms. Sci Total Environ 841:156676. https://doi.org/10.1016/j.scitotenv.2022.156676
Romanovski V, Zhang L, Su X, Smorokov A, Kamarou M (2022) Gypsum and high quality binders derived from water treatment sediments and spent sulfuric acid: chemical engineering and environmental aspects. Chem Eng Res Des 184:224–232. https://doi.org/10.1016/j.cherd.2022.06.008
Saikia BK, Saikia J, Rabha S, Finkelman RB (2017) Ambient nanoparticles/nanominerals and hazardous elements from coal combustion activity: implications on energy challenges and health hazards. Geosci Front 9(3):863–875. https://doi.org/10.1016/j.gsf.2017.11.013
Sánchez-Zapero J, Camacho F, Martinez-Sanchez E, Gorroño J, León-Tavares J, Benhadj I, Tote C, Swinnen E, Muñoz-Sabater J (2023) Global estimates of surface albedo from Sentinel-3 OLCI and SLSTR data for Copernicus Climate Change Service: algorithm and preliminary validation. Remote Sens EnviroN 287:113460. https://doi.org/10.1016/j.rse.2023.113460
SDE (Department of Economic Development) (2023) Numbers of opening and extinction of companies in RS, Brazil. https://jucisrs.rs.gov.br/numeros-de-abertura-e-extincao-de-empresas-no-rs. (Accessed 15 January 2023)
Silva LF, Oliveira ML, Neckel A, Maculan LS, Batista CM, Bodah BW, Cambrussi LP, Dotto GL (2022) Effects of atmospheric pollutants on human health and deterioration of medieval historical architecture (North Africa, Tunisia). Urban Clim 41:101046. https://doi.org/10.1016/j.uclim.2021.101046
Sjövall P, Bake KD, Pomerantz AE, Lu X, Mitra-Kirtley S, Mullins OC (2021) Analysis of kerogens and model compounds by time-of-flight secondary ion mass spectrometry (TOF-SIMS). Fuel 286:119373. https://doi.org/10.1016/j.fuel.2020.119373
Tang Y, Hu S, Wang H (2020) Using P-Cl inorganic ultrafine aerosol particles to prevent spontaneous combustion of low-rank coal in an underground coal mine. Fire Saf J 115:103140. https://doi.org/10.1016/j.firesaf.2020.103140
Teixeira C, Fernandes CR, Ahern J (2022) Adaptive planting design and management framework for urban climate change adaptation and mitigation. Urban for Urban Green 70:127548. https://doi.org/10.1016/j.ufug.2022.127548
Tian X, Zhang H, Hu C, Yan Y (2023) Preparation of microfiber composite nitrogen doped carbon nanotube membranes and their degradation properties of phenol in the structured fixed bed. J Environ Chem Eng 11(1):109255. https://doi.org/10.1016/j.jece.2022.109255
Trejos EM, Silva LF, Hower JC, Flores EM, González C, Pachon JE, Aristizábal BH (2021) Volcanic emissions and atmospheric pollution: a study of nanoparticles. Geosci Front 12(2):746–755. https://doi.org/10.1016/j.gsf.2020.08.013
Vithanage M, Bandara P, Novo LAB, Kumar A, Ambade B, Naveendrakumar G, Ranagalage M, Magana-Arachchi D (2022) Deposition of trace metals associated with atmospheric particulate matter: environmental fate and health risk assessment. Chemosphere 303:135051. https://doi.org/10.1016/j.chemosphere.2022.135051
Vouitsis I, Portugal J, Kontses A, Karlsson HL, Faria M, Elihn K, Juárez-Facio AT, Amato F, Piña B, Samaras Z (2023) Transport-related airborne nanoparticles: sources, different aerosol modes, and their toxicity. Atmos Environ 301:119698. https://doi.org/10.1016/j.atmosenv.2023.119698
Wölk F, Yuan T, Kis-Katos K, Fu X (2023) A temporal–spatial analysis on the socioeconomic development of rural villages in Thailand and Vietnam based on satellite image data. Comput Commun 203:146–162. https://doi.org/10.1016/j.comcom.2023.02.017
Xu XP, Ni S, Fu M, Xin Z, Luo N, Weng W (2017) Numerical investigation of airflow, heat transfer and particle deposition for oral breathing in a realistic human upper airway model. J Therm Biol 70:53–63. https://doi.org/10.1016/j.jtherbio.2017.05.003
Xu Q, Ning L, Yuan T, Wu H (2023) Application of data mining combined with power data in assessment and prevention of regional atmospheric pollution. Energy Rep 9:3397–3405. https://doi.org/10.1016/j.egyr.2023.02.016
Yuan H, Van De Moortèle B, Epicier T (2021) Accurate post-mortem alignment for Focused Ion Beam and Scanning Electron Microscopy (FIB-SEM) tomography. Ultramicroscopy 228:113265. https://doi.org/10.1016/j.ultramic.2021.113265
Zequan C, Li G, He J, Yang Z, Wang J (2022) A new parallel adaptive structural reliability analysis method based on importance sampling and K-medoids clustering. Reliab Eng Syst Safety 218:108124. https://doi.org/10.1016/j.ress.2021.108124
Zhang X, Wang H, Wang S, Liu Y, Yu W, Wang J, Xu Q, Li X (2022) Oceanic internal wave amplitude retrieval from satellite images based on a data-driven transfer learning model. Remote Sens Environ 272:112940. https://doi.org/10.1016/j.rse.2022.112940
Zhao L, Wang J, Gao HO, Xie Y, Jiang R, Hu Q, Sun Y (2017) Evaluation of particulate matter concentration in Shanghai’s metro system and strategy for improvement. Transp Res d: Transp Environ 53:115–127. https://doi.org/10.1016/j.trd.2017.04.010
Zheng X, Xiong H, Gong J, Yue L (2017) A morphologically preserved multi-resolution TIN surface modeling and visualization method for virtual globes. ISPRS J Photogramm Remote Sens 129:41–54. https://doi.org/10.1016/j.isprsjprs.2017.04.013
Zhou C, Peng X, Li X, Qi K, Gao L (2023) Stable CuFeO/Kaolin-based catalytic particle electrode in 3D heterogeneous electro-Fenton system for orange G removal: synthesis, performance and mechanism. J Environ Chem Eng 11(2):109562. https://doi.org/10.1016/j.jece.2023.109562
Zhu H, Cheng T, Li X, Ye X (2022) Comparison and evaluation of multiple satellite aerosol products over China in different scenarios under a unified criterion: preparation for consistent and high-quality dataset construction. Atmos Res 279:106374. https://doi.org/10.1016/j.atmosres.2022.106374
Zhu L, Xie C, Chen L, Dai X, Zhou Y, Pan H, Tian K (2023) Transport of microplastics in the body and interaction with biological barriers, and controlling of microplastics pollution. Ecotoxicol Environ Saf 255:114818. https://doi.org/10.1016/j.ecoenv.2023.114818
Zoheir B, Emam A, El-Wahed MAA, Soliman N (2019) Gold endowment in the evolution of the Allaqi-Heiani suture, Egypt: a synthesis of geological, structural, and space-borne imagery data. Ore Geol Rev 110:102938. https://doi.org/10.1016/j.oregeorev.2019.102938
Zorzi CGC, Neckel A, Maculan LS, Cardoso GT, Moro LD, Savio AAD, Carrasco LD, Oliveira ML, Bodah ET, Bodah BW (2022) Geo-environmental parametric 3D models of SARS-CoV-2 virus circulation in hospital ventilation systems. Geosci Front 13(6):101279. https://doi.org/10.1016/j.gsf.2021.101279
Zou Z, Yang X (2022) Volatile organic compound emissions from the human body: decoupling and comparison between whole-body skin and breath emissions. Build Environ 226:109713. https://doi.org/10.1016/j.buildenv.2022.109713
Acknowledgements
The authors thank the European Space Agency (ESA) and the U.S. National Aeronautics and Space Administration (NASA) for providing the unpublished and treated images from the Sentinel-3B SYN satellite, and the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website (http://www.ready.noaa.gov) used in this publication. The authors also thank the Center for Studies and Research on Urban Mobility (NEPMOUR+S/ATITUS), Brazil; Fundação Meridional, Brazil; Atlantic International Research Centre (AIR Centre) (https://www.aircentre.org/Scholarship/), Portugal; and the National Council for Scientific and Technological Development (CNPq), Brazil.
Funding
National Council for Scientific and Technological Development (CNPq).
Author information
Authors and Affiliations
Contributions
MGB, LSM, and GTC: conceptualization, funding acquisition. ETB, PCT, LSM, and MLSO: final manuscript writing. AN, BWB, LPL, and LFOS: review and editing.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Additional information
Responsible Editor: Gerhard Lammel
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Bortoluzzi, M.G., Neckel, A., Bodah, B.W. et al. Detection of atmospheric aerosols and terrestrial nanoparticles collected in a populous city in southern Brazil. Environ Sci Pollut Res 31, 3526–3544 (2024). https://doi.org/10.1007/s11356-023-31414-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-023-31414-7