71 citations as recorded by crossref.

1. Long-term contributions of VOC sources and their link to ozone pollution in Bronx, New York City L. Borlaza-Lacoste et al. https://doi.org/10.1016/j.envint.2024.108993
2. Personal exposure to PM2.5 oxidative potential and its association to birth outcomes L. Borlaza et al. https://doi.org/10.1038/s41370-022-00487-w
3. OPNet: A deep-learning approach for estimating particulate matter’s oxidative potential from satellite imagery A. Carbone et al. https://doi.org/10.1016/j.aeaoa.2025.100406
4. Comprehensive analysis of PM10 in the metropolitan area of São Paulo – Part I: Chemical characterisation and source apportionment J. Florêncio et al. https://doi.org/10.1016/j.atmosenv.2026.122286
5. Source apportionment of oxidative potential depends on the choice of the assay: insights into 5 protocols comparison and implications for mitigation measures P. Dominutti et al. https://doi.org/10.1039/D3EA00007A
6. Annual variation of source contributions to PM10 and oxidative potential in a mountainous area with traffic, biomass burning, cement-plant and biogenic influences K. Glojek et al. https://doi.org/10.1016/j.envint.2024.108787
7. Reshaping metal composition and sources to reduce PM2.5 oxidative potential by clean energy policies in Xi'an, China L. Zhang et al. https://doi.org/10.1016/j.atmosenv.2025.121742
8. Source apportionment of atmospheric PM10 oxidative potential: synthesis of 15 year-round urban datasets in France S. Weber et al. https://doi.org/10.5194/acp-21-11353-2021
9. Combining Satellite‐Derived PM2.5 Data and a Reduced‐Form Air Quality Model to Support Air Quality Analysis in US Cities C. Gallagher et al. https://doi.org/10.1029/2023GH000788
10. Soil and litter emission sources as important contributors to ozone production from volatile organic compounds in island tropical forests H. Zhou et al. https://doi.org/10.1016/j.envres.2025.122297
11. Oxidative potential in rural, suburban and city centre atmospheric environments in central Europe M. Vörösmarty et al. https://doi.org/10.5194/acp-23-14255-2023
12. Source-specific light absorption and radiative effects decreases and indications due to the lockdown Y. Qu et al. https://doi.org/10.1016/j.jenvman.2024.120600
13. Nine-year trends of PM10 sources and oxidative potential in a rural background site in France L. Borlaza et al. https://doi.org/10.5194/acp-22-8701-2022
14. Characterization of Oxidative Potential and Ecotoxicity of the Organic Fraction of Particulate Matter in a Coastal City in China: Implications for Human Respiratory Health K. Chen et al. https://doi.org/10.1021/acsestair.4c00177
15. Spatiotemporal variability in the oxidative potential of ambient fine particulate matter in the Midwestern United States H. Yu et al. https://doi.org/10.5194/acp-21-16363-2021
16. Toxicity source apportionment of fugitive dust PM2.5-bound polycyclic aromatic hydrocarbons using multilayer perceptron neural network analysis in Guanzhong Plain urban agglomeration, China Q. Zhang et al. https://doi.org/10.1016/j.jhazmat.2024.133773
17. Source-specific control leverage for reducing oxidative potential of PM2.5 revealed by explainable machine learning C. Hung et al. https://doi.org/10.1016/j.envpol.2026.128823
18. Airborne Micropollutants and Their Health Effects: A Comprehensive Overview on Krakow, Poland K. Styszko et al. https://doi.org/10.1088/1742-6596/3107/1/012010
19. Linking Switzerland's PM10 and PM2.5 oxidative potential (OP) with emission sources S. Grange et al. https://doi.org/10.5194/acp-22-7029-2022
20. Revisiting the atmospheric particles: Connecting lines and changing paradigms H. Rohra et al. https://doi.org/10.1016/j.scitotenv.2022.156676
21. Effects of VOC Mixtures and Oxidation Conditions on Particle-Bound ROS Formation, Persistence, and Cytotoxicity in Secondary Organic Aerosols L. Lu et al. https://doi.org/10.1021/acsestair.6c00175
22. Quantification of 21 sugars in tropospheric particulate matter by ultra-high-performance liquid chromatography tandem mass spectrometry P. Bros et al. https://doi.org/10.5194/amt-18-6315-2025
23. Explainable AI for predicting oxidative potential of fine particles and key chemical drivers S. Lee et al. https://doi.org/10.1016/j.jhazmat.2025.139842
24. Ascorbate oxidation driven by PM2.5-bound metal(loid)s extracted in an acidic simulated lung fluid in relation to their bioaccessibility A. Expósito et al. https://doi.org/10.1007/s11869-023-01436-8
25. Toolbox for accurate estimation and validation of Positive Matrix Factorization solutions in Particulate Matter source apportionment V. Dinh et al. https://doi.org/10.5194/amt-18-6817-2025
26. Sensitivity of PM10 oxidative potential to aerosol chemical composition at a Mediterranean urban site: ascorbic acid versus dithiothreitol measurements Á. Clemente et al. https://doi.org/10.1007/s11869-023-01332-1
27. Oxidative potential of particulate matter and its association to respiratory health endpoints in high-altitude cities in Bolivia L. Borlaza-Lacoste et al. https://doi.org/10.1016/j.envres.2024.119179
28. Inter-comparison of oxidative potential metrics for airborne particles identifies differences between acellular chemical assays P. Shahpoury et al. https://doi.org/10.1016/j.apr.2022.101596
29. Winter brown carbon over six of China's megacities: light absorption, molecular characterization, and improved source apportionment revealed by multilayer perceptron neural network D. Wang et al. https://doi.org/10.5194/acp-22-14893-2022
30. Unveiling the optimal regression model for source apportionment of the oxidative potential of PM10 V. Ngoc Thuy et al. https://doi.org/10.5194/acp-24-7261-2024
31. Analysis of interactions of particle-associated oxidative potential sources using multilayer perceptron neural networks: A case study in Shenyang, China S. Wei et al. https://doi.org/10.1016/j.envpol.2025.126868
32. Analysis of Spatio-Temporal Characteristics and Trend Forecast of Building Industry VOCs Emissions in China H. Dai et al. https://doi.org/10.3390/buildings12101661
33. Pollution sources affecting the oxidative potential of fine aerosols in a Portuguese urban-industrial area - an exploratory study N. Canha et al. https://doi.org/10.1007/s11869-024-01556-9
34. Oxidative potential of atmospheric brown carbon in six Chinese megacities: Seasonal variation and source apportionment D. Wang et al. https://doi.org/10.1016/j.atmosenv.2023.119909
35. Estimations of ambient fine particle and ozone level at a suburban site of Beijing in winter W. Liu et al. https://doi.org/10.1088/2515-7620/ac1f82
36. VAR-tree model based spatio-temporal characterization and prediction of O3 concentration in China H. Dai et al. https://doi.org/10.1016/j.ecoenv.2023.114960
37. Impact of COVID-19 lockdown on particulate matter oxidative potential at urban backgroundversustraffic sites L. Borlaza et al. https://doi.org/10.1039/D3EA00013C
38. Quantifying the contribution of ship emissions to black carbon pollution along the coast of the East China sea using machine learning approach S. Ding et al. https://doi.org/10.1016/j.ocecoaman.2025.107784
39. Size-segregated particulate matter oxidative potential near a ferromanganese plant: Associations with soluble and insoluble elements and their sources A. Expósito et al. https://doi.org/10.1016/j.apr.2024.102330
40. Oxidative potential of PM2.5: Source apportionment analysis across four Eastern Mediterranean sites M. Fadel et al. https://doi.org/10.1016/j.apr.2026.102917
41. Decadal trends (2013–2023) in PM10 sources and oxidative potential at a European urban supersite (Grenoble, France) V. Ngoc Thuy Dinh et al. https://doi.org/10.5194/acp-26-247-2026
42. Source apportionment of PM2.5 oxidative potential in an East Mediterranean site M. Fadel et al. https://doi.org/10.1016/j.scitotenv.2023.165843
43. Multilayer regression analysis and psychological intervention effect assessment study of college students’ tennis intervention for depressed mood J. Huang https://doi.org/10.2478/amns-2025-0478
44. Oxidative potential of atmospheric particles in Europe and exposure scenarios C. Tassel et al. https://doi.org/10.1038/s41586-025-09666-9
45. Effect of protesting by burning barricades on PM2.5: chemical composition and oxidative potential evaluation M. Fadel et al. https://doi.org/10.1016/j.envpol.2026.127955
46. Seasonal Changes in the Oxidative Potential of Urban Air Pollutants: The Influence of Emission Sources and Proton- and Ligand-Mediated Dissolution of Transition Metals P. Shahpoury et al. https://doi.org/10.1021/acsestair.4c00093
47. Discovering oxidative potential (OP) drivers of atmospheric PM10, PM2.5, and PM1 simultaneously in North-Eastern Spain M. in 't Veld et al. https://doi.org/10.1016/j.scitotenv.2022.159386
48. Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements R. Cheung et al. https://doi.org/10.1016/j.scitotenv.2024.172345
49. Refined prediction of SO2 concentration around Chinese coking enterprises and exposure risk assessment of different populations based on buffer Latin hypercube M. Lei et al. https://doi.org/10.1016/j.jclepro.2024.143833
50. Size matters: Cross-continental study of oxidative potential in size-fractionated particles from schools in Portugal and Angola I. Charres et al. https://doi.org/10.1016/j.jes.2026.03.049
51. Application of machine learning in atmospheric pollution research: A state-of-art review Z. Peng et al. https://doi.org/10.1016/j.scitotenv.2023.168588
52. The effects of photochemical aging and interactions with secondary organic aerosols on cellular toxicity of combustion particles R. Attah et al. https://doi.org/10.1016/j.jaerosci.2024.106473
53. Characteristics and source apportionment of VOCs and their contribution to ozone formation in a typical chemical industrial park Y. Jia et al. https://doi.org/10.1016/j.atmosenv.2026.122180
54. Numerical simulation of IL-8-based relative inflammation potentials of aerosol particles from vehicle exhaust and non-exhaust emission sources in Japan M. Kajino et al. https://doi.org/10.1016/j.aeaoa.2024.100237
55. Spatially resolved chemical data for PM10 and oxidative potential source apportionment in urban-industrial settings L. Massimi et al. https://doi.org/10.1016/j.uclim.2024.102113
56. Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique J. Camman et al. https://doi.org/10.5194/acp-24-3257-2024
57. Long-term trends reflecting regulatory impacts on VOCs sources in the New York City metropolitan area L. Borlaza-Lacoste et al. https://doi.org/10.1016/j.apr.2025.102789
58. Modelling oxidative potential of atmospheric particle: A 2-year study over France M. Vida et al. https://doi.org/10.1016/j.scitotenv.2025.178813
59. Cellulose in atmospheric particulate matter at rural and urban sites across France and Switzerland A. Brighty et al. https://doi.org/10.5194/acp-22-6021-2022
60. Interplay of chemical toxicants and urban microenvironments in the oxidative potential and comprehensive risk of road dust Q. Zhang et al. https://doi.org/10.1016/j.envres.2026.124538
61. Interpretable machine learning framework for air quality prediction in Istanbul using Shapley additive explanations (SHAP) E. Birinci et al. https://doi.org/10.1007/s00477-026-03168-4
62. WITHDRAWN: Identifying key drivers affecting oxidative potential in road dust and assessing the comprehensive risk involving urban land use data: A field study in Guanzhong urban cluster, China Q. Zhang et al. https://doi.org/10.1016/j.enceco.2025.06.003
63. Impact of biomass burning and non-exhaust vehicle emissions on PM10 levels in a mid-size non-industrial western Iberian city C. Pio et al. https://doi.org/10.1016/j.atmosenv.2022.119293
64. Insights the dominant contribution of biomass burning to methanol-soluble PM2.5 bounded oxidation potential based on multilayer perceptron neural network analysis in Xi'an, China Y. Luo et al. https://doi.org/10.1016/j.scitotenv.2023.168273
65. Disentangling fine particles (PM2.5) composition in Hanoi, Vietnam: Emission sources and oxidative potential P. Dominutti et al. https://doi.org/10.1016/j.scitotenv.2024.171466
66. Assessing the oxidative potential of dust from great salt Lake R. Attah et al. https://doi.org/10.1016/j.atmosenv.2024.120728
67. Tracing petrochemical emissions: Neural network-driven spectral fingerprint analysis of volatile organic compounds Z. Xiao et al. https://doi.org/10.1016/j.atmosenv.2025.121360
68. The impacts of regional transport on anthropogenic source contributions of PM2.5 in a basin city, China H. Liu et al. https://doi.org/10.1016/j.scitotenv.2024.170038
69. Oxidative potential of size-segregated particulate matter in the dust-storm impacted Hotan, northwest China J. An et al. https://doi.org/10.1016/j.atmosenv.2022.119142
70. Chemical and oxidative properties of fine particulate matter from near-road traffic sources N. Raparthi et al. https://doi.org/10.1016/j.envpol.2023.122514
71. Aerosol oxidative potential and reactive species predicted with a chemical kinetics model (KM-OP) A. Mishra et al. https://doi.org/10.5194/acp-26-10605-2026