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1. Combinatorial Chemistry for Optical Sensing Applications

Author: Díaz-García, M. E., Luis, G. Pina, Rivero-Espejel, I. A., Potyrailo, Radislav A., editor, and Mirsky, Vladimir M., editor
Published: 2009
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2. Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements

Author: K. Lange, A. Richter, T. Bösch, B. Zilker, M. Latsch, L. K. Behrens, C. M. Okafor, H. Bösch, J. P. Burrows, A. Merlaud, G. Pinardi, C. Fayt, M. M. Friedrich, E. Dimitropoulou, M. Van Roozendael, S. Ziegler, S. Ripperger-Lukosiunaite, L. Kuhn, B. Lauster, T. Wagner, H. Hong, D. Kim, L.-S. Chang, K. Bae, C.-K. Song, J.-U. Park, and H. Lee
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation in important air pollutants such as nitrogen dioxide (NO2). The South Korean instrument GEMS (Geostationary Environmental Monitoring Spectrometer), launched in February 2020, is the first geostationary instrument that is able to observe the diurnal variation in NO2. The measurements have a spatial resolution of 3.5 km × 8 km and cover a large part of Asia. This study compares 1 year of tropospheric NO2 vertical column density (VCD) observations from the operational GEMS L2 product, the scientific GEMS IUP-UB (Institute of Environmental Physics at the University of Bremen) product, the operational TROPOspheric Monitoring Instrument (TROPOMI) product, and ground-based differential optical absorption spectroscopy (DOAS) measurements in South Korea. The GEMS L2 tropospheric NO2 VCDs overestimate the ground-based tropospheric NO2 VCDs with a median relative difference of +61 % and a correlation coefficient of 0.76. The median relative difference is −2 % for the GEMS IUP-UB product and −16 % for the TROPOMI product, with correlation coefficients of 0.83 and 0.89, respectively. The scatter in the GEMS products can be reduced when observations are limited to the TROPOMI overpass time. Diurnal variations in tropospheric NO2 VCDs differ by the pollution level of the analyzed site but with good agreement between the GEMS IUP-UB and ground-based observations. Low-pollution sites show weak or almost no diurnal variation. In summer, the polluted sites show a minimum around noon, indicating the large influence of photochemical loss. Most variation is seen in spring and autumn, with increasing NO2 in the morning, a maximum close to noon, and a decrease towards the afternoon. Winter observations show rather flat or slightly decreasing NO2 throughout the day. Winter observations under low-wind-speed conditions at high-pollution sites show enhancements of NO2 throughout the day. This indicates that under calm conditions, dilution and the less effective chemical loss in winter do not balance the accumulating emissions. Diurnal variation observed at a low-pollution site follows seasonal wind patterns. A weekday–weekend effect analysis shows good agreement between the different products. However, the GEMS L2 product, while agreeing with the other data sets on weekdays, shows significantly less reduction on weekends. The influence of the stratospheric contribution and the surface reflectivity product on the satellite tropospheric NO2 VCD products is investigated. While the TM5 model's stratospheric VCDs, used in the TROPOMI product, are too high, resulting in tropospheric NO2 VCDs that are too low and even negative, when used in the GEMS IUP-UB retrieval, the GEMS L2 stratospheric VCD is too low. Surface reflectivity comparisons indicate that the GEMS L2 reflectivity makes a large contribution to the observed overestimation and scatter.
Published: 2024
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3. First evaluation of the GEMS formaldehyde product against TROPOMI and ground-based column measurements during the in-orbit test period

Author: G. T. Lee, R. J. Park, H.-A. Kwon, E. S. Ha, S. D. Lee, S. Shin, M.-H. Ahn, M. Kang, Y.-S. Choi, G. Kim, D.-W. Lee, D.-R. Kim, H. Hong, B. Langerock, C. Vigouroux, C. Lerot, F. Hendrick, G. Pinardi, I. De Smedt, M. Van Roozendael, P. Wang, H. Chong, Y. Cho, and J. Kim
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: The Geostationary Environment Monitoring Spectrometer (GEMS) on board GEO-KOMPSAT-2B was launched in February 2020 and has been monitoring atmospheric chemical compositions over Asia. We present the first evaluation of the operational GEMS formaldehyde (HCHO) vertical column densities (VCDs) during and after the in-orbit test (IOT) period (August–October 2020) by comparing them with the products from the TROPOspheric Monitoring Instrument (TROPOMI) and Fourier-transform infrared (FTIR) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments. During the IOT, the GEMS HCHO VCDs reproduced the observed spatial pattern of TROPOMI VCDs over the entire domain (r= 0.62) with high biases (10 %–16 %). We found that the agreement between GEMS and TROPOMI was substantially higher in Northeast Asia (r= 0.90), encompassing the Korean Peninsula and east China. GEMS HCHO VCDs captured the seasonal variation in HCHO, primarily driven by biogenic emissions and photochemical activities, but showed larger variations than those of TROPOMI over coastal regions (Kuala Lumpur, Singapore, Shanghai, and Busan). In addition, GEMS HCHO VCDs showed consistent hourly variations with MAX-DOAS (r= 0.77) and FTIR (r= 0.86) but were 30–40 % lower than ground-based observations. Different vertical sensitivities of GEMS and ground-based instruments caused these biases. Utilizing the averaging kernel smoothing method reduces the low biases by approximately 10 % to 15 % (normalized mean bias (NMB): −47.4 % to −31.5 % and −38.6 % to −26.7 % for MAX-DOAS and FTIR, respectively). The remaining discrepancies are due to multiple factors, including spatial collocation and different instrumental sensitivities, requiring further investigation using inter-comparable datasets.
Published: 2024
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4. Enrichment and Transcriptional Characterization of Stem Cells Isolated from Human Glioblastoma Cell Lines

Author: Ana G, Piña-Medina, Ana M, Hernández-Vega, Néstor F, Díaz, Ismael, Mancilla-Herrera, and Ignacio, Camacho-Arroyo
Subjects: Gene Expression Regulation, Neoplastic, Neural Stem Cells, Brain Neoplasms, Reverse Transcriptase Polymerase Chain Reaction, Cell Line, Tumor, Neoplastic Stem Cells, Humans, Intercellular Signaling Peptides and Proteins, Lewis X Antigen, AC133 Antigen, Flow Cytometry, Glioblastoma, Culture Media, Serum-Free
Abstract: Glioblastomas (GBM) are the most frequent and aggressive brain tumors due to their recurrence and resistance to current therapies. These characteristics are associated with the presence of glioma stem cells (GSCs), mainly identified by the detection of the membrane antigens CD133 and CD15. The main source of GSCs has been biopsies of tumors. However, alternatives are sought from cell lines because more homogeneous populations can be obtained with high yields. This chapter describes a method for the enrichment and characterization of GSCs from cell lines derived from human GBM by selective culture with serum-free neural stem cell medium and growth factors. The technique offers alternatives for the enrichment and characterization of GSCs, that could contribute to a better understanding of the biology of GBMs.
Published: 2020

5. 14C and Other Radionuclides in Impermeable Graphite Material Waste form Long Term Behavior

Author: Eva María Márquez, G. Piña, J Fachinger, and J L Leganés
Subjects: Archeology, Radionuclide, law, Environmental chemistry, General Earth and Planetary Sciences, Environmental science, Long term behavior, Graphite, Radiocarbon dating, law.invention
Abstract: The radiocarbon (14C) content of irradiated graphite is the most important problem for the management of Spanish irradiated graphite (Vandellós I NPP) as L&ILW, due to this material exceeding the maximum14C inventory for the C.A. El Cabril repository. Therefore, the encapsulation of graphite in an impermeable matrix and making an appropriate waste form are indicated as potential management options to be studied. The conversion of the graphite to a long-term stable glass matrix, called IGM (impermeable graphite matrix), uses a long-term stable inorganic binder which additionally encloses the graphite pore system. The world’s first IGM samples made with irradiated graphite have been manufactured in CIEMAT facilities. The durability of the matrix is investigated in leaching experiments in deionized water and granitic bentonite water. The results show that ∼0.05% of14C is leached. A species of organic carbon was found as formate and oxalate (∼10–1mg/L). CO was detected as volatile specie in both media in the first leaching steps; for deionized water (∼3.101mg/L) and in granitic bentonite water (ranging 1.101–3.101mg/L). These low values demonstrated the durability of the IGM glass matrix for final disposal.
Published: 2018
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6. 14C leaching and speciation studies on Irradiated graphite from vandellós I Nuclear Power Plant

Author: Esperanza Lara, G. Piña, Enrique Magro, Eva María Márquez, Lucía Sevilla, M. Rodríguez, and José Luís Gascón
Subjects: 010302 applied physics, Detection limit, Archeology, Radionuclide, Aqueous solution, Waste management, Radioactive waste, 01 natural sciences, 010305 fluids & plasmas, law.invention, law, 0103 physical sciences, Bentonite, Nuclear power plant, General Earth and Planetary Sciences, Environmental science, Graphite, Leaching (metallurgy)
Abstract: The understanding of the 14C behavior in waste packages could lead, in the Spanish context, to a revision of the management strategies for radioactive waste and a revaluation of the near surface repository devoted to the disposal of waste containing this radionuclide in high concentrations. To achieve this objective, and in the context of the EU project Carbon-14 Source Term (CAST), the authors of the work presented in this paper have performed leaching experiments with irradiated graphite considering two different scenarios. One, in which the leaching solution simulates some of the expected conditions in a repository where a granite/bentonite mixture has been used as backfill material, and the other, using deionized water as a high efficiency chemical removal agent and for comparison purposes. The analytical approach to measure the release rate and speciation of 14C from irradiated graphite samples in the aqueous and gaseous phase is also described. The main results obtained shows that, after 359 days of leaching, no 14C activity was detected above the detection limits, and only leaching rates regarding beta-gamma emitters were observed: 2×10–6 cm/day for 137Cs and 1×10–5 cm/day for 60Co in granite/bentonite water media and 4×10–6 cm/day for 137Cs in pure water.
Published: 2018
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7. Performance of a Modular Ton-Scale Pixel-Readout Liquid Argon Time Projection Chamber

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, C. Adriano, A. Aduszkiewicz, J. Aguilar, B. Aimard, F. Akbar, K. Allison, S. Alonso Monsalve, M. Alrashed, A. Alton, R. Alvarez, T. Alves, H. Amar, P. Amedo, J. Anderson, D. A. Andrade, C. Andreopoulos, M. Andreotti, M. P. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, A. Aranda-Fernandez, L. Arellano, E. Arrieta Diaz, M. A. Arroyave, J. Asaadi, A. Ashkenazi, D. Asner, L. Asquith, E. Atkin, D. Auguste, A. Aurisano, V. Aushev, D. Autiero, F. Azfar, A. Back, H. Back, J. J. Back, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, W. Baldini, J. Baldonedo, B. Baller, B. Bambah, R. Banerjee, F. Barao, G. Barenboim, P. B̃arham Alzás, G. J. Barker, W. Barkhouse, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, D. Barrow, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, L. Bathe-Peters, J. B. R. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. L. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, E. Belchior, G. Bell, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, D. Benjamin, F. Bento Neves, J. Berger, S. Berkman, J. Bernal, P. Bernardini, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, A. T. Bezerra, T. J. Bezerra, A. Bhat, V. Bhatnagar, J. Bhatt, M. Bhattacharjee, M. Bhattacharya, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. D. Blaszczyk, G. C. Blazey, E. Blucher, J. Bogenschuetz, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, R. Borges Merlo, A. Borkum, N. Bostan, J. Bracinik, D. Braga, B. Brahma, D. Brailsford, F. Bramati, A. Branca, A. Brandt, J. Bremer, C. Brew, S. J. Brice, V. Brio, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, J. Buergi, D. Burgardt, S. Butchart, G. Caceres V., I. Cagnoli, T. Cai, R. Calabrese, J. Calcutt, M. Calin, L. Calivers, E. Calvo, A. Caminata, A. F. Camino, W. Campanelli, A. Campani, A. Campos Benitez, N. Canci, J. Capó, I. Caracas, D. Caratelli, D. Carber, J. M. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, N. Carrara, L. Carroll, T. Carroll, A. Carter, E. Casarejos, D. Casazza, J. F. Castaño Forero, F. A. Castaño, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, C. Cerna, A. Cervelli, A. Cervera Villanueva, K. Chakraborty, S. Chakraborty, M. Chalifour, A. Chappell, N. Charitonidis, A. Chatterjee, H. Chen, M. Chen, W. C. Chen, Y. Chen, Z. Chen-Wishart, D. Cherdack, C. Chi, R. Chirco, N. Chitirasreemadam, K. Cho, S. Choate, D. Chokheli, P. S. Chong, B. Chowdhury, D. Christian, A. Chukanov, M. Chung, E. Church, M. F. Cicala, M. Cicerchia, V. Cicero, R. Ciolini, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. A. B. Coelho, A. Cohen, J. Collazo, J. Collot, E. Conley, J. M. Conrad, M. Convery, S. Copello, P. Cova, C. Cox, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, G. Crone, R. Cross, A. Cudd, C. Cuesta, Y. Cui, F. Curciarello, D. Cussans, J. Dai, O. Dalager, R. Dallavalle, W. Dallaway, H. da Motta, Z. A. Dar, R. Darby, L. Da Silva Peres, Q. David, G. S. Davies, S. Davini, J. Dawson, R. De Aguiar, P. De Almeida, P. Debbins, I. De Bonis, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, P. De Jong, P. Del Amo Sanchez, A. De la Torre, G. De Lauretis, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, G. Delle Monache, N. Delmonte, P. De Lurgio, R. Demario, G. De Matteis, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, P. Denton, G. W. Deptuch, A. De Roeck, V. De Romeri, J. P. Detje, J. Devine, R. Dharmapalan, M. Dias, A. Diaz, J. S. Díaz, F. Díaz, F. Di Capua, A. Di Domenico, S. Di Domizio, S. Di Falco, L. Di Giulio, P. Ding, L. Di Noto, E. Diociaiuti, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. J. Dolinski, D. Domenici, L. Domine, S. Donati, Y. Donon, S. Doran, D. Douglas, T. A. Doyle, A. Dragone, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, K. Dugas, P. Dunne, B. Dutta, H. Duyang, D. A. Dwyer, A. S. Dyshkant, S. Dytman, M. Eads, A. Earle, S. Edayath, D. Edmunds, J. Eisch, P. Englezos, A. Ereditato, T. Erjavec, C. O. Escobar, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, L. Fajt, A. Falcone, M. Fani’, C. Farnese, S. Farrell, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, G. Ferry, L. Fields, P. Filip, A. Filkins, F. Filthaut, R. Fine, G. Fiorillo, M. Fiorini, S. Fogarty, W. Foreman, J. Fowler, J. Franc, K. Francis, D. Franco, J. Franklin, J. Freeman, J. Fried, A. Friedland, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, R. Gaba, A. Gabrielli, A. M. Gago, F. Galizzi, H. Gallagher, A. Gallas, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, S. Ganguly, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, F. Gardim, S. Gardiner, D. Gastler, A. Gauch, J. Gauvreau, P. Gauzzi, S. Gazzana, G. Ge, N. Geffroy, B. Gelli, S. Gent, L. Gerlach, Z. Ghorbani-Moghaddam, T. Giammaria, D. Gibin, I. Gil-Botella, S. Gilligan, A. Gioiosa, S. Giovannella, C. Girerd, A. K. Giri, C. Giugliano, V. Giusti, D. Gnani, O. Gogota, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. V. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, D. Gonzalez-Diaz, M. Gonzalez-Lopez, M. C. Goodman, S. Goswami, C. Gotti, J. Goudeau, E. Goudzovski, C. Grace, E. Gramellini, R. Gran, E. Granados, P. Granger, C. Grant, D. R. Gratieri, G. Grauso, P. Green, S. Greenberg, J. Greer, W. C. Griffith, F. T. Groetschla, K. Grzelak, L. Gu, W. Gu, V. Guarino, M. Guarise, R. Guenette, E. Guerard, M. Guerzoni, D. Guffanti, A. Guglielmi, B. Guo, Y. Guo, A. Gupta, V. Gupta, G. Gurung, D. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, H. Hadavand, L. Haegel, R. Haenni, L. Hagaman, A. Hahn, J. Haiston, J. Hakenmueller, T. Hamernik, P. Hamilton, J. Hancock, F. Happacher, D. A. Harris, J. Hartnell, T. Hartnett, J. Harton, T. Hasegawa, C. Hasnip, R. Hatcher, K. Hayrapetyan, J. Hays, E. Hazen, M. He, A. Heavey, K. M. Heeger, J. Heise, S. Henry, M. A. Hernandez Morquecho, K. Herner, V. Hewes, A. Higuera, C. Hilgenberg, S. J. Hillier, A. Himmel, E. Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, T. Holvey, E. Hoppe, S. Horiuchi, G. A. Horton-Smith, M. Hostert, T. Houdy, B. Howard, R. Howell, I. Hristova, M. S. Hronek, J. Huang, R. G. Huang, Z. Hulcher, M. Ibrahim, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, M. Ismerio Oliveira, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, D. Jena, I. Jentz, X. Ji, C. Jiang, J. Jiang, L. Jiang, A. Jipa, F. R. Joaquim, W. Johnson, C. Jollet, B. Jones, R. Jones, D. José Fernández, N. Jovancevic, M. Judah, C. K. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. C. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, M. Kandemir, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, I. Katsioulas, A. Kauther, N. Kazaryan, L. Ke, E. Kearns, P. T. Keener, K. J. Kelly, E. Kemp, O. Kemularia, Y. Kermaidic, W. Ketchum, S. H. Kettell, M. Khabibullin, N. Khan, A. Khvedelidze, D. Kim, J. Kim, M. Kim, B. King, B. Kirby, M. Kirby, A. Kish, J. Klein, J. Kleykamp, A. Klustova, T. Kobilarcik, L. Koch, K. Koehler, L. W. Koerner, D. H. Koh, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, I. Kotler, M. Kovalcuk, V. Kozhukalov, W. Krah, R. Kralik, M. Kramer, L. Kreczko, F. Krennrich, I. Kreslo, T. Kroupova, S. Kubota, M. Kubu, Y. Kudenko, V. A. Kudryavtsev, G. Kufatty, S. Kuhlmann, J. Kumar, P. Kumar, S. Kumaran, P. Kunze, J. Kunzmann, R. Kuravi, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, T. Labree, T. Lackey, A. Lambert, B. J. Land, C. E. Lane, N. Lane, K. Lang, T. Langford, M. Langstaff, F. Lanni, O. Lantwin, J. Larkin, P. Lasorak, D. Last, A. Laudrain, A. Laundrie, G. Laurenti, E. Lavaut, A. Lawrence, P. Laycock, I. Lazanu, M. Lazzaroni, T. Le, S. Leardini, J. Learned, T. LeCompte, C. Lee, V. Legin, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, D. Leon Silverio, L. M. Lepin, J.-Y. Li, S. W. Li, Y. Li, H. Liao, C. S. Lin, D. Lindebaum, S. Linden, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, H. Liu, J. Liu, Y. Liu, S. Lockwitz, M. Lokajicek, I. Lomidze, K. Long, T. V. Lopes, J. Lopez, I. López de Rego, N. López-March, T. Lord, J. M. LoSecco, W. C. Louis, A. Lozano Sanchez, X.-G. Lu, K. B. Luk, B. Lunday, X. Luo, E. Luppi, J. Maalmi, D. MacFarlane, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, M. MacMahon, A. Maddalena, A. Madera, P. Madigan, S. Magill, C. Magueur, K. Mahn, A. Maio, A. Major, K. Majumdar, M. Man, R. C. Mandujano, J. Maneira, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, S. Manthey Corchado, V. N. Manyam, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, F. Marinho, A. D. Marino, T. Markiewicz, F. Das Chagas Marques, C. Marquet, D. Marsden, M. Marshak, C. M. Marshall, J. Marshall, L. Martina, J. Martín-Albo, N. Martinez, D. A. Martinez Caicedo, F. Martínez López, P. Martínez Miravé, S. Martynenko, V. Mascagna, C. Massari, A. Mastbaum, F. Matichard, S. Matsuno, G. Matteucci, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, T. McAskill, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, L. Meazza, V. C. N. Meddage, B. Mehta, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, A. C. E. A. Mercuri, A. Meregaglia, M. D. Messier, S. Metallo, J. Metcalf, W. Metcalf, M. Mewes, H. Meyer, T. Miao, A. Miccoli, G. Michna, V. Mikola, R. Milincic, F. Miller, G. Miller, W. Miller, O. Mineev, A. Minotti, L. Miralles, O. G. Miranda, C. Mironov, S. Miryala, S. Miscetti, C. S. Mishra, S. R. Mishra, A. Mislivec, M. Mitchell, D. Mladenov, I. Mocioiu, A. Mogan, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, D. Montanino, L. M. Montaño Zetina, M. Mooney, A. F. Moor, Z. Moore, D. Moreno, O. Moreno-Palacios, L. Morescalchi, D. Moretti, R. Moretti, C. Morris, C. Mossey, M. Mote, C. A. Moura, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, F. Muheim, A. Muir, M. Mulhearn, D. Munford, L. J. Munteanu, H. Muramatsu, J. Muraz, M. Murphy, T. Murphy, J. Muse, A. Mytilinaki, J. Nachtman, Y. Nagai, S. Nagu, R. Nandakumar, D. Naples, S. Narita, A. Nath, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, A. Nehm, J. K. Nelson, O. Neogi, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, R. Nichol, F. Nicolas-Arnaldos, A. Nikolica, J. Nikolov, E. Niner, K. Nishimura, A. Norman, A. Norrick, P. Novella, J. A. Nowak, M. Oberling, J. P. Ochoa-Ricoux, S. Oh, S. B. Oh, A. Olivier, A. Olshevskiy, T. Olson, Y. Onel, Y. Onishchuk, A. Oranday, M. Osbiston, J. A. Osorio Vélez, L. Otiniano Ormachea, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, S. Pan, P. Panda, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, D. Papoulias, S. Paramesvaran, A. Paris, S. Parke, E. Parozzi, S. Parsa, Z. Parsa, S. Parveen, M. Parvu, D. Pasciuto, S. Pascoli, L. Pasqualini, J. Pasternak, C. Patrick, L. Patrizii, R. B. Patterson, T. Patzak, A. Paudel, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, E. Pedreschi, S. J. M. Peeters, W. Pellico, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. G. Peres, Y. F. Perez Gonzalez, L. Pérez-Molina, C. Pernas, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, M. Pfaff, V. Pia, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, J. Pinchault, K. Pitts, K. Plows, R. Plunkett, C. Pollack, T. Pollman, D. Polo-Toledo, F. Pompa, X. Pons, N. Poonthottathil, V. Popov, F. Poppi, J. Porter, M. Potekhin, R. Potenza, J. Pozimski, M. Pozzato, T. Prakash, C. Pratt, M. Prest, F. Psihas, D. Pugnere, X. Qian, J. L. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, S. Rajagopalan, M. Rajaoalisoa, I. Rakhno, L. Rakotondravohitra, L. Ralte, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, R. Ray, H. Razafinime, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, E. Renner, A. Renshaw, S. Rescia, F. Resnati, D. Restrepo, C. Reynolds, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, J. S. Ricol, M. Rigan, E. V. Rincón, A. Ritchie-Yates, S. Ritter, D. Rivera, R. Rivera, A. Robert, J. L. Rocabado Rocha, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, J. Rodriguez Rondon, S. Rosauro-Alcaraz, P. Rosier, D. Ross, M. Rossella, M. Rossi, M. Ross-Lonergan, N. Roy, P. Roy, C. Rubbia, A. Ruggeri, G. Ruiz Ferreira, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, S. K. Sahoo, N. Sahu, P. Sala, N. Samios, O. Samoylov, M. C. Sanchez, A. Sánchez Bravo, P. Sanchez-Lucas, V. Sandberg, D. A. Sanders, S. Sanfilippo, D. Sankey, D. Santoro, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, I. Sarra, G. Savage, V. Savinov, G. Scanavini, A. Scaramelli, A. Scarff, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, B. Schuld, A. Segade, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, M. H. Shaevitz, P. Shanahan, P. Sharma, R. Kumar, K. Shaw, T. Shaw, K. Shchablo, J. Shen, C. Shepherd-Themistocleous, A. Sheshukov, W. Shi, S. Shin, S. Shivakoti, I. Shoemaker, D. Shooltz, R. Shrock, B. Siddi, M. Siden, J. Silber, L. Simard, J. Sinclair, G. Sinev, Jaydip Singh, J. Singh, L. Singh, P. Singh, V. Singh, S. Singh Chauhan, R. Sipos, C. Sironneau, G. Sirri, K. Siyeon, K. Skarpaas, J. Smedley, E. Smith, J. Smith, P. Smith, J. Smolik, M. Smy, M. Snape, E. L. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. R. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, A. Sousa, K. Soustruznik, F. Spinella, J. Spitz, N. J. C. Spooner, K. Spurgeon, D. Stalder, M. Stancari, L. Stanco, J. Steenis, R. Stein, H. M. Steiner, A. F. Steklain Lisbôa, A. Stepanova, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. Subash, A. Surdo, L. Suter, C. M. Sutera, K. Sutton, Y. Suvorov, R. Svoboda, S. K. Swain, B. Szczerbinska, A. M. Szelc, A. Sztuc, A. Taffara, N. Talukdar, J. Tamara, H. A. Tanaka, S. Tang, N. Taniuchi, A. M. Tapia Casanova, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, E. Tatar, R. Tayloe, D. Tedeschi, A. M. Teklu, J. Tena Vidal, P. Tennessen, M. Tenti, K. Terao, F. Terranova, G. Testera, T. Thakore, A. Thea, A. Thiebault, S. Thomas, A. Thompson, C. Thorn, S. C. Timm, E. Tiras, V. Tishchenko, N. Todorović, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, D. Tran, R. Travaglini, J. Trevor, E. Triller, S. Trilov, J. Truchon, D. Truncali, W. H. Trzaska, Y. Tsai, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Z. Tu, S. Tufanli, C. Tunnell, J. Turner, M. Tuzi, J. Tyler, E. Tyley, M. Tzanov, M. A. Uchida, J. Ureña González, J. Urheim, T. Usher, H. Utaegbulam, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. F. Valle, R. Van Berg, R. G. Van de Water, D. V. Forero, A. Vannozzi, M. Van Nuland-Troost, F. Varanini, D. Vargas Oliva, S. Vasina, N. Vaughan, K. Vaziri, A. Vázquez-Ramos, J. Vega, S. Ventura, A. Verdugo, S. Vergani, M. Verzocchi, K. Vetter, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, E. Villa, S. Viola, B. Viren, A. Vizcaya-Hernandez, T. Vrba, Q. Vuong, A. V. Waldron, M. Wallbank, J. Walsh, T. Walton, H. Wang, J. Wang, L. Wang, M. H. L. S. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, L. Warsame, M. O. Wascko, D. Waters, A. Watson, K. Wawrowska, A. Weber, C. M. Weber, M. Weber, H. Wei, A. Weinstein, H. Wenzel, S. Westerdale, M. Wetstein, K. Whalen, J. Whilhelmi, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, F. Wilson, R. J. Wilson, P. Winter, W. Wisniewski, J. Wolcott, J. Wolfs, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, M. Wospakrik, K. Wresilo, C. Wret, S. Wu, W. Wu, M. Wurm, J. Wyenberg, Y. Xiao, I. Xiotidis, B. Yaeggy, N. Yahlali, E. Yandel, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, O. Zapata, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, M. Zhao, E. Zhivun, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and on behalf of the DUNE Collaboration
Subjects: neutrino, near detector, Deep Underground Neutrino Experiment, DUNE, Physics, QC1-999, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations.
Published: 2024
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8. Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of NO2 and H2CO at Kinshasa and comparisons with TROPOMI observations

Author: R. Yombo Phaka, A. Merlaud, G. Pinardi, M. M. Friedrich, M. Van Roozendael, J.-F. Müller, T. Stavrakou, I. De Smedt, F. Hendrick, E. Dimitropoulou, R. Bopili Mbotia Lepiba, E. Phuku Phuati, B. L. Djibi, L. Jacobs, C. Fayt, J.-P. Mbungu Tsumbu, and E. Mahieu
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO2 and H2CO tropospheric vertical column densities (VCDtropo) performed for the first time in the city of Kinshasa. These measurements were conducted between November 2019 and July 2021 and processed using the standardized inversion tools developed in the ESA FRM4DOAS (Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations) project. The retrieved geophysical quantities are used to validate column observations from the TROPOspheric Monitoring Instrument (TROPOMI) over Kinshasa. In the validation, we experiment with three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (hourly average of MAX-DOAS VCDtropo at overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of −38 % for NO2 and −39 % for H2CO based on monthly comparison. The second case takes into account the different vertical sensitivities of the two instruments and the a priori profile. We note significant changes in the median bias for both compounds: −12 % for NO2 and +11 % for H2CO. The third case builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a median bias of +44 % for NO2 and a median bias of +4 % for H2CO. However this case is impacted by low sampling and is considered less reliable. The findings from this study underscore the significance of employing a realistic a priori profile in TROPOMI column extraction, particularly within heavily polluted urban zones like Kinshasa. The investigation also highlights the necessity for prudence when integrating the MAX-DOAS line of sight due to the noise generated during subsampling and the limited horizontal sensitivity of MAX-DOAS observations. Importantly, the study further reveals the pronounced pollution levels of NO2, H2CO and aerosols in both the city of Kinshasa and its adjacent regions, underscoring the imperative for consistent monitoring and effective regulatory measures by local authorities.
Published: 2023
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9. Exposure Assessment to Environmental Chemicals in Children from Ciudad Juarez, Chihuahua, Mexico

Author: Ana K. González-Palomo, Ángeles C. Ochoa-Martínez, Arturo Torres-Dosal, Tania Ruíz-Vera, Edna M. Rico-Escobar, Jorge D. Martin Del Campo, Sandra T. Orta-García, Lucia G. Pruneda-Álvarez, Iris G. Piña-Lopez, Leticia Carrizales-Yáñez, and Iván N. Pérez-Maldonado
Subjects: Male, 010504 meteorology & atmospheric sciences, Health, Toxicology and Mutagenesis, chemistry.chemical_element, 010501 environmental sciences, Toxicology, 01 natural sciences, chemistry.chemical_compound, Animal science, Polybrominated diphenyl ethers, Biomonitoring, medicine, Humans, Ecotoxicology, Child, Mexico, 0105 earth and related environmental sciences, Creatinine, medicine.diagnostic_test, Environmental Exposure, General Medicine, Environmental exposure, Pollution, Mercury (element), chemistry, Environmental chemistry, Environmental Pollutants, Female, Blood lead level, Geometric mean
Abstract: It has been demonstrated that the human biomonitoring of susceptible populations is a valuable method for the identification of critical contaminants. Therefore, the purpose of this study was to assess the exposure profile for arsenic (As), lead (Pb), mercury (Hg), 1-hydroxypyrene (1-OHP), 1,1-bis(p-chlorophenyl)-2,2,2-trichloroethane (DDT), 1,1-dichloro-2,2-bis(p-chlorophenyl) ethylene (DDE), polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs) in children living in Ciudad Juarez, Chihuahua, Mexico (a major manufacturing center in Mexico). In 2012, we evaluated a total of 135 healthy children living in Ciudad Juarez since birth. The total PBDEs levels ranged from nondetectable (< LOD) to 215 ng/g lipid, with a mean total PBDEs level of 29.5 ± 53.0 ng/g lipid (geometric mean ± standard deviation). The mean total PCBs level in the study participants was 29.0 ± 10.5 ng/g lipid (range 4.50-50.0 ng/g lipid). The mean concentration of total DDT (DDT + DDE) was 11.9 ± 6.70 ng/g lipid (range 3.00-26.0 ng/g lipid). The mean 1-OHP levels was 1.2 ± 1.1 µmol/mol creatinine (range
Published: 2016
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10. Masquerade syndrome: An eye problem as a manifestation of a more sinister disease

Author: M C, Muñoz Reyes, J M, Romero Requena, Y G, Piña Alcántara, J, Bueno Álvarez-Arenas, and A, Ortiz Cansado
Subjects: Diagnosis, Differential, Male, Uveitis, Choroiditis, Fatal Outcome, Ureteral Neoplasms, Carcinoma, Humans, Hydronephrosis, Syndrome, Middle Aged, Papilledema
Abstract: A middle-aged man with cardiovascular risk factors, who suffered from a slight loss of unilateral vision for 6 months. After obtaining a diagnosis of diffuse choroiditis+papillitis within a probable masquerade syndrome, the patient was referred to outpatient Internal Medicine where this diagnosis was confirmed as an extended neoplastic disease.
Published: 2018

11. Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, C. Adriano, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, F. Akbar, B. Ali-Mohammadzadeh, K. Allison, S. Alonso Monsalve, M. AlRashed, C. Alt, A. Alton, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, S. Antusch, A. Aranda-Fernandez, L. Arellano, L. O. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Ayala Lara, M. Ayala-Torres, F. Azfar, A. Back, H. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, G. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, J. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, E. Belchior Batista das Chagas, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, A. T. Bezerra, T. J. Bezerra, A. Bhardwaj, V. Bhatnagar, M. Bhattacharjee, D. Bhattarai, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. D. M. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, A. Borkum, N. Bostan, P. Bour, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Branca, A. Brandt, J. Bremer, C. Brew, S. J. Brice, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, I. Butorov, I. Cagnoli, T. Cai, D. Caiulo, R. Calabrese, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, A. Caminata, A. Campos Benitez, D. Caratelli, D. Carber, J. M. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, T. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, G. Cavallaro, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, E. Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, M. S. Chavarry Neyra, H. Chen, M. Chen, Y. Chen, Z. Chen, Z. Chen-Wishart, Y. Cheon, D. Cherdack, C. Chi, S. Childress, R. Chirco, A. Chiriacescu, K. Cho, S. Choate, D. Chokheli, P. S. Chong, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, M. Chung, E. Church, V. Cicero, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. Coelho, J. Collot, N. Colton, E. Conley, R. Conley, J. Conrad, M. Convery, S. Copello, P. Cova, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, R. Cross, A. Cudd, C. Cuesta, Y. Cui, D. Cussans, J. Dai, O. Dalager, H. Da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, S. De, P. Debbins, I. De Bonis, M. Decowski, A. De Gouvea, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, V. De Leo, D. Delepine, M. Delgado, A. Dell’Acqua, N. Delmonte, P. De Lurgio, J. R. De Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. W. Deptuch, A. De Roeck, V. De Romeri, G. De Souza, R. Devi, R. Dharmapalan, M. Dias, J. Diaz, F. Díaz, F. Di Capua, A. Di Domenico, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, G. Dirkx, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. Dolinski, L. Domine, Y. Donon, D. Douglas, A. Dragone, G. Drake, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, P. Dunne, B. Dutta, H. Duyang, O. Dvornikov, D. Dwyer, A. Dyshkant, M. Eads, A. Earle, D. Edmunds, J. Eisch, L. Emberger, S. Emery, P. Englezos, A. Ereditato, T. Erjavec, C. Escobar, L. Escudero Sanchez, G. Eurin, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, M. Fani’, C. Farnese, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, P. Fernandez Menendez, F. Ferraro, L. Fields, P. Filip, F. Filthaut, R. Fine, G. Fiorillo, M. Fiorini, V. Fischer, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, S. Fogarty, W. Foreman, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, A. Gabrielli, A. Gago, H. Gallagher, A. Gallas, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, S. Ganguly, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, J. Gauvreau, P. Gauzzi, G. Ge, N. Geffroy, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, P. Giammaria, T. Giammaria, N. Giangiacomi, D. Gibin, I. Gil-Botella, S. Gilligan, C. Girerd, A. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, D. González Caamaño, D. Gonzalez-Diaz, M. Gonzalez-Lopez, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, R. Gran, E. Granados, P. Granger, C. Grant, D. Gratieri, P. Green, S. Green, S. Greenberg, L. Greenler, J. Greer, J. Grenard, C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, E. Guardincerri, V. Guarino, M. Guarise, R. Guenette, E. Guerard, M. Guerzoni, D. Guffanti, A. Guglielmi, B. Guo, A. Gupta, V. Gupta, K. Guthikonda, P. Guzowski, M. M. Guzzo, S. Gwon, C. Ha, K. Haaf, A. Habig, H. Hadavand, R. Haenni, A. Hahn, J. Haiston, P. Hamacher-Baumann, T. Hamernik, P. Hamilton, J. Han, D. A. Harris, J. Hartnell, T. Hartnett, J. Harton, T. Hasegawa, C. Hasnip, R. Hatcher, K. W. Hatfield, A. Hatzikoutelis, C. Hayes, K. Hayrapetyan, J. Hays, E. Hazen, M. He, A. Heavey, K. M. Heeger, J. Heise, S. Henry, M. Hernandez Morquecho, K. Herner, J. Hewes, C. Hilgenberg, T. Hill, S. J. Hillier, A. Himmel, E. Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, I. Hristova, M. S. Hronek, J. Huang, Z. Hulcher, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, F. Jediny, D. Jena, Y. Jeong, C. Jesús-Valls, X. Ji, J. Jiang, L. Jiang, S. Jiménez, A. Jipa, F. Joaquim, W. Johnson, N. Johnston, B. Jones, M. Judah, C. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, F. Kamiya, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, O. Kemularia, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, A. Klustova, T. Kobilarcik, K. Koehler, L. W. Koerner, D. H. Koh, S. Kohn, P. P. Koller, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. Kostelecky, K. Kothekar, R. Kralik, L. Kreczko, F. Krennrich, I. Kreslo, W. Kropp, T. Kroupova, S. Kubota, Y. Kudenko, V. A. Kudryavtsev, S. Kuhlmann, S. Kulagin, J. Kumar, P. Kumar, P. Kunze, R. Kuravi, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, D. Kwak, A. Lambert, B. Land, C. E. Lane, K. Lang, T. Langford, M. Langstaff, J. Larkin, P. Lasorak, D. Last, A. Laundrie, G. Laurenti, A. Lawrence, I. Lazanu, R. LaZur, M. Lazzaroni, T. Le, S. Leardini, J. Learned, P. LeBrun, T. LeCompte, C. Lee, S. Lee, G. Lehmann Miotto, R. Lehnert, M. Leigui de Oliveira, M. Leitner, L. M. Lepin, S. Li, Y. Li, H. Liao, C. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, T. Lord, J. LoSecco, W. C. Louis, X. Lu, K. Luk, B. Lunday, X. Luo, E. Luppi, T. Lux, V. P. Luzio, J. Maalmi, D. MacFarlane, A. Machado, P. Machado, C. Macias, J. Macier, A. Maddalena, A. Madera, P. Madigan, S. Magill, K. Mahn, A. Maio, A. Major, J. A. Maloney, G. Mandrioli, R. C. Mandujano, J. C. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, V. N. Manyam, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, R. Marie, F. Marinho, A. D. Marino, T. Markiewicz, D. Marsden, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martín-Albo, N. Martinez, D. A. Martinez Caicedo, P. Martínez Miravé, S. Martynenko, V. Mascagna, K. Mason, A. Mastbaum, F. Matichard, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, E. Mazzucato, T. McAskill, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, M. Messier, W. Metcalf, M. Mewes, H. Meyer, T. Miao, G. Michna, V. Mikola, R. Milincic, G. Miller, W. Miller, J. Mills, O. Mineev, A. Minotti, O. G. Miranda, S. Miryala, C. Mishra, S. Mishra, A. Mislivec, M. Mitchell, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. A. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, D. Montanino, L. M. Montaño Zetina, S. Moon, M. Mooney, A. F. Moor, D. Moreno, D. Moretti, C. Morris, C. Mossey, M. Mote, E. Motuk, C. A. Moura, J. Mousseau, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, D. Munford, H. Muramatsu, M. Murphy, S. Murphy, J. Musser, J. Nachtman, Y. Nagai, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, A. Nath, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, H. Newton, R. Nichol, F. Nicolas-Arnaldos, A. Nikolica, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, J. Ochoa-Ricoux, A. Olivier, A. Olshevskiy, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, E. Parozzi, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. Peeters, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, V. Pia, F. Piastra, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, K. Plows, R. Plunkett, F. Pompa, X. Pons, N. Poonthottathil, F. Poppi, S. Pordes, J. Porter, S. Porzio, M. Potekhin, R. Potenza, B. V. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, M. Prest, S. Prince, F. Psihas, D. Pugnere, X. Qian, J. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, A. Rakotonandrasana, L. Rakotondravohitra, R. Rameika, M. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Raut, H. Razafinime, R. Razakamiandra, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, A. Renshaw, S. Rescia, F. Resnati, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, L. C. Rice, J. S. Ricol, A. Rigamonti, Y. Rigaut, E. V. Rincón, H. Ritchie-Yates, D. Rivera, A. Robert, J. Rocabado Rocha, L. Rochester, M. Roda, P. Rodrigues, J. V. Rodrigues da Silva Leite, M. J. Rodriguez Alonso, J. Rodriguez Rondon, S. Rosauro-Alcaraz, P. Rosier, B. Roskovec, M. Rossella, M. Rossi, J. Rout, P. Roy, A. Rubbia, C. Rubbia, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, N. Sahu, P. Sala, N. Samios, O. Samoylov, M. Sanchez, V. Sandberg, D. A. Sanders, D. Sankey, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, D. Sgalaberna, M. Shaevitz, S. Shafaq, F. Shaker, M. Shamma, R. Sharankova, H. R. Sharma, R. Sharma, R. K. Sharma, K. Shaw, T. Shaw, K. Shchablo, C. Shepherd-Themistocleous, A. Sheshukov, S. Shin, I. Shoemaker, D. Shooltz, R. Shrock, H. Siegel, L. Simard, J. Sinclair, G. Sinev, J. Singh, L. Singh, P. Singh, V. Singh, R. Sipos, F. Sippach, G. Sirri, A. Sitraka, K. Siyeon, K. Skarpaas, E. Smith, P. Smith, J. Smolik, M. Smy, E. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, F. Soto Ugaldi, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, M. Stancari, L. Stanco, C. Stanford, R. Stein, H. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. Suárez Sunción, H. Sullivan, A. Surdo, V. Susic, L. Suter, C. Sutera, Y. Suvorov, R. Svoboda, B. Szczerbinska, A. M. Szelc, N. Talukdar, H. Tanaka, S. Tang, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, N. Tata, E. Tatar, R. Tayloe, A. Teklu, P. Tennessen, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, T. Thakore, A. Thea, C. Thorn, S. Timm, V. Tishchenko, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, R. Travaglini, J. Trevor, S. Trilov, W. H. Trzaska, Y. Tsai, Z. Tsamalaidze, K. Tsang, N. Tsverava, S. Z. Tu, S. Tufanli, C. Tull, J. Tyler, E. Tyley, M. Tzanov, L. Uboldi, M. A. Uchida, J. Urheim, T. Usher, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. D. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, D. Vannerom, F. Varanini, D. Vargas Oliva, G. Varner, J. Vasel, S. Vasina, G. Vasseur, N. Vaughan, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, C. Wallis, T. Walton, H. Wang, J. Wang, L. Wang, M. H. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, K. Wawrowska, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, W. Wisniewski, J. Wolcott, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, C. Wret, W. Wu, Y. Xiao, B. Yaeggy, E. Yandel, G. Yang, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, Y. Yoon, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and DUNE Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 $$\pm 0.6$$ ± 0.6 % and 84.1 $$\pm 0.6$$ ± 0.6 %, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.
Published: 2023
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12. ENTRAP and its potential interaction with European networks

Author: G. Piña, L. Fuks, J. P. Guisset, S. Steyer, P. Van Iseghem, S. Koivuranta, W. Neckel, C. Lierse, A. Dodaro, H. Tietze Jaensch, E. Vico del Cerro, L. Boucher, L. Van Velzen, Dodaro, Alessandro, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratory of Medical Biophysics, and Faculty of Medicine
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Engineering, safe disposal of radioactive waste, destructive and non-destructive testing of radioactive waste forms, quality assurance of nuclear waste, nuclear-waste characterization, 010504 meteorology & atmospheric sciences, Scope (project management), business.industry, Field (Bourdieu), Radioactive waste, destructive and non-destructive testing of radioactive waste form, 010502 geochemistry & geophysics, 01 natural sciences, Construction engineering, Geochemistry and Petrology, ddc:550, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, business, Quality assurance, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: ENTRAP comprises a pan-European cooperation of leading scientific institutions and regulatory bodies in the field of nuclear-waste characterization and its quality assurance for the safe disposal of radioactive waste. Here, the scope of this cooperation is presented and explained and links or interfaces for a potential collaboration with partners fulfilling tasks of IDG-TP are pursued.
Published: 2015
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13. Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns

Author: K. L. Chan, P. Valks, K.-P. Heue, R. Lutz, P. Hedelt, D. Loyola, G. Pinardi, M. Van Roozendael, F. Hendrick, T. Wagner, V. Kumar, A. Bais, A. Piters, H. Irie, H. Takashima, Y. Kanaya, Y. Choi, K. Park, J. Chong, A. Cede, U. Frieß, A. Richter, J. Ma, N. Benavent, R. Holla, O. Postylyakov, C. Rivera Cárdenas, and M. Wenig
Subjects: Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract: We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.
Published: 2023
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14. Characterization of errors in satellite-based HCHO ∕ NO2 tropospheric column ratios with respect to chemistry, column-to-PBL translation, spatial representation, and retrieval uncertainties

Author: A. H. Souri, M. S. Johnson, G. M. Wolfe, J. H. Crawford, A. Fried, A. Wisthaler, W. H. Brune, D. R. Blake, A. J. Weinheimer, T. Verhoelst, S. Compernolle, G. Pinardi, C. Vigouroux, B. Langerock, S. Choi, L. Lamsal, L. Zhu, S. Sun, R. C. Cohen, K.-E. Min, C. Cho, S. Philip, X. Liu, and K. Chance
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO2) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO2 + RO2 (LROx) to the chemical loss of NOx (LNOx). Subsequently, we challenge the predictive power of HCHO/NO2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LROx/LNOx. FNRs show a strongly linear (R2=0.94) relationship with LROx/LNOx, but only on the logarithmic scale. Following the baseline (i.e., ln(LROx/LNOx) = −1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NOx-sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the ROx–HOx cycle. We calculate high ozone production rates (PO3) dominated by large HCHO × NO2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO3 and HCHO × NO2 becomes more pronounced when moving towards NOx-sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km2). A pixel with a grid size of 216 km2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO2 columns, should be above 1.2–1.5 × 1016 molec. cm−2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric.
Published: 2023
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15. Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble

Author: J. Douros, H. Eskes, J. van Geffen, K. F. Boersma, S. Compernolle, G. Pinardi, A.-M. Blechschmidt, V.-H. Peuch, A. Colette, and P. Veefkind
Subjects: Geology, QE1-996.5
Abstract: The Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument, launched in October 2017, provides unique observations of atmospheric trace gases at a high resolution of about 5 km, with near-daily global coverage, resolving individual sources like thermal powerplants, industrial complexes, fires, medium-scale towns, roads, and shipping routes. Even though Sentinel-5P (S5P) is a global mission, these datasets are especially well suited to test high-resolution regional-scale air quality (AQ) models and provide valuable input for emission inversion systems. In Europe, the Copernicus Atmosphere Monitoring Service (CAMS) has implemented an operational regional AQ forecasting capability based on an ensemble of several European models, available at a resolution of 0.1∘ × 0.1∘. In this paper, we present comparisons between TROPOMI observations of nitrogen dioxide (NO2) and the CAMS AQ forecasts and analyses of NO2. We discuss the different ways of making these comparisons and present quantitative results in the form of maps for individual days, summer and winter months, and a time series for European subregions and cities between May 2018 and March 2021. The CAMS regional products generally capture the fine-scale daily and averaged features observed by TROPOMI in much detail. In summer, the comparison shows a close agreement between TROPOMI and the CAMS ensemble NO2 tropospheric columns with a relative difference of up to 15 % for most European cities. In winter, however, we find a significant discrepancy in the column amounts over much of Europe, with relative differences up to 50 %. The possible causes for these differences are discussed, focusing on the possible impact of retrieval and modeling errors. Apart from comparisons with the CAMS ensemble, we also present results for comparisons with the individual CAMS models for selected months. Furthermore, we demonstrate the importance of the free tropospheric contribution to the estimation of the tropospheric column and thus include profile information from the CAMS configuration of the ECMWF's (European Centre for Medium-Range Weather Forecasts) global integrated model above 3 km altitude in the comparisons. We also show that replacing the global 1∘ × 1∘ a priori information in the retrieval by the regional 0.1∘ × 0.1∘ resolution profiles of CAMS leads to significant changes in the TROPOMI-retrieved tropospheric column, with typical increases at the emission hotspots up to 30 % and smaller increases or decreases elsewhere. As a spinoff, we present a new TROPOMI NO2 level 2 (L2) data product for Europe, based on the replacement of the original TM5-MP generated global a priori profile by the regional CAMS ensemble profile. This European NO2 product is compared with ground-based remote sensing measurements of six Pandora instruments of the Pandonia Global Network and nine Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments. As compared to the standard S5P tropospheric NO2 column data, the overall bias of the new product for all except two stations is 5 % to 12 % smaller, owing to a reduction in the multiplicative bias. Compared to the CAMS tropospheric NO2 columns, dispersion and correlation parameters with respect to the standard data are, however, superior.
Published: 2023
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16. Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. AlRashed, C. Alt, A. Alton, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, S. Antusch, A. Aranda-Fernandez, L. Arellano, L. O. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Ayala Lara, M. Ayala-Torres, F. Azfar, M. Babicz, A. Back, H. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, G. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, E. Batista das Chagas, J. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, C. Beigbeder, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, T. S. Bezerra, A. Bhardwaj, V. Bhatnagar, M. Bhattacharjee, D. Bhattarai, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. Blaszczyk, G. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, M. Bongrand, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, A. Borkum, N. Bostan, P. Bour, C. Bourgeois, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Branca, A. Brandt, J. Bremer, D. Breton, C. Brew, S. J. Brice, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, I. Butorov, I. Cagnoli, T. Cai, D. Caiulo, R. Calabrese, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, A. Caminata, M. Campanelli, D. Caratelli, D. Carber, J. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, T. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, G. Cavallaro, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, E. Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, M. Chavarry Neyra, H. Chen, M. Chen, Y. Chen, Z. Chen, Z. Chen-Wishart, Y. Cheon, D. Cherdack, C. Chi, S. Childress, R. Chirco, A. Chiriacescu, G. Chisnall, K. Cho, S. Choate, D. Chokheli, P. S. Chong, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, M. Chung, E. Church, V. Cicero, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. Coelho, N. Colton, E. Conley, R. Conley, J. Conrad, M. Convery, S. Copello, P. Cova, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, R. Cross, A. Cudd, C. Cuesta, Y. Cui, D. Cussans, O. Dalager, H. Da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, S. De, P. Debbins, I. De Bonis, M. Decowski, A. De Gouvea, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, N. Delmonte, P. De Lurgio, J. R. De Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. W. Deptuch, A. De Roeck, V. De Romeri, G. De Souza, R. Devi, R. Dharmapalan, M. Dias, F. Diaz, J. Diaz, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, G. Dirkx, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. Dolinski, L. Domine, Y. Donon, D. Douglas, D. Douillet, A. Dragone, G. Drake, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, P. Dunne, B. Dutta, H. Duyang, O. Dvornikov, D. Dwyer, A. Dyshkant, M. Eads, A. Earle, D. Edmunds, J. Eisch, L. Emberger, S. Emery, P. Englezos, A. Ereditato, T. Erjavec, C. Escobar, G. Eurin, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, M. Fani’, C. Farnese, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, P. Fernandez Menendez, M. Fernandez Morales, F. Ferraro, L. Fields, P. Filip, F. Filthaut, M. Fiorini, V. Fischer, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, S. Fogarty, W. Foreman, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, F. Fuentes Robayo, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, A. Gabrielli, A. Gago, H. Gallagher, A. Gallas, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, R. Gandrajula, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, J. Gauvreau, G. Ge, N. Geffroy, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, P. Giammaria, T. Giammaria, N. Giangiacomi, D. Gibin, I. Gil-Botella, S. Gilligan, C. Girerd, A. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, D. Gonzalez-Diaz, M. Gonzalez-Lopez, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, R. Gran, E. Granados, P. Granger, A. Grant, C. Grant, D. Gratieri, P. Green, L. Greenler, J. Greer, J. Grenard, C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, E. Guardincerri, V. Guarino, M. Guarise, R. Guenette, E. Guerard, M. Guerzoni, D. Guffanti, A. Guglielmi, B. Guo, A. Gupta, V. Gupta, K. Guthikonda, R. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, C. Ha, K. Haaf, A. Habig, H. Hadavand, R. Haenni, A. Hahn, J. Haiston, P. Hamacher-Baumann, T. Hamernik, P. Hamilton, J. Han, D. A. Harris, J. Hartnell, T. Hartnett, J. Harton, T. Hasegawa, C. Hasnip, R. Hatcher, K. W. Hatfield, A. Hatzikoutelis, C. Hayes, K. Hayrapetyan, J. Hays, E. Hazen, M. He, A. Heavey, K. M. Heeger, J. Heise, S. Henry, M. Hernandez Morquecho, K. Herner, J. Hewes, C. Hilgenberg, T. Hill, S. J. Hillier, A. Himmel, E. Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, J. Hoyos, I. Hristova, M. S. Hronek, J. Huang, Z. Hulcher, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, F. Jediny, D. Jena, Y. Jeong, C. Jesús-Valls, X. Ji, L. Jiang, S. Jiménez, A. Jipa, R. Johnson, W. Johnson, N. Johnston, B. Jones, S. Jones, M. Judah, C. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, F. Kamiya, N. Kaneshige, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, O. Kemularia, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, A. Klustova, T. Kobilarcik, K. Koehler, L. W. Koerner, D. H. Koh, S. Kohn, P. P. Koller, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. Kostelecky, K. Kothekar, R. Kralik, L. Kreczko, F. Krennrich, I. Kreslo, W. Kropp, T. Kroupova, S. Kubota, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, P. Kumar, P. Kunze, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, D. Kwak, A. Lambert, B. Land, C. E. Lane, K. Lang, T. Langford, M. Langstaff, J. Larkin, P. Lasorak, D. Last, A. Laundrie, G. Laurenti, A. Lawrence, I. Lazanu, R. LaZur, M. Lazzaroni, T. Le, S. Leardini, J. Learned, P. LeBrun, T. LeCompte, C. Lee, S. Lee, G. Lehmann Miotto, R. Lehnert, M. Leigui de Oliveira, M. Leitner, L. M. Lepin, S. Li, Y. Li, H. Liao, C. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, T. Lord, J. LoSecco, W. C. Louis, X. Lu, K. Luk, B. Lunday, X. Luo, E. Luppi, T. Lux, V. P. Luzio, J. Maalmi, D. MacFarlane, A. Machado, P. Machado, C. Macias, J. Macier, A. Maddalena, A. Madera, P. Madigan, S. Magill, K. Mahn, A. Maio, A. Major, J. A. Maloney, G. Mandrioli, R. C. Mandujano, J. C. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, V. N. Manyam, L. Manzanillas, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, R. Marie, F. Marinho, A. D. Marino, D. Marsden, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martin-Albo, N. Martinez, D. A. Martinez Caicedo, P. Martínez Miravé, S. Martynenko, V. Mascagna, K. Mason, A. Mastbaum, F. Matichard, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, E. Mazzucato, T. McAskill, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, M. Messier, W. Metcalf, T. Mettler, M. Mewes, H. Meyer, T. Miao, G. Michna, T. Miedema, V. Mikola, R. Milincic, G. Miller, W. Miller, J. Mills, O. Mineev, A. Minotti, O. G. Miranda, S. Miryala, C. Mishra, S. Mishra, A. Mislivec, M. Mitchell, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. A. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, L. M. Montano Zetina, S. Moon, M. Mooney, A. F. Moor, D. Moreno, D. Moretti, C. Morris, C. Mossey, M. Mote, E. Motuk, C. A. Moura, J. Mousseau, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, D. Munford, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, A. Nath, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, H. Newton, R. Nichol, F. Nicolas-Arnaldos, A. Nikolica, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, J. Ochoa-Ricoux, A. Olivier, A. Olshevskiy, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, E. Parozzi, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. Peeters, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, V. Pia, F. Piastra, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, K. Plows, R. Plunkett, R. Poling, F. Pompa, X. Pons, N. Poonthottathil, F. Poppi, S. Pordes, J. Porter, M. Potekhin, R. Potenza, B. V. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, M. Prest, S. Prince, F. Psihas, D. Pugnere, X. Qian, J. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, A. Rakotonandrasana, L. Rakotondravohitra, R. Rameika, M. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Raut, R. Razakamiandra, E. Rea, J. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, A. Renshaw, S. Rescia, F. Resnati, A. Reynolds, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, L. C. Rice, J. Ricol, A. Rigamonti, Y. Rigaut, E. V. Rincón, H. Ritchie-Yates, D. Rivera, A. Robert, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, E. Rodriguez Bonilla, J. Rodriguez Rondon, S. Rosauro-Alcaraz, M. Rosenberg, P. Rosier, B. Roskovec, M. Rossella, M. Rossi, J. Rout, P. Roy, A. Rubbia, C. Rubbia, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, T. Safford, N. Sahu, P. Sala, N. Samios, O. Samoylov, M. Sanchez, V. Sandberg, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, A. Sergi, D. Sgalaberna, M. Shaevitz, S. Shafaq, F. Shaker, M. Shamma, R. Sharankova, H. R. Sharma, R. Sharma, R. K. Sharma, T. Shaw, K. Shchablo, C. Shepherd-Themistocleous, A. Sheshukov, S. Shin, I. Shoemaker, D. Shooltz, R. Shrock, H. Siegel, L. Simard, J. Sinclair, G. Sinev, J. Singh, L. Singh, P. Singh, V. Singh, R. Sipos, F. Sippach, G. Sirri, A. Sitraka, K. Siyeon, K. Skarpaas, A. Smith, E. Smith, P. Smith, J. Smolik, M. Smy, E. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, F. Soto Ugaldi, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, M. Stancari, L. Stanco, C. Stanford, D. Stefan, R. Stein, H. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. Suárez Sunción, R. Sulej, H. Sullivan, D. Summers, A. Surdo, V. Susic, L. Suter, C. Sutera, R. Svoboda, B. Szczerbinska, A. M. Szelc, H. Tanaka, S. Tang, A. Tapia, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, N. Tata, E. Tatar, R. Tayloe, A. Teklu, P. Tennessen, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, T. Thakore, A. Thea, J. L. Thompson, C. Thorn, S. Timm, V. Tishchenko, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, R. Travaglini, J. Trevor, S. Trilov, W. H. Trzaska, Y. Tsai, Z. Tsamalaidze, K. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, L. Uboldi, M. A. Uchida, J. Urheim, T. Usher, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, D. Vannerom, F. Varanini, D. Vargas, G. Varner, J. Vasel, S. Vasina, G. Vasseur, N. Vaughan, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, C. Wallis, H. Wang, J. Wang, L. Wang, M. H. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, K. Wawrowska, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, W. Wisniewski, J. Wolcott, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, C. Wret, W. Wu, Y. Xiao, F. Xie, B. Yaeggy, E. Yandel, G. Yang, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, Y. Yoon, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, and R. Zwaska
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.
Published: 2022
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17. Horizontal distribution of tropospheric NO2 and aerosols derived by dual-scan multi-wavelength multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in Uccle, Belgium

Author: E. Dimitropoulou, F. Hendrick, M. M. Friedrich, F. Tack, G. Pinardi, A. Merlaud, C. Fayt, C. Hermans, F. Fierens, and M. Van Roozendael
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Dual-scan ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric nitrogen dioxide (NO2) and aerosols were carried out in Uccle (50.8∘ N, 4.35∘ E; Brussels region, Belgium) for 2 years from March 2018 to February 2020. The MAX-DOAS instrument operated in both UV and visible wavelength ranges in a dual-scan configuration consisting of two submodes: (1) an elevation scan in a fixed viewing azimuthal direction and (2) an azimuthal scan in a fixed low elevation angle (2∘). By analyzing the O4 and NO2 differential slant column density (dSCD) at six different wavelength intervals along every azimuthal direction and by applying a new optimal-estimation-based inversion approach (the so-called mapping MAX-DOAS technique), the horizontal distribution of the NO2 near-surface concentrations and vertical column densities (VCDs) as well as the aerosol near-surface extinction coefficients are retrieved along 10 azimuthal directions. The retrieved horizontal NO2 concentration profiles allow the identification of the main NO2 hotspots in the Brussels area. Correlative comparisons of the retrieved horizontal NO2 distribution were conducted with airborne, mobile, air quality model, and satellite datasets, and overall good agreement is found. The comparison with TROPOMI observations from operational and scientific data products reveals that the characterization of the horizontal distribution of tropospheric NO2 VCDs by ground-based measurements and an adequate a priori NO2 profile shape in TROPOMI retrievals lead to better consistency between satellite and ground-based datasets.
Published: 2022
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18. Radiochemical analysis of chlorine-36

Author: G. Piña, M. Rodríguez, and E. Lara
Subjects: Materials science, Radiochemistry, Chlorine-36, Liquid scintillation counting, Isotopes of chlorine, Radioactive waste, chemistry.chemical_element, General Physics and Astronomy, Contamination, Nuclear physics, chemistry, Scintillation counter, Chlorine, Ion-exchange resin
Abstract: The radioactive chlorine isotope, 36Cl, decays with a half-life of 3×105 years by emitting a beta particle (98 %) and by electron capture. The aim of this paper is to propose a radiochemical separation method of 36Cl from the other beta-gamma emitters present in low and medium radioactive wastes such as spent ion exchange resins and evaporator concentrates, that arise from Nuclear Power Plants and particularly in the wastes that come from decommissioning activities of graphite reactors, in order to provide data for 36Cl inventory calculations. The separation method proposed is based on an oxidation technique where chlorine is trapped by NaOH. 36Cl beta emissions are measured by liquid scintillation counting by the dual label technique in order to avoid the contamination produced by 14C which is also trapped by NaOH and which is the main contaminant present in graphite samples. The sensitivity of this method is sufficient to achieve the needed thresholds for the radiological characterization of the radioactive materials to which this method can be applied.
Published: 2006
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19. Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. AlRashed, C. Alt, A. Alton, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, S. Antusch, A. Aranda-Fernandez, L. Arellano, L. O. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Ayala Lara, M. Ayala-Torres, F. Azfar, A. Back, H. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, P. Barham Alzas, G. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, E. Batista das Chagas, J. B. R. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. L. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, C. Beigbeder, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, T. J. C. Bezerra, A. Bhardwaj, V. Bhatnagar, M. Bhattacharjee, D. Bhattarai, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, M. Bongrand, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, A. Borkum, N. Bostan, P. Bour, C. Bourgeois, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Branca, A. Brandt, J. Bremer, D. Breton, C. Brew, S. J. Brice, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, I. Butorov, I. Cagnoli, T. Cai, D. Caiulo, R. Calabrese, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, A. Caminata, M. Campanelli, D. Caratelli, D. Carber, J. C. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, T. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, G. Cavallaro, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, E. Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, M. S. S. Chavarry Neyra, H. Chen, M. Chen, Y. Chen, Z. Chen, Z. Chen-Wishart, Y. Cheon, D. Cherdack, C. Chi, S. Childress, R. Chirco, A. Chiriacescu, G. Chisnall, K. Cho, S. Choate, D. Chokheli, P. S. Chong, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, M. Chung, E. Church, V. Cicero, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. A. B. Coelho, N. Colton, E. Conley, R. Conley, J. Conrad, M. Convery, S. Copello, P. Cova, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, R. Cross, A. Cudd, C. Cuesta, Y. Cui, D. Cussans, O. Dalager, H. da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, S. De, P. Debbins, I. De Bonis, M. P. Decowski, A. De Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, N. Delmonte, P. De Lurgio, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. W. Deptuch, A. De Roeck, V. De Romeri, G. De Souza, R. Devi, R. Dharmapalan, M. Dias, F. Diaz, J. S. Díaz, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, G. Dirkx, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. Dolinski, L. Domine, Y. Donon, D. Douglas, D. Douillet, A. Dragone, G. Drake, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, P. Dunne, B. Dutta, H. Duyang, O. Dvornikov, D. Dwyer, A. Dyshkant, M. Eads, A. Earle, D. Edmunds, J. Eisch, L. Emberger, S. Emery, P. Englezos, A. Ereditato, T. Erjavec, C. Escobar, G. Eurin, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, M. Fani’, C. Farnese, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, P. Fernandez Menendez, M. Fernandez Morales, F. Ferraro, L. Fields, P. Filip, F. Filthaut, M. Fiorini, V. Fischer, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, S. Fogarty, W. Foreman, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, F. Fuentes Robayo, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, A. Gabrielli, A. Gago, H. Gallagher, A. Gallas, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, R. Gandrajula, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, J. Gauvreau, G. Ge, N. Geffroy, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, P. Giammaria, T. Giammaria, N. Giangiacomi, D. Gibin, I. Gil-Botella, S. Gilligan, C. Girerd, A. K. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. V. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, D. Gonzalez-Diaz, M. Gonzalez-Lopez, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, R. Gran, E. Granados, P. Granger, A. Grant, C. Grant, D. Gratieri, P. Green, L. Greenler, J. Greer, J. Grenard, W. C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, E. Guardincerri, V. Guarino, M. Guarise, R. Guenette, E. Guerard, M. Guerzoni, D. Guffanti, A. Guglielmi, B. Guo, A. Gupta, V. Gupta, K. K. Guthikonda, R. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, C. Ha, K. Haaf, A. Habig, H. Hadavand, R. Haenni, A. Hahn, J. Haiston, P. Hamacher-Baumann, T. Hamernik, P. Hamilton, J. Han, D. A. Harris, J. Hartnell, T. Hartnett, J. Harton, T. Hasegawa, C. Hasnip, R. Hatcher, K. W. Hatfield, A. Hatzikoutelis, C. Hayes, K. Hayrapetyan, J. Hays, E. Hazen, M. He, A. Heavey, K. M. Heeger, J. Heise, S. Henry, M. A. Hernandez Morquecho, K. Herner, J. Hewes, C. Hilgenberg, T. Hill, S. J. Hillier, A. Himmel, E. Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, J. Hoyos, I. Hristova, M. S. Hronek, J. Huang, Z. Hulcher, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, F. Jediny, D. Jena, Y. S. Jeong, C. Jesús-Valls, X. Ji, L. Jiang, S. Jiménez, A. Jipa, R. Johnson, W. Johnson, N. Johnston, B. Jones, S. Jones, M. Judah, C. K. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, F. Kamiya, N. Kaneshige, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, O. Kemularia, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, A. Klustova, T. Kobilarcik, K. Koehler, L. W. Koerner, D. H. Koh, S. Kohn, P. P. Koller, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, R. Kralik, L. Kreczko, F. Krennrich, I. Kreslo, W. Kropp, T. Kroupova, S. Kubota, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, P. Kumar, P. Kunze, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, D. Kwak, A. Lambert, B. Land, C. E. Lane, K. Lang, T. Langford, M. Langstaff, J. Larkin, P. Lasorak, D. Last, A. Laundrie, G. Laurenti, A. Lawrence, I. Lazanu, R. LaZur, M. Lazzaroni, T. Le, S. Leardini, J. Learned, P. LeBrun, T. LeCompte, C. Lee, S. Y. Lee, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, L. M. Lepin, S. W. Li, Y. Li, H. Liao, C. S. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, T. Lord, J. M. LoSecco, W. C. Louis, X.-G. Lu, K. B. Luk, B. Lunday, X. Luo, E. Luppi, T. Lux, V. P. Luzio, J. Maalmi, D. MacFarlane, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, A. Maddalena, A. Madera, P. Madigan, S. Magill, K. Mahn, A. Maio, A. Major, J. A. Maloney, G. Mandrioli, R. C. Mandujano, J. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, V. N. Manyam, L. Manzanillas, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, R. Marie, F. Marinho, A. D. Marino, D. Marsden, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martín-Albo, N. Martinez, D. A. Martinez Caicedo, P. Martínez Miravé, S. Martynenko, V. Mascagna, K. Mason, A. Mastbaum, F. Matichard, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, E. Mazzucato, T. McAskill, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, M. D. Messier, W. Metcalf, T. Mettler, M. Mewes, H. Meyer, T. Miao, G. Michna, T. Miedema, V. Mikola, R. Milincic, G. Miller, W. Miller, J. Mills, O. Mineev, A. Minotti, O. G. Miranda, S. Miryala, C. S. Mishra, S. R. Mishra, A. Mislivec, M. Mitchell, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, L. M. Montañno Zetina, S. H. Moon, M. Mooney, A. F. Moor, D. Moreno, D. Moretti, C. Morris, C. Mossey, M. Mote, E. Motuk, C. A. Moura, J. Mousseau, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, D. Munford, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, A. Nath, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, H. Newton, R. Nichol, F. Nicolas-Arnaldos, A. Nikolica, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, J. Ochoa-Ricoux, A. Olivier, A. Olshevskiy, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, E. Parozzi, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. J. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. M. Peeters, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. G. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, V. Pia, F. Piastra, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, K. Plows, R. Plunkett, R. Poling, F. Pompa, X. Pons, N. Poonthottathil, F. Poppi, S. Pordes, J. Porter, M. Potekhin, R. Potenza, B. V. K. S. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, M. Prest, S. Prince, F. Psihas, D. Pugnere, X. Qian, J. L. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, A. Rakotonandrasana, L. Rakotondravohitra, R. Rameika, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Raut, R. F. Razakamiandra, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, A. Renshaw, S. Rescia, F. Resnati, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, L. C. J. Rice, J. S. Ricol, A. Rigamonti, Y. Rigaut, E. V. Rincón, H. Ritchie-Yates, D. Rivera, A. Robert, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, E. Rodriguez Bonilla, J. Rodriguez Rondon, S. Rosauro-Alcaraz, M. Rosenberg, P. Rosier, B. Roskovec, M. Rossella, M. Rossi, J. Rout, P. Roy, A. Rubbia, C. Rubbia, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, T. Safford, N. Sahu, K. Sakashita, P. Sala, N. Samios, O. Samoylov, M. C. Sanchez, V. Sandberg, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, A. Sergi, D. Sgalaberna, M. H. Shaevitz, S. Shafaq, F. Shaker, M. Shamma, R. Sharankova, H. R. Sharma, R. Sharma, R. K. Sharma, T. Shaw, K. Shchablo, C. Shepherd-Themistocleous, A. Sheshukov, S. Shin, I. Shoemaker, D. Shooltz, R. Shrock, H. Siegel, L. Simard, J. Sinclair, G. Sinev, J. Singh, L. Singh, P. Singh, V. Singh, R. Sipos, F. W. Sippach, G. Sirri, A. Sitraka, K. Siyeon, K. Skarpaas, A. Smith, E. Smith, P. Smith, J. Smolik, M. Smy, E. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. R. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, F. A. Soto Ugaldi, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, M. Stancari, L. Stanco, C. Stanford, R. Stein, H. M. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. M. Suárez Sunción, H. Sullivan, D. Summers, A. Surdo, V. Susic, L. Suter, C. M. Sutera, R. Svoboda, B. Szczerbinska, A. M. Szelc, H. Tanaka, S. Tang, A. Tapia, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, N. Tata, E. Tatar, R. Tayloe, A. M. Teklu, P. Tennessen, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, T. Thakore, A. Thea, J. L. Thompson, C. Thorn, S. C. Timm, V. Tishchenko, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, R. Travaglini, J. Trevor, S. Trilov, W. H. Trzaska, Y. Tsai, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, L. Uboldi, M. A. Uchida, J. Urheim, T. Usher, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. D. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. F. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, D. Vannerom, F. Varanini, D. Vargas Oliva, G. Varner, J. Vasel, S. Vasina, G. Vasseur, N. Vaughan, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, C. Wallis, H. Wang, J. Wang, L. Wang, M. H. L. S. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, M. O. Wascko, D. Waters, A. Watson, K. Wawrowska, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, W. Wisniewski, J. Wolcott, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, C. Wret, W. Wu, Y. Xiao, F. Xie, B. Yaeggy, E. Yandel, G. Yang, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, Y. S. Yoon, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and DUNE Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $$\times $$ × 6 $$\times $$ × 6 m $$^3$$ 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.
Published: 2022
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20. Ground-based validation of the MetOp-A and MetOp-B GOME-2 OClO measurements

Author: G. Pinardi, M. Van Roozendael, F. Hendrick, A. Richter, P. Valks, R. Alwarda, K. Bognar, U. Frieß, J. Granville, M. Gu, P. Johnston, C. Prados-Roman, R. Querel, K. Strong, T. Wagner, F. Wittrock, and M. Yela Gonzalez
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: This paper reports on ground-based validation of the atmospheric OClO data record produced within the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC SAF) using the Global Ozone Monitoring Experiment (GOME)-2A and GOME-2B instrument measurements, covering the 2007–2016 and 2013–2016 periods, respectively. OClO slant column densities are compared to correlative measurements collected from nine Zenith-Scattered-Light Differential Optical Absorption Spectroscopy (ZSL-DOAS) instruments from the Network for the Detection of Atmospheric Composition Change (NDACC) distributed in both the Arctic and Antarctic. Sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings. On this basis, we infer systematic uncertainties of about 25 % (i.e., about 3.75×1013 molec. cm−2) between the different ground-based data analyses, reaching total uncertainties ranging from about 26 % to 33 % for the different stations (i.e., around 4 to 5×1013 molec. cm−2). Time series at the different sites show good agreement between satellite and ground-based data for both the inter-annual variability and the overall OClO seasonal behavior. GOME-2A results are found to be noisier than those of GOME-2B, especially after 2011, probably due to instrumental degradation effects. Daily linear regression analysis for OClO-activated periods yield correlation coefficients of 0.8 for GOME-2A and 0.87 for GOME-2B, with slopes with respect to the ground-based data ensemble of 0.64 and 0.72, respectively. Satellite minus ground-based offsets are within 8×1013 molec. cm−2, with some differences between GOME-2A and GOME-2B depending on the station. Overall, considering all the stations, a median offset of about -2.2×1013 molec. cm−2 is found for both GOME-2 instruments.
Published: 2022
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21. Radiochemical analysis of 93Zr

Author: G. Piña, M. Rodríguez, A.G. Espartero, and José Antonio Suárez
Subjects: chemistry.chemical_compound, Radiation, Stripping (chemistry), Chemistry, Liquid–liquid extraction, Yield (chemistry), Extraction (chemistry), Liquid scintillation counting, Radiochemistry, Xylene, Isotopes of zirconium, Nuclear chemistry, Neutron activation
Abstract: The zirconium isotope 93 Zr is a long-lived pure β -particle-emitting radionuclide, which is produced by nuclear fission and neutron activation of the stable isotope 92 Zr. This element is a constituent of the structural components of nuclear reactor vessels. A selective liquid–liquid extraction method for radiochemical separation of Zr, based on liquid–liquid extraction with 1-(2′-thenoyl)-3,3,3-trifluoroacetone in xylene and a subsequent stripping of 93 Zr by an aqueous acid solution, has been developed. The method was utilised to separate Zr from other pure β -particle and β – γ emitters in different kinds of samples. Decontamination factors higher than 99% for the pure β -particle and β – γ emitters and an overall chemical yield of 80% were obtained. The sensitivity of the method allows the determination of the isolated 93 Zr by liquid scintillation counting and the minimum detectable activity value obtained was 0.067 Bq over a counting period of 60 min.
Published: 2002
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22. Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data

Author: J. van Geffen, H. Eskes, S. Compernolle, G. Pinardi, T. Verhoelst, J.-C. Lambert, M. Sneep, M. ter Linden, A. Ludewig, K. F. Boersma, and J. P. Veefkind
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Nitrogen dioxide (NO2) is one of the main data products measured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite, which combines a high signal-to-noise ratio with daily global coverage and high spatial resolution. TROPOMI provides a valuable source of information to monitor emissions from local sources such as power plants, industry, cities, traffic and ships, and variability of these sources in time. Validation exercises of NO2 v1.2–v1.3 data, however, have revealed that TROPOMI's tropospheric vertical column densities (VCDs) are too low by up to 50 % over highly polluted areas. These findings are mainly attributed to biases in the cloud pressure retrieval, the surface albedo climatology and the low resolution of the a priori profiles derived from global simulations of the TM5-MP chemistry model. This study describes improvements in the TROPOMI NO2 retrieval leading to version v2.2, operational since 1 July 2021. Compared to v1.x, the main changes are the following. (1) The NO2-v2.2 data are based on version-2 level-1b (ir)radiance spectra with improved calibration, which results in a small and fairly homogeneous increase in the NO2 slant columns of 3 % to 4 %, most of which ends up as a small increase in the stratospheric columns. (2) The cloud pressures are derived with a new version of the FRESCO cloud retrieval already introduced in NO2-v1.4, which led to a lowering of the cloud pressure, resulting in larger tropospheric NO2 columns over polluted scenes with a small but non-zero cloud coverage. (3) For cloud-free scenes a surface albedo correction is introduced based on the observed reflectance, which also leads to a general increase in the tropospheric NO2 columns over polluted scenes of order 15 %. (4) An outlier removal was implemented in the spectral fit, which increases the number of good-quality retrievals over the South Atlantic Anomaly region and over bright clouds where saturation may occur. (5) Snow/ice information is now obtained from ECMWF weather data, increasing the number of valid retrievals at high latitudes. On average the NO2-v2.2 data have tropospheric VCDs that are between 10 % and 40 % larger than the v1.x data, depending on the level of pollution and season; the largest impact is found at mid and high latitudes in wintertime. This has brought these tropospheric NO2 closer to Ozone Monitoring Instrument (OMI) observations. Ground-based validation shows on average an improvement of the negative bias of the stratospheric (from −6 % to −3 %), tropospheric (from −32 % to −23 %) and total (from −12 % to −5 %) columns. For individual measurement stations, however, the picture is more complex, in particular for the tropospheric and total columns.
Published: 2022
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23. Radiochemical analysis of 41Ca and 45Ca

Author: M. Rodríguez, G. Piña, A.G. Espartero, and José Antonio Suárez
Subjects: Radionuclide, Radiochemistry, Radiation, Stable isotope ratio, Chemistry, Calcium Radioisotopes, Liquid scintillation counting, Chlorine-36, Radioactive waste, Human decontamination, Nuclear reactor, Beta Particles, law.invention, Neutron capture, Gamma Rays, law
Abstract: The radioactive isotopes of calcium, 41Ca ( t 1/2 =1.03×10 5 yr ) and 45Ca ( t 1/2 =163 d ), are produced by neutron capture in the stable isotopes 40Ca and 44Ca, respectively. These radionuclides are present in the environment due to the reactions between the galactic cosmic rays and the earth's surface, and in nuclear power plants by the activation of the structural components of nuclear reactor vessels. The aim of this paper is to propose a radiochemical separation method of 41Ca and 45Ca from the other beta–gamma emitters present in radioactive materials, based on selective precipitation reactions. The activities were measured by liquid scintillation counting (LSC). The obtained decontamination factors are satisfactory for each radioactive component of the initial sample in that their activities in the final product were lower than the minimum detectable activity (MDA) due to the effectiveness of the radiochemical procedure. The sensitivity of the method allows the radiological characterization of 41Ca and 45Ca content in radioactive materials.
Published: 2000
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24. Qualification tests of coatings for inner walls in a BWR reactor

Author: M. Balcazar, L. Rojas, L. Tavera, and G. Piña-Villalpando
Subjects: Fission products, Radiation, Nuclear engineering, Radiochemistry, Uranium dioxide, Radioactive waste, Human decontamination, Particle detector, chemistry.chemical_compound, Petrochemical, chemistry, Boiling water reactor, Research reactor, Instrumentation
Abstract: Qualification tests of coatings for inner walls in a Boiling Water Reactor (BWR) were performed under request for decontamination purposes. Several types of coatings were contaminated with fission products obtained from a UO 2 solution irradiated in a nuclear research reactor, afterwards a successive decontamination process according with standards based on γ activity was applied. In each decontamination stage, α and γ activity measurements were made on the probes. Results obtained for α activity using nuclear track detectors are presented as an alternative assessment method during the decontamination process.
Published: 1999
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25. Radon decay products attached to clothes in a nuclear laboratory

Author: M. Balcázar, G. Piña-Villalpando, A. Chávez, M. Alfaro, and D. Mendoza
Subjects: Radiation, Chemistry, Radiochemistry, Radon Decay Products, chemistry.chemical_element, Radon, Radon chamber, Whole body, Instrumentation, Radioactive decay
Abstract: A whole body counter determined the presence of radioactivities up to 21.8 kBq for 214Bi and up to 18.7 kBq for 214Pb attached to clothes of workers in a Nuclear Research Laboratory. A radon survey reveals that 80% of the monitoring areas have radon concentration values lower than 500 Bq m−3, while 10% of the sampling points with values bigger than 1 kBq m−3 correspond to the workers mentioned above. By exposing samples of 0.04 m2 clothes in a radon chamber, it was observed that radon decay products 214Bi and 214Pb were attached to them with an activity of 315–618 Bq per each kBq m−3 of Rn concentration additionally, fibres characterised with a lower electrostatics build up showed the lower attachment.
Published: 1999
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26. Development and application of a radioactivity characterization system for low-level radioactive waste

Author: A.G. Espartero, G Piña, and José Antonio Suárez
Subjects: Physics, Nuclear and High Energy Physics, Measurement method, Range (particle radiation), Silicon, Attenuation, Radiochemistry, Radioactive waste, chemistry.chemical_element, Characterization (materials science), Correction algorithm, chemistry, Electromagnetic shielding, Instrumentation
Abstract: Low-level technological radioactive wastes, in Spain, are commonly produced in research and medical centers. These wastes must be characterized before conditioning in order to determine their radioactive content for inventory purposes. A prototype has been designed for beta–gamma radiological characterization of standardized 25 l bags containing heterogeneous low-density technological radioactive wastes within the density range 0.05–0.6 g/cm 3 . The system consists of an iron shielding box with three NaI(Tl) and a silicon implanted detectors for gamma and gross beta activity determinations, respectively. The study of the measurement method, carried out with rotating scanning, included the optimization of the detection solid angle to minimize the uncertainties and the influence of the relative position of the radioactive material. Several materials and densities, in the range aforementioned, were considered to obtain the experimental attenuation factors, used for fitting a correction algorithm in function of density and γ-emission energy. The sensitivity of this method, calculated for the most frequent average density of this kind of waste (0.1 g/cm 3 ), is lower than 50 Bq/kg for the main β – γ emitters ( 137 Cs and 60 Co) and lower than 480 Bq/kg for gross beta activity.
Published: 1999
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27. An improved TROPOMI tropospheric NO2 research product over Europe

Author: S. Liu, P. Valks, G. Pinardi, J. Xu, K. L. Chan, A. Argyrouli, R. Lutz, S. Beirle, E. Khorsandi, F. Baier, V. Huijnen, A. Bais, S. Donner, S. Dörner, M. Gratsea, F. Hendrick, D. Karagkiozidis, K. Lange, A. J. M. Piters, J. Remmers, A. Richter, M. Van Roozendael, T. Wagner, M. Wenig, and D. G. Loyola
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.
Published: 2021
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28. Dose distribution studies of a gamma industrial irradiator using a PC code

Author: D.P. Sloan and G. Piña-Villalpando
Subjects: Physics, Radiation, Dosimeter, business.industry, Dose distribution, Computational physics, symbols.namesake, Absorbed dose, Code (cryptography), symbols, Gaussian quadrature, Dosimetry, Irradiation, Cobalt-60, Nuclear medicine, business
Abstract: This paper present a comparison between calculated and experimental absorbed dose values, for a typical product, irradiated in a 60 Co industrial irradiator, at ININ. Such industrial irradiator is two tiers and two layer systems, with overlapping product to source configuration; source activity was around 300 kCi. Calculated absorbed dose values were obtained by FUGI code, running in a PC microcomputer. This code is based in a point kernel over the source area, by means of Gauss quadrature technique, based in FUDGE-4A code. Build-up factors were estimated by Goldstein and Wilkins factors for punctual sources, using Taylor's approximation formula. Experimental dosimetry data of Petri dishes packages, with apparent density of 0.13 g/cm 3 data was performed using red acrylic dosimeters, during irradiation; required minimum dose for this material was 15 kGy. Absorbed dose data have shown good approximation, particulary a 15% desviation of results from FUGI code. However, this code can be used for rough calculation of irradiator parameters, before trying to use a more complex and time-consuming code, for detailed analysis.
Published: 1998
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29. Testing of an active alphameter unit in a radon generating chamber

Author: A. Chávez, G. Piña-Villalpando, and M. Balcázar
Subjects: Waiting time, Radiation, Chemistry, Nuclear engineering, Detector, Radiochemistry, Detection performance, chemistry.chemical_element, Radon chamber, Radon, Instrumentation, Atmospheric emissions
Abstract: A controlled radon chamber was used to test the detection performance of a portable active radon detector. The elapsed time to reach detection equilibrium with the radon atmosphere was three hours; the radon detector was sensitive to daily temperature changes. After using the radon detector three hours waiting time is required to place it in a new radon environment.
Published: 1997
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30. Use of computer code for dose distribution studies in A 60CO industrial irradiator

Author: D.P. Sloan and G. Piña-Villalpando
Subjects: Radiation, Source code, business.industry, media_common.quotation_subject, Pellets, Value (computer science), Computational physics, Geometric progression, Product (mathematics), Absorbed dose, Dosimetry, Irradiation, Nuclear medicine, business, media_common, Mathematics
Abstract: This paper presents a benchmark comparison between calculated and experimental absorbed dose values tor a typical product, in a 60 Co industrial irradiator, located at ININ, Mexico. The irradiator is a two levels, two layers system with overlapping product configuration with activity around 300kCi. Experimental values were obtanied from routine dosimetry, using red acrylic pellets. Typical product was Petri dishes packages, apparent density 0.13 g/cm 3 ; that product was chosen because uniform size, large quantity and low density. Minimum dose was fixed in 15 kGy. Calculated values were obtained from QAD-CGGP code. This code uses a point kernel technique, build-up factors fitting was done by geometrical progression and combinatorial geometry is used for system description. Main modifications for the code were related with source sumilation, using punctual sources instead of pencils and an energy and anisotropic emission spectrums were included. Results were, for maximum dose, calculated value (18.2 kGy) was 8% higher than experimental average value (16.8 kGy); for minimum dose, calculated value (13.8 kGy) was 3% higher than experimental average value (14.3 kGy).
Published: 1995
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31. Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements

Author: I. De Smedt, G. Pinardi, C. Vigouroux, S. Compernolle, A. Bais, N. Benavent, F. Boersma, K.-L. Chan, S. Donner, K.-U. Eichmann, P. Hedelt, F. Hendrick, H. Irie, V. Kumar, J.-C. Lambert, B. Langerock, C. Lerot, C. Liu, D. Loyola, A. Piters, A. Richter, C. Rivera Cárdenas, F. Romahn, R. G. Ryan, V. Sinha, N. Theys, J. Vlietinck, T. Wagner, T. Wang, H. Yu, and M. Van Roozendael
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5 × 5.5 km2. This paper assesses the performances of the TROPOMI formaldehyde (HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30 % in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns (larger than 5 × 1015 molec. cm−2) the median bias between OMI and TROPOMI HCHO columns is not larger than 10 % (< 0.4 × 1015 molec. cm−2). For lower columns, OMI observations present a remaining positive bias of about 20 % (< 0.8 × 1015 molec. cm−2) compared to TROPOMI in midlatitude regions. Here, we also use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020), where a global FTIR (Fourier transform infrared) network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (−25 % for HCHO columns larger than 8 × 1015 molec. cm−2), while no significant bias is found for medium-range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25 % for individual pixels and by up to a factor of 3 when considering daily averages in 20 km radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors (5 years) and opens new perspectives to study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical interactions.
Published: 2021
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32. Neutron spectra profile in beam ports of a triga mark III experimental reactor

Author: M. Balcázar, L. Tavera, A. Delfin, R. Mazon, M.E. Camacho, and G. Piña
Subjects: chemistry.chemical_compound, Materials science, Lithium borate, chemistry, Neutron flux, Nuclear engineering, Radiochemistry, General Engineering, Neutron cross section, Neutron spectra, Research reactor, Beam (structure), TRIGA
Abstract: Fluences data profile inside four beam tubes at a nuclear research reactor has been using activation foils together with CR39 plastic detectors covered with lithium borate converter, to obtain discrete and continuous neutron fluence measurements.
Published: 1993
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33. Radon detection system, design, test and performance

Author: A. Chávez, M. Navarrete, M. Balcázar, and G. Piña-Villalpando
Subjects: Battery (electricity), Time delay and integration, Physics, Nuclear and High Energy Physics, Data processing, business.product_category, Temperature control, Photovoltaic system, Real-time computing, chemistry.chemical_element, Radon, Surface coating, chemistry, Laptop, business, Instrumentation
Abstract: A portable radon detection system (α-Inin) has been designed and constructed for using it in adverse environmental conditions where humidity, temperature and chemical vaporous are present. The minimum integration time is in periods of 15 min during 41 days. A 12 V battery and a photovoltaic module allow the α-Inin autonomy in field measurements. Data is collected by means of a laptop computer where data processing and α-Inin programming are carried out. α-Inin performance was simultaneously tested in a controlled radon chamber, together with a commercial α-Meter.
Published: 1999
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34. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign

Author: J.-L. Tirpitz, U. Frieß, F. Hendrick, C. Alberti, M. Allaart, A. Apituley, A. Bais, S. Beirle, S. Berkhout, K. Bognar, T. Bösch, I. Bruchkouski, A. Cede, K. L. Chan, M. den Hoed, S. Donner, T. Drosoglou, C. Fayt, M. M. Friedrich, A. Frumau, L. Gast, C. Gielen, L. Gomez-Martín, N. Hao, A. Hensen, B. Henzing, C. Hermans, J. Jin, K. Kreher, J. Kuhn, J. Lampel, A. Li, C. Liu, H. Liu, J. Ma, A. Merlaud, E. Peters, G. Pinardi, A. Piters, U. Platt, O. Puentedura, A. Richter, S. Schmitt, E. Spinei, D. Stein Zweers, K. Strong, D. Swart, F. Tack, M. Tiefengraber, R. van der Hoff, M. van Roozendael, T. Vlemmix, J. Vonk, T. Wagner, Y. Wang, Z. Wang, M. Wenig, M. Wiegner, F. Wittrock, P. Xie, C. Xing, J. Xu, M. Yela, C. Zhang, and X. Zhao
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (the Netherlands) in September 2016 with the aim of assessing the consistency of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, long-path DOAS, direct-sun DOAS, Sun photometer and meteorological instruments). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations, with the focus on aerosol optical thicknesses (AOTs), trace gas vertical column densities (VCDs) and trace gas surface concentrations. The algorithms are based on three different techniques: six use the optimal estimation method, two use a parameterized approach and one algorithm relies on simplified radiative transport assumptions and analytical calculations. To assess the agreement among the inversion algorithms independent of inconsistencies in the trace gas slant column density acquisition, participants applied their inversion to a common set of slant columns. Further, important settings like the retrieval grid, profiles of O3, temperature and pressure as well as aerosol optical properties and a priori assumptions (for optimal estimation algorithms) have been prescribed to reduce possible sources of discrepancies. The profiling results were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions; however, these are sometimes at different altitudes and of different magnitudes. Under clear-sky conditions, the root-mean-square differences (RMSDs) among the results of individual participants are in the range of 0.01–0.1 for AOTs, (1.5–15) ×1014molec.cm-2 for trace gas (NO2, HCHO) VCDs and (0.3–8)×1010molec.cm-3 for trace gas surface concentrations. These values compare to approximate average optical thicknesses of 0.3, trace gas vertical columns of 90×1014molec.cm-2 and trace gas surface concentrations of 11×1010molec.cm-3 observed over the campaign period. The discrepancies originate from differences in the applied techniques, the exact implementation of the algorithms and the user-defined settings that were not prescribed. For the comparison against supporting observations, the RMSDs increase to a range of 0.02–0.2 against AOTs from the Sun photometer, (11–55)×1014molec.cm-2 against trace gas VCDs from direct-sun DOAS observations and (0.8–9)×1010molec.cm-3 against surface concentrations from the long-path DOAS instrument. This increase in RMSDs is most likely caused by uncertainties in the supporting data, spatiotemporal mismatch among the observations and simplified assumptions particularly on aerosol optical properties made for the MAX-DOAS retrieval. As a side investigation, the comparison was repeated with the participants retrieving profiles from their own differential slant column densities (dSCDs) acquired during the campaign. In this case, the consistency among the participants degrades by about 30 % for AOTs, by 180 % (40 %) for HCHO (NO2) VCDs and by 90 % (20 %) for HCHO (NO2) surface concentrations. In former publications and also during this comparison study, it was found that MAX-DOAS vertically integrated aerosol extinction coefficient profiles systematically underestimate the AOT observed by the Sun photometer. For the first time, it is quantitatively shown that for optimal estimation algorithms this can be largely explained and compensated by considering biases arising from the reduced sensitivity of MAX-DOAS observations to higher altitudes and associated a priori assumptions.
Published: 2021
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35. Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author: T. Verhoelst, S. Compernolle, G. Pinardi, J.-C. Lambert, H. J. Eskes, K.-U. Eichmann, A. M. Fjæraa, J. Granville, S. Niemeijer, A. Cede, M. Tiefengraber, F. Hendrick, A. Pazmiño, A. Bais, A. Bazureau, K. F. Boersma, K. Bognar, A. Dehn, S. Donner, A. Elokhov, M. Gebetsberger, F. Goutail, M. Grutter de la Mora, A. Gruzdev, M. Gratsea, G. H. Hansen, H. Irie, N. Jepsen, Y. Kanaya, D. Karagkiozidis, R. Kivi, K. Kreher, P. F. Levelt, C. Liu, M. Müller, M. Navarro Comas, A. J. M. Piters, J.-P. Pommereau, T. Portafaix, C. Prados-Roman, O. Puentedura, R. Querel, J. Remmers, A. Richter, J. Rimmer, C. Rivera Cárdenas, L. Saavedra de Miguel, V. P. Sinyakov, W. Stremme, K. Strong, M. Van Roozendael, J. P. Veefkind, T. Wagner, F. Wittrock, M. Yela González, and C. Zehner
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.
Published: 2021
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36. Assessment of the TROPOMI tropospheric NO2 product based on airborne APEX observations

Author: F. Tack, A. Merlaud, M.-D. Iordache, G. Pinardi, E. Dimitropoulou, H. Eskes, B. Bomans, P. Veefkind, and M. Van Roozendael
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Sentinel-5 Precursor (S-5P), launched in October 2017, carrying the TROPOspheric Monitoring Instrument (TROPOMI) nadir-viewing spectrometer, is the first mission of the Copernicus Programme dedicated to the monitoring of air quality, climate, and ozone. In the presented study, the TROPOMI tropospheric nitrogen dioxide (NO2) level-2 (L2) product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) has been validated over strongly polluted urban regions by comparison with coincident high-resolution Airborne Prism EXperiment (APEX) remote sensing observations (∼ 75 m × 120 m). Satellite products can be optimally assessed based on (APEX) airborne remote sensing observations, as a large amount of satellite pixels can be fully mapped at high accuracy and in a relatively short time interval, reducing the impact of spatiotemporal mismatches. In the framework of the S-5P validation campaign over Belgium (S5PVAL-BE), the APEX imaging spectrometer has been deployed during four mapping flights (26–29 June 2019) over the two largest urban regions in Belgium, i.e. Brussels and Antwerp, in order to map the horizontal distribution of tropospheric NO2. For each flight, 10 to 20 TROPOMI pixels were fully covered by approximately 2700 to 4000 APEX measurements within each TROPOMI pixel. The TROPOMI and APEX NO2 vertical column density (VCD) retrieval schemes are similar in concept. Overall, for the ensemble of the four flights, the standard TROPOMI NO2 VCD product is well correlated (R = 0.92) but biased negatively by −1.2 ± 1.2 × 1015 molec cm−2 or −14 ± 12 %, on average, with respect to coincident APEX NO2 retrievals. When replacing the coarse 1∘ × 1∘ the massively parallel (MP) version of the Tracer Model version 5 (TM5) a priori NO2 profiles by NO2 profile shapes from the Copernicus Atmospheric Monitoring Service (CAMS) regional chemistry transport model (CTM) ensemble at 0.1∘ × 0.1∘, R is 0.94 and the slope increases from 0.82 to 0.93. The bias is reduced to −0.1 ± 1.0 × 1015 molec cm−2 or −1.0 ± 12 %. The absolute difference is on average 1.3 × 1015 molec cm−2 (16 %) and 0.7 × 1015 molec cm−2 (9 %), when comparing APEX NO2 VCDs with TM5-MP-based and CAMS-based NO2 VCDs, respectively. Both sets of retrievals are well within the mission accuracy requirement of a maximum bias of 25 %–50 % for the TROPOMI tropospheric NO2 product for all individual compared pixels. Additionally, the APEX data set allows the study of TROPOMI subpixel variability and impact of signal smoothing due to its finite satellite pixel size, typically coarser than fine-scale gradients in the urban NO2 field. For a case study in the Antwerp region, the current TROPOMI data underestimate localized enhancements and overestimate background values by approximately 1–2 × 1015 molec cm−2 (10 %–20 %).
Published: 2021
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37. Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations

Author: G. Pinardi, M. Van Roozendael, F. Hendrick, N. Theys, N. Abuhassan, A. Bais, F. Boersma, A. Cede, J. Chong, S. Donner, T. Drosoglou, A. Dzhola, H. Eskes, U. Frieß, J. Granville, J. R. Herman, R. Holla, J. Hovila, H. Irie, Y. Kanaya, D. Karagkiozidis, N. Kouremeti, J.-C. Lambert, J. Ma, E. Peters, A. Piters, O. Postylyakov, A. Richter, J. Remmers, H. Takashima, M. Tiefengraber, P. Valks, T. Vlemmix, T. Wagner, and F. Wittrock
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.
Published: 2020
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38. Validation of TROPOMI tropospheric NO2 columns using dual-scan multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in Uccle, Brussels

Author: E. Dimitropoulou, F. Hendrick, G. Pinardi, M. M. Friedrich, A. Merlaud, F. Tack, H. De Longueville, C. Fayt, C. Hermans, Q. Laffineur, F. Fierens, and M. Van Roozendael
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of aerosols and tropospheric nitrogen dioxide (NO2) were carried out in Uccle (50.8∘ N, 4.35∘ E), Brussels, during 1 year from March 2018 until March 2019. The instrument was operated in both the UV and visible wavelength ranges in a dual-scan configuration consisting of two sub-modes: (1) an elevation scan in a fixed viewing azimuthal direction (the so-called main azimuthal direction) pointing to the northeast and (2) an azimuthal scan in a fixed low elevation angle (2∘). By applying a vertical profile inversion algorithm in the main azimuthal direction and a parameterization technique in the other azimuthal directions, near-surface NO2 volume mixing ratios (VMRs) and vertical column densities (VCDs) were retrieved in 10 different azimuthal directions. The dual-scan MAX-DOAS dataset allows for partly resolving the horizontal distribution of NO2 around the measurement site and studying its seasonal variations. Furthermore, we show that measuring the tropospheric NO2 VCDs in different azimuthal directions improves the spatial colocation with measurements from the Sentinel-5 Precursor (S5P), leading to a reduction of the spread in validation results. By using NO2 vertical profile information derived from the MAX-DOAS measurements, we also resolve a systematic underestimation in S5P NO2 data due to the use of inadequate a priori NO2 profile shape data in the satellite retrieval.
Published: 2020
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39. Satellite validation strategy assessments based on the AROMAT campaigns

Author: A. Merlaud, L. Belegante, D.-E. Constantin, M. Den Hoed, A. C. Meier, M. Allaart, M. Ardelean, M. Arseni, T. Bösch, H. Brenot, A. Calcan, E. Dekemper, S. Donner, S. Dörner, M. C. Balanica Dragomir, L. Georgescu, A. Nemuc, D. Nicolae, G. Pinardi, A. Richter, A. Rosu, T. Ruhtz, A. Schönhardt, D. Schuettemeyer, R. Shaiganfar, K. Stebel, F. Tack, S. Nicolae Vâjâiac, J. Vasilescu, J. Vanhamel, T. Wagner, and M. Van Roozendael
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: The Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns took place in Romania in September 2014 and August 2015. They focused on two sites: the Bucharest urban area and large power plants in the Jiu Valley. The main objectives of the campaigns were to test recently developed airborne observation systems dedicated to air quality studies and to verify their applicability for the validation of space-borne atmospheric missions such as the TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P). We present the AROMAT campaigns from the perspective of findings related to the validation of tropospheric NO2, SO2, and H2CO. We also quantify the emissions of NOx and SO2 at both measurement sites. We show that tropospheric NO2 vertical column density (VCD) measurements using airborne mapping instruments are well suited for satellite validation in principle. The signal-to-noise ratio of the airborne NO2 measurements is an order of magnitude higher than its space-borne counterpart when the airborne measurements are averaged at the TROPOMI pixel scale. However, we show that the temporal variation of the NO2 VCDs during a flight might be a significant source of comparison error. Considering the random error of the TROPOMI tropospheric NO2 VCD (σ), the dynamic range of the NO2 VCDs field extends from detection limit up to 37 σ (2.6×1016 molec. cm−2) and 29 σ (2×1016 molec. cm−2) for Bucharest and the Jiu Valley, respectively. For both areas, we simulate validation exercises applied to the TROPOMI tropospheric NO2 product. These simulations indicate that a comparison error budget closely matching the TROPOMI optimal target accuracy of 25 % can be obtained by adding NO2 and aerosol profile information to the airborne mapping observations, which constrains the investigated accuracy to within 28 %. In addition to NO2, our study also addresses the measurements of SO2 emissions from power plants in the Jiu Valley and an urban hotspot of H2CO in the centre of Bucharest. For these two species, we conclude that the best validation strategy would consist of deploying ground-based measurement systems at well-identified locations.
Published: 2020
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40. Validation of Aura-OMI QA4ECV NO2 climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

Author: S. Compernolle, T. Verhoelst, G. Pinardi, J. Granville, D. Hubert, A. Keppens, S. Niemeijer, B. Rino, A. Bais, S. Beirle, F. Boersma, J. P. Burrows, I. De Smedt, H. Eskes, F. Goutail, F. Hendrick, A. Lorente, A. Pazmino, A. Piters, E. Peters, J.-P. Pommereau, J. Remmers, A. Richter, J. van Geffen, M. Van Roozendael, T. Wagner, and J.-C. Lambert
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 Pmolec.cm-2 (5 %–10 %) and a dispersion of 0.2 to 1 Pmolec.cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec.cm-2) up to −10 Pmolec.cm-2 (−40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec.cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.
Published: 2020
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41. TROPOMI–Sentinel-5 Precursor formaldehyde validation using an extensive network of ground-based Fourier-transform infrared stations

Author: C. Vigouroux, B. Langerock, C. A. Bauer Aquino, T. Blumenstock, Z. Cheng, M. De Mazière, I. De Smedt, M. Grutter, J. W. Hannigan, N. Jones, R. Kivi, D. Loyola, E. Lutsch, E. Mahieu, M. Makarova, J.-M. Metzger, I. Morino, I. Murata, T. Nagahama, J. Notholt, I. Ortega, M. Palm, G. Pinardi, A. Röhling, D. Smale, W. Stremme, K. Strong, R. Sussmann, Y. Té, M. van Roozendael, P. Wang, and H. Winkler
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: TROPOMI (the TROPOspheric Monitoring Instrument), on board the Sentinel-5 Precursor (S5P) satellite, has been monitoring the Earth's atmosphere since October 2017 with an unprecedented horizontal resolution (initially 7 km2×3.5 km2, upgraded to 5.5 km2×3.5 km2 in August 2019). Monitoring air quality is one of the main objectives of TROPOMI; it obtains measurements of important pollutants such as nitrogen dioxide, carbon monoxide, and formaldehyde (HCHO). In this paper we assess the quality of the latest HCHO TROPOMI products versions 1.1.(5-7), using ground-based solar-absorption FTIR (Fourier-transform infrared) measurements of HCHO from 25 stations around the world, including high-, mid-, and low-latitude sites. Most of these stations are part of the Network for the Detection of Atmospheric Composition Change (NDACC), and they provide a wide range of observation conditions, from very clean remote sites to those with high HCHO levels from anthropogenic or biogenic emissions. The ground-based HCHO retrieval settings have been optimized and harmonized at all the stations, ensuring a consistent validation among the sites. In this validation work, we first assess the accuracy of TROPOMI HCHO tropospheric columns using the median of the relative differences between TROPOMI and FTIR ground-based data (BIAS). The pre-launch accuracy requirements of TROPOMI HCHO are 40 %–80 %. We observe that these requirements are well reached, with the BIAS found below 80 % at all the sites and below 40 % at 20 of the 25 sites. The provided TROPOMI systematic uncertainties are well in agreement with the observed biases at most of the stations except for the highest-HCHO-level site, where it is found to be underestimated. We find that while the BIAS has no latitudinal dependence, it is dependent on the HCHO concentration levels: an overestimation (+26±5 %) of TROPOMI is observed for very low HCHO levels (<2.5×1015 molec. cm−2), while an underestimation (-30.8%±1.4 %) is found for high HCHO levels (>8.0×1015 molec. cm−2). This demonstrates the great value of such a harmonized network covering a wide range of concentration levels, the sites with high HCHO concentrations being crucial for the determination of the satellite bias in the regions of emissions and the clean sites allowing a small TROPOMI offset to be determined. The wide range of sampled HCHO levels within the network allows the robust determination of the significant constant and proportional TROPOMI HCHO biases (TROPOMI =+1.10±0.05 ×1015+0.64±0.03 × FTIR; in molecules per square centimetre). Second, the precision of TROPOMI HCHO data is estimated by the median absolute deviation (MAD) of the relative differences between TROPOMI and FTIR ground-based data. The clean sites are especially useful for minimizing a possible additional collocation error. The precision requirement of 1.2×1016 molec. cm−2 for a single pixel is reached at most of the clean sites, where it is found that the TROPOMI precision can even be 2 times better (0.5–0.8×1015 molec. cm−2 for a single pixel). However, we find that the provided TROPOMI random uncertainties may be underestimated by a factor of 1.6 (for clean sites) to 2.3 (for high HCHO levels). The correlation is very good between TROPOMI and FTIR data (R=0.88 for 3 h mean coincidences; R=0.91 for monthly means coincidences). Using about 17 months of data (from May 2018 to September 2019), we show that the TROPOMI seasonal variability is in very good agreement at all of the FTIR sites. The FTIR network demonstrates the very good quality of the TROPOMI HCHO products, which is well within the pre-launch requirements for both accuracy and precision. This paper makes suggestions for the refinement of the TROPOMI random uncertainty budget and TROPOMI quality assurance values for a better filtering of the remaining outliers.
Published: 2020
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42. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2

Author: K. Kreher, M. Van Roozendael, F. Hendrick, A. Apituley, E. Dimitropoulou, U. Frieß, A. Richter, T. Wagner, J. Lampel, N. Abuhassan, L. Ang, M. Anguas, A. Bais, N. Benavent, T. Bösch, K. Bognar, A. Borovski, I. Bruchkouski, A. Cede, K. L. Chan, S. Donner, T. Drosoglou, C. Fayt, H. Finkenzeller, D. Garcia-Nieto, C. Gielen, L. Gómez-Martín, N. Hao, B. Henzing, J. R. Herman, C. Hermans, S. Hoque, H. Irie, J. Jin, P. Johnston, J. Khayyam Butt, F. Khokhar, T. K. Koenig, J. Kuhn, V. Kumar, C. Liu, J. Ma, A. Merlaud, A. K. Mishra, M. Müller, M. Navarro-Comas, M. Ostendorf, A. Pazmino, E. Peters, G. Pinardi, M. Pinharanda, A. Piters, U. Platt, O. Postylyakov, C. Prados-Roman, O. Puentedura, R. Querel, A. Saiz-Lopez, A. Schönhardt, S. F. Schreier, A. Seyler, V. Sinha, E. Spinei, K. Strong, F. Tack, X. Tian, M. Tiefengraber, J.-L. Tirpitz, J. van Gent, R. Volkamer, M. Vrekoussis, S. Wang, Z. Wang, M. Wenig, F. Wittrock, P. H. Xie, J. Xu, M. Yela, C. Zhang, and X. Zhao
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.
Published: 2020
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43. Comparison of tropospheric NO2 columns from MAX-DOAS retrievals and regional air quality model simulations

Author: A.-M. Blechschmidt, J. Arteta, A. Coman, L. Curier, H. Eskes, G. Foret, C. Gielen, F. Hendrick, V. Marécal, F. Meleux, J. Parmentier, E. Peters, G. Pinardi, A. J. M. Piters, M. Plu, A. Richter, A. Segers, M. Sofiev, Á. M. Valdebenito, M. Van Roozendael, J. Vira, T. Vlemmix, and J. P. Burrows
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Multi-axis differential optical absorption spectroscopy (MAX-DOAS) tropospheric NO2 column retrievals from four European measurement stations are compared to simulations from five regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model evaluation, MAX-DOAS data are closer to the regional model data in terms of horizontal and vertical resolution, and multiple measurements are available during daylight, so that, for example, diurnal cycles of trace gases can be investigated. In general, there is good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 35 % and 70 % for individual models and 45 % to 75 % for the ensemble median for tropospheric NO2 vertical column densities (VCDs), indicating that emissions, transport and tropospheric chemistry of NOx are on average well simulated. However, large differences are found for individual pollution plumes observed by MAX-DOAS. Most of the models overestimate seasonal cycles for the majority of MAX-DOAS sites investigated. At the urban stations, weekly cycles are reproduced well, but the decrease towards the weekend is underestimated and diurnal cycles are overall not well represented. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals, and models fail to reproduce observed changes in diurnal cycles for weekdays versus weekends. The results of this study show that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.
Published: 2020
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44. Evaluating different methods for elevation calibration of MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) instruments during the CINDI-2 campaign

Author: S. Donner, J. Kuhn, M. Van Roozendael, A. Bais, S. Beirle, T. Bösch, K. Bognar, I. Bruchkouski, K. L. Chan, S. Dörner, T. Drosoglou, C. Fayt, U. Frieß, F. Hendrick, C. Hermans, J. Jin, A. Li, J. Ma, E. Peters, G. Pinardi, A. Richter, S. F. Schreier, A. Seyler, K. Strong, J.-L. Tirpitz, Y. Wang, P. Xie, J. Xu, X. Zhao, and T. Wagner
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: We present different methods for in-field elevation calibration of MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) instruments that were applied and inter-compared during the second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2). One necessary prerequisite of consistent MAX-DOAS retrievals is a precise and accurate calibration of the elevation angles of the different measuring systems. Therefore, different methods for this calibration were applied to several instruments during the campaign, and the results were inter-compared. This work first introduces and explains the different methods, namely far- and near-lamp measurements, white-stripe scans, horizon scans and sun scans, using data and results for only one (mainly the Max Planck Institute for Chemistry) instrument. In the second part, the far-lamp measurements and the horizon scans are examined for all participating groups. Here, the results for both methods are first inter-compared for the different instruments; secondly, the two methods are compared amongst each other. All methods turned out to be well-suited for the calibration of the elevation angles of MAX-DOAS systems, with each of them having individual advantages and drawbacks. Considering the results of this study, the systematic uncertainties of the methods can be estimated as ±0.05∘ for the far-lamp measurements and the sun scans, ±0.25∘ for the horizon scans, and around ±0.1∘ for the white-stripe and near-lamp measurements. When comparing the results of far-lamp and horizon-scan measurements, a spread of around 0.9∘ in the elevation calibrations is found between the participating instruments for both methods. This spread is of the order of a typical field of view (FOV) of a MAX-DOAS instrument and therefore affecting the retrieval results. Further, consistent (wavelength dependent) offsets of 0.32∘ and 0.40∘ between far-lamp measurements and horizon scans are found, which can be explained by the fact that, despite the flat topography around the measurement site, obstacles such as trees might mark the visible horizon during daytime. The observed wavelength dependence can be explained by surface albedo effects. Lastly, the results are discussed and recommendations for future campaigns are given.
Published: 2020
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45. An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

Author: S. Liu, P. Valks, G. Pinardi, J. Xu, A. Argyrouli, R. Lutz, L. G. Tilstra, V. Huijnen, F. Hendrick, and M. Van Roozendael
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94.
Published: 2020
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46. Radiological Characterisation of Low- And Medium-Level Nuclear Wastes

Author: G. Piña, José Antonio Suárez, A.G. Espartero, M. Rodríguez, and J. L. Gascón
Subjects: Waste management, business.industry, Radiological weapon, Final product, Environmental science, Nuclear power, business
Abstract: Low- and medium-level nuclear wastes are generated mainly in the operation of nuclear power plants. The radiological characterisation of these wastes is required during their treatment and conditioning as well as during their storage as a final product in drums. Such requirements make it possible to know the radioactive content for radionuclide-inventory purposes in the final repository.
Published: 2000
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47. Is a scaling factor required to obtain closure between measured and modelled atmospheric O4 absorptions? An assessment of uncertainties of measurements and radiative transfer simulations for 2 selected days during the MAD-CAT campaign

Author: T. Wagner, S. Beirle, N. Benavent, T. Bösch, K. L. Chan, S. Donner, S. Dörner, C. Fayt, U. Frieß, D. García-Nieto, C. Gielen, D. González-Bartolome, L. Gomez, F. Hendrick, B. Henzing, J. L. Jin, J. Lampel, J. Ma, K. Mies, M. Navarro, E. Peters, G. Pinardi, O. Puentedura, J. Puķīte, J. Remmers, A. Richter, A. Saiz-Lopez, R. Shaiganfar, H. Sihler, M. Van Roozendael, Y. Wang, and M. Yela
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: In this study the consistency between MAX-DOAS measurements and radiative transfer simulations of the atmospheric O4 absorption is investigated on 2 mainly cloud-free days during the MAD-CAT campaign in Mainz, Germany, in summer 2013. In recent years several studies indicated that measurements and radiative transfer simulations of the atmospheric O4 absorption can only be brought into agreement if a so-called scaling factor () is applied to the measured O4 absorption. However, many studies, including those based on direct sunlight measurements, came to the opposite conclusion, that there is no need for a scaling factor. Up to now, there is no broad consensus for an explanation of the observed discrepancies between measurements and simulations. Previous studies inferred the need for a scaling factor from the comparison of the aerosol optical depths derived from MAX-DOAS O4 measurements with that derived from coincident sun photometer measurements. In this study a different approach is chosen: the measured O4 absorption at 360 nm is directly compared to the O4 absorption obtained from radiative transfer simulations. The atmospheric conditions used as input for the radiative transfer simulations were taken from independent data sets, in particular from sun photometer and ceilometer measurements at the measurement site. This study has three main goals: first all relevant error sources of the spectral analysis, the radiative transfer simulations and the extraction of the input parameters used for the radiative transfer simulations are quantified. One important result obtained from the analysis of synthetic spectra is that the O4 absorptions derived from the spectral analysis agree within 1 % with the corresponding radiative transfer simulations at 360 nm. Based on the results from sensitivity studies, recommendations for optimised settings for the spectral analysis and radiative transfer simulations are given. Second, the measured and simulated results are compared for 2 selected cloud-free days with similar aerosol optical depths but very different aerosol properties. On 18 June, measurements and simulations agree within their (rather large) uncertainties (the ratio of simulated and measured O4 absorptions is found to be 1.01±0.16). In contrast, on 8 July measurements and simulations significantly disagree: for the middle period of that day the ratio of simulated and measured O4 absorptions is found to be 0.82±0.10, which differs significantly from unity. Thus, for that day a scaling factor is needed to bring measurements and simulations into agreement. Third, recommendations for further intercomparison exercises are derived. One important recommendation for future studies is that aerosol profile data should be measured at the same wavelengths as the MAX-DOAS measurements. Also, the altitude range without profile information close to the ground should be minimised and detailed information on the aerosol optical and/or microphysical properties should be collected and used. The results for both days are inconsistent, and no explanation for a O4 scaling factor could be derived in this study. Thus, similar but more extended future studies should be performed, including more measurement days and more instruments. Also, additional wavelengths should be included.
Published: 2019
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48. An improved total and tropospheric NO2 column retrieval for GOME-2

Author: S. Liu, P. Valks, G. Pinardi, I. De Smedt, H. Yu, S. Beirle, and A. Richter
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: An improved algorithm for the retrieval of total and tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment-2 (GOME-2) is presented. The refined retrieval will be implemented in a future version of the GOME Data Processor (GDP) as used by the EUMETSAT Satellite Application Facility on Atmospheric Composition and UV Radiation (AC-SAF). The first main improvement is the application of an extended 425–497 nm wavelength fitting window in the differential optical absorption spectroscopy (DOAS) retrieval of the NO2 slant column density, based on which initial total NO2 columns are computed using stratospheric air mass factors (AMFs). Updated absorption cross sections and a linear offset correction are used for the large fitting window. An improved slit function treatment is applied to compensate for both long-term and in-orbit drift of the GOME-2 slit function. Compared to the current operational (GDP 4.8) dataset, the use of these new features increases the NO2 columns by ∼1–3×1014 molec cm2 and reduces the slant column error by ∼24 %. In addition, the bias between GOME-2A and GOME-2B measurements is largely reduced by adopting a new level 1b data version in the DOAS retrieval. The retrieved NO2 slant columns show good consistency with the Quality Assurance for Essential Climate Variables (QA4ECV) retrieval with a good overall quality. Second, the STRatospheric Estimation Algorithm from Mainz (STREAM), which was originally developed for the TROPOspheric Monitoring Instrument (TROPOMI) instrument, was optimised for GOME-2 measurements to determine the stratospheric NO2 column density. Applied to synthetic GOME-2 data, the estimated stratospheric NO2 columns from STREAM shows good agreement with the a priori truth. An improved latitudinal correction is introduced in STREAM to reduce the biases over the subtropics. Applied to GOME-2 measurements, STREAM largely reduces the overestimation of stratospheric NO2 columns over polluted regions in the GDP 4.8 dataset. Third, the calculation of AMF applies an updated box-air-mass factor (box-AMF) look-up table (LUT) calculated using the latest version 2.7 of the Vector-LInearized Discrete Ordinate Radiative Transfer (VLIDORT) model with an increased number of reference points and vertical layers, a new GOME-2 surface albedo climatology, and improved a priori NO2 profiles obtained from the TM5-MP chemistry transport model. A large effect (mainly enhancement in summer and reduction in winter) on the retrieved tropospheric NO2 columns by more than 10 % is found over polluted regions. To evaluate the GOME-2 tropospheric NO2 columns, an end-to-end validation is performed using ground-based multiple-axis DOAS (MAXDOAS) measurements. The validation is illustrated for six stations covering urban, suburban, and background situations. Compared to the GDP 4.8 product, the new dataset presents improved agreement with the MAXDOAS measurements for all the stations.
Published: 2019
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49. [Postankylosis condylectomy of the temporomandibular joint in a 5-year old girl. Report of a case]

Author: J J, Ortega Alejandre, J, Avila Parrao, and G, Piña Velazco
Subjects: Child, Preschool, Ankylosis, Mandibular Condyle, Humans, Female, Maxillofacial Injuries, Trismus, Temporomandibular Joint Disorders, Maxillofacial Development
Abstract: A case of post-traumatic temporomandibular joint ankylosis is described, and the technique of the treatment is detailed. Previous review of the literature was made in order to know the advantages of the treatment. There are several reports of children who have suffered facial injuries and fractures of the facial bones that became into ankylosis, characterized by the formation of new temporomandibular joint surfaces. The patient was a five years old girl who presented ankylosis of TMJ due to a car accident six months before. The symptom were: Limitation of motion, persistent close lock of mouth (2 mm) muscle pain that causes the patient to avoid eating foods, and the gradual loose of phonetic function. Condylectomy of the left mandibular condyle was performed to correct the mechanical problems associated to ankylosis. The patient had an uncomplicated postoperative course, and now are waiting the outcome of the treatment by a follow up study.
Published: 1990

50. Improved aerosol correction for OMI tropospheric NO2 retrieval over East Asia: constraint from CALIOP aerosol vertical profile

Author: M. Liu, J. Lin, K. F. Boersma, G. Pinardi, Y. Wang, J. Chimot, T. Wagner, P. Xie, H. Eskes, M. Van Roozendael, F. Hendrick, P. Wang, T. Wang, Y. Yan, L. Chen, and R. Ni
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: Satellite retrieval of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is critical for NOx pollution and impact evaluation. For regions with high aerosol loadings, the retrieval accuracy is greatly affected by whether aerosol optical effects are treated implicitly (as additional “effective” clouds) or explicitly, among other factors. Our previous POMINO algorithm explicitly accounts for aerosol effects to improve the retrieval, especially in polluted situations over China, by using aerosol information from GEOS-Chem simulations with further monthly constraints by MODIS/Aqua aerosol optical depth (AOD) data. Here we present a major algorithm update, POMINO v1.1, by constructing a monthly climatological dataset of aerosol extinction profiles, based on level 2 CALIOP/CALIPSO data over 2007–2015, to better constrain the modeled aerosol vertical profiles. We find that GEOS-Chem captures the month-to-month variation in CALIOP aerosol layer height (ALH) but with a systematic underestimate by about 300–600 m (season and location dependent), due to a too strong negative vertical gradient of extinction above 1 km. Correcting the model aerosol extinction profiles results in small changes in retrieved cloud fraction, increases in cloud-top pressure (within 2 %–6 % in most cases), and increases in tropospheric NO2 VCD by 4 %–16 % over China on a monthly basis in 2012. The improved NO2 VCDs (in POMINO v1.1) are more consistent with independent ground-based MAX-DOAS observations (R2=0.80, NMB = −3.4 %, for 162 pixels in 49 days) than POMINO (R2=0.80, NMB = −9.6 %), DOMINO v2 (R2=0.68, NMB = −2.1 %), and QA4ECV (R2=0.75, NMB = −22.0 %) are. Especially on haze days, R2 reaches 0.76 for POMINO v1.1, much higher than that for POMINO (0.68), DOMINO v2 (0.38), and QA4ECV (0.34). Furthermore, the increase in cloud pressure likely reveals a more realistic vertical relationship between cloud and aerosol layers, with aerosols situated above the clouds in certain months instead of always below the clouds. The POMINO v1.1 algorithm is a core step towards our next public release of the data product (POMINO v2), and it will also be applied to the recently launched S5P-TROPOMI sensor.
Published: 2019
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