RUBEN CEJUDO

Dr. RUBEN CEJUDO

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Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 July 2023 in Environmental Science and Pollution Research
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TSTeresa Salazar-Rojas
Teresa Salazar-Rojas
RUBEN CEJUDORUBEN CEJUDO
RUBEN CEJUDO
MGMarco V. Gutiérrez-Soto
Marco V. Gutiérrez-Soto
GCGuillermo Calvo-Brenes
Guillermo Calvo-Brenes

1 February 2019 in Revista Internacional de Contaminación Ambiental
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CDCarmen Delgado
Carmen Delgado
FRANCISCO BAUTISTAFRANCISCO BAUTISTA
FRANCISCO BAUTISTA
AGAVTANDIL GOGICHAISHVILI
AVTANDIL GOGICHAISHVILI
JCJose Luis Cortés-Esquivel
Jose Luis Cortés-Esquivel
PQPatricia Quintana
Patricia Quintana
RUBEN CEJUDORUBEN CEJUDO
RUBEN CEJUDO
IDENTIFICACIÓN DE LAS ZONAS CONTAMINADAS CON METALES PESADOS EN EL POLVO URBANO DE LA CIUDAD DE MÉXICO

17 February 2021 in Atmosphere
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AAAnahi Aguilera
Anahi Aguilera
Dorian Bautista-HernándezDorian Bautista-Hernández
Dorian Bautista-Hernández
FRANCISCO BAUTISTAFRANCISCO BAUTISTA
FRANCISCO BAUTISTA
AGAVTANDIL GOGICHAISHVILI
AVTANDIL GOGICHAISHVILI
RUBEN CEJUDORUBEN CEJUDO
RUBEN CEJUDO
Environmental pollution is a negative externality of urbanization and is of great concern due to the fact that it poses serious problems to human health. Pollutants, such as heavy metals, have been found in urban road dust; however, it is unclear whether the urban form has a role in its accumulation, mainly in cases where there is no dominant unique source. We collected 482 samples of road dust, we determined the concentrations of five heavy metals (Cr, Cu, Pb, Zn, and Ni) using inductively coupled plasma optical emission spectrometry (ICP-OES), and then we derived the pollution load index (PLI). After estimating the mostly anthropogenic origin of these pollutants based on global levels of reference, there were two main aims of this study. Firstly, to analyze the spatial correlation of heavy metals, and secondly, to identify the main factors that influenced the heavy metal concentrations in the road dust of Mexico City. We did this by using a spatial autocorrelation indicator (Global Moran’s I) and applying ordinary least squares (OLS) and spatial regression models. The results indicated low levels of positive spatial autocorrelation for all heavy metals. Most variables failed to detect any relationship with heavy metals. The median strip area in the roads had a weak (significance level of 90%) but consistent positive relationship with Cr, Cu, Ni, Pb, and the PLI. The distance to the airport had a weak (significance level of 90%) and inverse relationship with Pb. Manufacturing units were associated with an increase in Cu (significance level of 95%), while the entropy index was associated with an increase in Ni (significance level of 95%).


1 March 2019 in Quaternary Research
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AGAVTANDIL GOGICHAISHVILI
AVTANDIL GOGICHAISHVILI
CGCatriel Greco
Catriel Greco
RRRafael Garcia Ruiz
Rafael Garcia Ruiz
LDLucas Pereyra Domingorena
Lucas Pereyra Domingorena
RUBEN CEJUDORUBEN CEJUDO
RUBEN CEJUDO
MTMyriam Tarragó
Myriam Tarragó
We report comprehensive rock-magnetic and archaeointensity investigations from 21 well-constrained pottery fragments from the Catamarca province of northwest Argentina. The absolute ages of the studied sites are ascertained by several high-quality radiometric ages and range between 1940 to 114014C yr BP. Magnetic mineralogy experiments indicates that the remanence is carried by thermally stable Ti-poor titanomagnetites. Forty-seven samples belonging to 11 out of 98 studied potsherds yielded reliable absolute intensity determinations judging from the quality parameters associated with the Thellier double-heating experiments. Moreover, we analyzed the available absolute geomagnetic intensities associated with the radiometric ages to construct the first intensity paleosecular variation curve (PSVC) for South America using thermoremanent magnetization carried by burned archaeological artifacts obtained in the present investigation and 79 other selected archaeointensities (out of 213 published in the literature). The dataset is used to build the PSVC reference curve by combined bootstrap and temporal P-spline methods. The variation curve shows significant differences with the global prediction model SHA.DIF.14k mainly based on the GEOMAGIA database. This intensity PSVC curve shows reasonably good agreement with paleosecular variation curves for Europe between 850 through 1150 BC and for Asia between 1000 and 1500 BC. This regional curve may be used as most reliable archaeomagnetic dating tool for the major part of South America (Peru, Brazil, Argentina, Chile, and Bolivia) for the last two millennia.