In zones where aerosol properties have been poorly characterized, satellite-based (MODIS) and ground-based (AERONET) aerosol optical depth (AOD) values typically differ. In this work, we use machine-learning based methods (artificial neural networks and support vector machines) to obtain corrected AOD values taken from MODIS in regions that are positioned far from AERONET stations. The method has been validated using several approaches. The area suitable for improvement covers 62

We present a method to correct aerosol optical depth (AOD) values taken from Collection 6 MODIS observations, which resulted in values closer to those recorded by the ground-based network AERONET. The method is based on machine learning techniques (Artificial Neural Networks and Support Vector Regression), and uses MODIS AOD values and meteorological parameters as inputs. The method showed improved results, compared with the direct MODIS AOD, when applied to nine stations in South America. The percentage of improvement, measured in terms of R2, ranged from 2% (Alta Floresta) to 79% (Buenos Aires). This improvement was also quantified considering the percentage of data within the MODIS expected error, being 91% for this method and 57% for direct correlation. The method corrected not only the systematic bias in temporal data series but also the outliers. To highlight this ability, the results for each AERONET station were individually analyzed. Considering the results as a whole, this method showed to be a valuable tool to enhance MODIS AOD retrievals, especially for locations with systematic deviations.

Four monitoring campaigns between the years 2009 and 2018 were conducted in Córdoba City, Argentina, to detect toxic metals in PM2.5 samples. The concentrations of As, Cd, Pb, Cu, Cr, Mn, Hg, Ni, and Zn, together with several other elements, were measured. The average metal concentrations followed the order: Zn > Cr > Cu > Mn > Pb > V > Ni > As ~ Sb > Cd > Tl > Pd > Hg > Pt. From the analysis of the temporal variation in the elemental concentration of PM2.5, results show seasonal variations that reach, in general, a maximum in the coldest seasons and a minimum in the warmer seasons. These differences could be explained by the different weather conditions during each season, the influence of the El Niño/La Niña regimen, and the presence of fires on certain sampling dates. The source apportionment analysis performed for the period 2017–2018 showed the contribution to PM2.5 of combustion of heavy fuel oil and diesel-powered vehicles, pet coke, metallurgical and nonferrous industries, paint plant factory, traffic, and natural sources like the soil and road dust. This last analysis completed the assignment of sources for the 10-year period of study. Thus, the results of this work contribute to the implementation of emission reduction strategies in order to decrease the impact of PM2.5 on the environment and the human health.

Accurate estimates of total global solar irradiance reaching the Earth’s surface are relevant since routine measurements are not always available. This work aimed to determine which of the models used to estimate daily total global solar irradiance (TGSI) is the best model when irradiance measurements are scarce in a given site. A model based on an artificial neural network (ANN) and empirical models based on temperature and sunshine measurements were analyzed and evaluated in Córdoba, Argentina. The performance of the models was benchmarked using different statistical estimators such as the mean bias error (MBE), the mean absolute bias error (MABE), the correlation coefficient ( r ), the Nash-Sutcliffe equation (NSE), and the statistics t test ( t value). The results showed that when enough measurements were available, both the ANN and the empirical models accurately predicted TGSI (with MBE and MABE ≤ |0.11| and ≤ |1.98| kWh m −2 day −1 , respectively; NSE ≥ 0.83; r ≥ 0.95; and | t values| < t critical value). However, when few TGSI measurements were available (2, 3, 5, 7, or 10 days per month) only the ANN-based method was accurate (| t value| < t critical value), yielding precise results although only 2 measurements per month were available for 1 year. This model has an important advantage over the empirical models and is very relevant to Argentina due to the scarcity of TGSI measurements.

A total of 175 aerosol samples were collected during the winter-spring months of 2014-2015 in Cordoba, Argentina. The samples were collected in five size fractions that ranged from < 0.25 to 10 mu m using a SIOUTAS impactor in a 6-h period and analyzed by synchrotron radiation X-ray fluorescence to obtain elemental aerosol mass concentrations for As, Ca, Co, Cr, Cu, Fe, K, Mn, Ni, Pb, Si, S, Ti, V, and Zn. An analysis of the distribution of the elements in the different collected fractions was performed to infer the most likely sources of particulate matter. From the analysis, it was found that the particulate matter fraction smaller than 0.25 mu m was mostly affected by emissions from traffic and combustion, while the particulate matter fraction ranging from 2.5 to 10 mu m was mostly influenced by re-suspension of road dust. In addition, the results indicated the presence of Si, typically found in coarse particulate matter and in large amounts in particles smaller than 0.25 mu m. To infer the sources of aerosols causing the deterioration of air quality, principal component analysis was performed. The smallest particles, due to their toxicity, are likely to produce more adverse health effects than larger size fractions. These results show the need to monitor their atmospheric emissions in order to preserve air quality. Synchrotron radiation X-ray fluorescence analysis of the elemental composition of particles smaller than 0.25 mu m in Cordoba city constitutes the first contribution to the knowledge base of the concentrations of toxic metals in this size fraction. These results are relevant because there is a lack of data in South American cities.

Long-range atmospheric transport is one of the most important ways in which persistent organic pollutants can be transported from their source to remote and pristine regions. Here, we report the results of the first Argentinian measurements of organochlorine pesticides in the Antarctic region. During a 9665-km track onboard OV ARA Puerto Deseado, within the framework of Argentinian Antarctic Expeditions, air samples were taken using high-volume samplers and analyzed using GC-μECD. HCB, HCHs, and endosulfans were the major organic pollutants found, and a north-south gradient in their concentrations was evident by comparing data from the Argentinian offshore zone to the South Scotia Sea.

Global ultraviolet-B irradiance (UV-B, 280-315 nm) measurements made at the campus of the University of Cordoba, Argentina were analyzed to quantify the effects of ozone and aerosols on surface UV-B erythemal irradiance (UVER). The measurements have been carried out with a YES Pyranometer during the period 2000-2013. The effect of ozone and aerosols has been quantified by means of the Radiation Amplification Factor (RAF) and by an aerosol factor (AF, analogous to RAF), respectively. The overall mean RAF under cloudless conditions was (1.2 +/- 0.3) %, ranging from 0.67 to 2.10% depending on solar zenith angle (SZA) and on Aerosol Optical Depth (AOD). The RAF increased with the SZA with a clear trend. Similarly, the aerosol effect under almost-constant ozone and SZA showed that, on average, a 1% increase in AOD forced a decrease of (0.15 +/- 0.04) % in the UVER, with a range of 0.06 to 0.27 and no defined trend as a function of the SZA. To analyze the effect of absorbing aerosols, an effective single scattering albedo (SSA) was determined by comparing the experimental UVER with calculations carried out with the TUV radiative transfer model. (C) 2017 Elsevier Ltd. All rights reserved.

In this work, PM2.5 samples were collected in the winter-spring months of 2014-2016 at an urban site in Cordoba. Cordoba is the second largest city in Argentina and is an important industrial and touristic center. The collected samples were individually analyzed for chemical composition using different techniques. The soluble inorganic ions and carbonaceous particles were determined from bulk aerosol samples for the first time in the city. The mass concentrations of PM2.5, organic carbon, elemental carbon, inorganic ions and metals were determined according to the mass balance. The dominant mass components were organic matter and elemental carbon (54.8%), mineral dust (6.1%), secondary inorganic aerosols (3.0%), and salt (1.2%). A principal component analysis was applied to the samples and resulted in five major factors that explained 79% of the variance in PM2.5. These factors represented combustion, industrial sources, soil dust, secondary inorganic aerosol, and salt, and each explained between 11% and 20% of the variance. A comparison with the results from a previous campaign (2010-2011) revealed appreciable changes in the PM2.5 chemical composition. These changes were attributed to the two extreme meteorological conditions that prevailed in the region. The years 2014-2016 were largely dominated by the warm phase of the El Nifio Southern Oscillation, which leads to humid and cold weather in the Cordoba region, while the samples from 2010 to 2011 were collected during the dry and hot years resulting from the La Nifia regime. (C) 2017 Elsevier Ltd. All rights reserved.

AEROSOL Robotic Network (AERONET), Moderate Resolution Imaging Spectroradiometer (MODIS) and global UV-B (280–315nm) irradiance measurements and calculations were combined to investigate the effects of aerosol loading on the ultraviolet B radiation (UV-B) reaching the surface under cloudless conditions in Córdoba, Argentina. The aerosol radiative forcing (ARF) and the aerosol forcing efficiency (ARFE) were calculated for an extended period of time (2000–2013) at a ground-based monitoring site affected by different types and loading of aerosols. The ARFE was evaluated by using the aerosol optical depth (AOD) at 340nm retrieved by AERONET at the Cordoba CETT site. The individual and combined effects of the single scattering albedo (SSA) and the solar zenith angle (SZA) on the ARFE were also analyzed. In addition, and for comparison purposes, the MODIS AOD at 550nm was used as input in a machine learning method to better characterize the aerosol load at 340nm and evaluate the ARFE retrieved from AOD satellite measurements. The ARFE at the surface calculated using AOD data from AERONET ranged from (–0.11±0.01) to (–1.76±0.20) Wm–2 with an average of –0.61 Wm–2; however, when using AOD data from MODIS (TERRA/AQUA satellites), it ranged from (–0.22±0.03) to (–0.65±0.07) Wm–2 with an average value of –0.43 Wm–2. At the same SZA and SSA, the maximum difference between ground and satellite-based was 0.22 Wm–2.

In this work, we present a method to predict missing aerosol optical depth (AOD) values at an AERONET station. The aim of the method is to fill gaps and/or to extrapolate temporal series in the station datasets, i.e. to obtain AOD values under cloudy sky conditions and in other situations where there is a temporary or permanent lack of data. To accomplish that, we used historical AOD values at two stations, air mass trajectories passing through both of them (calculated by using the HYSPLIT model) and ANN calculations to process all the information. The variables included in the neural network training were the station numbers, parameters representing the annual average trend of meteorological conditions, the number of hours and the distance traveled by the air mass between the stations, and the arrival height of the air mass. The method was firstly applied to predict AOD at 440 nm in 9 stations located in the East Coast of the US, during the years 1999-2012. The coefficient of determination r(2) between measured and calculated AOD values was 0.855, which show the good performance of the method. Besides, this result represents a remarkable improvement compared to three simple approaches. To further validate the method, we applied it to another region (Iberian Peninsula) with different characteristics (lower density of AERONET stations, different meteorology, and lower wind field spatial resolution). Although the results are still good (r(2) = 0.67), the performance of the method was affected by these characteristics. Considering the obtained results, this method can be used as a powerful tool to predict AOD values in several conditions. The methodology can also be easily adapted to predict AOD values at other wavelengths or other aerosol optical properties. (C) 2015 Elsevier Ltd. All rights reserved.

This work presents the analysis of the long-term observations of aerosol optical properties in the central region of Argentina. Monitoring of aerosol parameters was carried out at the Cordoba-CETT AERONET site (31° 31′ S, 64° 27′ W, 730m.a.s.l.) from November 1999 until December 2010. Long-term measurements of aerosol optical depth, Ångström exponent, fine mode fraction and single scattering albedo were analyzed and compiled to describe the climatology of the optical properties of the aerosols of the region. The knowledge of the optical properties of aerosols and their spatial distribution is required to evaluate aerosol effects on the climate system. This information provides an opportunity for understanding how aerosols might influence the regional radiation budget. Results show that aerosol optical depth at 340nm is characterized by low values from February to April (monthly average of 0.15±0.05), very low values from May to June (monthly average of 0.08±0.03) and a sustained increase from July to September (monthly average of 0.20±0.09) reaching a value of 0.26. From this dataset, no long-term trends are observable. Results of the inter-annual variations of the Ångström exponent between 440 and 870nm reflect an important difference in the year 2004 compared to the other 11 years of the study. A possible explanation of this fact is elaborated with the help of back trajectory analysis. Finally, three episodes are described and analyzed, as they produced important increases of the daily aerosol optical depth value. We explained these episodes with a combination of air mass trajectory analysis, meteorology and the MODIS fire counts product.

24-h samplings of PM10 and PM2.5 have been carried out during the period July 2009 April 2010 at an urban and at a semi-urban site of Cordoba City (Argentina). The samples in the PM2.5 fraction weighted in the average 71 +/- 21 mu g m(-3) and 67 +/- 18 mu g m(-3) respectively, whereas the samples of the same sites in the PM10 fraction weighted 107 +/- 31 mu g m(-3) and 101 +/- 14 mu g m(-3). The chemical composition of aerosol particles was determined by synchrotron radiation X-ray fluorescence (SR-XRF). Elemental composition was different in the two fractions: in the finer one the presence of elements with crustal origin is reduced, while the anthropogenic elements, with a relevant environmental and health impact, appear to be increased. An important but unmeasured component is likely constituted by organic and elemental carbon compounds. Multivariate analysis (Positive Matrix Factorization) of the SR-XRF data resolved a number of components (factors) which, on the basis of their chemical compositions, were assigned physical meanings. (C) 2011 Elsevier Ltd. All rights reserved.

In Argentina no historical or present programs exist specifically assessing ecosystem health with respect to photochemical air pollution, although phytotoxic concentrations of near-ground ozone have been documented in recent years. Here we report our preliminary findings on field observations of ozone-like injury found in natural plant populations and agroecosystems late in the 2005 growing season in the Southern Hemisphere. Several possible ozone bioinidicator plants which have not been previously documented were observed to exhibit foliar symptoms consistent with ozone-induced injury. Based on these results we intend to expand field surveys and complete the screening process for injury confirmation of the plant species described here. For this and future research we will be using controlled chamber studies based in the US. Continuous monitoring of tropospheric ozone does not currently take place in the region of central Argentina. The combined evidence provided by intermittent air quality sampling and the presence of ozone-like injury to vegetation indicates the need to establish air quality and ozone biomonitoring networks in this region.

Abstract. A new mechanism to simulate the formation of secondary organic aerosols (SOA) from reactive primary hydrocarbons is presented, together with comparisons with experimental smog chamber results and ambient measurements found in the literature. The SOA formation mechanism is based on an approach using calculated vapor pressures and a selection of species that can partition to the aerosol phase from a gas phase photochemical mechanism. The mechanism has been validated against smog chamber measurements using α-pinene, xylene and toluene as SOA precursors, and has an average error of 17%. Qualitative comparisons with smog chamber measurements using isoprene were also performed. A comparison against SOA production in the TORCH 2003 experiment (atmospheric measurements) had an average error of only 12%. This contrasts with previous efforts, in which it was necessary to increase partition coefficients by a factor of 500 in order to match the observed values. Calculations for rural and urban-influenced regions in the eastern U.S. suggest that most of the SOA is biogenic in origin, mainly originated from isoprene. A 0-dimensional calculation based on the New England Air Quality Study also showed good agreement with measured SOA, with about 40% of the total SOA from anthropogenic precursors. This mechanism can be implemented in a general circulation model (GCM) to estimate global SOA formation under ambient NOx and HOx levels.

Daily sampling of atmospheric PM10 particulate was carried out using a continuously weighing, Tapered Element Oscillating Microbalance (TEOM) equipped with a PM10 size selective inlet. The TEOM collects PM10 on a small filter interfaced with an inertial mass transducer, which allows near continuous weighing of the filter as the deposit accumulates. The sampler was sited at several urban and sub-urban places in Córdoba City, Argentina. With the complete data set of chemical and meteorological variables (CO, NOx, O3, wind speed, wind direction, ambient temperature, total and UV radiation, pressure and relative humidity, etc.) a stepwise regression was performed to select which variables have a major influence on the amount of PM10 measured. Results are presented from the June 1995–May 1996 field campaign. Data for PM10 values largely exceeded the one day standard average value of 150 μg m−3 during several days. The largest amount of particulate has been measured during the winter season. The primary aim of this work is to define the concentration characteristics of ambient PM10 at each site where this pollutant has been measured and to examine the seasonal variation of PM10.

Results of field measurements carried out from June 15 to December 31, 1995, in Córdoba city (Argentina) are presented. During this field campaign, surface ozone mixing ratios were generally around 30–35 ppb (afternoon peak). However, during the first week of September, days with excessive ozone values close to 100 ppb were found. These elevated ozone concentrations appeared together with high values of NOx, CO, PM10, and an unusual meteorological situation for this time of the year. These results made this episode an interesting one to be studied in more detail. In this work, we used chemical and meteorological data to trace the region from where the assumed precursors were emitted and we identified possible source characteristics.

El proyecto tiene como objetivo principal alcanzar una mejor comprension de los mecanismos que influyen en la capa inferior de la atmosfera o troposfera, tanto desde el punto de vista teorico como experimental. (...) Se utilizaran modelos radioactivos para evaluar en forma cuantitativa el flujo de radiacion que llega a la superficie terrestre en nuestra ciudad en las distintas estaciones como funcion de la concentracion de especies absorbentes, dispersion y/o absorcion por particulados y aerosoles, concentracion de vapor de agua y factores meteorologicos. (...) Se espera ademas realizar estudios de sensibilidad con el objetivo de analizar el efecto de cambios en las condiciones fisicoquimicas del ambiente y su influencia en la velocidad de las reacciones quimicas que tienen lugar en la atmosfera. El enfasis mayor se pondra en aquellas reacciones iniciadas por la absorcion de radiacion proveniente del sol, en las cuales participan especies que absorben en la region del espectro electromagnetico conocido como UV cercano. Este analisis es fundamental a la hora de optar por combustibles alternativos con el proposito de mejorar la calidad del aire en una region. En este periodo del proyecto se finalizara con el desarrollo y se haran las pruebas necesarias de un modelo matematico que permite la simulacion de la dispersion y procesos de transporte producidos por una chimenea o escape industrial, teniendo en cuenta las reacciones quimicas que ocurriran (fuentes y sumideros) poniendo especial enfasis en la cuantificacion de las concentraciones que recibiran los seres humanos y la vegetacion en sitios criticos de la region. Este trabajo es de gran importancia ya que permitira prever el impacto que tendran las emisiones gaseosas reactivas de una industria, incinerador, etc. en la salud de la poblacion. El uso de estos modelos es una pieza fundamental de lo que se conoce como Estudios de impacto ambiental.

The atmospheric concentrations of several primary species: NO, NO2, NOx, CO, SO2, reactive hydrocarbons (ROG) and other 15 atmospheric and meteorological variables have been measured at several locations in Córdoba city, Argentina since June 1995. The measurements are carried out using two mobile stations to cover several important areas of Córdoba. The objective of this work is to estimate the effects of meteorology and urban structure on the air quality levels for this city using simple statistics. We analyze the correlation between primary pollutants (CO and NOx) and site locations of the air quality monitoring stations (AQMS) during the whole 1995 field campaign. In this study we take the measured data for primary pollutants and group them by location and time of the year. The results of this work may be useful to forecast air pollution episodes. Also we can get indirect information about emissions and maybe identify source characteristics. Once the influences of topography, meteorology, and land use will be fully characterized, the existing monitoring data will be used to do air quality modeling analysis and to select monitoring locations. The use of mobile stations instead of stationary ones at this stage is justified because of limited funding. Therefore, it is a valid option to decide in the future the additional instrumentation required to characterize completely the atmospheric urban area.