Intercomparison Between Surrogate, Explicit, and Full Treatments of VSL Bromine Chemistry Within the CAM-Chem Chemistry-Climate Model.

Many Chemistry-Climate Models (CCMs) include a simplified treatment of brominated very short-lived (VSLBr) species by assuming CH3Br as a surrogate for VSLBr. However, neglecting a comprehensive treatment of VSLBr in CCMs may yield an unrealistic representation of the associated impacts. Here, we use the Community Atmospheric Model with Chemistry (CAM-Chem) CCM to quantify the tropospheric and stratospheric changes between various VSLBr chemical approaches with increasing degrees of complexity (i.e., surrogate, explicit, and full). Our CAM-Chem results highlight the improved accuracy achieved by considering a detailed treatment of VSLBr photochemistry, including sea-salt aerosol dehalogenation and heterogeneous recycling on ice-crystals. Differences between the full and surrogate schemes maximize in the lowermost stratosphere and midlatitude free troposphere, resulting in a latitudinally dependent reduction of ∼1-7 DU in total ozone column and a ∼5%-15% decrease of the OH/HO2 ratio. We encourage all CCMs to include a complete chemical treatment of VSLBr in the troposphere and stratosphere.

PM2.5 monitoring during a 10-year period: relation between elemental concentration and meteorological conditions.

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 total solar irradiance estimates under irradiance measurements scarcity scenarios.

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.

Recovery of the histogram of hourly ozone distribution from weekly average concentrations.

A simple method is presented for estimating hourly distribution of air pollutants, based on data collected by passive sensors on a weekly or bi-weekly basis with no need for previous measurements at a site. In order for this method to be applied to locations where no hourly records are available, reference data from other sites are required to generate calibration histograms. The proposed procedure allows one to obtain the histogram of hourly ozone values during a given week with an error of about 30%, which is good considering the simplicity of this approach. This method can be a valuable tool for sites that lack previous hourly records of pollutant ambient concentrations, where it can be used to verify compliance with regulations or to estimate the AOT40 index with an acceptable degree of exactitude.

A method to estimate emission rates from industrial stacks based on neural networks.

This paper presents a technique based on artificial neural networks (ANN) to estimate pollutant rates of emission from industrial stacks, on the basis of pollutant concentrations measured on the ground. The ANN is trained on data generated by the ISCST3 model, widely accepted for evaluation of dispersion of primary pollutants as a part of an environmental impact study. Simulations using theoretical values and comparison with field data are done, obtaining good results in both cases at predicting emission rates. The application of this technique would allow the local environment authority to control emissions from industrial plants without need of performing direct measurements inside the plant.

Red de monitoreo del aire

Este trabajo tuvo como objetivo determinar la situación existente en materia de calidad de aire en el área de Río Tercero, colaborar técnicamente con el municipio de dicha ciudad, redactar un manual completo de instrucciones y procedimiento de uso de los sensores ya existentes

Red de monitoreo del aire

Este trabajo tuvo como objetivo determinar la situación existente en materia de calidad de aire en el área de Río Tercero, colaborar técnicamente con el municipio de dicha ciudad, redactar un manual completo de instrucciones y procedimiento de uso de los sensores ya existentes