Filterable PM2.5 concentrations and their chemical characterizations were analyzed for 67 boilers and 25 indirect furnaces located in the Metropolitan Area of Costa Rica from February 2014 to November 2015. The PM2.5 samples were characterized by their composition, focusing on trace elements, inorganic ions and organic and elemental carbon. The results of PM2.5 concentrations ranged from 72 to 735 mgm-3, with the highest concentrations found for sources using biomass fuel, particularly Type B boilers, and the lowest values for diesel boilers. Further speciation of fine particulate matter (PM) showed significant levels of vanadium and nickel for boilers that use heavy fuel oil (bunker); 4886 and 1942 μgm-3, respectively. Copper and manganese were the most relevant metals for biomass burning sources, due to plant absorption from the soil. As for ion concentration, sulfate presented the highest concentrations for biomass boilers and furnaces, whereas chloride only presented the highest concentrations for furnaces. To complete the balance, organic and elemental carbon (OC and EC) analyses were made, in which biomass burning sources presented values five times higher than oil fuels. A Spearman's correlation analysis was made for the data set, revealing significant relationships between heavy metals, sulfate, and fine PM with respect to heavy fuel oil. For the biomass sources, the correlations pointed to K, Na, Mn and, in some cases, oxygen. | Se analizaron las concentraciones filtrables de PM2.5 y sus caracterizaciones químicas para 67 calderas y 25 hornos indirectos ubicados en el Área Metropolitana de Costa Rica desde febrero de 2014 hasta noviembre de 2015. Las muestras de PM2.5 se caracterizaron por su composición, centrándose en oligoelementos, iones inorgánicos y carbono orgánico y elemental. Los resultados de las concentraciones de PM2.5 variaron de 72 a 735 mgm-3, con las concentraciones más altas encontradas para fuentes que utilizan combustible de biomasa, particularmente calderas Tipo B, y el valores más bajos para calderas diesel. Una mayor especiación de partículas finas (PM) mostró una significativa niveles de vanadio y níquel para calderas que utilizan fuel oil pesado (bunker); 4886 y 1942 mgm-3, respectivamente. El cobre y el manganeso fueron los metales más relevantes para las fuentes de combustión de biomasa, debido a Absorción de plantas del suelo. En cuanto a la concentración de iones, el sulfato presentó las mayores concentraciones para calderas y hornos de biomasa, mientras que el cloruro solo presentó las concentraciones más altas para los hornos. Para completar el balance, se realizaron análisis de carbono orgánico y elemental (OC y EC), en los cuales las fuentes de combustión de biomasa presentaron valores cinco veces superiores a los combustibles derivados del petróleo. La correlación de Spearman. Se realizó un análisis para el conjunto de datos, revelando relaciones significativas entre metales pesados, sulfato y PM fino con respecto al fuelóleo pesado. Para las fuentes de biomasa, las correlaciones apuntaron a K, Na, Mn y, en algunos casos, oxígeno. | As concentrações filtráveis ​​de PM2,5 e suas caracterizações químicas foram analisadas para 67 caldeiras e 25 fornos indiretos localizados na Região Metropolitana da Costa Rica de fevereiro de 2014 a novembro de 2015. As amostras de PM2,5 foram caracterizadas por sua composição, com foco em oligoelementos, íons inorgânicos e carbono orgânico e elementar. Os resultados para as concentrações de PM2,5 variaram de 72 a 735 mgm-3, com as concentrações mais altas encontradas para fontes que usam combustível de biomassa, particularmente caldeiras Tipo B, e os valores mais baixos para caldeiras a diesel. A maior especiação de partículas finas (PM) mostrou níveis significativos de vanádio e níquel para caldeiras que usam óleo combustível pesado (bunker); 4886 e 1942 mgm-3, respectivamente. O cobre e o manganês foram os metais mais relevantes para as fontes de combustão da biomassa, devido à absorção das plantas do solo. Em relação à concentração de íons, o sulfato apresentou as maiores concentrações para caldeiras e fornos a biomassa, enquanto o cloreto apresentou as maiores concentrações apenas para os fornos. Para completar o balanço, foram realizadas análises de carbono orgânico e elementar (OC e EC), nas quais as fontes de combustão de biomassa apresentaram valores cinco vezes maiores que os combustíveis derivados do petróleo. A correlação de Spearman. Uma análise foi realizada para o conjunto de dados, revelando relações significativas entre metais pesados, sulfato e MP fino em relação ao óleo combustível pesado. Para fontes de biomassa, as correlações apontaram para K, Na, Mn e, em alguns casos, oxigênio. | Universidad Nacional, Costa Rica | Universidad Autónoma Metropolitana, México | Escuela de Ciencias Ambientales

PM2.5 and PM10 samples were collected at 4 and 14 sampling sites, respectively, located in the Metropolitan area of Costa Rica (MACR), during 2010-2011. These sites were representative of commercial, industrial and residential zones of this region. Concentrations of elemental carbon (EC) and organic carbon (OC) were analyzed using the IMPROVE thermal-optical reflectance (TOR) method. OC and EC concentrations were higher in commercial and industrial sites and showed clear seasonal variations with higher concentrations observed in the rainy season (May-November) than in the dry season (December-April), due to wind patterns in the study area. Total carbonaceous aerosol accounted for 35% of PM10 and 56% of PM2.5 mass. Good correlation between OC and EC in PM10 (R=0.89-0.75) and PM2.5 (R=0.79-0.64) indicated that they had common dominant sources of combustion such as industrial activities and traffic emissions. The annual average concentrations of estimated SOC (Secondary Organic Carbon) in the MACR PM10 samples showed values between 0.65-8.49 mg/m3, accounting for 48% and 56% of the OC in PM10 and PM2.5 respectively. Positive Matrix Factorization (PMF) identified five principal sources for OC and EC in particles: gasoline vehicles, diesel vehicles, on road traffic, wood smoke and industrial combustion. The contribution of each of the source varied between the PM10 and PM2.5 size fractions. | Se recolectaron muestras de PM2.5 y PM10 en 4 y 14 sitios de muestreo, respectivamente, ubicados en el Área Metropolitana de Costa Rica (MACR), durante 2010-2011. Estos sitios eran representativos de zonas comerciales, industriales y residenciales de esta región. Las concentraciones de carbono elemental (CE) y carbono orgánico (OC) se analizaron utilizando el método IMPROVE termoóptica reflectancia (TOR). Las concentraciones de OC y CE fueron mayores en los sitios comerciales e industriales y mostraron claras variaciones estacionales con concentraciones más altas observadas en la temporada de lluvias (mayo-noviembre) que en la estación seca (diciembre-abril), debido a los patrones de viento en el área de estudio. El aerosol carbonoso total representó el 35% de PM10 y el 56% de la masa de PM2.5. La buena correlación entre OC y EC en PM10 (R = 0,89-0,75) y PM2,5 (R = 0,79-0,64) indicó que tenían fuentes de combustión dominantes comunes como las actividades industriales y las emisiones de tráfico. Las concentraciones medias anuales de SOC (Carbono Orgánico Secundario) estimado en las muestras MACR PM10 mostraron valores entre 0.65-8.49 mg / m3, representando el 48% y 56% de la OC en PM10 y PM2.5 respectivamente. La Factorización de Matriz Positiva (PMF) identificó cinco fuentes principales de OC y EC en partículas: vehículos de gasolina, vehículos diesel, en el tráfico rodado, humo de leña y combustión industrial. La contribución de cada una de las fuentes varió entre las fracciones de tamaño PM10 y PM2.5. | As amostras de PM2.5 e PM10 foram coletadas em 4 e 14 locais de amostragem, respectivamente, localizados na área metropolitana da Costa Rica (MACR), durante 2010-2011. Esses locais eram representativos das zonas comerciais, industriais e residenciais desta região. As concentrações de carbono elementar (CE) e carbono orgânico (OC) foram analisadas usando o método IMPROVE de refletância ótica-térmica (TOR). As concentrações de OC e EC foram maiores nos locais comerciais e industriais e mostraram claras variações sazonais com maiores concentrações observadas na estação chuvosa (maio-novembro) do que na estação seca (dezembro-abril), devido aos padrões de vento na área de estudo. O aerossol carbonáceo total foi responsável por 35% da massa de PM10 e 56% da massa de PM2,5. A boa correlação entre OC e EC em PM10 (R = 0,89-0,75) e PM2,5 (R = 0,79-0,64) indicou que eles tinham fontes dominantes comuns de combustão, como atividades industriais e emissões de tráfego. As concentrações médias anuais estimadas de SOC (Carbono Orgânico Secundário) nas amostras MACR PM10 apresentaram valores entre 0,65-8,49 mg / m3, representando 48% e 56% do OC em PM10 e PM2,5 respectivamente. A Fatoração de Matriz Positiva (PMF) identificou cinco fontes principais de CO e CE em partículas: veículos a gasolina, veículos a diesel, no tráfego rodoviário, fumaça de lenha e combustão industrial. A contribuição de cada uma das fontes variou entre as frações de tamanho PM10 e PM2,5. | Universidad Nacional, Costa Rica | Universidad de Costa Rica | Instituto Nacional de Ecología, Mexico | Universidad Nacional Autónoma de México, México | Escuela de Ciencias Ambientales

The estuarine ecosystem of Madre de Dios Lagoon (MDL), in the Caribbean Coast of Costa Rica, is exposed to contamination with pesticide residues coming from the upstream agricultural areas. Biomarkers can provide a better indication of the fitness of biota in real mixture exposure scenarios than traditional lethal dose toxicity measurements. Here, we measured biomarkers of biotransformation, oxidative stress, and neurotoxicity on Astyanax aeneus, an abundant fish species in MDL. Glutathione S-transferase activity (GST), catalase activity (CAT), lipid peroxidation (LPO), and cholinesterase activity (ChE) were measured in fish collected during seven sampling campaigns, carried out between 2016 and 2018. Pesticide residues were analyzed in surface water samples collected every time fish were sampled. Residues of 25 pesticides, including fungicides, insecticides, and herbicides, were detected. The biomarkers measured in A. aeneus varied along the sampling moments, with biotransformation and oxidative stress signals showing a coupled response throughout the assessment. Furthermore, significant correlations were established between three biomarkers (GST, LPO, and CAT) and individual pesticides, as well as between GST and LPO with groups of pesticides with shared biocide action. Among pesticides, insecticide residues had a major influence on the responses observed in fish. This work demonstrates the chronic exposure to pesticide residues in MDL and how such exposure is related to physiological responses in fish that can affect their health and potentially, the trophic networks. This early warning information should be considered to improve the protection of estuarine ecosystems in the tropics. | El ecosistema estuarino de la Laguna Madre de Dios (MDL), en la Costa Caribe de Costa Rica, está expuesto a la contaminación con residuos de pesticidas procedentes de las zonas agrícolas situadas aguas arriba. Los biomarcadores pueden proporcionar una mejor indicación de la aptitud de la biota en escenarios reales de exposición a mezclas que las mediciones tradicionales de toxicidad de dosis letales. Aquí medimos biomarcadores de biotransformación, estrés oxidativo y neurotoxicidad en Astyanax aeneus, una especie de pez abundante en MDL. Actividad glutatión S-transferasa (GST), actividad catalasa (CAT), peroxidación lipídica (LPO) y actividad colinesterasa (ChE) se midieron en peces recolectados durante siete campañas de muestreo, realizadas entre 2016 y 2018. Residuos de pesticidas se analizaron en muestras de agua superficial recolectadas cada vez que se tomaron muestras de peces. Residuos de 25 pesticidas, incluidos fungicidas, Se detectaron insecticidas y herbicidas. Los biomarcadores medidos en A. aeneus variaron a lo largo de los momentos de muestreo, con señales de biotransformación y estrés oxidativo que muestran una respuesta acoplada a lo largo de la evaluación. Además, Se establecieron correlaciones significativas entre tres biomarcadores (GST, LPO y CAT) y pesticidas individuales, así como como entre GST y LPO con grupos de plaguicidas con acción biocida compartida. Entre los plaguicidas, los residuos de insecticidas habían una influencia importante en las respuestas observadas en los peces. Este trabajo demuestra la exposición crónica a residuos de pesticidas en MDL y cómo dicha exposición se relaciona con respuestas fisiológicas en los peces que pueden afectar su salud y, potencialmente, la redes tróficas. Esta información de alerta temprana debe considerarse para mejorar la protección de los ecosistemas estuarinos. en los trópicos. | Universidad Nacional, Costa Rica | Springer, Alemania | Escuela de Ciencias Biológicas

Elevated manganese (Mn) in drinking water has been reported worldwide. While, naturally occurring Mn in groundwater is generally the major source, anthropogenic contamination by Mn-containing fungicides such as mancozeb may also occur. The main objective of this study was to examine factors associated with Mn and ethylenethiourea (ETU), a degradation product of mancozeb, in drinking water samples from villages situated near banana plantations with aerial spraying of mancozeb. Drinking water samples (n = 126) were obtained from 124 homes of women participating in the Infants' Environmental Health Study (ISA, for its acronym in Spanish), living nearby large-scale banana plantations. Concentrations of Mn, iron (Fe), arsenic (As), lead (Pb), cadmium (Cd) and ethylenethiourea (ETU), a degradation product of mancozeb, were measured in water samples. Only six percent of samples had detectable ETU concentrations (limit of detection (LOD) = 0.15 μg/L), whereas 94% of the samples had detectable Mn (LOD = 0.05 μg/L). Mn concentrations were higher than 100 and 500 μg/L in 22% and 7% of the samples, respectively. Mn was highest in samples from private and banana farm wells. Distance from a banana plantation was inversely associated with Mn concentrations, with a 61.5% decrease (95% CI: −97.0, −26.0) in Mn concentrations for each km increase in distance. Mn concentrations in water transported with trucks from one village to another were almost 1000 times higher than Mn in water obtained from taps in houses supplied by the same well but not transported, indicating environmental Mn contamination. Elevated Mn in drinking water may be partly explained by aerial spraying of mancozeb; however, naturally occurring Mn in groundwater, and intensive agriculture may also contribute. Drinking water risk assessment for mancozeb should consider Mn as a health hazard. The findings of this study evidence the need for health-based World Health Organization (WHO) guidelines on Mn in drinking water.

Exposure to suspended particulate matter (PM), found in the air, is one of the most acute environmental problems that affect the health of modern society. Among the different airborne pollutants, heavy metals (HMs) are particularly relevant because they are bioaccumulated, impairing the functions of living beings. This study aimed to establish a method to predict heavy metal concentrations in leaves and road dust, through their magnetic properties measurements. For this purpose, machine learning, automatic linear regression (MLR), and support vector machine (SVM) were used to establish models for the prediction of airborne heavy metals based on leaves and road dust magnetic properties. Road dust samples and leaves of two common evergreen species (Cupressus lusitanica/Casuarina equisetifolia) were sampled simultaneously during two different years in the Great Metropolitan Area (GMA) of Costa Rica. MLR and SVM algorithms were used to establish the relationship between airborne heavy metal concentrations based on single (χlf) and multiple (χlf y χdf) leaf magnetic properties and road dust. Results showed that Fe, Cu, Cr, V, and Zn concentrations were well-simulated by SVM prediction models, with adjusted R² values ≥ 0.7 in both training and test stages. By contrast, the concentrations of Pb and Ni were not well-simulated, with adjusted R² values < 0.7 in both training and test stages. Heavy metal predicción models using magnetic properties of leaves from Casuarina equisetifolia, as collectors, yielded better prediction results than those based on the leaves of Cupressus lusitanica and road dust, showing relatively higher adjusted R² values and lower errors (MAE and RMSE) in both training and test stages. SVM proved to be the best prediction model with variations between single (χlf) and multiple (χlf y χdf) magnetic properties depending on the element studied.

This study was a baseline with quantitative data of marine litter along the Gulf of Nicoya, Costa Rica. The objective of the study was to quantify marine litter and its association with human activities in this estuarine gulf. A total of fourteen sandy beaches were cataloged by the degree of urbanization, tourism intensity, beach cleaning programs, and tributary rivers as possible drivers of marine litter presence. The items of the marine litter were separated and weighted by type. Analysis by the clean coastal index (CCI) and multivariate statistics were applied to find spatial patterns in marine litter in the gulf. On beaches with the highest touristic activity, cigarette butts and straws were the main components. Locations with river plume influence, less frequent cleanup, or waste cans showed more bottles, plastic parts, and sanitary waste than beaches in other conditions. A beach in a fisherman town had recently utilized plastic bags, household goods, and boat parts in the marine litter. A wildlife refuge beach showed only small plastic and coffee foam cup fragments that came with currents from other points in the estuary. River basin management, solid waste disposal programs, and environmental education to avoid single-use items combined with correct waste disposal are needed to reduce marine litter in tropical countries focused on ecological tourism.

Moín, on the Caribbean coast of Costa Rica, is a multi-use coastal zone with a variety of human activities that can cause metal pollution. With the purpose of assessing the current environmental burden due to heavy metal presence in the marine environment of Moín, and their bioaccumulation in organisms of the nearby coral reef, we determined seven metals in samples of bottom sediments, macroalgae (Cryptonemia crenulata) and sponge (Cinachyrella kuekenthali). The results were compared with samples from the southern Caribbean, an area with little human activity. Using ICP-MS, results showed a concentration range for sediments Mn > Cu > Zn > Cr > Ni > Pb > Cd, algae Mn > Cu > Zn > Ni > Cr > Pb > Cd and sponge Mn > Cu > Zn > Ni > Cr > Cd > Pb, relatively low concentrations overall and no differences observed between sites. Bioconcentration factor > 1 was determined for Cd, Cu, Ni and Zn, while concentrations in sediments were below the SQG thresholds. Our study provides the first data on metal concentrations in a macroalgae and a sponge from the Costa Rican Caribbean.

PM10 and PM2.5 levels, concentrations of major ionic components, trace elements, and organic and elemental carbon were evaluated from samples collected in 4 sites (industrial, commercial and residential zones) located in the metropolitan area of Costa Rica. The annual mean PM levels were higher in high traffic–commercial (HE–01) and industrial (BE–02) sites, 55 μg m–3 and 52 μg m–3 for PM10 and 37 μg m–3 and 36 μg m–3 for PM2 5, respectively. The major components of PM25 were organic matter (OM) and elemental carbon (EC) (44.5–69.9%), and secondary ions (16.1–27.2%), whereas the major components of PM10 were OM+EC (32.7–59.4%), crustal material (23.5–35.6%) and secondary ions (11.4–26.9%). For the most of the sampling sites, PM10 and PM2.5 concentrations were lower during the dry season and increased gradually in the rainy season due to wind patterns. PMF model identified 8 principle sources for PM10 and PM2.5 in the industrial site (crustal, secondary sulfate, secondary nitrate, secondary organic, traffic, sea–salt aerosols, industrial and oil combustion), 6 and 5 sources in commercial and residential sites, respectively. The source contributions showed a clear seasonal pattern for all the sites.