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1.
Environ Sci Pollut Res Int ; 30(60): 125596-125608, 2023 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-38006481

RESUMO

The main objective of the research was to study the environmental "price" of the large-scale, milk production from a rarely known perspective, from the mapping of the estrogenic footprint (the amount of oestrus-inducer hormonal products, and the generated endoestrogens) in the resulting slurry in a dairy cow farm. These micropollutants are endocrine-disrupting chemicals (EDCs) and can be dangerous to the normal reproductive functions even at ng/kg concentration. One of them, 17ß-estradiol, has a 20,000 times stronger estrogenic effect than bisphenol-A, a widely known EDC of industrial origin. While most studies on EDCs are short-term and/or laboratory based, this study is longitudinal and field-based. We sampled the slurry pool on a quarterly basis between 2017 and 2020. Our purpose was testing the estrogenic effects using a dual approach. As an effect-based, holistic method, we developed and used the YES (yeast estrogen screen) test employing the genetically modified Saccharomyces cerevisiae BJ3505 strain which contains human estrogenic receptor. For testing exact molecules, UHPLC-FLD was used. Our study points out that slurry contains a growing amount of EDCs with the risk of penetrating into the soil, crops and the food chain. Considering the Green Chemistry concept, the most benign ways to prevent of the pollution of the slurry is choosing appropriate oestrus-inducing veterinary pharmaceuticals (OIVPs) and the separation of the solid and liquid parts with adequate treatment methods. To our knowledge, this is the first paper on the adaptation of the YES test for medicine and slurry samples, extending its applicability. The adapted YES test turned out to be a sensitive, robust and reliable method for testing samples with potential estrogenic effect. Our dual approach was successful in evaluating the estrogenic effect of the slurry samples.


Assuntos
Disruptores Endócrinos , Poluentes Ambientais , Drogas Veterinárias , Poluentes Químicos da Água , Bovinos , Animais , Humanos , Poluentes Ambientais/farmacologia , Poluentes Químicos da Água/análise , Estrogênios/química , Estradiol/química , Saccharomyces cerevisiae , Disruptores Endócrinos/química
2.
Sci Total Environ ; 767: 145426, 2021 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-33550056

RESUMO

Bioaerosols play a major role in the plant life of ecosystems. In addition, they have a profound impact on human health, since they may cause lung diseases or allergies. The key objective of this study is to assess the below cloud scavenging effect of rainfall on pollen concentration. The analysis is based on a sampling carried out in León, Spain, between 2015 and 2018. The rainfall variables and the pollen concentrations have been obtained with a disdrometer and a volumetric Hirst type spore-trap, respectively. In order to evaluate the scavenging, three parameters have been calculated: scavenging efficiency (through the concentration-weighted average (%ΔC)), the scavenging coefficient (λ) and the percentage of events with a decrease in pollen concentration (%ES) also called events with effective scavenging. 71% of rain events presented an effective scavenging that affected all types of pollen. The %ΔC mean value of total pollen was 24 ± 18% (positive values indicate an effective scavenging) and the types of pollen with the highest values were Castanea and Cupressaceae (71 and 40%, respectively). A linear model (R2 = 0.94) to estimate the pollen concentration after rain was built with variables such as pollen concentration before rain and other variables from a weather station and a disdrometer. Furthermore, we have shown the possibility of knowing in real time the probable Cupressaceae pollen concentration, from the initial pollen concentration and the physical parameters of rain (such as raindrop size, rain intensity or volume swept by raindrops in their falling path).


Assuntos
Poluentes Atmosféricos , Poluentes Atmosféricos/análise , Alérgenos/análise , Ecossistema , Humanos , Pólen/química , Estações do Ano , Espanha , Tempo (Meteorologia)
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