961 resultados para pesticide contaminants


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This paper, based on the outcome of discussions at a NORMAN Network-supported workshop in Lyon (France) in November 2014 aims to provide a common position of passive sampling community experts regarding concrete actions required to foster the use of passive sampling techniques in support of contaminant risk assessment and management and for routine monitoring of contaminants in aquatic systems. The brief roadmap presented here focusses on the identification of robust passive sampling methodology, technology that requires further development or that has yet to be developed, our current knowledge of the evaluation of uncertainties when calculating a freely dissolved concentration, the relationship between data from PS and that obtained through biomonitoring. A tiered approach to identifying areas of potential environmental quality standard (EQS) exceedances is also shown. Finally, we propose a list of recommended actions to improve the acceptance of passive sampling by policy-makers. These include the drafting of guidelines, quality assurance and control procedures, developing demonstration projects where biomonitoring and passive sampling are undertaken alongside, organising proficiency testing schemes and interlaboratory comparison and, finally, establishing passive sampler-based assessment criteria in relation to existing EQS.

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Background: persons who are 65 years or older often spend an important part of their lives indoors thus adverse indoor climate might influence their health status. Objective: to evaluate the influence of indoor air quality and contaminants on older people’s respiratory health. Design: cross-sectional study. Setting: 21 long-term care residences (LTC) in the city of Porto, Portugal. Subjects: older people living in LTC with ≥65 years old. Methods: the Portuguese version of BOLD questionnaire was administered by an interviewer to older residents able to participate (n = 143). Indoor air contaminants (IAC) were measured twice, during winter and summer in 135 areas. Mixed effects logistic regression models were used to study the association between the health questionnaire results and the monitored IAC, adjusted for age, smoking habits, gender and number of years living in the LTC. Results: cough (23%) and sputum (12%) were the major respiratory symptoms, and allergic rhinitis (18%) the main selfreported illness. Overall particulate matter up to 2.5 micrometres in size median concentration was above the reference levels both in winter and summer seasons. Peak values of particulate matter up to 10 micrometres in size (PM10), total volatile organic compounds, carbon dioxide, bacteria and fungi exceeded the reference levels. Older people exposed to PM10 above the reference levels demonstrated higher odds of allergic rhinitis (OR = 2.9, 95% CI: 1.1–7.2). Conclusion: high levels of PM10 were associated with 3-fold odds of allergic rhinitis. No association was found between indoor air chemical and biological contaminants and respiratory symptoms.

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Aiming to introduce a multiresidue analysis for the trace detection of pesticide residues belonging to organophosphorus and triazine classes from olive oil samples, a new sample preparation methodology comprising the use of a dual layer of “tailor-made” molecularly imprinted polymers (MIPs) SPE for the simultaneous extraction of both pesticides in a single procedure has been attempted. This work has focused on the implementation of a dual MIP-layer SPE procedure (DL-MISPE) encompassing the use of two MIP layers as specific sorbents. In order to achieve higher recovery rates, the amount of MIP layers has been optimized as well as the influence of MIP packaging order. The optimized DL-MISPE approach has been used in the preconcentration of spiked organic olive oil samples with concentrations of dimethoate and terbuthylazine similar to the maximum residue limits and further quantification by HPLC. High recovery rates for dimethoate (95%) and terbuthylazine (94%) have been achieved with good accuracy and precision. Overall, this work constitutes the first attempt on the development of a dual pesticide residue methodology for the trace analysis of pesticide residues based on molecular imprinting technology. Thus, DL-MISPE constitutes a reliable, robust, and sensitive sample preparation methodology that enables preconcentration of the target pesticides in complex olive oil samples, even at levels similar to the maximum residue limits enforced by the legislation.

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Pesticide residues in food and environment pose serious health risks to human beings. Plant protection laws, among other things, regulate misuse of agricultural pesticides. Compliance with such laws consequently reduces risks of pesticide residues in food and the environment. Studies were conducted to assess the compliance with plant protection laws among tomato farmers in Mvomero District, Morogoro Region, Tanzania. Compliance was assessed by examining pesticide use practices that are regulated by the Tanzanian Plant Protection Act (PPA) of 1997. A total of 91 tomato farmers were interviewed using a structured questionnaire. Purposive sampling was used in selecting at least 30 respondent farmers from each of the three villages of Msufini, Mlali and Doma in Mvomero District, Morogoro Region. Simple Random Sampling was used to obtain respondents from the sampling frame. Individual and social factors were examined on how they could affect pesticide use practices regulated by the law. Descriptive statistics, mainly frequency, were used to analyze the data while associations between variables were determined using Chi-Square and logistic regression model. The results showed that respondents were generally aware of the existence of laws on agriculture, environment and consumer health, although none of them could name a specific Act. The results revealed further that 94.5% of the farmers read instructions on the pesticides label. However, only 21% used the correct doses of pesticides, 40.7% stored pesticides in special stores, 68.1% used protective gear, while 94.5% always read instructions on the label before using a pesticide product. Training influenced the application rate of pesticide (p < 0.001) while awareness of agricultural laws significantly influenced farmers’ tendency to read information on the labels (p < 0.001). The results showed further that education significantly influenced the use of protective gears by farmers (p = 0.042). Education also significantly affected the manner in which farmers stored pesticide-applying equipment (p = 0.024). Furthermore, farmers’ awareness of environmental laws significantly (p = 0.03) affected farmers’ disposal of empty pesticide containers. Results of this study suggest the need for express provisions on safe use and handling of pesticides and related offences in the Act, and that compliance should be achieved through education rather than coercion. Results also suggest establishment of pesticide disposal mechanisms and structures to reduce unsafe disposal of pesticide containers. It is recommended that farmers should be educated and trained on proper use of pesticides. Farmers’ awareness on laws affecting food, environment and agriculture should be improved.

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This work objective was to estimate the bioconcentration factor (BCF) of thirty six pesticides used in the Brazilian integrated apple production systems (IAP), in order to select priority pesticides to be monitored in apples. A hypothetical apple orchard was assumed and the model applied was according to Paraíba (2007) [Pesticide bioconcentration modeling for fruit trees. Chemosphere (66:1468-1475)]. The model relates BCF with plant and pesticide characteristics. The octanol-water partition coefficients of pesticides and their degradation rates in the soil were used. The following plant variables were considered: growth rate, total dry biomass, daily water transpiration rate, and total volume of water necessary to produce one kg of fresh fruit per plant. The pesticide stem-water partition coefficient and the transpiration stream concentration factor were calculated using equations that relate each coefficient with the octanol-water partition coefficient. The pesticide BCF in fruits is an important indicator of the pesticide affinity to fruits, and helps to improve the integrated production systems.

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The model presented allows simulating the pesticide concentration in fruit trees and estimating the pesticide bioconcentration factor in fruits of woody species. The model allows estimating the pesticide uptake by plants through the water transpiration stream and also the time in which maximum pesticide concentration occur in the fruits. The equation proposed presents the relationships between bioconcentration factor (BCF) and the following variables: plant water transpiration volume (Q), pesticide transpiration stream concentration factor (TSCF), pesticide stem-water partition coefficient (KWood,w), stem dry biomass (M) and pesticide dissipation rate in the soil-plant system (kEGS). The modeling started and was developed from a previous model ?Fruit Tree Model? (FTM), reported by Trapp and collaborators in 2003, to which was added the hypothesis that the pesticide degradation in the soil follows a first order kinetic equation. The model fitness was evaluated through the sensitivity analysis of the pesticide BCF values in fruits with respect to the model entry data variability.

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Homeowners, landowners, pesticide applicators, and farmers are concerned about pesticide drift. It may injure a homeowner’s garden or flowers or ruin a neighboring farmer’s crop. While no Maryland court has considered the issue of liability from pesticide drift, courts in other states have. These decisions provide some guidance on how a Maryland court might handle the issue. Depending on the facts of the drift case, pesticide applicators and farmers could owe damages for nuisance or trespass case, or for uses inconsistent with the pesticide label.

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Poster presented at the ICFC 2015 - International Conference on Food Contaminants. Infarmed, Lisbon, 14-15 April 2015

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On the one hand, pesticides may be absorbed into the body orally, dermally, ocularly and by inhalation and the human exposure may be dietary, recreational and/or occupational where toxicity could be acute or chronic. On the other hand, the environmental fate and toxicity of the pesticide is contingent on the physico-chemical characteristics of pesticide, the soil composition and adsorption. Human toxicity is also dependent on the exposure time and individual’s susceptibility. Therefore, this work will focus on the development of an Artificial Intelligence based diagnosis support system to assess the pesticide toxicological risk to humanoid, built under a formal framework based on Logic Programming to knowledge representation and reasoning, complemented with an approach to computing grounded on Artificial Neural Networks. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.

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Pesticides applications have been described by many researches as a very inefficient process. In some cases, there are reports that only 0.02% of the applied products are used for the effective control of the problem. The main factor that influences pesticides applications is the droplet size formed on spraying nozzles. Many parameters affects the dynamic of the droplets, like wind, temperature, relative humidity, and others. Small droplets are biologically more active, but they are affected by evaporation and drift. On the other hand, the great droplets do not promote a good distribution of the product on the target. In this sense, associated with the risk of non target areas contamination and with the high costs involved in applications, the knowledge of the droplet size is of fundamental importance in the application technology. When sophisticated technology for droplets analysis is unavailable, is common the use of artificial targets like water-sensitive paper to sample droplets. On field sampling, water-sensitive papers are placed on the trials where product will be applied. When droplets impinging on it, the yellow surface of this paper will be stained dark blue, making easy their recognition. Collected droplets on this papers have different kinds of sizes. In this sense, the determination of the droplet size distribution gives a mass distribution of the material and so, the efficience of the application of the product. The stains produced by droplets shows a spread factor proportional to their respectives initial sizes. One of methodologies to analyse the droplets is a counting and measure of the droplets made in microscope. The Porton N-G12 graticule, that shows equaly spaces class intervals on geometric progression of square 2, are coulpled to the lens of the microscope. The droplet size parameters frequently used are the Volumetric Median Diameter (VMD) and the Numeric Median Diameter. On VMD value, a representative droplets sample is divided in two equal parts of volume, in such away one part contains droplets of sizes smaller than VMD and the other part contains droplets of sizes greater that VMD. The same process is done to obtaining the NMD, which divide the sample in two equal parts in relation to the droplets size. The ratio between VMD and NMD allows the droplets uniformity evaluation. After that, the graphics of accumulated probability of the volume and size droplets are plotted on log scale paper (accumulated probability versus median diameter of each size class). The graphics provides the NMD on the x-axes point corresponding to the value of 50% founded on the y-axes. All this process is very slow and subjected to operator error. So, in order to decrease the difficulty envolved with droplets measuring it was developed a numeric model, implemented on easy and accessfull computational language, which allows approximate VMD and NMD values, with good precision. The inputs to this model are the frequences of the droplets sizes colected on the water-sensitive paper, observed on the Porton N-G12 graticule fitted on microscope. With these data, the accumulated distribution of the droplet medium volumes and sizes are evaluated. The graphics obtained by plotting this distributions allow to obtain the VMD and NMD using linear interpolation, seen that on the middle of the distributions the shape of the curves are linear. These values are essential to evaluate the uniformity of droplets and to estimate the volume deposited on the observed paper by the density (droplets/cm2). This methodology to estimate the droplets volume was developed by 11.0.94.224 Project of the CNPMA/EMBRAPA. Observed data of herbicides aerial spraying samples, realized by Project on Pelotas/RS county, were used to compare values obtained manual graphic method and with those obtained by model has shown, with great precision, the values of VMD and NMD on each sampled collector, allowing to estimate a quantities of deposited product and, by consequence, the quantities losses by drifty. The graphics of variability of VMD and NMD showed that the quantity of droplets that reachs the collectors had a short dispersion, while the deposited volume shows a great interval of variation, probably because the strong action of air turbulence on the droplets distribution, enfasizing the necessity of a deeper study to verify this influences on drift.

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The application of spectroscopy to the study of contaminants in soils is important. Among the many contaminants is arsenic, which is highly labile and may leach to non-contaminated areas. Minerals of arsenate may form depending upon the availability of specific cations for example calcium and iron. Such minerals include carminite, pharmacosiderite and talmessite. Each of these arsenate minerals can be identified by its characteristic Raman spectrum enabling identification.