Literature DB >> 24651055

Environmentally Optimised Sprayer (EOS)--A software application for comprehensive assessment of environmental safety features of sprayers.

Grzegorz Doruchowski1, Paolo Balsari2, Emilio Gil3, Paolo Marucco4, Manfred Roettele5, Hans-Joachim Wehmann6.   

Abstract

Despite technological progress in pesticide application equipment, chemical crop protection continues to contribute to environmental pollution. Water is at risk of contamination with pesticides from point and diffuse sources and could be reduced to a great extent with a better sprayer design. The sprayer manufacturers and pesticide applicators need to take more responsibility for the prevention of water pollution and therefore they have to make environmentally responsible decisions at different stages, from designing to servicing sprayers. The objective of the presented work was to develop an interactive application that would support decisions made by sprayer manufacturers during the production process, and by pesticide applicators when selecting and operating the sprayers. The EOS (Environmentally Optimised Sprayer) is an application evaluating the risk mitigation potential of sprayers based on their technological features, within five risk areas, representing sources of pollution: (i) Inside Contamination; (ii) Outside Contamination; (iii) Filling; (iv) Spray Loss & Drift; (v) Remnants. The evaluator completes the EOS questionnaire by checking for the technical solutions identified in the evaluated sprayer and the result reflects the sprayer quality in terms of potential environmental risk mitigation. The EOS tool also proved its awareness raising facility and educative value when used during training activities and university courses.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  E-learning; Environmental risk; Risk mitigation; Training; Water protection

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Year:  2014        PMID: 24651055     DOI: 10.1016/j.scitotenv.2014.02.112

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Automated Mobile Hot Mist Generator: A Quest for Effectiveness in Fruit Horticulture.

Authors:  Dmitriy Khort; Alexey Kutyrev; Nikolay Kiktev; Taras Hutsol; Szymon Glowacki; Maciej Kuboń; Tomasz Nurek; Anatolii Rud; Zofia Gródek-Szostak
Journal:  Sensors (Basel)       Date:  2022-04-20       Impact factor: 3.576

  1 in total

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