IDEAS home Printed from https://ideas.repec.org/a/plo/pwat00/0000124.html
   My bibliography  Save this article

Leveraging high spatiotemporal resolution data of pesticides applied to agricultural fields in California to identify toxicity reduction opportunities

Author

Listed:
  • Nicol Parker
  • Ashley Larsen
  • Priyanka Banerjee
  • Arturo A Keller

Abstract

Pesticides remain a leading environmental hazard, imperiling aquatic and terrestrial ecosystems. Reducing pesticide toxicity is hampered by the ability to evaluate toxicity over large extents, the spatiotemporal resolution of pesticide use data, the ability to assess cumulative toxicity, and the identification of health/economic contributions of different pesticide application sites. We introduce the Environmental Release Tool, a sub-tool of the Pesticide Mitigation Prioritization Model, to advance these four areas. Using daily pesticide use reports required for agricultural applicators in California, we quantify the applied toxicity of pesticides to fish as well as aquatic invertebrates, nonvascular plants, and vascular plants. With the tool’s ability to quantify applied toxicity for hundreds of pesticides and watersheds simultaneously, we explore the significance of accounting for cumulative applied pesticide toxicity for application sites and watersheds statewide. Our results show that 14 pesticides account for 99.9% of applied toxicity, and 16 of 432 application site types introduce 90% of toxicity for taxa investigated. We also find cumulative applied toxicity within watersheds was significantly greater (p

Suggested Citation

  • Nicol Parker & Ashley Larsen & Priyanka Banerjee & Arturo A Keller, 2023. "Leveraging high spatiotemporal resolution data of pesticides applied to agricultural fields in California to identify toxicity reduction opportunities," PLOS Water, Public Library of Science, vol. 2(8), pages 1-23, August.
  • Handle: RePEc:plo:pwat00:0000124
    DOI: 10.1371/journal.pwat.0000124
    as

    Download full text from publisher

    File URL: https://journals.plos.org/water/article?id=10.1371/journal.pwat.0000124
    Download Restriction: no

    File URL: https://journals.plos.org/water/article/file?id=10.1371/journal.pwat.0000124&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pwat.0000124?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lindh, Thomas & Malmberg, Bo, 2007. "Demographically based global income forecasts up to the year 2050," International Journal of Forecasting, Elsevier, vol. 23(4), pages 553-567.
    2. Madden, Gary & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," Telecommunications Policy, Elsevier, vol. 31(1), pages 31-44, February.
    3. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    4. Kumar, V. & Sunder, Sarang & Sharma, Amalesh, 2015. "Leveraging Distribution to Maximize Firm Performance in Emerging Markets," Journal of Retailing, Elsevier, vol. 91(4), pages 627-643.
    5. Hu, Xincheng & Banks, Jonathan & Wu, Linping & Liu, Wei Victor, 2020. "Numerical modeling of a coaxial borehole heat exchanger to exploit geothermal energy from abandoned petroleum wells in Hinton, Alberta," Renewable Energy, Elsevier, vol. 148(C), pages 1110-1123.
    6. Garcia-Ferrer, Antonio & Bujosa-Brun, Marcos, 2000. "Forecasting OECD industrial turning points using unobserved components models with business survey data," International Journal of Forecasting, Elsevier, vol. 16(2), pages 207-227.
    7. Ariana Chang & Tian‐Shyug Lee & Hsiu‐Mei Lee, 2024. "Applying sustainable development goals in financial forecasting using machine learning techniques," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(3), pages 2277-2289, May.
    8. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
    10. Jaewon Kwak & Huiseong Noh & Soojun Kim & Vijay P. Singh & Seung Jin Hong & Duckgil Kim & Keonhaeng Lee & Narae Kang & Hung Soo Kim, 2014. "Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea," IJERPH, MDPI, vol. 11(10), pages 1-19, October.
    11. Armstrong, J. Scott & Collopy, Fred & Yokum, J. Thomas, 2005. "Decomposition by causal forces: a procedure for forecasting complex time series," International Journal of Forecasting, Elsevier, vol. 21(1), pages 25-36.
    12. Paroissien, Emmanuel, 2020. "Forecasting bulk prices of Bordeaux wines using leading indicators," International Journal of Forecasting, Elsevier, vol. 36(2), pages 292-309.
    13. Philippe St-Aubin & Bruno Agard, 2022. "Precision and Reliability of Forecasts Performance Metrics," Forecasting, MDPI, vol. 4(4), pages 1-22, October.
    14. Barrow, Devon K., 2016. "Forecasting intraday call arrivals using the seasonal moving average method," Journal of Business Research, Elsevier, vol. 69(12), pages 6088-6096.
    15. Drechsel, Katja & Scheufele, Rolf, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10/2010, Halle Institute for Economic Research (IWH).
    16. repec:cup:judgdm:v:14:y:2019:i:4:p:395-411 is not listed on IDEAS
    17. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    18. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    19. Aliyeva, Xeniya & Memon, Shazim Ali & Nazir, Kashif & Kim, Jong, 2024. "Energy consumption forecasting in PCM-integration buildings considering building and environmental parameters for future climate scenarios," Energy, Elsevier, vol. 310(C).
    20. Kumar, V. & Leone, Robert P. & Gaskins, John N., 1995. "Aggregate and disaggregate sector forecasting using consumer confidence measures," International Journal of Forecasting, Elsevier, vol. 11(3), pages 361-377, September.
    21. Rocha Souza, Leonardo & Jorge Soares, Lacir, 2007. "Electricity rationing and public response," Energy Economics, Elsevier, vol. 29(2), pages 296-311, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pwat00:0000124. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: water (email available below). General contact details of provider: https://journals.plos.org/water .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.