DISCLAIMER: The tools, as they currently stand, are provided for research and informational purposes only. The underlying models, assumptions, data sources, and methodologies are experimental and might have not yet been peer-reviewed or independently validated. Outputs may be incomplete, uncertain, or inaccurate and should be interpreted with caution. The tools do not provide regulatory, medical, legal, toxicological, or professional risk assessment advice. For the time being, it must not be used as a substitute for expert judgment, regulatory review, or established risk-assessment frameworks, nor relied upon for decision-making related to human health, environmental protection, occupational safety, product registration, compliance, or policy.
Use of these tools for unlawful, harmful, misleading, or unethical purposes—including but not limited to regulatory circumvention, misrepresentation of risk, or inappropriate application to real-world pesticide use decisions—is strictly prohibited. The tool is provided “as is,” without warranties of any kind, express or implied, including but not limited to accuracy, fitness for a particular purpose, or non-infringement.

National maps - air

Author: Daniel Martins Figueiredo (d.m.figueiredo@uu.nl)
Last update: 05/02/2026

This tool demonstrates calculated concentrations in air for a selected set of pesticides across  three countries. The tool can be used to identify areas where concentrations are higher and mapped values can be used as input to calculate exposure from inhalation and to link to epidemiological studies.

To estimate the airborne pesticide concentrations at a national scale, it is crucial to assess both the initial spray drift (i.e. pesticide that moves outside the area of application) and subsequent volatilization of active substances (AS) following application. The proportion of AS entering the atmosphere depends on factors such as application method, meteorological conditions, and crop canopy characteristics.

First, each agricultural field (polygon) is assigned an AS mass based on crop type and pesticide application data. Second, each individual field is paired to the closest meteorological station. Next, pesticide dispersion in the air is modeled using a short-range Gaussian plume approach, similar to Lebeau et al. (2011). Volatilization from soil and plants follows the same equations as the PEARL model (Van den Berg et al. 2016). The dispersion model incorporates real-world meteorological data, including wind speed, humidity, and atmospheric stability, to simulate the spread of pesticides in the air.

For each country, different simulations were made to test usability of the modelling framework, computational efficiency, and uncertainty in model output. Moreover, this approach shows that to produce air concentration maps there are different ways the model can be ran, and depending on the setting the output can become different:

For the Netherlands, simulations were made multiple times to account for variability within periods when farmers could have applied a pesticide. The output is an average value at 10meters downwind from each field and then all values were averaged in a 1kmx1km grid resolution. Here, meteorological conditions were set (based on expert input) for: No rain fall during spraying; temperatures above 5 and below 28 degrees Celsius; Relative humidity above 40%; Wind speed below 5 meters per second.
For Czech Republic, given the smaller number of agricultural plots per km2, air concentrations were estimated at 50meters distance around the centroid of each field for the 8 most predominant wind directions and assuming a low droplet size class of 30 μm. The output is an average value from all fields for each 2.5kmx2.5km grid resolution.
For Denmark, air concentrations were estimated similarly as for Czech Republic. The output is an average value from all fields for each 1kmx1km grid resolution.
Important to note that only downward spraying was included in this simulation.

References:
  • Figueiredo, D. M., Duyzer, J., Huss, A., Krop, E. J., Gerritsen-Ebben, M., Gooijer, Y., Vermeulen, R. C., 2021. Spatio-temporal variation of outdoor and indoor pesticide air concentrations in homes near agricultural fields. Atmospheric Environment, 262, 118612. https://doi.org/10.1016/j.atmosenv.2021.118612.
  • Lebeau, F., Verstraete, A., Stainier, C., Destain, M. 2011. RTDrift: A real time model for estimating spray drift from ground applications. Computers and Electronics in Agriculture, 77(2), 161-174. https://doi.org/10.1016/j.compag.2011.04.00
  • van den Berg, F., Tiktak, A., Boesten, J.J.T.I., van der Linden, A.M.A. 2016. PEARL model for pesticide behaviour and emissions in soil-plant systems; Description of processes. The Statutory Research Tasks Unit for Nature & the Environment (WOT Natuur & Milieu). WOt-technical report 61. https://edepot.wur.nl/377664.