Operator exposure modeling

PRINCIPLES OF OPERATOR EXPOSURE MODELLING 175 PHED PESTICIDE HANDLERS EXPOSURE DATABASE 176 General Description 176 Qnality of Data 177 Formnlations and Use Scenarios 177 Use in Risk Assessment 178 Exposnre Rednction Measures 178 Model Updates 179 Comments on the Model 179 GERMAN MODEL 180 General Description 180 Formulations and Use Scenarios 181 Use in Risk Assessment 182 Exposure Reduction Measures 182 Model Updates 182 Comments on the Model 183... 

UK-POEM UK PREDICTIVE OPERATOR EXPOSURE MODEL General Description 183 Formulations and Use Scenarios 183 Use in Risk Assessment 184 Exposure Reduction Measures 186 Model Updates 186 Comments on the Model 186 DUTCH MODEL 187 General Description 187 Formulations and Use Scenarios 187 Use in Risk Assessment 188 Exposure Reduction Measures 189 Model Updates 189 Comments on the Model 189 EUROPOEM DATABASE 189 General Description 189 Formulations and Use Scenarios 190 Use in Risk Assessment 192 Exposure Reduction Measures 194 Model Updates 194 Comments on the Model 194... 

EUROPOEM (1996). The Development, Maintenance and Dissemination of a European Predictive Operator Exposure Model (EUROPOEM) Database, AIR3 CT93-1370, TNO-BIBRA International, Carshalton, Survey, UK. 

POEM (1992). UK Predictive Operator Exposure Model (POEM) A Users Guide, Pesticides Safety Directorate, York, UK. 

The establishment of a statistically sound data-set on usage allows an evaluation of likely operator exposure, as realistic work rates can be derived from the data collected, such as average field size, area sprayed per operator per day, amount of pesticide handled per day, etc. All of these factors are vital in refining predicted operator exposure models, and are discussed at length by Hamey (2001). 

Mathematical exposure models applied to urban areas have been presented by Jensen [23], Kousa et al. [20] and Wu et al. [24]. The model presented by Jensen [23] is based on the use of traffic flow computations and the operational street pollution model (OSPM) for evaluating outdoor air pollutants concentrations in urban areas. The activity patterns of the population have been evaluated using... 

The application of pesticides is widespread in agriculture and elsewhere, and the concomitant risks depend on their toxicity, and duration and frequency, as well as the level of exposure (Henderson et al., 1993 Krieger and Ross, 1993). Exposure may be incidental or almost continuous. This is true not only for workers (occupational exposure), but also for the general public and people who may be considered as bystanders, who are not involved in the actual occupational activities with pesticides, but are close enough to get exposed. In this present chapter, only operator exposure will be discussed because agricultural re-entry modelling is discussed in Chapter 2 and residential post-application exposure modelling in Chapter 6 of this book. 

Kangas, J. and S. Sihvonen (1996). Comparison of Predictive Models for Pesticide Operator Exposure, TemaNord 560, Nordic Council of Ministers, Copenhagen, Denmark. 

Lunchick, C. and P.Y. Harney (1998). Operator exposure different models give different answers - or do they , in Conference Documentation Registration of Agrochemicals in Europe, IBC Global UK Conferences Limited, London. 

Ross, J.H. and M.H. Dong (1997). The use of probabilistic modeling to determine reentry intervals, in Operator Exposure and Agrochemicals, IBC UK Conferences Workshop Communication, 22-24 April, London. 

The harmonization of the regulation of plant protection products throughout the EU has resulted in harmonized data requirements for occupational, bystander and worker exposure assessment. These requirements are outlined in Annex III of Council Directive 91/414/EEC. This annex lists product-related exposure data requirements and, consistent with the tiered approach outlined above, provides some advice as to when different data are required (Harney, 2000). An estimation of operator exposure, using, where available, a suitable calculation model, must always be made and reported. Actual exposure data must be provided where the risk assessment indicates that a health-based value is exceeded or where no appropriate calculation model exists to estimate exposure. 

One of the major components of the operational dose uptake assessment process has been the development of a detailed plant operational model broken down to an individual task level. Preparation of the model commenced early in the project design and drew on the extensive experience gained by BNFL over many years of designing, operating, and decommissioning plutonium plants and more recent experience of operating MOX fuel fabrication plants. This experience provided valuable data on both the manpower requirements and task durations for both process and maintenance operations and on the main potential short- and long-term sources of operational exposure and how these exposures could be adequately controlled. 

Pharmacy preparation from raw materials or through adapting of products, as well as reconstitution of medicines accounts for numerous different preparation methods, batch sizes and operators. Some exposure measurements have been performed with these methods for small-scale preparation in pharmacies [52], which led to a specific exposure model for small-scale preparation in pharmacies for inhalation exposure. 

Exposure-response modeling is not standardized and the results can be operator and model dependent. 

For the purposes of the BPD a project was commissioned by DG Environment and conducted by Institutes/ organisations from 6 European Member States, together with representatives from industry. The aims of this project were to develop relevant exposure scenarios of humans to biocidal products and to develop operational predictive models for the purposes of authorisation of biocidal products in each of the 23 product types. The report and proposed models from this project is expected to be finalised in mid-2003. 

Figure 4. System operator—data transport system— exposure model.

---