Golf turf managers often have many options for controlling destructive turf pests. Many factors are evaluated before choosing a particular control option. Factors such as cost, efficacy, and turf safety are often part of the knowledge base of the golf turf manager, or this information is readily obtainable from sales staff, university extension sources, magazines, trade articles, etc. The golf turf manager evaluates this information and then makes a decision regarding the choice of pesticide or biological control option for a particular pest. Information regarding the potential environmental impact of using a particular pesticide or biological control option is much more difficult to obtain, and hence most turf managers do not include information on environmental safety in their decision-making process. The purpose of this project is to provide golf turf managers with information that will permit them to include environmental safety into their decision-making process just as they would cost, efficacy, etc. The challenge of this project is to take the enormous amount of information available regarding pesticide impact on the environment and reduce this to a level that is scientifically valid and yet can be readily used by golf turf managers. Several approaches have been taken by researchers to reduce data to a more usable format. One with some familiarity to the turfgrass community is the EIQ (Environmental Impact Quotient) developed by Kovach et al. (1992) to assess pesticide impact in agricultural settings. The EIQ is an algebraic model that reports a single composite number to represent the environmental impact of a pesticide. The value of the model is its simplicity; each pesticide is awarded a single numerical score. However, this simplicity has also resulted in criticism of the model for precisely this reason; i.e., it does not quantify potential risk. The model can be broken out into three components—farmworker, consumer, and ecological—which reduces some of the criticism of oversimplification. Similarly, in the Netherlands, researchers have developed an environmental yardstick to estimate the risk associated with using a particular pesticide (Reus and Leendertse, 2000). The yardstick estimates risk for three different areas: risk of groundwater contamination, risk to soil organisms, and risk to aquatic organisms. Potential risk is estimated by impact points with the more impact points awarded a pesticide, the higher its impact on the environment. The environmental yardstick was introduced for field crops in 1994 and a separate yardstick for greenhouse crops was introduced in 1997. The yardstick is a modified risk assessment tool that calculates the expected concentration of the pesticide in the targeted area, e.g. groundwater, versus the drinking water standard for that pesticide. Most models can be classified into two general categories, one of which uses an approach similar to the EIQ, which manipulates the physico-chemical properties, environmental toxicity data, and human health data into a numerical ranking of pesticide safety. The second approach, as exemplified by the Netherlands yardstick, is to use a simple model to estimate pesticide concentration in groundwater, surface water, foliage, or other area of interest, and then compare the estimated concentration to the concentration estimated to have an environmental impact. This ratio is then put into context for the end user. This is considered a risk assessment model and other researchers have used variations on this approach (Padovani et al.,2004; Peterson, 2006). More in-depth, site-specific models go beyond the scope of this project. This project is aimed at developing a model that will allow turf managers across the United States to rapidly and conveniently ascertain the relative environmental risk of using specific pesticides in a turf care program. Further, the model should allow the turf manager to differentiate the relative risks on specific areas of concern such as groundwater, surface water, wildlife, and human health.