All the data from these 46 new sites were included back to 1986. Yet this significant shift in the database produced results which were marginally lower, but substantially the same, for all the model variations with an R2 greater than 0.5. Second the conclusiveness of statistics-based studies rely on randomness and independence assumptions, and we believe there is little evidence to support the claim that the meteorological effects are so correlated with the oxyfuel effects that they significantly bias the results towards too high of an implied oxyfuel impact. Figures 1 and 1a in our report clearly show that the mean observed CO concentrations for 1992 were above the trend line for our Model 12 and that the 1993 observations were much lower than the regression line. Yet it can be seen in these same figures that the mean 1991 and 1994 data were nearly equivalent to the 1992-1993 pair but apparently providing a bias in the opposite direction.
Every data point is given equal weight along the regression line.
That is, a 1994 data point counts as much as a 1993 data point even if the oxyfuel program was initiated between 1992 and 1993. For example, in Figure 1 the 1993 data can be thought of as pulling the regression lines down just as much as the 1994 data might be considered to be pulling the regression lines up. Since these particular data by themselves clearly pull the regression lines toward a higher implied oxyfuel impact, the expected result is a lower implied value for the oxyfuel effect. Indeed, this intentional biasing of the data reduced the computed oxyfuel impact down to approximately 10 percent from the approximately 13 percent seen when the 1996 data were included. Judging by Figure 1a we would expect a similar increase to about 16 percent if we were to selectively remove the 1991 and 1994 data that clearly bias the implied oxyfuel effect in the opposite direction to the 1992 and 1993 data.