Power plants near Fairbanks Alaska emit PM2.5 pollution into the surrounding air. Assume that one of these power plants is located 7 km directly downwind of the powerplant. Assume the equivalent stack height is 63 meters tall and assume that you can model the dispersion of the PM2.5 using the Gaussian Plume model. (a) (12 pts) During the fall/winter, the surface windspeeds are 4 m/s and you often have cloudy days, so the stability class of the atmosphere is D. In the later spring and summer, the windspeed is a little lower and there is more sunlight, so you have a stability class of B. Using the Gaussian plume model, show which season has the greatest dispersion (i.e.. the largest amount of spreading in the pollution plume). Calculate the dispersion coefficients for each season and then explain which conditions lead to greater dispersion and why. Note, tables that may be helpful here are provided at the end of the exam. (b) (4 pts) Draw two figures demonstrating possible differences in the plume behavior between the two seasons and discuss if the town of Fairbanks will be expected to experience higher concentrations of PM2.5 from the power plant in the spring/summer or the fall/winter. Note that you need to draw the figures, but no calculations are required here. You should provide a qualitative explanation. (c) (4 pts, 2 pts each) Say the town experiences an inversion layer. (i) (ii) Would you expect the air quality to be better or worse with the inversion layer? Why? What factors would determine whether the power plant is contributing to the pollution in the town during the inversion layer? Note that no calculations are required here for either (i) or (ii), this is a qualitative answer. Tables These tables are screenshots directly from the lecture material. The circles and highlights refer to the example problems in the lectures and should not necessarily be used to solve the problems on this exam. WINDSPEED Stability Class A B C D E F Stability A HECKEY B D F Description Very unstable 0 19 19 Moderately unstable Slightly unstable. Australia 92 0 2 China 83 France India 10 78 2.5 81 Japan 61 27 1 Norway United 75 Kingdom United 71 States Neutral Slightly stable Stable a 213 156 104 68 50.5 34 8 15 12 16.5 12 99 6 10 C 32 40 27 41 40 0.15 36 0.15 Country Fossil Nuclear Renewables Efficiency fuel (%) (%) (%) 0.20 440.8 106.6 61.0 33.2 22.8 14.35 0.25 0.40 0.60 Table 6.6. Electricity generation, energy mix, MJ oil per kW.hr, and CO per kW.hr x 1 km my[(n)] 1.941 1.149 0.911 0.725 0.678 0.740 d MJ OE[(b)] per kW.hrl(d)] 10.0 9-3 0.9 10.8 5-4 6.6 7.1 0.71 0.66 0.06 CO[(c)], kg per kW.hrl(d)] 0.77 0.38 f 9.27 3.3 0.47 0 -1.7 -1.3 -0.35 0.54 C 459.7 108.2 61.0 44.5 55.4 62.6 x 1 km d 2.094 1.098 0.911 0.516 0.305 0.180 f -9.6 2.0 0 -13.0 -34.0 -48.6 (a) Conversion efficiency of fossil fuel to electricity. (b) MJ of fossil fuel (oil equivalent) used in energy mix per kW.hr of delivered electricity from all sources. (c) CO2 release per kW.hr of delivered electricity from all sources. (d) 1 kW.hr is 3.6 M.J. 10