Fk rh n n

Figure 6.16. Comparison between the original direct estimates of the damage costs per ton of NOx emission with correlation best fit. ln( Cost) = 0.5144n(ozone) + 0.790.ln(population) + 5.99 where ozone is the 2nd 1-hour maximum in ppm; population expressed in 1000s.

Sources: (Pace) Ottinger et al., 1990; (CEC) California Energy Commission, 1993; (S&K) Small and Kazimi, 1995; (MN) Minnesota Public Utility Commission, 1997; (M&D) McCubbin and Delucchi, 1999.

TABLE 6.12. Using Societal Costs to Weigh Environmental Impacts

Source

Geographic Reference

Effect

Unit

PM10

SOx

NOx

VOCs

CO

McCubbin and

United States

Health

$/kg

46.96

30.25

6.53

0.49

0.04

Delucchi

(1999);

Delucchi

et al. (2002)

Small and

Los Angeles

Health

$/kg

126.39

138.85

13.48

4.47

Kazimi

(1995)

CEC (1993)

CA South

Health and

$/kg

68.01

10.60

20.68

9.87

0.00

Coast

other

EPS (Steen,

OECD

Health and

ELU/kga

36.00

3.27

2.13

2.14

0.03

1999)

other

EI-99

Europe

Health

DALY/kg

3.75E-04

5.46E-05

8.87E-05

6.46E-07

(Goedkoop

(respiratory)

and

Spriensma,

2000)

$/kgb

25.00

3.64

5.91

0.04

bAssuming an economic value of $66,667 per DALY (disability-adjusted life year) based on a statistical value of life (S VL) of $5 million divided by a life expectancy of 75 years.

bAssuming an economic value of $66,667 per DALY (disability-adjusted life year) based on a statistical value of life (S VL) of $5 million divided by a life expectancy of 75 years.

in the original studies, not inflation-accelerated. The EPS (Environmental Priority Strategy in product development) damage estimates (Steen, 1999) are expressed as ELU (Environmental Load Unit) per kg, where one ELU is approximately equal to one 1998 ECU (European Currency Unit, €). Note that EI-99 weighting factors (Goedkoop and Spriensma, 2000) for health damage were reported not in monetary units, but in terms of loss in disability-adjusted life years (DALY) per kg of emission. However, the EI-99 health damage factors were also converted to dollar figures in Table 6.12, to facilitate comparison with monetary damage estimates from other studies, by assigning a literature-based monetary value on their original damage estimates.

Cost estimates and weighting for the different air pollutants vary among the different studies in Table 6.12, which can be attributed primarily to the differences in geographical reference and assumptions. As in our earlier discussion, broad-based cost estimates (e.g., for overall United States, Europe, or OECD member states) tend to be lower than specific urban estimates (e.g., for Los Angeles).

There exists a certain degree of consistency among the studies. All sets of estimates clearly point to airborne particles (PM10 is the common categorization among the different studies in Table 6.12) as having among the highest marginal damage costs per kilogram emitted. Carbon monoxide (CO) is also consistently ranked the lowest in terms of cost per kilogram emitted. However, the order of weighting differs among the different studies for the other pollutants, as are the weightings themselves. Thus, in using societal costs in weighting various environmental impacts, one must select one or a few sets of estimates that best match the project's geographic settings as well as one's corporate philosophy. Uncertainties in the estimates must be properly taken into account through sensitivity analysis.

6.2.4.7 Conclusions. Estimations of societal costs (and benefits) can be meaningful sustainability indicators for management in predicting where future costs may arise, and they can be useful in facility design and optimization with respect to "rolling up" environmental impact metrics to include these potential future costs. The process of estimating societal costs, while methodologically complex, is most important not in the acceptance of a final numerical value; that can always be challenged. Instead, they should be viewed in terms of order-of-magnitude and direction of societal concerns. Understanding this, looking differently at how business decisions impact the communities from which they are granted license to operate and to grow, and engaging those who are making business decisions to recognize that there are real costs to the company associated with externalities, is an important step in ensuring sustainability.

Acknowledgements. We gratefully acknowledge Gulf Coast Hazardous Research Center (GCHSRC Project 051LUB2810 Extension), which partially funded this work.

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