Air pollution and buildings: An estimation of damage costs in france
The total damage cost is the sum of renovation cost and amenity loss. We show that amenity loss can be inferred from renovation expenditures without carrying out a contingent valuation; the amenity loss is approximately equal to the renovation cost. We review the methodologies for calculating air po...
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Veröffentlicht in: | Environmental Impact Assessment Review 1999-07, Vol.19 (4), p.361-385 |
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Sprache: | eng |
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Zusammenfassung: | The total damage cost is the sum of renovation cost and amenity loss. We show that amenity loss can be inferred from renovation expenditures without carrying out a contingent valuation; the amenity loss is approximately equal to the renovation cost. We review the methodologies for calculating air pollution damage to buildings, as well as the data available for their implementation in France. There are no inventories of building materials and surface areas for France, but we have been able to obtain data for frequencies and costs of renovation activities. By regressing these data we derive a “combined dose-response function” for the renovation cost as a function of pollution. We find that the most important variables are income and concentration of particles, whereas a correlation with SO
2 is not clear. This could be understood if most renovation expenditures in France are occasioned by soiling (primarily due to particles) rather than corrosion (primarily due to SO
2). For historical buildings and monuments we have been able to find only data for total national expenditures; they imply that the cost of pollution damage is somewhat smaller than for utilitarian buildings. Based on detailed models for atmospheric dispersion and for the geographical distribution of buildings, we calculate the damage cost caused by individual sources of pollution. We compare our results with other estimates in the literature, and we discuss the uncertainties. We also find that, compared to the cost of health damage, the cost of damage to buildings is smaller by about two orders of magnitude. |
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ISSN: | 0195-9255 1873-6432 |
DOI: | 10.1016/S0195-9255(98)00040-7 |