PAPERS ~~~~~~~~~~~PAPER NO.78 41VP ~~TOWARD ENVIRONMENTALLY AND SOCIALLY SUSTAINABLE DEVELOPMENT POLLUTION MA-NAGEMENT S E RIES. Eviron-menta Costs 7.5 5.800 -1.682 R = A/if (B.4) Neutral < 2 7.778 -1.592 2-5 6.843 -1.600 where A is the area of the city in square 5-7.5 6.245 -1.619 kilometers (the city need not be circular). The > 7.5 5.893 -1.624 parameters c hknit, p(hkn, and yhk., are taken from Tables B.1, B.2, and B.3. The frequency Stable parametersf refer to the contents of Table B.4. 2< 5 7.256 -.8241 5-7.5 6.976 -1.433 If data on wind speed and atmospheric stability Sources: Dennis (1978); WHO (1989); Sebastian, Lvovsky, and de are not available for the area under Koning (1999). Pollution Management Series 73 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities Table B.2 Coefficients for the dispersion model: Table B.4 Example of a completed meteorological Medium-stack point sources frequency factor table Atmospheric Atmospheric stability and wind Frequency stability and speed (miles per second) factor (fl wind speed Unstable (miles per second) 13 < 2 0.0 Unstable 2-5 f2 =0.0 < 2 6.391 -1.492 5-5 fi3 = 0 2-5 6.075 - 1.724 5-7.5 f3 = 0.1 5-7.5 5.925 -1.712 >7.5 > 7.5 5.800 -1.682 Neutral Neutral < 2 f2= 0.1 < 2 7.778 -1.592 2-5 f22= 0.2 2-5 6.843 -1.600 5-7.5 f23 = 0.2 5-7.5 6.245 -1.619 > 7.5 f24 =O.1 > 7.5 5.893 -1.624 Stable Stable < 2 f3 = 0.I < 2 7.398 -0.872 2-5 f32 = 0.1 2-5 7.256 - 1.241 57.5 f33 = °.° 5-7.5 6.976 -I .433 Note: Frequency factors must sum to unity. Sources: Dennis (1978); WHO (1989); Sebastian, Lvovsky, and de Sources: Dennis (1978); WHO (1989); Sebastian, Lvovsky, and de Koning (1999). Koning (1999). Calibration of the Model In this context, calibration means adjusting the results of the model such that the predicted Table B.3 Coefficients for the dispersion model: centrs of the v arious pouninthe - ~~~~concentrations of the various pollutants in the High-stack point sources modeling results match the concentrations Atmospheric actually measured. Calibration is highly wind speed desirable; even in the most sophisticated of (miles per second) dispersion models, there can be a large Unstable discrepancy between predicted and actual < 2 1.171 0.855 -0.284 concentrations. Ideally, calibration of the 2-5 1.034 0.427 -0.230 dispersion model described above requires both 5-7.5 0.600 0.327 -0.216 > 7.5 0.647 0.251 -0.232 an emissions inventory of the city itself and a > 75067 021 0measure of background (or rural) Neutral concentrations. The procedure is first to define < 2 -30.801 19.537 -3.117 and then to adjust a scaling parameter in the 2-5 - 13.820 7.981 - 1.226 equation linking emissions and concentrations 5-7.5 -9.381 6.243 -I. 124 such that, given the emissions inventories for > 7.5 -6.275 4.250 -0.821 particular pollutants, the model reproduces Stable exactly the increase in ambient concentrations < 2 -18.380 3.978 0.000 above background levels. If a complete 2-5 -44.510 20.894 -2.654 emissions inventory and sufficient data on Sources: Dennis (1978); WHO (1989); Sebastian, Lvovsky, and de background levels of pollution are not available, calibration should at least ensure that the 74 Environment Department Papers The Dispersion Model computed concentrations arising from fuel use concentrations of sulfates and nitrates would do not exceed concentrations of those pollutants fall in a plausible range for a given city based on based on ambient measurements and are in a testing and cross-checking several parameters. range of a plausible proximity to measured In the version reported in this paper, shares of values. In this analysis the model was calibrated secondary sulfates in fuel-induced PM10 vary for S02, ambient levels of which were assumed across cities from 13 to 17 percent; shares of to be largely caused by fuel combustion within a secondary nitrates have a larger range, from 3 to city. For Krakow and Shanghai the assumption 22 percent. The contribution of sulfates to PM,0 was that about 20 percent of S02 comes from is greatest in Krakow, where large volumes of outside sources (large power plants). coal are used, whereas nitrates make the highest contribution to PM10 in Bangkok. Overall, the Modeling Secondary Sulfates and Nitrates contribution of secondary particulates to The process of formation of secondary sulfates exposure to PM10 from fuel use for the whole and nitrates is complex, and an accurate sample of six cities is 25 percent. That figure is approach requires sophisticated dispersion/ the share of secondary sulfates and nitrates in photochemical modeling that is beyond the incremental PM10 levels that is attributed to fuel capacity of a rapid assessment exercise. The combustion only; it does not represent the approach taken here was to review and draw on ambient level observed in these cities. This available evidence (based on chemical analyses estimate seems to provide a reasonable, and of the ambient air or on appropriate dispersion rather conservative, proxy that is believed to be modeling) on the species composition of fine a better alternative than simply ignoring the particulates in various locations. Secondary contribution of secondary particulates. sulfates and nitrates (not emitted as such but formed in the air from SO2 and NO emissions) It should be emphasized that the purpose of this are functions of the ambient levels of exercise is to estimate the damage costs from pollutants. A modeling of the Shanghai area fuel combustion, not the levels of secondary estimated that average concentrations of particulates per se. Thus, the robustness of the sulfates are about one-sixth of average SO approach should be evaluated in the context of concentrations (Streets et al. 1997). 2 the overall assumptions and results of this rapid assessment. Note that the PMI,-based dose- While we recognize that this relationship will response functions were applied to the vary across locations, depending on climate and estimated contributions of secondary sulfates meteorological conditions, we took a very and nitrates, not the existing dose-response primitive approach in our calculations. Sulfate functions for sulfates and PM2,5, which are levels were assumed to be 16 percent of the much higher. Thus, the effective contribution of estimated SO2 levels, and, after testing a secondary particulates to the health effects and number of assumptions, levels of secondary damage costs of fuel use was assumed to be nitrates were modeled at 4 to 6 percent of the significantly lower than the percentages of PM 10 estimated NOX concentrations in the individual given above. This means that the modeled cities in question. For each city, these crude contribution of secondary particulates to health assumptions were validated by the analysis of damage from PM10 exposure is at the lower end data on the levels of sulfates and nitrates in of the possible contribution and does not various places in relation to the composition of overstate the social costs of fuels. combustion sources, to ensure that the resulting Pollution Management Series 75 Annex C Estimating Predicted Willingness to Pay (WTP) to Avoid Morbidity In TER (1996), WTP estimates are determined keeping with the results of Brajer et al. (1991), for each of several health states. A translog there appears to be an interaction between the model is fitted to the data, and it can be shown QWB score and the duration of the illness. that the following simplification is acceptable: This equation is next used to predict willingness (C. 1) to pay to avoid health states relevant to the air ln(WTP) = 3.68 + 2.75 * [ln(QWB )12 ' pollution epidemiology literature that are not - 1.55*1n(QWB)*ln(DAYS) dealt with in the morbidity valuation literature. To do so, the QWB score corresponding to each where WTP is willingness to pay in 1993 U.S. health state and a statement regarding the dollars; QWB is quality of well-being; and duration of the illness are required (Table C.1). DAYS is the duration of the illness in days. The The predicted WTP for the morbidity end- estimated regression has an R2 of 0.89 and, in points related to air pollution are given in Table Table C. 1 Derivation of quality of well-being (QWB) scores for different health states identified in the air pollution literature Physical Social QWB Health status Mobility activity activity Symptom score' Respiratory hospital 0.090 0.077 0.106 0.299 0.428 admissions Asthma attacks 0 0.060 0.061 0.257 0.622 Emergency room visits 0.062 0.077 0.061 0.299 0.501 Bed disability days 0 0.077 0.061 0.257 0.605 Lower respiratory illness in 0 0 0 0.257 0.743 children Respiratory symptoms 0 0 0 0.257 0.743 Cough days 0 0 0 0.257 0.743 Chest discomfort days 0 0 0 0.299 0.701 Minor restricted activity 0 0 0 0.257 0.743 days Eye irritation 0 0 0 0.230 0.770 Phlegm 0 0 0 0.170 0.830 Note: a. The QWB score is I minus the sum of the weights in the preceding columns. Source: Kaplan et al. (1993). Pollution Management Series 77 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities C.2. Restricted activity days (RADs) are defined (MRAD), employing the weights 0.4 and 0.6, as a weighted average of a bed disability day respectively. (BDD) and a minor restricted activity day Table C.2 Willingness to pay to avoid health states identified in the air pollution literature Duration Predicted WTP Health status QWB score (days) (1990 U.S. dollars) Respiratory hospital admissions 0.428 9.5 4,275 (RHAs)a Asthma attacks 0.622 1 63 Emergency room visits 0.501 1 126 Bed disability days (BDDs) 0.605 1 69 Lower respiratory illness in 0.743 1 44 children, cases Respiratory symptoms 0.743 1 44 Cough days 0.743 1 44 Chest discomfort days 0.701 1 50 Minor restricted activity days 0.743 1 44 (MRADs) Eye irritationb 0.770 1 41 Phlegmb 0.830 1 38 Restricted activity days (RADs) -C I 53 Notes: a. Average duration of RHAs refers to average duration of admissions due to emphysema and bronchitis (National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Md.). b. Values for eye irritation and phlegm were not used in this six-city exercise but are given for further applications of the approach. c. RADs are a weighted average of BDDs and MRADs. Sources: TER (1996); authors' calculations. 78 Environment Department Papers Annex D Values for Visibility, Soiling, and Corrosion Visibility context of urban airsheds is discussed by Noll et al. (1968). The meteorological range of visibility Its or tistinguis wee the is inversely proportional to the scattering biveanef wofk visibili in, the citesamwher pioale coefficient of the particles (assuming that the parks, where the purpose of a visit is mainly absorption of light by particles and gases is parks wher the urpoe of visi is minlyinsignificant). If it is assumed that the scattering recreational sightseeing. This section deals coefficintt is por utoa toat e m asseof exclusively with the former set of benefits. It is coefficient is proportional to the mass of perhaps not valid to suppose that since particles per cubic meter of air, a very tractable individuals spend most of their time at home or relationship exists. This last step is a at work, residential values are of greater simplification, since the scattering coefficient is importance than recreational values. a function not only of the total mass of particles Nevertheless, the dispersion model used in this but also of their size. report deals exclusively with air pollution Notwithstanding the problem of differences in within the urban area itself (see Annex B), as the the sizes of particles, the following relationship, extent to which emissions arising from attributable to Noll et al. (1968), has been tested particular urban conurbations degrade visibility and has been found to provide a satisfactory in particular areas of major recreational interest andohation f provisatinfa cannot be known. Furthermore, even if because approximation of prevailing visibility in a of the aesthetic qualities of nearby national variety of locations: parks, visibility possesses greater value in that context, it is difficult to see how the existing V =884.8 (D. 1) literature relating to visibility in the Grand M Canyon National Park (Balson, Carson, and Mitchell 1990) or the national parks of the where V, measured in miles, is prevailing southwestern United States in general (Schulze visibility (defined as the greatest visibility that et al. 1983) could easily be adapted for use in is attained or surpassed around at least half of the context of other recreational areas, each of the horizon circle, not necessarily in continuous which is unique. sectors, at noon in dry conditions) and M is the concentration of particulate matter in hg/m3. Information on visibility ranges in urban areas Note that in this relationship, as pollution of developing countries and on how they might increases, the marginal effects on visibility be affected by differences in pollution is not decrease. This point is extremely important in readily available. Nonetheless, there exists a what follows. Also, the relationship is close relationship between the concentration of dependent on ambient humidity being below 70 particles, their light-scattering coefficient, and percent of the saturation point, to eliminate the visibility. The nature of this relationship in the possibility of any reduction in visibility due to Pollution Management Series 79 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities adsorption on particles. More complex WTP = 46.4 x ln(V2 /V,) + 79.7: (D.2) relationships linking visibility range to xDUMMYx ln(V2Iv,) particulates of various descriptions, absorption by gases, and humidity levels are also available where WTP is individual willingness to pay in (see, for example, Landrieu 1997).weeWP1 dvda llgest a (see, for example, Landrieu 1997). 1993 US dollars; V1 and V2 are the initial and The literature detailing willingness to pay for final visibility ranges measured in miles; and improvements in visibility in the context of the DUMMY is a dummy variable that takes the home and workplace has generally utilized the value unity for the studies of Tolley et al. (1984) contingent valuation method (CVM) approach, and zero otherwise. The equation explains 74 whereby respondents are shown photographs percent of the variation in the data. The relating to different visual ranges and are asked significance of the multiplicative dummy their willingness to pay for changes in the variable illustrates the fact that the study of frequency with which particular visual ranges Tolley et al. suffers from significant embedding prevail. Unfortunately, under this approach it and should almost certainly be discounted (i.e., has been found difficult to distinguish between the last term in the equation should be willingness to pay for improvements in dropped). visibility and other motivations such as health benefits, reduced soiling, and so on. The Unusually for damage cost estimates, the evidence is limited because of the small number marginal damage curve falls as the of studies that have accounted for the possible concentration of particulates rises. The reason is embedding of other perceived benefits aside that even though marginal willingness to pay from enhanced visibility This is a significant for the additional mile rises as the current criticism that has undermined confidence in the visibility range falls, the increase in the visibility results of previous major studies (e.g., Tolley et range for a unit reduction in particulate al. 1984). McClelland et al. (1991) sought to concentrations falls even faster. This overcome the embedding problem by asking phenomenon has been noted by others (see respondents to allocate their expressed WTP to Repetto 1981). The declining marginal damage different motivations. Only 18 percent of the function for impairment of visibility because of expressed willingness to pay for the particulates may help explain why individuals improvement in air quality depicted in that living in large urban conurbations in developing study was ascribed to the motivation of countries might be unwilling to pay much at the improving visibility margin for a reduction in air pollution insofar as The existing iterature comprises five separate its effect on visibility range is concerned: in a studies (Brookshire et al. 1979; Loehman et al. high-pollution situation, the improvement in 1980; Rae 1983; Tolley et al. 1984; McClelland et visibility obtained from a unit reduction in al. 1991) and incorporates nine different U.S. particulate concentration is likely to be rather cities. The results are analyzed by means of an small (see Table D.1). unweighted least-squares regression. The following equation was estimated to explain Although it is possible to present estimates of household willingness to pay. Note that the U.S. households' marginal willingness to pay functional form is selected such that the for improvements in visibility, serious problems willingness to pay for a zero change in visibility remain in transferring these estimates to the is zero and that the equation is consistent with developing-country context. This is because the the assumption of diminishing marginal income elasticity of willingness to pay for willingness to pay for visibility enhancement. improvements in the range of visibility is not The estimated equation is: known. However, it is probable that the income 80 Environment Department Papers Values for Visibility, Soiling, and Corrosion Table D. I Marginal willingness to pay for visibility Furthermore the same model illustrates improvements by restricting particulate concentrations, United why the observed increase in States (1990 U.S. dollars) expenditure on cleaning understates the Total suspended aWTP/am true marginal willingness to pay. Given particulates (TSP) Visibility av/8m (U.S. dollars the choice, an individual confronted with (pg/mr) range (miles) (miles) per pg/m3 TSP) an increase in pollution will note the 50 17.7 0.35 0.80 increase in the relative price of 100 8.8 0.09 0.50 cleanliness and purchase less of it. Thus, 150 5.9 0.04 0.30 compensating the individual by the 200 4.4 0.02 0.20 observed increase in expenditure on 250 3.5 0.01 0. 10 cleaning is insufficient. Note further that Note: Damage cost estimates are given per pg/m3 of TSP To convert to PM 0, a reduction in cleaning expenditures is multiply by 1.8 1. even acceptable as an economic outcome. Source: Authors' calculations.acpbl A negative damage cost estimate as a lower bound is not very useful for a figure that elasticity of WTP would be no less than unity, is presumed to be positive. since the benefits from extended visibility are primarily aesthetic in nature. This assumption, This point is important because although coupled with the arguments given above, several studies have been conducted on the indicates that visibility effects are likely to be effects of air pollution and soiling, most of them very small in developing countries, present increased expenditure on cleaning costs Soiling as the appropriate measure. Thus, for example, Ridker's (1967) study of how laundry and dry- Air pollution results in soiling of materials and cleaning costs vary across 144 U.S. cities with an increased need for washing and various levels of pollution could only provide a maintenance. Soiling in this context refers to lower bound for the true WTP. Ridker justified particulate soiling within the household sector, his finding that no relationship between not to soiling damage to the commercial and particulates and such expenditures existed by industrial sector or damage done to public arguing that such operations are undertaken on buildings or historic monuments. a rigid schedule that is independent of location. In fact, however, such a finding is consistent To place the alternative studies in proper wit u.lt maiiain context, it is instructive to consider briefly the with utility maximizaton. theory underlying cleaning cost studies. In the most basic model the individual is modeled as The theoretically correct measure of WTP can consuming two goods: a numeraire good and a only be derived from household production good referred to as cleanliness. Cleanliness is function (HPF) studies in which the observed positively related to the frequency of cleaning expenditure on cleaning commodities is and negatively related to the level of pollution. explained as the outcome of some utility Each cleaning episode incurs a cost, and the maximization process. A significant criticism of individual has to allocate his or her budget the HPF models, however, is that although the between cleaning and the numeraire good. expenditure surveys on which they are based Within the context of this very simple model, it include spending on cleaning outlays, they do can be shown that the appropriate measure of not currently account for the time cost incurred marginal willingness to pay to reduce pollution by those who choose to do the cleaning is the increased expenditure required to themselves, since such information is not maintain the current level of cleanliness. typically available in consumer expenditure Pollution Management Series 81 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities surveys. In fact, cleaning is likely to involve a household in 1971 prices. Converting to 1990 considerable amount of own-labor input. prices gives US$5.40 per household per pg/m3 According to Watson and Jaksch (1982), only a of TSP, or US$2.10 per capita. These results can small part of all cleaning tasks is contracted out, be compared with the CVM approach of and if labor costs, valued at typical contractual McClelland et al. (1991), described in the rates, were added, aggregate cleaning preceding section. In principle, that study expenditures would rise by 400 percent. Thus, if measures WTP directly and appears to indicate only expenditures on cleaning products are a household WTP of US$2.60 per pg/m3 of TSP accounted for, and not nonmarketed labor, the in 1990 prices, or US$1.00 per capita (although it largest element of the costs associated with is questionable whether this is a good way of soiling from air pollution is omitted. Although it eliciting preferences for avoiding soiling is questionable whether full market rates should damages). The dissimilarity of the MRI results be charged for cleaning tasks, this point still and the Watson and Jaksch results indicates that carries considerable force. Given this current the former might not provide a very useful shortcoming of HPF studies, Ridker's (1967) lower bound. The large difference between the estimate might seem more appealing: define a McClelland et al. study and the Watson and number of different cleaning tasks, examine Jaksch study, both of which purport to measure how the frequency with which they are WTP, may reflect the strong assumptions that undertaken varies according to ambient levels underlie the specification of the model used by of particulate pollution, and then, on the basis Watson and Jaksch. of the cost of each task (including the costs of both labor and cleaning materials), compute the Once more, it is difficult to transfer these figures additional costs attributed to air pollution. into the context of developing countries because MR] (1980) is based on this approach. The of lack of information on the relevant income frequency of 27 different cleaning tasks was elasticities (that is, the willingness of poor determined by questionnaire for residents of individuals to take time from earning money to Pennsylvania. Of these tasks, 11 proved clean their houses) but also perhaps because of sensitive to the level of air pollution, although differences in housing, cultural values, and data for only 9 of them were included in the attitudes toward cleanliness. In this study we actual report. The frequency of cleaning was started with a median estimate of US$1.07 per linked in a regression to the ambient level of individual per ,g/m3 of TSP and reduced it by TSP. The associated costs were obtained from a half to adjust roughly for a typical urban survey of cleaning contractors. household in a developing country, for which the list of tasks in Table D.2 is clearly excessive. The results of the MRI report are reproduced in The value can be converted to a PM10-based Table D.2. They indicate a lower bound on measure by multiplying by 1.8. soiling costs of US$2.82 per household per pg/ m3 of TSP in 1990 prices, or US$1.07 per capita. Cross-sectional analysis of per capita As anticipated, these exceed the measures expenditures on household cleaning goods in obtained from the work of Watson and Jaksch the 1980 International Comparisons Project (1982), who calculate a household WTP on the (ICP) points to an income elasticity of demand basis of the HPF approach. According to their for such commodities of 0.89, with a standard study, an improvement in air quality from error of 0.09. This same income elasticity was primary to secondary levels (a change of 15 pg/ used to scale estimates of soiling damage in this m3 of TSP) results in a gain of US$25 per study 82 Environment Department Papers Values for Visibility, Soiling, and Corrosion Table D.2 Household cleaning tasks, their frequencies per unit of TSFP and their costs Unit cost (1990 Change in frequency Additional cost (U.S. Task U.S. dollars) per lpg/m3 TSP dollars per /lg/m3 TSP) Replace air conditioner filters 3.38 0.005 0.02 Wash floors 20.29 0.040 0.81 Wash windows on inside 1.69 0.078 0.13 Clean venetian blinds/shades 11.84 0.048 0.57 Clean screens 0.67 0.006 0.00 Wash windows on outside 5.07 0.053 0.27 Clean storm windows 6.76 0.015 0.10 Clean outdoor furniture 33.82 0.006a 0.20 Clean gutters 50.73 0.014 0.71 Total 2.82 Note: The typical household has 2.63 persons. Prices were converted from 1970 to 1990 price levels using a consumer price index (CPI) deflator of 3.37. To convert from TSP to PM l multiply by 1.8. Half of the total value is used in study calculations. a. The frequency of cleaning outdoor furniture is presented as a nonlinear function of TSP concentrations. For the sake of simplicity, the figure given refers to the marginal effect evaluated at 100 pg/m3 TSP Sources: MRI ( 1980); authors' calculations. Materials Damage shortened. This time lapse is determined by the rate of corrosion and the "acceptable" degree of Air~~~ polto-nue damagetomerasdmge. The concept of an acceptable degree of including stone, brick, painted surfaces, metals, corrsio len somep and acyto teg rubber, and fabrics, is a Widespread problem. establishment of damage functions, but in The main pollutant involved is SO2, but the principle, this concept can be observed from corrosive effects may be reinforced by exposure p . U to nitrogen dioxide (NO2), ozone (03), and actual behavior. Using such assumptons, it is acidity in precipitation (H+), as well as by the possible to convert the dose-response functions more general effects of the climate. Annual to damage functions expressed as lifetime surface recession of exposed materials is functions, that is, functions expressing the predicted from the extensive international work lifetime of materials as a function of exposure to on the relevant dose-response relationships (see pollutants. Although the total replacement cost Pearce 1997 for a recent survey). Most of the may be constant by type of material, the annual work on valuing material damage costs has cost of replacement will obviously be higher the utilized this dose-response literature. shorter the time period to replacement; for any no-pollution context, there will be a given The dose-response function cannot be used to annual replacement cost, and there will be a compute economic damage directly; the next higher annual replacement cost for the with- stage is to derive a damage function. As pollution case and so on for a gradient of levels corrosion increases, the time that elapses before of pollution. The difference between the two is replacement, repainting, or repair takes place is the annual economic damage done by pollution. Pollution Management Series 83 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities Given these lifetime functions, valuation then Suppose that all householders and businesses requires the compilation of an inventory of have maintenance contracts with contractors to materials exposed. This is a major task in itself maintain their property at an agreed standard of without which the results of the dose-response- repair. The price of maintaining property at a function literature carinot even be applied. After certain standard of repair is obviously an this, valuation of unit impacts is required. This increasing function of the level of.air pollution. valuation has generally taken the form of If the level of air pollution falls, the cost of valaton asgenerally tae h om fproviding the same standard of maintenance contractual costs for various maintenance jobs alofal,nd cost sangsreslt indee (i.e., the cost of materials plus the cost of labor). are the cost savings indiate by thel e . . ~~~~~are the cost savings indicated by the lifetime Reduced lifetimes of building materials or maintenance approach, But this is not the end of shortened maintenance cycles may not, the story because, unless.the demand for however, fully reflect the true costs of air maintenance services is completely price pollution; they ignore, among other things, inelastic, the demand for maintenance services avertive behavior such as use of corrosion- per time period will increase. Thus, the total resistant materials, which can be a significant change in economic surplus is given by the additional cost factor. In effect, the replacement reduction in the cost of providing the old cost approach to materials damage suggests quantity of maintenance plus the surplus that annual costs (AC) imposed by a change in generated by the additional maintenance the level of pollution are given by: services demanded. Hence the cost savings on their own yield a lower bound on true WTP. AAC=UCxSARx[---] (D.3) Lo L, Calthrop (1996) has assembled the U.S. and where UC is the unit cost of replacement; SAR is European literature to derive estimates of s ' ~~~~damage per ton of pollutant (see Table D.3). the stock at risk; and L and L are the old and dmg e o fpluat(e al .) the k tr a 1 Since methodologies differ and data reliability new levels of pollution, respectively. These varies substantially, it is difficult to compare the lifetimes are themselves ratios of the critical results across studies. However, some general (replacement) damage threshold to the annual conclusions emerge: for the United States, a amount of damage as indicated by the dose- figure of about US$200 per ton of SO2 seems response function. consistent with the studies, with a range of US$150-$250 per ton. For Europe the range is This methodology assumes that the individual wider, US$45-$2,020 per ton of SO2, but with a will take action at the same level of damage as range of US$250-$600 appearing more likely before and will not attempt to maintain his or after outliers have been discounted. (All values her property in a higher state of repair than are in 1993 dollars.) Finally, the values for NOX previously. In fact, that assumption will lead to are suspect, since the links between NOX and an overestimate of cost savings associated with damage to buildings are very uncertain and the studies are few. maintenance but an underestimate of the overall economic benefits. More specifically, the Per capita averages of these damage costs are connection between the damage-cost measure in US$12.50 for SO2 and US$11.30 for NO2 or the maintenance cycle approach and the US$0.50 per ,g/m3 for SO2 and US$0.25 per conceptually more appropriate WTP measure is Pg/m3 for NO2 in 1993 dollars. Conversion of best understood by considering the market for these values to 1990 dollars yields US$0.45 for maintenance services (see, for example, SO2 and US$0.20 for NO2. The latter is used in MATHTEC 1984). our calculations. 84 Environment Department Papers Values for Visibility, Soiling, and Corrosion We turn, finally, to the task of transferring the tolerated in the countries listed in Table D.3. results of this literature to the developing- Both assumptions ensure that spending on country context. Pearce (1997) points out that home repairs and maintenance rises as per use of damage cost figures from industrial capita income increases. The income elasticity of countries takes no account of variations in the expenditure on repairs and household "acceptable" degree of damage or significant maintenance is calculated, using data from the differences in the likely amounts of property per 1980 International Comparisons Project, to be person. In particular, it is unreasonable to 0.64, with a standard error of 0.10. Scaling the assume that the "critical threshold" is anything damage cost estimates using the income other than the outcome of choice and easy to elasticity of expenditure on household repairs envisage that what passes for a critical and maintenance yields a lower-bound estimate threshold in developing countries might be for per capita costs of materials damage in other considerably in excess of what would be countries. Table D.3 Estimates of costs of damage from corrosion: Various studies (1993 U.S. dollars) Pollutant and country Damage costs Total emissions Population Damage per (various studies) (dollars per ton) (thousands of tons) (millions) capita (dollars) Sulfur dioxide (SO) United States 150-250 17,700 250 14.20 United Kingdom 285 3,755 57 18.80 United Kingdom 45-250 3,755 57 9.70 United Kingdom 610 3,755 57 40.20 Germany 1,160-2,020 961 79 19.30 Germany 300-570 961 79 5.30 Germany 400 961 79 4.90 Germany 110 961 79 1.30 France 300 1,261 57 6.60 Average 12.50 Average per pg/m3 SO, 0.50 /pers/,uglm3 Nitrogen dioxide (NOJ United Kingdom 425 2,729 57 20.30 Germany 75 2,688 79 2.60 Average 11.30 Average per pg/m3 NO2 0.25 /pers/pg/m3 Note: Annual average S02 concentrations are between 20 pg/rm3 and 30 pg/nm3 in the United States and the United Kingdom; average N02 concentrations are between 40 pg/mr3 and 50 pg/m3 (for the urban areas that account for the most of the population and property values in those countries). The same concentrations are assumed for France and Germany. Thus, average damages per person were divided over 25 Ug/M3 for So2 and 45 pg/M3 for N02. Sources: Compiled by D. Maddison from Fisher, Chestnut, and Violette (1989); WEC (1992); Feliu, Morcillo, and Feliu (1993); Kucera et al. (1993. 1995); ECOTEC Etd. (1994); Upfert (1989, 1994); United Kingdom (1994); EC (1995); ApSimon and Cowell (1996); Calthrop (1996); Cowell and ApSimon (1996); Glomsrod et al. (1996); Haagenrud and Henriksen (1996); Kucera (1996); U.S. Bureau of the Census (1996); Landrieu (1997); WRI (1996); U.S. Department of Energy data. Pollution Management Series 85 Annex E City Data on Fuel Use Table E. I Bangkok: Quantity and quality of fuel use, by economic sector Suboptimal Modern power plants! district Large industry Small industry Land transport Fuel plants (H) heating (M) (M) (L) Residential (L) (L) Coal Thousands of tons Ash content (percent) Sulfur content (percent) Petroleum products Fuel oil Thousands of tons 2,300.0 500.0 300.0 Sulfur content 1.5 0.5 0.25 (percent) Motor diesel oil Thousands of tons 600.0 Sulfur content 0.5 0.5 0.5 0.5 (percent) Gasoline Thousands of tons 830.0 Fuelwood Thousands of tons Note: H. high-stack source; M, medium-stack source: L, low-stack (or low-level) source. Sources: WHO and UNEP (1992): Radian International consultant report(1997). Pollution Management Series 87 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities Table E.2 Krakow: Quantity and quality of fuel use, by economic sector Suboptimal Modern power plantsl district Large industry Land transport Fuel plants (H) heating (M) (M) Small industry (L) Residential (L) (L) Coal Thousands of tons 3,096.0 175.0 12.0 143.0 84.0 Ash content (percent) 11.8 12.0 12.0 9.9 12.0 Sulfur content 1.5 1.5 1.5 1.5 1.5 (percent) Petroleum products Fuel oil Thousands of tons 3.0 Sulfur content 2.2 (percent) Distillate oil Thousands of tons Sulfur content (percent) Motor diesel oil Thousands of tons 114.0 Sulfur content 0.3 (percent) Gasoline Thousands of tons 135.0 Note: H, high-stack source; M, medium-stack source; L, low-stack (or low-level) source. Also includes coal use by a large steel mill with a high stack. Sources: Adamson et al. (I1996); Janzten (1995). Table E.3 Manila: Quantity and quality of fuel use, by economic sector Suboptimal Modern power plants! district Large industry Small industry Land transport Fuel plants (H) heating (M) (M) (L) Residential (L) (L) Coal Thousands of tons Ash content (percent) Sulfur content (percent) Petroleum products Fuel oil Thousands of tons 1,198.5 2,405.5 1,037.0 510.0 Sulfur content 3.0 1.5 0.5 0.5 (percent) Motor diesel oil Thousands of tons Sulfur content 0.5 (percent) Gasoline Thousands of tons 719.0 Fuelwood Thousands of tons Note: H, high-stack source; M, medium-stack source; L, low-stack (or low-level) source. Source: World Bank (I 997h). 88 Environment Department Papers City Data on Fuel Use Table E.4 Mumbai: Quantity and quality of fuel use, by economic sector Suboptimal Modern power plants! district Large industry Small industry Land transport Fuel plants (H) heating (M) (M) (L) Residential (L) (L) Coal Thousands of tons 298.0 350.0 250.0 100.0 Ash content (percent) 12.0 12.0 12.0 12.0 Sulfur content (percent) 0.5 0.5 0.5 0.5 Petroleum products Fuel oil Thousands of tons 927.0 626.0 261.0 480.0 Sulfur content (percent) 1.0 2.0 1.1 1.3 0.15 Motor diesel oil Thousands of tons 243.4 Sulfur content (percent) 0.5 Gasoline Thousands of tons 248.6 Fuelwood Thousands of tons 192.0 101.0 Note: H, high-stack source; M, medium-stack source; L, low-stack (or low-level) source. Source: World Bank (1997g). Table E.5 Santiago: Quantity and quality of fuel use, by economic sector Suboptimal Modern power plants! district Large industry Land transport Fuel plants (H) heating (M) (M) Small industry (L) Residential (L) (L) Coal Thousands of tons Ash content (percent) Sulfur content (percent) Petroleum products Fuel oil Thousands of tons 46.0 575.0 476.0 Sulfur content 1.0 1.0 0.5 (percent) Motor diesel oil Thousands of tons 315.0 Sulfur content 0.5 (percent) Gasoline Thousands of tons 740.0 Fuelwood Thousands of tons) 327.0 168.0 Note: H. high-stack source; M, medium-stack source; L, low-stack (or low-level) source. Sources: World Bank (1994); interim consultant report. Pollution Management Series 89 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities Table E.6 Shanghai: Quantity and quality of fuel use, by economic sector Suboptimal Modem power plants! district Large industry Land transport Fuel plants (H) heating (M) (M) Small industry (L) Residential (L) (L) Coal Thousands of tons I 1,000.0 3,200.0 11,000.0 2,200.0 1,500.0 Ash content (percent) 17.0 20.0 20.0 20.0 5.0 Sulfur content 1.0 1.0 1.0 1.0 1.0 (percent) Petroleum products Fuel oil Thousands of tons 369.0 2,800.0 740.0 460.0 Sulfur content 0.5 0.5 0.5 0.5 (percent) Motor diesel oil Thousands of tons 455.0 Sulfur content 1.5 (percent) Gasoline Thousands of tons 840.0 Fuelwood Thousands of tons Note: H, high-stack source; M, medium-stack source; L, low-stack (or low-level) source. Sources: World Bank (1997d); World Bank staff (for diesel and gasoline sales). 90 Environment Department Papers Notes 1. PM10 is particulate matter less than 10 urban agglomerations is not assessed microns in aerodynamic diameter. because the assessment is based on fuel use inventory within a city or agglomeration. 2. The use of diesel by railroads and intercity In the case of Krakow, which is adjacent to transport is not included in this a large coal-mining and industrial region, assessment. long-range pollution is estimated to increase local damage from large sources 3. These are health impacts attributable to by 40-50 percent (authors' estimates based exposure to outdoor (ambient) air on Adamson et al. 1996). This impact, pollution only. Exposure to high levels of although significant, does not change the indoor air pollution in households using fundamental importance of small sources solid fuels (coal, wood, and agricultural in local pollution; in Krakow, it would waste) is not assessed in the study. On a increase the contribution of large sources global scale, health impacts from indoor to local damage from 10 to 14 percent. exposure are very significant and are considered greater than those from 5. The fuel prices shown in Figure 1.8 and outdoor pollution (World Bank 1992, 1993; Table 1.6 are the following 1993 spot Smith 1993, 1998; WHO 1997). Most of the market (producer) prices: coal, Australian people who suffer from high levels of export; fuel oil, diesel (gas oil), and indoor pollution are rural, but poor urban gasoline prices, Rotterdam product prices. families are also affected. The health costs (The gasoline price is for regular unleaded of fuel use would be considerably greater if and the fuel oil price is for fuel oil with 1 indoor pollution were taken into account. percent sulfur content, which is close to the average sulfur content of the fuel oil 4. The category "Power plants" in Figure 1.4 aggregate in the sample.) The local coal and throughout the study includes only prices shown in Figure 1.9 and Table 1.7 are modern, well-controlled power plants with wholesale prices for power plants and high stacks. This restriction explains the large boilers and retail prices for small very low contribution of the power sector users. Local prices are for different years to local damages. Suboptimal power within the range 1991-94. The sources are stations and generators, which are IEA and OECD (1995, 1996); Adamson et common in Shanghai, as well as Krakow's al. (1996); Kubota (1996); World Bank large district heating boilers, are included 1997f; World Bank staff. in the category "Large boilers." Long-range pollution from power plants and other 6. For example, emissions factors for diesel large sources that are located outside vehicles assume that a large share of high- Pollution Management Series 91 Environmental Costs of Fossil Fuels - A Rapid Assessment Method with Application to Six Cities sulfur diesel is used in uncontrolled or European Union are currently considering poorly maintained old vehicles that emit the adoption of stricter standards. substantial amounts of particulates and S02. The assumptions and emissions 11. Some recent studies (Oberdorster et al. factors are modified for each city on the 1995; Seaton et al. 1995; Peters et al. 1997) basis of city-specific or country-specific go even further, indicating that ultrafine information, including the composition of particles in ambient air may be responsible the vehicle fleet by age and type, where for the observed health effects because of available. their high biological and toxicological reactivity. Ultrafine particles are the 7. USEPA Website . smallest fraction of fine particulates (typically smaller than 0.05 mm) that exist 8. A lower level of exposure was assumed for in a nucleation mode. The most prevalent Shanghai because the impact of fuel is ambient ultrafine particles are elemental assessed for all of Shanghai province and organic carbon particles (Hilderman et (population 13.5 million). The province has al. 1994). a lower overall population density than that of other cities, where the assessment 12. In addition, a study by Zejda et al. (1997) of pertains to the area within the immediate air pollution and daily mortality in city or agglomeration boundaries. Katowice, Poland, yielded a central estimate of a 0.7 percent change in total 9. In the sample of six cities, fuel combustion mortality per 10 ,ug/m3 change in PM10 contributes 42 percent of total exposure to levels. This result is consistent with Table PM10. Fuel use inventories may be 3.3. The study is not included in the meta- incomplete for some cities (especially for analysis because a complete report is not Bangkok and Santiago) because of the available in English. limitations of the secondary data available. Thus, the contribution of fuel burning to 13. The adverse health impact of lead, in PM10 exposure might be larger. Since major combination with the availability of low- fuel uses are incorporated into our cost options for introducing unleaded analysis, however, any possible difference gasoline, has hastened a worldwide trend is unlikely to exceed a margin of 20 percent toward phasing out leaded gasoline. In for Bangkok and Santiago and is even recent years transport in Bangkok, smaller for other cities. Shanghai, and Mumbai has become lead free, and Santiago is following this path. 10. The pre-1997 WHO guidelines for annual average levels of PM10 are 40-60 ,ug/m3. In 14. Shares in the total population of the cities 1997 WHO discontinued its threshold level of children under 14 and asthmatics, which guidelines for particulates after substantial are used in some dose-response functions evidence was accumulated that adverse in Table 3.4, were assumed to be 0.27 and health effects occurred even at much lower 0.05 for each city, on the basis of U.S. data. levels of exposure. Organisation for If city-specific values for these parameters Economic Cooperation and Development are available, they should be used to obtain (OECD) standards for PM10 typically range more accurate results. However, possible between 40 and 50 ,ug/m3 (annual local variations in these values make little average), and the United States and the difference to the total social costs of health 92 Environment Department Papers Notes impacts and do not affect any conclusions dollars). This corresponds to US$5,785 in from the analysis (see Chapter 6). 1990 prices, using the consumer price 15. Monte Carlo (random) simulations were index (CPI) for medical care. Given an used to generate the distribution of average duration of a hospital stay of willingness to pay to avoid a case of about 9.5 days, weekly earnings of US$421, pollution-related bronchitis, drawing from and a five-day week, the cost of lost output the distributions for the three variables: would be US$85 per day. The COI for an willingness to pay to avoid a severe case of RHA is therefore US$6,589. Rowe et al. chronic bronchitis: the severity level of an (1986) assess the medical cost of an ERV as average pollution-related case of chronic US$90 in 1986 prices. Using the medical bronchitis; and the WTP elasticity. care CPI, this would be US$135 in 1990 dollars, and adding the cost of a day's 16. Cropper and Krupnick (1990) estimate that wages brings the cost to US$220. the average cost of a hospital stay for 17. 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