Urban Transport 441 Reduce health risks by subsidizing particulate traps on new diesel cars R. M. M. Van den Brink & L. Van Bree Netherlands Environmental Assessment Agency, RIVM, The Netherlands Abstract From 2010 on, new diesel cars sold in the European Union will probably have to be equipped with particulate traps to be able to meet the Euro-5 emission standards. In order to possibly diminish the health impacts of exposure to airborne particulates, the Dutch Ministry of the Environment is going to subsidize particulate traps on new diesel cars between 1 January 2005 and the time the Euro-5 emissions standards come into force. The Ministry asked the Netherlands Environmental Assessment Agency to assess the possible short-term health risk reduction of this subsidy programme for 2010. The total number of premature deaths due to short-term exposure to PM 10 in the Netherlands is approximately 2800. However, there is still much uncertainty about what part of the total PM 10 causes this observed acute mortality. For this reason the health risk reduction of the particulate trap subsidy programme was estimated using three different assumptions on which part of PM 10 is actually causing acute premature mortality. From the assessment we can presume the subsidy programme to result in around 40 fewer premature deaths (~1% of 2800) in 2010 due to short-term exposure to PM 10 in the case only primary anthropogenic PM 10 causes the observed acute health impact. In the hypothetical case that only the carbonaceous part of primary anthropogenic primary PM 10 or Black Smoke cause the observed health impact, the health benefit is estimated at around 5% of 2800. One should bear in mind that the share of all diesel cars in total PM 10 emissions in the Netherlands in 2010 is only 6% and the share of diesel cars in the average PM 10 concentration is even smaller, around 1%. Despite the uncertainty about what fraction of PM 10 causes the observed short-term health impacts, subsidizing particulate traps could still be justified from a precautionary perspective and besides, long-term exposure to diesel PM is harmful to humans. Keywords: diesel particulate trap, PM 10, health impact assessment, traffic.
442 Urban Transport 1 Introduction For several years now the health impact of airborne particulate matter has been an important scientific and political issue. The National Institute for Public Health and the Environment (RIVM) has recently published the results of a study on the health impact of short-term exposure to PM 10 in the Netherlands [1]. Here, approximately 5000 people in the Netherlands were shown to die prematurely each year as a result of short-term exposure to ambient ozone and PM 10 concentrations. PM 10 appears to be responsible for about 2800 of these 5000 premature deaths, mainly among the elderly, who die a few days to a few weeks earlier than would have been the case in complete absence of airborne PM 10. Ambient particulates (PM) consist of a complex heterogeneous mixture of various components. Up to now it has not been possible to quantify the contributions from different sources and different PM constituents to relate to the health effects caused by PM exposure. The focus has been mainly on PM 10 referring to the inhalable fraction (less than 10 µm in diameter) of particulate matter. PM 10, consisting of many different chemical compounds and size classes, is also used in European environmental policy as a tracer to determine the health impact of airborne particulate matter. As Figure 1 shows, measured concentrations of PM 10 can only partly be explained by air quality modelling of anthropogenic PM 10 emissions. measured (~38 µg/m 3 ) primary (~6 µg/m 3 ) modelled anthropogenic (~16 µg/m 3 ) secondary inorganic (~10µg/m 3 ) non-modelled (~22 µg/m 3 ) natural (? µg/m 3 ) non-modelled anthropogenic (? µg/m 3 ) combustion (~2.5 µg/m 3 ) other (~3.5 µg/m 3 ) EC OC Figure 1: Source apportionment of the average measured PM 10 concentration in the Netherlands in 1995 [1]. The gap between measurements and modelling results is partly due to nonmodelled natural PM 10 (sea salt, crustal materials and fugitive dust); however, non-identified anthropogenic sources and secondary organic PM 10 might contribute to this gap. Anthropogenic PM 10 can be subdivided into primary PM 10 emitted by emission sources and secondary inorganic PM 10 (nitrates, sulphates
Urban Transport 443 and ammonium salts), formed by chemical reactions between gaseous pollutants. Primary anthropogenic PM 10 originates from fuel combustion, wear and tear and industrial processes. Particulates from fuel combustion consist of elemental carbon (EC or soot), organic compounds and sulphates. In abatement efforts much has been done to reduce the total mass concentration of PM 10, although it would seem reasonable to focus more on PM 10 fractions that may prove more critical to health effects, such as emissions from traffic in general and diesel engines in particular [3]. For instance, new diesel cars and trucks have been subject to emission standards for several emission compounds including PM 10. As a result of applying these emission standards, the PM 10 emissions of road traffic decreased by 45% between 1992 and 2001 [2]. The average PM 10 concentration in the Netherlands decreased by almost 30% between 1992 and 2001 [2]. Road traffic had quite a small share in the total anthropogenic PM 10 emissions by Dutch emission sources in 2001[2]. Besides, almost 50% of the airborne PM 10 comes from foreign PM 10 sources and nonmodelled PM 10 sources (including natural sources) [1]. In order to further decrease PM 10 concentrations, the European Union member states have to comply with air quality standards (Daughter Directives). According to the first Daughter Directive, the annual average PM 10 concentration may not exceed 40 µg/m 3 as of 1 January 2005. However, even with PM 10 concentrations well below European Union standards, people s health will still be adversely affected, because no threshold has been found for the occurrence of health effects [1]. There are strong indications that both natural PM 10 and secondary inorganic PM 10 only have minor adverse health impacts, if any [3]. Many believe that only ultra-fine soot particles from diesel fuel combustion are responsible for the health effects caused by particulate matter, but the weight of evidence is rather weak. According to the WHO [3], health effects are most likely associated with particles from fossil fuel combustion, although the scientific evidence is not watertight and other sources may still play a role. For example, mortality rates in densely populated (urban) areas in the Netherlands do not significantly differ from mortality rates in rural areas [1], whereas people living in cities are exposed to higher soot concentrations than people in rural villages [4]. In addition, the WHO recently concluded on the basis of both toxicological and epidemiological evidence, that some coarse particulate matter (PM 2,5-10 ) as well could have acute effects on health endpoints, although the picture is rather unclear [3]. These coarse particulates originate from wear and tear (for instance, from tires and brake linings) and possibly also from natural sources. Despite the fairly limited scientific evidence that traffic emissions and diesel soot are responsible for some or all adverse health effects from exposure to ambient PM, several European countries, including the Netherlands, recently adopted a subsidy programme for new diesel passenger cars fitted with diesel particulate traps. The expectation is that such a measure will result in appreciable health risk reductions. The subsidy programme is an attempt to accelerate the use of particulate traps. After 1 January 2009 particulate traps will probably become standard equipment for every new diesel car so as to meet Euro-5 emissions
444 Urban Transport standards. At the request of the Dutch Ministry of Environment, the Netherlands Environmental Assessment Agency (MNP-RIVM) was to assess the effect on total premature mortality in 2010 of the Dutch particle trap subsidy programme, which will be launched on 1 January 2005. This paper will describe this source risk assessment, in which only the acute health effects will be evaluated assuming that the chronic health effects will still be negligible by 2010. 2 Methodology An approach sometimes used is to predict health benefits on the basis of a proportional reduction of PM 10 mass concentration, assuming a direct relationship between the two. This approach embodies a high degree of uncertainty because there is much uncertainty about what part of total PM 10 causes acute mortality and other health effects. In this health impact assessment we used three approaches (hypotheses), taking into account, as far as possible, the current views on health-relevant and possibly causal PM 10 fractions: 1) Use of statistical correlations between PM 10 concentration and mortality, while assuming that only anthropogenic primary PM 10 causes short-term health effects; 2) Use of statistical correlations between PM 10 concentration and mortality, while assuming that only the carbonaceous fraction of primary anthropogenic PM 10 (PM carb ) (elemental carbon + organic carbon) causes short-term health effects; 3) Use of statistical correlations between Black Smoke (BS) concentration and mortality, while assuming all BS causes short-term health effects. The first hypothesis contains the current view that the anthropogenic secondary PM fraction (e.g. inorganic sulphates, nitrates, chlorides, ammonium salts and wind-blown dust like silicate clays) are less relevant [3][9]. The second hypothesis reflects the view that combustion-derived particle emissions are (mainly) responsible for the observed adverse health effects [3]. The third assessment uses an indicator that is also strongly correlated with combustion-related emissions. In the past, Black Smoke measurement, based on the decreased reflectance or increased light absorbance of filters loaded with soot, was used to indicate the total particulate matter concentration. However, for ambient PM there is no quantitative relationship between reflectance (of a sampled filter) and particle mass. On the other hand, the current reflectance measurement of BS filters has been found to correlate highly with elemental carbon [1]. To assess the effect of subsidizing particulate traps, we used the following equation: E part. trap Ctransport HE HE (1) Etransport Ctotal where the components are: HE = change in acute health effect due to change in the average concentration (number of deaths)
Urban Transport 445 E part.trap = change in emissions due to particulate traps (kg) E transport = total transport emissions (kg) C transport = transport-related concentration (µg/m 3 ) C total = average concentration (all sources) (µg/m 3 ) HE = total number of premature deaths caused by short-term exposure Chapter 3 briefly overviews the estimation of acute health impacts (HE) due to short-term exposure to particulates in the Netherlands made in the RIVM report [1]. Chapter 4 deals with the transport-related concentration (C transport ) and the average concentration (C total ), and Chapter 5 with transport emissions (E traffic ) and the change in emissions due to subsidizing particulate traps ( E part.trap ). Chapter 6 assesses the acute health benefit gained when applying particulate traps ( HE). The assessment results are discussed in Chapter 7. 3 Estimation of premature mortality In 2002 RIVM assessed premature mortality caused by short-term exposure to PM 10 [1] using a two-component model comparing the difference in observed daily mortality and modelled mortality with the PM 10 and ozone concentrations during the preceding week (lag time). From this comparison RIVM deducted the relationship between PM 10 concentration and the relative increase in mortality (Relative Risk). RIVM did a comparable time-series analysis for Black Smoke (BS) and ozone. Table 1 shows these modelling results based on Dutch timeseries studies. A Relative Risk of 1.054 per 100 µg/m 3 means that the mortality rate increases by 5.4% if the concentration increases by 100 µg/m 3. Table 1: Association between total premature mortality and air pollution (Relative Risk (RR), average and 95% confidence interval (CI)) using a two component model (PM 10 /O 3 and BS/O 3 ) and average particle concentrations during the preceding week [1]. pollutant average 95% CI PM 10 (week average) 1.054 per 100 µg/m 3 1.042 1.067 per 100 µg/m 3 Black Smoke (week average) 1.071 per 50 µg/m 3 1.058 1.085 per 50 µg/m 3 Using an average daily PM 10 concentration of approximately 40 µg/m 3 and a total annual mortality rate of 130,000, RIVM estimated a premature death rate in the Netherlands of 2800 (95% CI: 2200 3500) as a result of short-term exposure to PM 10. In the same way, RIVM calculated the total number of premature deaths due to short-term exposure to BS. Using the average BS concentration in the Netherlands of about 11 µg/m 3, RIVM estimated that around 2000 (95% CI: 1700 2500) people die prematurely as a result of short-term exposure to BS. It is not coincidental that both numbers are of the same order of magnitude. BS and PM 10 are strongly interrelated, so an increase in PM 10 concentration will
446 Urban Transport almost always coincide with an increase in the BS concentration. Furthermore, by using a PM 10 /O 3 model, the observed increase in mortality rate is attributed to PM 10 and ozone, whereas by using a BS/O 3 model, the same, or almost the same, increase in mortality is attributed to BS and ozone. By using these numbers in this assessment we will probably overestimate the acute health risk reduction of particulate traps in 2010. This is because the PM 10 concentration is expected to decrease from 40 µg/m 3 to around 30 µg/m 3 in 2010 due to the reduction of anthropogenic PM 10 emissions. However, to be able to compare the different assessments and to compensate for lack of information on the expected BS concentration in 2010, we use the number of premature deaths as mentioned above, namely about 2800 (PM 10 ) and 2000 (BS). It should be noted that, in addition to premature mortality, ambient air pollution and PM 10 or BS are also associated with a variety of morbidity effects like hospital admissions, worsening of asthma, use of medication and serious lung function decline. Although not the subject of this study, we may expect emission reductions to also result in a similar relative decrease in morbidity effects (leading to larger absolute numbers of people benefiting because the health effects are larger). 4 PM concentration and transport contribution Table 2 shows modelled source contributions to the anticipated anthropogenic PM 10 concentration in the Netherlands in 2010. The total PM 10 concentration in 2010 is expected to be around 30 µg/m 3. The contribution of Dutch transport to the country-average PM 10 concentration is very modest, only 3% ( 0.8 / 30 ), which means that reducing PM 10 emissions from Dutch transport will have a minor effect on the country-average PM 10 concentration. Table 2: Source contributions to average anthropogenic PM 10 concentration in the Netherlands in 2010 assuming a business-as-usual policy [1]. [µg/m 3 ] primary PM 10 secondary inorganic PM 10 primary + secondary inorganic PM 10 Dutch emission sources 2.0 1.5 3.5 of which transport a) 0.8 0.5 1.3 foreign emission sources 2.7 4.9 7.6 of which transport a) 0.9 1.4 2.3 all emission sources 4.8 6.3 11.1 of which transport a) 1.7 1.9 3.6 a) Including international sea-going ships in Dutch sea harbours. However, from epidemiological studies it appears that anthropogenic primary PM 10, in particular, is associated with health impact (see Chapter 1) and anthropogenic secondary inorganic PM 10 with natural PM 10 to a much lesser extent. Focusing only on anthropogenic primary PM 10 will increase the estimated
Urban Transport 447 health effect of measures in the transport sector: the share of transport in the average anthropogenic primary PM 10 concentration is 17% ( 0.8 / 4.8 ). In the first assessment we assumed the anthropogenic primary PM 10 concentration to be responsible for the observed health impact. If we use country-average concentrations as in Table 2, we will underestimate the health effect of particulate traps. This is because most people live in urban areas and the contribution of Dutch transport to the anthropogenic primary PM 10 concentration in urban areas is much higher than on average. Table 3 shows both the source contribution to the country-average PM 10 concentration and a typical source contribution to the PM 10 concentration in large cities (urban background). In the first assessment, we use the source contribution to the urban background concentration to assess the health risk reduction of particulate traps assuming anthropogenic primary PM 10 responsible for acute health impact. In other words, we use: C transport = 1.5 µg/m 3 and C total = 6.4 µg/m 3 in equation 1. In the second assessment we assumed that the observed acute health impact is caused by carbonaceous particles (PM carb ), consisting of elemental carbon (soot) and organic carbon (PAHs). Carbonaceous particles originate from combustion sources like transport, industries and power generation. Table 3 shows total PM 10 emissions per sector in 2010 and the share of carbonaceous emissions. Table 3 also shows the source contribution to the country-average PM 10 anthropogenic primary concentration and to the country-average PM carb or EC+OC concentration. Table 3: Total PM 10 emissions by Dutch emission sources in 2010 per sector and the contribution to PM 10 and EC+OC concentration in 2010 [1]. a) transport industry energy agriculture other total PM 10 emissions (million kg) Dutch sources 11.4 13.2 0.5 8.8 7.7 41.6 of which EC+OC 7.2 2.2 0.5 0.1 2.3 12.3 PM 10 concentration (µg/m 3 ) Dutch sources 0.8 0.2 0.0 0.5 0.5 2.0 of which EC+OC a) 0.5 0.0 0.0 0.0 0.1 0.6 other countries 0.9 0.7 0.3 0.1 0.6 2.7 of which EC+OC a) 0.6 0.1 0.3 0.0 0.2 0.8 all sources 1.7 0.9 0.3 0.6 1.1 4.8 of which EC+OC 1.1 0.2 0.3 0.0 0.3 1.4 a) Derived assuming that EC+OC have the same residence times as noncarbonaceous PM 10 and that dispersion characteristics are comparable. From Table 3 we conclude that Dutch transport is almost 35% (0.5/1.4) responsible for the country-average concentration of carbonaceous PM 10. However, in the transport contribution to the urban background PM 10 concentration in large cities is higher than the transport contribution to the
448 Urban Transport country-average PM 10 concentration (Table 4). In the same way, the contribution of transport to the carbonaceous PM 10 concentration is also probably higher in urban areas than on average. We estimated the transport contribution to the carbonaceous PM 10 concentration by assuming the relative share of EC+OC in primary PM 10 per sector to be independent of the concentration. We used the relative shares from Table 3 to derive the EC+OC concentration contributions in urban areas reported in Table 4. The relative share of Dutch transport in urban background EC+OC concentration is approximately 50%. In the second assessment, we used C transport /C total = 50% in equation 1, assuming EC+OC to be responsible for the observed acute health impact. Table 4: Source contributions to the anthropogenic primary PM 10, PMcarb (in 2010) and EC concentration (in 2001) assuming a business-as-usual policy [1, 4]. Primary PM a) 10 [µg/m 3 ] PM carb EC [µg/m 3 ] [µg/m 3 ] source country urban urban urban average background - background - background - in 2010 large cities in large cities in large cities 2010 2010 in 2001 Dutch emission 2.0 3.7 1.1 - sources of which transport 0.8 1.5 0.9 0.6 foreign emission 2.7 2.7 b) 0.8 - sources of which transport a) 0.9 0.9 b) 0.6 - all emission sources 4.8 6.4 1.9 1.2 of which transport a) 1.7 2.4 1.5 - Assessment 1 Assessment 2 Assessment 3 Dutch transport s share 17% 23% 50% 50% a) Results of modelling, assuming a 2010 business-as-usual policy [1]; b) We assumed the contribution of foreign emission sources to the concentration in large cities as being comparable to the contribution to the average concentration; c) Derived from PM10 concentrations at urban background stations in large cities in 2010 and the share of EC + EC in anthropogenic primary PM10 concentration (Table 2); d) Results of measurements in Amsterdam and Rotterdam (urban background stations) and in Vredepeel and De Zilk (rural background sites) in the Netherlands in 2001 [4]. Data on BS concentrations and the contribution of transport in large cities in 2010 are not available. Data on elemental carbon concentration are available, but there is no physical relationship between EC and BS. Besides, the absolute concentrations of EC and BS in urban areas differ sharply. However, we did assume that the relative contribution of transport to the BS concentration can be c) d)
Urban Transport 449 approximated by the relative transport contribution to the elemental carbon (EC) concentration. Table 4 also shows the unweighted average EC concentration on two urban background measuring sites in 2001 (= 1.2 µg/m 3 ). As background concentration we used the unweighted average EC concentrations on a rural agricultural site and a rural seashore site (= 0.6 µg/m 3 ). The difference between the urban background and the rural background is assumed to be 100% transport-related. This means that the relative transport contribution to the BS concentration in urban areas is 50%. In the third assessment, we use: C transport /C total = 50% in equation 1, assuming that Black Smoke is responsible for the observed acute health impact. 5 Transport PM emissions and effect of particulate traps As shown in equation 1, we need to know the total primary emissions from transport to estimate the health effects of particulate traps. Besides this, we need to know the absolute decrease in emissions as a result of the particulate trap stimulation programme. To calculate the latter we also need to know what emissions come from diesel cars, how many diesel cars are to be equipped with particulate traps in the case of a stimulation programme and by what percentage particulate traps reduce emissions. Table 5: Primary PM 10, PM carb and EC emissions from transport in 2010 [1]. PM 10 [mill. kg] PM b) carb [mill.kg] EC c) [mill. kg] combustion wear & tear total combustion combustion passenger cars 2.3 2.2 4.5 2.3 0.9 of which diesel 1.8 0.8 2.6 1.8 0.9 vans 0.8 0.6 1.4 0.8 0.4 trucks and lorries 1.0 1.1 2.0 1.0 0.5 buses 0.1 0.0 0.2 0.1 0.1 other road transport 0.4 0.0 0.4 0.4 0.1 total road transport 4.6 3.9 8.5 4.6 2.0 total non-road 5.6 0.0 5.6 5.6 2.6 transport a) total transport 10.2 3.9 14.1 10.2 4.6 a) Including international sea-going ships in Dutch sea harbours; b) Assuming combustion PM10 emissions to be 100% carbonaceous; c) EC emissions derived from PM10 combustion emissions assuming that diesel particulate contain 50% EC and petrol particulates 5% [5]. Table 5 shows total transport primary PM 10 emissions, PM carb emissions (EC+OC) and EC emissions in 2010. Total transport primary PM 10 emissions come to 14.1 million kg, of which only 1.8 million kg come from diesel car
450 Urban Transport exhaust. If all diesel cars are fitted with particulate traps in 2010, which would completely eliminate exhaust PM 10 emissions, the maximum emission reduction will be 13% (= 1.8 / 14.1 ) of total transport PM 10 emissions. EC emissions will be reduced by 20% (= 0.9 / 4.6 ). We believe the contribution of Dutch transport to the PM 10, PM carb and EC concentration in the urban background to mainly consist of road transport emissions. We therefore used the total road transport emissions in equation 1 instead of total transport emissions. In other words: in assessment 1, E transport = 8.5 million kg PM 10, in assessment 2, 4.6 million kg PM carb and in assessment 3, 2.0 million kg EC. The Dutch subsidy programme is not meant to equip old diesel cars with particulate traps but to increase the sales of new diesel cars with particulate traps. The programme is to start on 1 January 2005 and will last until the Euro-5 emission standards force the use of particulate traps. Euro-5 emission standards are currently under discussion but are expected to come into force no later than 2010. In 2010, diesel cars sold between 2005 and 2010 account for around 55% of all diesel car kilometres. So in 2010 only part of the diesel car fleet can be equipped with particulate traps. We assume that an average of 50% of the diesel cars sold between 2005 and 2010 will be equipped with particulate traps, and that the stimulation programme will be fully responsible for the sales of particulate-trap-equipped diesel cars. We have not taken in consideration that some manufacturers are already selling diesel cars with particulate filters and that many European car manufacturers, in particular, will come up with particulate-trap-equipped diesel cars in the coming years. We assume this development to be the result of car manufacturers anticipating the subsidy programmes which are in preparation in Germany and the Netherlands. In our assessment we assume particulate traps to reduce PM 10 and EC emissions (mass) by 90% [5]. 6 Short-term health risk reduction through the particulatetrap subsidy programme Combining the results from sections 3 to 5 we can derive the effect of the particulate trap stimulation programme on premature mortality in 2010 (see Table 6). Assessment 1, where the total number of premature deaths associated with daily PM 10 exposure is used and where only anthropogenic primary PM 10 is assumed to be health-relevant, results in a decrease in the total annual number of premature deaths of around 40, slightly more than 1% of the total number of premature deaths associated with short-term exposure to PM 10. Assessment 2, where the total number of premature deaths associated with daily PM 10 exposure is used and where only carbonaceous PM 10 is assumed to be health-relevant, results in a decrease in the total annual number of premature deaths of around 130, almost 5% of the total number of premature deaths associated with shortterm exposure to PM 10. Assessment 3, where the total number of premature deaths associated with daily black smoke (BS) exposure is used, results in a
Urban Transport 451 decrease of 120 deaths, which is 6% of the total number of premature deaths associated with short-term exposure to BS. Table 6: Summary of health impact assessments using various assumptions (hypotheses) for PM fractions responsible for PM-associated shortterm health impact. responsible for health impact total number of premature deaths relevant concentration (all sources) absolute transport contribution relative transport contribution road transport emissions effect of particulate traps emission reduction decrease in annual number of premature deaths in 2010 element in equation 1 assessment 1 assessment 2 assessment 3 anthropogenic carbonaceous Black Smoke primary PM 10 PM 10 (PM carb ) (BS) HE 2800 a) 2800 a) 2000 b) (2200 3500) (2200 3500) (1700 2500) C total 6.4 µg/m 3 1.9 µg/m 3 1.2 µg/m 3 c) C tramsport 1.5 µg/m 3 0.9 µg/m 3 0.6 µg/m 3 c) (C total / C tramsport ) * 100% 23% 50% 50% E transport 8.5 mill. kg 4.6 mill. kg 2.0 mill. kg E part. traps -0.4 mill. kg -0.4 mill. kg -0.2 mill. kg (E part. traps / E transport ) * 100% HE -5% -10% -10% 40 130 120 a) Total number of premature deaths associated with short-term exposure to the current PM 10 concentration (40 µg/m 3 ) in the Netherlands; b) Total number of premature deaths associated with short-term exposure to the current black smoke concentration (11 µg/m 3 ) in the Netherlands; c) Traffic contribution to EC used as a proxy for the traffic contribution to BS. Table 6 shows the effect on premature mortality in Assessment 2 (assuming PM carb as the causal fraction in PM 10 ) to be comparable to the effect in Assessment 3, where we started with the total number of premature deaths due to BS exposure. From this comparison we should not conclude that PM carb is the most harmful fraction of PM 10. The reason that both assessments lead to approximately the same health risk reduction is that Assessments 2 and 3 start, in principle, from the same number of premature deaths; this number is then divided over the two components in the model. In addition, BS and PM 10 concentrations are highly correlated: an increase in PM 10 concentration is almost
452 Urban Transport always accompanied by an increase in BS level. The use of relative risks for PM 10 and the average PM 10 concentration therefore leads to approximately the same number of premature deaths as when the relative risk for BS from the same study and the average BS concentration are used. Because the share of traffic in both the PM carb and the BS concentration is around 50%, both assessments give about the same health impact and the same health risk reduction of subsidizing particulate traps. In conclusion, the health risk reduction of the subsidy programme depends on the assumptions about what part of PM 10 causes premature mortality. The more we focus on the particulate fraction emitted by traffic, the higher the calculated health risk reduction is (Assessment 1 2). When we choose a more trafficrelated air pollutant (BS instead of PM 10 ) to calculate premature mortality, we will also obtain a higher health gain (Assessment 1 3). Another conclusion from our assessments is that the relative effect of the 2010 programme on premature mortality is approximately -5% at the maximum. One should bear in mind that the share of all diesel cars in total PM 10 emissions in the Netherlands in 2010 is only 6% and the share of diesel cars in the average PM 10 concentration is even smaller, around 1%. Equipping all diesel cars in 2010 with particulate traps would quadruple the effect on acute premature mortality, because in our assessment around 25% of all diesel cars in 2010 are equipped with a subsidized particulate trap. However, retrofitting older diesel cars with particulate traps is not very realistic. 7 Uncertainty and discussion Calculating health risk reductions from planned or implemented PM emission control measures is surrounded with uncertainties. Relative risk factors to be used in impact assessment change over time due to altered PM composition resulting from abatement measures. A specific emission reduction as a result of an abatement scenario or a particular control measure may not necessarily run parallel with a reduction in the causal component for health effects. Impact assessments are usually not regionalized and benefits from particular regional or urban measures are difficult to assess. To overcome these uncertainties we will have to use a number of assumptions or even run the risk reduction assessment by means of a hypothesis. Assessments like these could be improved by doing a time-series analysis using locations with a distinctive PM 10 composition, e.g. a rural village and a large city. Different chemical and size fractions of PM 10 should also be measured. In the hypothetical case that only PM 0.1 (ultrafine PM) causes premature mortality, comparable relative risk factors for PM 0.1 in both rural villages and large cities will be the result. Relative risk factors for PM 10 will, in this case, be lower in rural villages than in large cities, because the share of PM 0.1 in PM 10, although relatively small, is larger in large cities than in rural villages. To assess the health impact of chronic exposure to PM and to estimate the possible chronic health risk reduction as a result of specific emission control
Urban Transport 453 measures is even more difficult. IIASA recently assessed that tens to hundreds of thousands of people die prematurely in Europe per year, a rate that is associated with a shortened life expectancy of about 1-3 years [7][8]. IIASA used PM 2.5 epidemiological cohort data [6] from the United States. However, these chronic health impact assessments are surrounded by large uncertainties and are not understood. Therefore, we did not use these cohort data to assess the chronic health effects of particulate traps. In an effort to try to deal with chronic PM exposure from diesel engine emissions we estimated the decrease in lung cancer of equipping all diesel vehicles (cars and trucks) with particle traps. We used the California EPA unit risk factor for diesel PM and lung cancer and the average concentration of diesel PM on urban background sites in 2010. An almost 100% decrease in diesel PM concentration would, from a long-term perspective, then result in a decrease in the annual number of lung cancer victims of around 50, which is 0.04% of total annual mortality in the Netherlands. It should, however, be noted that this health risk reduction due to decreased chronic exposure will be observable only after a rather long period of time and relatively short-term interventions might not be that effective on a short notice. Despite the uncertainty about what fraction of PM 10 causes the observed short-term health impacts, subsidizing particulate traps could still be justified from a precautionary perspective and besides, long-term exposure to diesel PM is harmful to humans. References [1] RIVM. On health risks of ambient PM in the Netherlands, National Institute for Public Health and the Environment: Bilthoven, The Netherlands, 2002. (http://www.rivm.nl/bibliotheek/rapporten/650010032.pdf) [2] RIVM, Milieubalans 2004 (Environmental Balance 2004 Summary) National Institute for Public Health and the Environment: Bilthoven, The Netherlands, 2004. [3] WHO, Health Aspects of Air Pollution results from the WHO project Systematic Review of Health Aspects of Air Pollution in Europe, World Health Organisation: Copenhagen, Denmark, June 2004. (http://www.euro.who.int/document/e83080.pdf). [4] Visser, H., Buringh, E. & Van Breugel, P.B., Composition and Origin of Airborne Particulate Matter in the Netherlands, National Institute of Public Health and the Environment: Bilthoven, The Netherlands, 2001. [5] Burgwal, E. van de, Foster, D.L., Bremmers, D.A.C.M. & Gense, N.L.J., In-use compliance programme passenger cars; annual report 2003, TNO Automotive: Delft, The Netherlands, 2004. [6] Pope, C.A., Burnett, R.T., Thun, M.J., Calle, E.E., Krewski, D., Ito, K. & Thurston, G.D., Lung cancer, cardiopulmonary mortality and long-term exposure to fine particulate air pollution. JAMA 287, pp. 1132 1141, 2002.
454 Urban Transport [7] WHO, WHO Air Quality Guidelines for Europe, 2nd edition, WHO Regional Publications, European Series, No. 91, 2000. [8] IIASA, Baseline Scenarios for the Clean Air for Europe (CAFE) Programme: Final Report, International Institute for Applied Systems Analysis: Laxenburg, Austria, October 2004. [9] Schlesinger R.B. & Cassee F.R, Atmospheric secondary inorganic particulate matter: the toxicological perspective as a basis for health effects risk assessment, Inhalation Toxicology 15, pp. 197 235, 2003.