Public Health Impacts of Combustion Emissions in the United

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Public Health Impacts of Combustion Emissions in the United Kingdom Steve H. L. Yim and Steven R. H. Barrett* Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States S Supporting Information *

ABSTRACT: Combustion emissions are a major contributor to degradation of air quality and pose a risk to human health. We evaluate and apply a multiscale air quality modeling system to assess the impact of combustion emissions on UK air quality. Epidemiological evidence is used to quantitatively relate PM2.5 exposure to risk of early death. We find that UK combustion emissions cause ∼13,000 premature deaths in the UK per year, while an additional ∼6000 deaths in the UK are caused by non-UK European Union (EU) combustion emissions. The leading domestic contributor is transport, which causes ∼7500 early deaths per year, while power generation and industrial emissions result in ∼2500 and ∼830 early deaths per year, respectively. We estimate the uncertainty in premature mortality calculations at −80% to +50%, where results have been corrected by a low modeling bias of 28%. The total monetized life loss in the UK is estimated at £6−62bn/year or 0.4−3.5% of gross domestic product. In Greater London, where PM concentrations are highest and are currently in exceedance of EU standards, we estimate that non-UK EU emissions account for 30% of the ∼3200 air quality-related deaths per year. In the context of the European Commission having launched infringement proceedings against the UK Government over exceedances of EU PM air quality standards in London, these results indicate that further policy measures should be coordinated at an EUlevel because of the strength of the transboundary component of PM pollution.

1. INTRODUCTION Poor air quality adversely impacts human health.1,2 In particular, long-term exposure to fine particulate matter results in an increased risk of premature mortality,1,3−5 with the likelihood of a causal link estimated at 90%.6,7 Although other anthropogenic air pollutants are known to cause adverse health impacts, long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) is understood to be the air pollution exposure metric that is most consistently and independently associated with early death, and which accounts for the majority of the health costs of air pollution.1,4 In 2009, the Committee on the Medical Effects of Air Pollutants (COMEAP) estimated that there were ∼29,000 early deaths in the UK in 2008 due to anthropogenic PM air pollution.4 This corresponds to ∼340,000 life-years lost per year.4 The COMEAP approach was based on a combination of modeling and measurements of PM concentrations with a scheme designed to achieve “mass closure” relative to measured concentrations. Stedman et al.8 developed the method applied by COMEAP to map PM concentrations across the UK at background and roadside locations by summing modeled and empirical components. In addition to the aforementioned health impacts, the UK is currently not in compliance with the legally binding EU PM air quality standard on account of exceedances in London.9 Because of this, the European Commission has recently launched infringement proceedings against the UK Govern© 2012 American Chemical Society

ment for this continuing breach, with the potential for unlimited fines subject to ruling by the European Court of Justice.9 Results of Whyatt et al.10 indicate that emissions control of primary PM alone would not be sufficient to meet European Union (EU) limit values for PM concentrations. Andersson et al.11 estimated the contribution of different European regions to population PM exposure and premature mortality. In the UK, the costs and benefits of the past and potential mitigation policies for electricity generation and road transport were estimated using a combination of dispersion modeling and empirical components for secondary PM.12 While these studies have added to understanding of PM concentrations in the UK, the attribution of air quality-related premature mortalities to different sectorsboth within the UK and from the rest of the EUhas not previously been quantified. The primary control the UK has on its PM concentrations is by influencing domestic (i.e., within the UK) combustion emissions, although a significant fraction of impacts may be transboundary.11 The predominant sources of anthropogenic PM pollution are combustion emissions of primary PM and precursors of secondary PM. Here we estimate the number of Received: Revised: Accepted: Published: 4291

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Simulated baseline concentrations are validated against UK National Air Quality Archive time series data from 79 O3, 79 NO2, 61 PM10, and 4 PM2.5 measurement stations. See Section 3 of the SI for further information on the air quality simulation and validation. 2.3. Health Impacts. The relationship between long-term exposure to particulate matter and health has been quantified in epidemiological studies.21−26 These studies have consistently found that long-term exposure to particulate matter less than 2.5 μm in diameter (i.e., PM2.5) is associated with increased risk of premature mortality. Assessing long-term PM2.5 exposure is thought to capture ∼80% of monetized health impacts of air pollution.27 We therefore focus on long-term PM2.5 exposure and associated increased risk of premature mortality. Concentration−response functions (CRFs) relate changes in PM2.5 exposure to changes in premature mortality risk. A U.S. EPA expert elicitation study reported a 1% (with a range of 0.4−1.8%) decrease in annual all-cause deaths per μg/m3 decrease in annual average PM2.5 exposure.1 Results are similar to an EU expert elicitation study.28 We apply the EPA CRF to estimate early deaths in UK due to long-term exposure of sector-attributable PM2.5 for adults over 30 years of age. The UK all-cause baseline death incidence rate is based on WHO Health Statistics and Health Information Systems (2004). Population density data are derived from the Gridded Population of the World (GPWv3) at a 2.5′ resolution.29

domestic early deaths per year attributable to UK combustion emissions from sectors including power generation, commercial, institutional, residential and agricultural sources, industry, and transport. We also quantify the contribution of non-UK EU emissions to air quality-related deaths in the UK, and vice versa. The purpose of this is to inform UK and EU air quality and emissions policy development.

2. MATERIALS AND METHODS Our overall approach is to derive a temporally, spatially, and chemically resolved emissions inventory for the UK (at high resolution) and the EU (at low resolution) suitable for use in a state-of-the-science atmospheric chemistry-transport model. We evaluate meteorological and baseline air quality simulations to quantify the extent to which the modeling approach reproduces observed meteorological fields, total PM, and other species concentrations due to all emissions. Scenarios are modeled in which each sector’s combustion emissions are removed in-turn. We attribute the difference between the resultant PM concentrations for each sector simulation and the simulation of total PM to the respective sector. Nonlinearities are assessed for UK emissions by modeling a case where all UK combustion emissions are removed. The impact of UK combustion emissions on EU air quality and vice versa are also simulated. Premature mortality impacts of each sector are estimated by overlaying sector-attributable PM concentrations onto population density, and multiplying the resultant exposure by a concentration−response function. 2.1. Emissions. Emissions in the UK are derived from the 2007 National Atmospheric Emissions Inventory (NAEI),13 which has a horizontal resolution of 1 km ×1 km. In the rest of Europe, the 2007 European Monitoring and Evaluation Programme (EMEP)14 inventory is applied for area sources. EMEP has a horizontal resolution of 50 km ×50 km. Point source emissions outside the UK are from the European Pollutant Release and Transfer Register (E-PRTR).15 We calculate plume rise in-line for each point source according to Briggs et al.16 Emissions are divided into United Nations Economic Commission for Europe (UNECE) source categories (“sectors” in this paper): (a) power generation; (b) commercial, institutional, residential, and agricultural sources; (c) industry; (d) road transport; and (e) other transport. Uncertainties in the emissions inventories, and temporal and vertical emissions profiles are described in Section 1.4 of the Supporting Information (SI), along with assumed chemical speciation profiles for VOCs, NOx, SOx, and primary PM emissions. 2.2. Meteorological and Air Quality Modeling. The Weather Research and Forecasting Model (WRF)17 is used to derive meteorological fields, driven by six-hourly ECMWF reanalysis for the year 2005.18 European meteorology is simulated at a resolution of 40.5 km, with a two-way nest to a 13.5 km domain encompassing the UK. Meteorology is validated with reference to 106 wind stations and 139 temperature stations in the UK. See Section 2 of the SI for further information on the meteorological simulation and validation. The regional chemistry-transport model CMAQ19 is applied to simulate air quality in Europe at a resolution of 40.5 km, with a nested 13.5 km grid for the UK. The global chemistrytransport model GEOS-Chem20 is applied for 2005 to provide boundary conditions to the CMAQ 40.5 km European domain.

3. RESULTS AND DISCUSSION 3.1. Model Evaluation. A set of statistical measures as recommended by U.S. EPA is estimated30 including index of agreement. An index of agreement of 1 indicates perfect agreement between the model and observations, while 0 indicates no agreement. On average, the WRF model achieved 0.83 indices of agreement for both wind speed and temperature. The simulated mean wind speed has a bias of +18% and temperature (in °C) −6% relative to observations. Further statistical parameters are given in Table 4 in the SI. Average indices of agreement for O3, NO2, PM10, and PM2.5 are 0.63, 0.53, 0.5, and 0.7, respectively. Other model evaluation metrics are shown in Tables 5 and 6 of the SI. The annual mean PM2.5 modeling bias for all stations is −28% or −20% excluding the roadside station, where the greatest bias is −52% and the smallest is −9%. We note that the average bias for PM10 in the UK is −65%, likely due to incomplete representation of coarse PM in our PM2.5-focused setup. We represent the uncertainty in our CMAQ results for PM2.5 as having a nominal bias of −28% with an uncertainty range of −65% to −9%, where the lower bound has been extended to capture the mean bias in PM10. This assumed bias is due to a combination of emissions and atmospheric modeling uncertainty. (See Section 3 in the SI for further discussion on emissions uncertainty and assessment of modeling biases.) 3.2. PM2.5 Impacts. Figure 1 depicts the annual average ground-level PM2.5 concentration due to different combustion sources. A gradient from northwest to southeast is observed which is consistent with the finding in Stedman et al.8 Road transport contributes the highest proportion of the annual average ground-level PM2.5 concentration among all sectors, especially in southeast England. The population-weighted PM2.5 concentration attributable to road transport in the UK is 0.75 μg/m3. Figure 2 illustrates annual average ground-level soot (black carbon (BC)) and nitrogen dioxide (NO2) concentrations attributable to road transport. The ground4292

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Figure 3. Annual average (a) BC concentration due to UK other transport and (b) SO4 concentration due to UK power generation emissions.

representing approximately half of total national SOx emissions. Figure 3b depicts the annual average ground-level sulfate concentration due to power generation. The Northern East Midlands region has a ground-level sulfate perturbation of up to 1 μg/m3. This is likely attributable to the five major (>1900 MW capacity) power plants located in that region. In part due to the southwesterly prevailing winds in southeast England, the population-weighted ground-level PM2.5 concentration in London due to power generation is 0.38 μg/m3a third of road transport’s impact. Finally, combustion emissions from commercial buildings, institutional, residential, agriculture, and industries together contribute 0.26 μg/m3 to the population-weighted PM2.5 concentration in the UK. Impacts are approximately even throughout southern and central England. 3.3. Health Impacts (Nominal Estimates). Applying the central CRF (a 1% increase in risk of premature mortality per μg/m3 of long-term exposure to PM2.5) to our CMAQ results we calculate “nominal” estimates of early deaths per year attributable to each sector, which are shown in Table 1. A total

Figure 1. Annual average PM2.5 concentration due to combustion emissions from (a) power generation; (b) commercial, institutional, residential, and agricultural sources; (c) industry; (d) road transport; (e) other transport; and (f) all UK combustion sources.

Figure 2. Annual average (a) BC and (b) NO2 concentration due to UK road transport emissions.

Table 1. Central Estimates for Early Deaths Per Year in the UK by Combustion Sector Calculated Using the High Resolution Modeling Domaina

level [BC] and [NO2] perturbation due to road transport has local peaks in cities due to the localized nature of BC and NOx emissions and their direct (i.e., non-secondary) impacts. By contrast, the total (primary + secondary) PM2.5 impacts of road transport are relatively diffuse (Figure 1a). Population-weighted [PM2.5] due to road transport in London is 1.21 μg/m3, which is 1.6 times higher than the UK average for populationweighted [PM2.5] due to road transport. Other transport is the second highest contributor to population-weighted annual average ground-level [PM2.5] (closely followed by power generation). According to the NAEI, other transport produces 21% (0.02 Tg (−20 to +30%)) of UK annual primary PM2.5 emissions, ahead of other sectors. Figure 3a shows the annual average ground-level [BC] due to other transport. It illustrates the local peaks of BC at (marine) ports and airports. Other transport contributes 0.42 μg/m3 to population-weighted [PM2.5] in the UK. It is calculated that the London population-weighted [PM2.5] attributable to other transport emissions is 0.51 μg/m3. This is partly associated with the London airports, including Heathrow, Luton, Gatwick, Stansted, and London City. Combustion emissions from power generation result in an average population-weighted PM2.5 concentration of 0.4 μg/m3 in the UK. Among different PM2.5 species due to power generation, sulfate aerosol accounts for 62% of the total population-weighted PM2.5. According to the NAEI, power generation is responsible for 0.29 Tg (±4%) of SOx emissions,

nominal early deaths/year (UK)

sector power generation commercial, institutional, residential and agriculture industry road transport other transport all UK combustion

corrected central estimate and uncertainty (90% CI)

1700 1100

2500 (1400−3800) 1600 (850−2400)

560 3300 1800 9000

830 (440−1200) 4900 (2600−7200) 2600 (1400−4000) 13,000 (6900−20,000)

a

Note that results from simulations of individual sectors do not sum exactly to results from a simulation of all UK combustion sectors due to nonlinearities. (Nonlinearities result in a 6% discrepancy in early deaths when comparing the sum of sector simulations to the all-sector simulation results.)

of 9000 UK premature mortalities are estimated to be attributable to UK combustion emissions, of which 3300, 1800, and 1700 deaths per year are due to road transport, other transport, and power generation emissions, respectively. We note that the road transport estimate in particular is likely to be an underestimate, as the peaks in roadside PM2.5 may not be accurately represented due to our model resolution. For example, while CMAQ underestimates [PM2.5] by 20% on average at the non-roadside PM monitoring stations, it 4293

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underestimates the average PM2.5 concentration by 52% at the London Marylebone Road station (located 1 m from the curb). We use ArcGIS to overlay CMAQ gridded results for each sector onto UK administrative regions. The nominal estimate for number of premature deaths caused by different combustion sources in different UK administrative districts is shown in Section 5 of the SI, along with the definition of districts. We find that power generation has greater health impacts than other transport in South Yorkshire districts and Yorkshire and the Humber region; however, compared to power generation, other transport causes more combustion emissions-attributable premature mortalities in the South West and East districts, Merseyside district, and London. Road transport contributes 27−50% (36% on average) of the total combustion emissions-attributable premature mortalities across the different districts. In particular, the results show that road transport causes 660 premature mortalities in Greater London, representing half of total premature mortalities in the city associated with all combustion emissions. For London, we calculate that the premature mortalities associated with the other transport and power generation are 280 and 200, respectively. The higher health impacts due to other transport compared to power generation may be associated with airports around Londonespecially Heathrow to the west and Gatwick to the southand the prevailing southwesterly wind. This means that power generation emissions, which are predominantly to the northeast of major population centers and have higher effective emissions heights, are less damaging on a per unit emission basis to UK public health. 3.4. Uncertainty Estimation. We estimate the uncertainty in the premature mortality calculations. The uncertainty in the CRF is accounted for with a triangular probability distribution of multipliers with (low, nominal, high) values of (0.355, 1.06, 1.81),23 where the low, nominal, and high values correspond to the vertices of the distribution function. The bias and uncertainty in modeling PM concentrations is represented by a triangular distribution of multipliers with (low, nominal, high) values of (1.09, 1.25, 1.65). A uniform distribution with range (1, 1.06) is selected to account for the uncertainty due to the nonlinearities when comparing the sum of sector simulations to the all-sector simulation results. The ∼10% probability of no causal link between PM2.5 exposure and premature mortality has not been accounted for quantitatively. Uncertainty ranges and corrected central estimates accounting for biases in modeling are shown in Table 1, where ranges are 90% confidence intervals. For example, the corrected central estimate for premature mortalities attributable to road transport emissions is 4900 per year with a range of 2600−7200, which can be compared to the nominal estimate of 3300. Estimates for other sectors are given in Table 1. We note that a potentially significant unquantified uncertainty is the differential toxicity among PM species. Expert committees have concluded that there is currently no strong basis for an alternative to the assumption of equal toxicity among PM species.30 However, BC is likely more toxic than other PM constituents,31 which indicates that the health impact of road transport is likely to be further underestimated. 3.5. Transboundary Impacts. Understanding transboundary air pollution is of importance when considering environmental policy measures at an EU level. Figure 4a illustrates the annual average PM2.5 concentration associated with combustion emissions from non-UK EU sources. We find that the PM2.5

Figure 4. Impact of non-UK EU combustion emissions on the UK expressed as (a) an absolute perturbation, and (b) the percentage of total UK PM2.5 contributed by non-UK EU combustion emissions.

perturbation due to non-UK EU combustion emissions is approximately 2 μg/m3 in the southeast of the UK and ∼1 μg/ m3 in the Midlands. This result is consistent with the finding of Malcolm et al.32 The population-weighted PM2.5 concentration in London due to non-UK EU combustion emissions is 1.17 μg/m3, which is approximately equal to the impact of UK road transport emissions (1.21 μg/m3). We estimate that 4100 (nominal estimate) early deaths are associated with non-UK EU combustion emissions, of which 650 are in London as shown in Table 2. (A corrected central estimate and uncertainty range is also given in Table 2.) Figure 4b shows the percentage of total UK PM 2.5 contributed by non-UK EU combustion emissions. (Here “total” is the sum of PM2.5 caused by UK plus non-UK EU combustion emissions.) It can be seen that the minimum value is 30% in the Midlands and the Central Belt in Scotland, while in the Highlands >70% of [PM2.5] is due to non-UK EU emissions. Our results show that [PM2.5] attributable to nonUK EU combustion emissions accounts for approximately 40% of the total along parts of the south and east coasts of England. The PM2.5 concentration at monitoring stations at Rochester, Barcombe Mills, Southampton, Yarner Wood, and Stoke Ferryanalyzed in Malcolm et al.also indicates that ∼40% of total [PM2.5] comes from outside UK. Table 2 depicts the nominal and corrected central estimates (with uncertainty ranges) for early deaths per year in the UK and the rest of the EU. Results for the rest of the EU are based on the lower resolution (40.5 km) CMAQ results. Non-UK EU combustion emissions result in 4100 (nominal estimate) premature deaths in the UK per year, while UK combustion emissions account for 8500 early deaths in the UK. This indicates that transboundary pollution accounts for one-third of the combustion emissions-attributable deaths per year in the UK. Conversely, UK combustion emissions cause 3100 premature mortalities per year in other EU member states, or 2% of the total 130,000 early deaths per year in the non-UK EU. As non-UK EU emissions are higher than the UK alone, this implies that on a per unit emission basis, the UK “exports” more public health damage to the rest of the EU than it “imports”. This is consistent with prevailing southwesterly/ westerly winds. 3.6. Implications for Policy. The road transport sector is found to be the major contributor to PM2.5 exposure in the UK, and the resulting premature mortalities are comparable to the 2946 deaths due to road accidents in 2007,33 indicating that the 4294

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Table 2. Central Estimates for Early Deaths Per Year in the UK and the Rest of the EU Calculated Using Results from the LowResolution Domain for Non-UK Deaths and the High-Resolution Domain for UK Deathsa emissions sources removed all UK combustion all non-UK EU combustion total a

UK early deaths/year

non-UK EU early deaths/year

greater London early deaths/year

8460 [12,000 (6800−19,000)] 4100 [6000 (3200−9000)] 12,560

3100 [4500 (2400−6700)] 130,000 [190,000 (100,000−290,000)] 133,100

1500 [2200 (1100, 3300)] 650 [960 (530−1400)] 2150

Corrected central estimates and uncertainty ranges are shown in italics.

Notes

public health impacts of road transport are likely to be 50% greater than fatal accidents as measured by attributable premature mortalities. (The number of deaths on UK roads decreased to 1850 in 2010.) We note that an air quality-related mortality is not equivalent to a fatal road accident in terms of life years lost on average. For example, approximately half of those who died on UK roads in 2007 were under 40, implying a loss of life of ∼35 life years per mortality, compared to the ∼12 life years lost per air quality mortality estimated by COMEAP. This means that road accidents are still likely to result in a greater loss of life years than road transport emissions. Approximately one-sixth of PM2.5 exposure attributable to transport (as a whole) is BC (see Tables 7 and 8 in the SI). This can be compared to 1−2% for other sectors and is indicative of the extent to which road transport has localized impacts due to the positive correlation between road transport emissions and population density. On the other hand, sulfate impacts of road transport represent 1% of the sector’s total PM2.5 impact, which can be compared to figures of 10% for industry to 62% for power generation. This is consistent with the low sulfur fuel used in road transport in the UK and the high sulfur coal-fired power stations in use. Taken together, these findings suggest further efforts to reduce UK power station SOx emissions should be assessed for their costs and benefits, while for road transport the planned reductions in allowable primary PM emissions may have significant health benefits. In terms of economic impacts, we estimate that combustion emissions cost the UK £6−62bn/year. This corresponds to 0.4−3.5% of UK gross domestic product in 2007. The bounds correspond to medians of typical EU and U.S. approaches to monetizing early deaths (see Section 6 of the SI). The extent of transboundary pollution between the UK and other EU member states can be illustrated by noting that (i) one-third of premature mortalities in the UK caused by combustion emissions are due to emissions from other EU member states, and (ii) UK combustion emissions cause onethird again as many early deaths in the rest of the EU as they do in the UK. These results indicate that further policy measures should be coordinated at an EU-level because of the strength of the transboundary component of PM pollution, and that the EU as a whole is responsible for air quality in any given member state.

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The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was started under the Energy Efficient Cities initiative at the University of Cambridge, funded by EPSRC. We thank EPSRC for initial funding and MIT for supporting the conclusion of the work.

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ASSOCIATED CONTENT

* Supporting Information S

Further discussion, analyses, and results. This material is available free of charge via the Internet at http://pubs.acs.org.

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REFERENCES

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