The new proposed Hong Kong Air Quality Objectives: A health impact assessment. A scientific appraisal of the health impacts arising from the new

Transcription

1 Version: AQO_ The new proposed Hong Kong Air Quality Objectives: A health impact assessment A scientific appraisal of the health impacts arising from the new Air Quality Objectives proposed by Ove Arup & Partners Hong Kong Ltd in the public consultation forum on 20 th March 2009 Hak-Kan Lai PhD, Chit-Ming Wong PhD, Sarah McGhee PhD, Anthony Hedley MD Department of Community Medicine School of Public Health The University of Hong Kong 5/F, William MW Mong Building, 21, Sassoon Road, Pokfulam, Hong Kong June 2009 Address for correspondence: Professor AJ Hedley hrmrajh@hkucc.hku.hk Dr CM Wong hrmrwcm@hkucc.hku.hk Dr HK Lai laihk@hkucc.hku.hk Department of Community Medicine School of Public Health 5/F, 21 Sassoon Road, Pokfulam, Hong Kong Tel: Fax: commed@hkucc.hku.hk.hk

2 What benefits can we expect from the new proposed Air Quality Objectives for Hong Kong? A health impact assessment An epidemiological and economic appraisal of the population health effects and community costs arising from air pollution in Hong Kong based on the proposals made by Ove Arup & Partners Hong Kong Ltd 2

3 Executive summary Key messages in this appraisal:! EU or UK s standard are no longer the most stringent standards. For example, the UK standards were established half a decade before the WHO guidelines/interim targets published in 2006, that is about 10 years ago, i.e. Hong Kong should not base decision making on old standards (Appendix 1, page 37).! This appraisal is based on the principle that AQOs are meant to safeguard the population health from polluting activities.! The appraisal is based on the pollutant concentrations recorded in general monitoring stations and the use of a valid prediction model to forecast the change of the annual mean levels under the newly proposed short-term AQOs.! The method for counting exceedance currently used by the consultant is not compatible with the World Health Organization guidelines or the European Union method (Table 1, page 9).! Increasing the number of exceedances as proposed by Arup could elevate the annual mean concentrations of pollutant (Figure 5, page 12).! The AQOs proposed by Arup do not correspond to either the WHO guidelines or interim targets because of the high number of permitted exceedances (Table 3, page 14).! There is special concern about SO 2. The Arup IT-1 for 24-hour SO 2 may lead to increasing pollution from sulphur-rich fuels and an elevation of the annual mean concentrations of SO 2 (Figure 6, page 16).! None of the Arup AQOs will reliably achieve air quality improvement from the existing levels to at least halfway towards the levels which would be achieved through compliance with WHO Air Quality Guidelines (AQG) (Table 4, page 23).! Arup AQOs may substantially increase (e.g. by 250%) the total numbers of young children with respiratory ill-health symptoms and the number of deaths attributable to air pollution will remain high (Table 6, page 28).! Only by adopting AQOs which will reliably achieve predicted mean levels at least halfway towards those expected under the WHO AQG will we initially ensure reduction of adverse population health effects. With such an approach, the total cost of the health burden can be reduced by about 70% from the current level (as in 2007).! An independent surveillance system for monitoring the progress of the exceedances of AQO is proposed as an extension of the Hedley Environmental Index (page 35). 3

4 Abbreviations and glossary AQG Air Quality Guideline AQO Air Quality Objective Arup Ove Arup & Partners Hong Kong Ltd CNG compressed natural gas EPD Environmental Protection Department EU EEA the European Union s European Environment Agency IT interim targets NAAQS National Ambient Air Quality Standards Ni Nickel NO 2 Nitrogen dioxide NO x Nitrogen oxides O 3 Ozone PM 10 Particulate matters will aerodynamic diameter less than 10!m PM 2.5 Particulate matters will aerodynamic diameter less than 2.5!m RSP Respirable suspended particulates SAR Special Administrative Region SO 2 Sulphur dioxide US EPA the United States Environmental Protection Agency V Vanadium WHO World Health Organization!g m -3 Micrograms per cubic metre 4

5 1.0 Background In 2007 the Hong Kong SAR government implemented a review of the air quality objectives which were introduced in 1987 and have remained unmodified since. In 1987 the World Health Organization published its first edition of the WHO Air Quality Guidelines for Europe. Two further editions and updates followed in 2000 and 2004, but Hong Kong did not modify its AQOs at these times. In 2000 the WHO formed a new steering group to lead and coordinate a further comprehensive review of the research evidence on the relationship between air quality and health. In October 2005, following a final meeting in Bonn of the Working Group including the principal reviewers, the WHO published its new report on Air Quality Guidelines: global update 2005, together with an executive summary. The hard copy version, including minor edits was published in Both China and the Hong Kong SAR were represented at the final working group meeting. One of these representatives was a full member of the Steering Group throughout its deliberations and the other a reviewer of the draft report. The new WHO AQGs are based on a comprehensive review of the extensive scientific literature on air pollution and health effects, amounting to several hundred scientific papers emanating from authors on five continents. There was a substantial amount of information from Asia considered by the expert review, including reports from mainland China and Hong Kong. In the Executive Summary of this AQG global update WHO identified only sixteen key references (out of 301 in the full report) in support of its conclusions; two of these are from Hong Kong. A summary of the current evidence on air pollution and health effects can be found in Air Pollution and Public Health: The current avoidable burden of health problems, community costs and harm to future generations (AJ Hedley. February 2009 Amended June 2009). The WHO AQGs represent the best evidence currently available on the benefits of cleaner air. The guidelines do not necessarily define safe air because there is no identifiable threshold for the harm to health from pollutants, however the guidelines do indicate the minimum levels of air quality control needed for the protection of public health given the current state of our knowledge. The WHO AQGs are designed to offer guidance in reducing the health impacts of air pollution and are intended for worldwide use to support actions to achieve clean air, which is a basic requirement of human health and well-being. A comparison of the 1987 Hong Kong AQO with the current WHO guidelines clearly demonstrates how far adrift the present Hong Kong regulatory indicators are from the WHO advisory. The community costs in terms of doctor visits, hospital admissions and deaths, together with their dollar values can be reliably estimated from Hong Kong routine data on air quality, health care utilisation and deaths on a daily basis ( 5

6 2.0 Air pollutants 2.1 What are the criteria pollutants? The World Health Organization identifies five pollutants, particulates (PM 10 ), nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ), ozone (O 3 ) and carbon monoxide, as the most prevalent and important pollutants relevant to health protection. Although carbon monoxide, at present urban levels, is a potentially important cause of health problems such as cardiovascular disease, the current research focus is mainly on the other four pollutants PM 10 (also referred to as Respirable Suspended Particulates (RSP)), NO 2, SO 2 and O 3. The most important sources of these air pollutants include power generation, marine and port activities, road traffic and manufacturing industry. The most polluting fuels include coal, heavy residual oil and both gasoline and diesel for road vehicles. In Hong Kong, since the legislative restriction of sulphur to 0.5% by weight in all land based fuels in 1990 and subsequent regulation of road diesel to ultra low sulphur (ULSD) content of 0.005%, the sulphur dioxide concentrations together with other toxic emissions from high sulphur fuels such as nickel and vanadium have been greatly reduced over a period of 20 years, resulting in health benefit gains in terms of reduction of mortality and morbidity. Nevertheless, this improvement is modest when compared with other metropolitan cities, such as London (see Appendix 1) or Delhi where the mandatory use of compressed natural gas (CNG) led to marked improvement in air quality. Furthermore levels of SO 2 are now once again on the increase. For particulates and nitrogen dioxide, the levels in Hong Kong have remained much higher than in many other cities of the same population scale (data not shown) and have been more or less stable at these high levels for many years (Figure 1 and 2). A very high level of exceedances of the current WHO guidelines characterises the pattern of pollution in Hong Kong. It is also clear that the levels of pollution are much higher during the cool season than the warm season. Although the resident population benefits from the lower levels of pollutants (mainly PM 10 and NO 2 ) during the warm seasons, due to southerly air mass movements and other meteorological factors, daily levels of pollutants often exceed WHO 24-hour guidelines and the average remains well above the annual guideline. In addition, the roadside pollution levels are also much higher than the levels recorded at general stations, which are located at the rooftop of the buildings at an average of about 20 metres above ground. These spatial and seasonal variations in pollutant exposures must be considered in relation to the health impacts of interventions and not simply annual average levels. 6

7 Figure 1. PM 10 concentrations (µg m -3 ) from year 2003 to 2008 compared with the WHO 24-hourly and annual guidelines. WHO Guideline (24-Hourly) WHO Guideline (Annual) Figure 2. NO 2 concentrations (µg m -3 ) from year 2003 to 2008 compared with the WHO 1-hourly and annual guidelines. WHO Guideline (1-Hourly) WHO Guideline (Annual) 7

8 2.2 An objective method to define an average pollution level for Hong Kong the population exposure perspective When assessing the ambient average pollution level, it is important to look at the levels that can best represent the population exposures. Simply using either the general station average or the roadside station average cannot provide an objective representation of the overall population exposure because in terms of population-time (i) at least 50% of the Hong Kong population live or work beside busy roads (McGhee et al., 2005), (ii) the whole Hong Kong population spends about 10% of time in transportation or as pedestrians at street level being exposed to the roadside levels, (iii) the road emissions are not easily dispersed in many densely populated districts due to the canyon street effects (characterised by narrow roads surrounded by tall buildings), and (iv) the proposed traffic emission controls in relation to expected health gains cannot be fully assessed without taking account of changes in roadside levels as well as the ambient average. A full description and discussion of the methodology and justification for this approach is presented in a separate report (Lai et al 2009). The averaging methods can be varied based on different perspectives and methodologies but from a public health point of view, we should determine the level that can best represent the average levels we breathe daily, rather than the average levels we are seldom exposed to. For example, the daily exposures of relatively few individuals will be confined to zones where pollutant levels are low or more dispersed. Properly designed long-term individual exposure studies are not available in Hong Kong and are beyond the scope of this appraisal. In this report, we use the mean of both the average of general stations and the average of the roadside stations as a proxy for annual average population exposures (Appendix 2) for accountability of the health burdens attributable to air pollution in Hong Kong (see Section 4). In fact, at the present time it makes relatively little difference which proxy measure is used for accountability because pollutant levels are so high at all sites. However in the future, when ambient pollutant levels may be lower, roadside levels will assume greater importance in exposure measures and accountability. Nevertheless we should emphasise that, in the following section, we appraise the Arup AQOs based on general stations only because roadside stations are not regarded as background stations for counting the number of exceedances. 2.3 WHO Air Quality Guidelines and methods of counting exceedances The WHO AQG provide a number of single limit values for ten minutes, hourly, 24 hourly and annual averaging times. While the annual levels provide a bench mark for long-term protection of population health, the shorter averaging times are recognized as potentially important drivers of overall pollutant exposures. This is why they are linked to limits on the number of exceedances allowed in a specified period of time. For example, 24-hour guidelines for PM are typically set at the 99 th percentile, indicating that they should not be exceeded on more than 1% of the days in the year, i.e. about 3 to 4 days. WHO does not make provision for exceedances for SO 2 and NO 2. 8

9 This type of measure is important for air quality in Hong Kong because at present many short-term WHO AQG are exceeded on a very large number of days annually (Table 1). At present, there are two common approaches in counting the number of exceedances. One based on the maximum levels of all general stations, i.e. if any one station or multiple stations exceeded the target level during the averaging time period, one exceedance is counted (the US EPA method). The other one is based on the average number of exceedances among all general stations in urban and suburban areas (the EU EEA method). Table 1. Exceedances of WHO air quality guidelines in year 2007 Air WHO air quality guidelines No. of exceedances in 2007 pollutants Target levels (!g m -3 ) Allowable no. of exceedances EU EEA method 1 US EPA method 2 Arup s method 3 SO 2 IT-1: 24-hr at day IT-2: 24-hr at 50 0 day AQG: 24-hr at 20 0 day PM 10 IT-1: 24-hr at days IT-2: 24-hr at days IT-3: 24-hr at 75 3 days AQG: 24-hr at 50 3 days PM 2.5 IT-1: 24-hr at 75 3 days IT-2: 24-hr at 50 3 days IT-3: 24-hr at days AQG: 24-hr at 25 3 days NO 2 AQG: 1-hr at hour O 3 IT-1: max 8-hr at day AQG: max 8-hr at day For simplification, the effect of a possible unequal distribution of missing data across seasons was not adjusted for. 0:00 was used as the first hour in the averaging time for 24-hr and max 8-hr period. 1 Average counts of all urban and suburban general stations (Tap Mun, which is located in a rural zone, cannot be included). 2 Based on the maximum levels of all general stations including Tap Mun. 3 Reported by Arup on 7 th of April 2009 (Attachment 1 #CB(1) 1257/08-09(03)) but the calculation methodology was not disclosed yet. For PM 2.5, general stations include Tsuen Wan, Tung Chung, Yuen Long and Tap Mun (the only station that depends on the maximum method of counting exceedances). The average number of exceedances as described in the EU EEA s method, which is also well-referenced to the WHO AQG, is the most compatible method to determine the exceedances of the short-term WHO guidelines, particularly for PM 10 and PM 2.5 guidelines, which clearly specify the relationship between the distributions of the average 24-hour level and its 99 th percentile and the annual average concentrations (WHO 2006). If the number of exceedances are counted from the maximum levels among all general stations as described in the US EPA method, the allowable number of exceedances in the WHO guideline would become difficult to interpret because WHO guidelines are derived from epidemiological evidence based on average population exposures instead of the maximum levels occurring in different geographical regions at different times of the year. Apparently, the HKSAR government s consultant Arup has adopted the counting method based on the maximum levels of all general stations (the US EPA s method). Although details of Arup s methodology is still not disclosed at this time we assume that Arup interpreted the meaning of WHO s allowable exceedances in the same way that they counted the number of exceedances. We appraise the Arup AQOs according to this assumption (see Section 3). 9

10 2.4 Distributions of the criteria pollutants The average long-term levels of pollution are the most important measures of health related exposures but high pollution episodes can also cause large numbers of acute health outcomes and they both aggravate chronic existing disease conditions. Average pollutant levels may be strongly influenced by the number and magnitude of high pollution episodes. The improvement of air quality requires consistency in reducing pollution episodes as well as strategic interventions in the reduction of routine emissions to reduce both the short and average long-term population exposure levels. A good understanding of the characteristics of the distributions of pollutant concentrations responsible for population exposures is therefore important in formulating air quality objectives. Levels of air pollutants are log-normally distributed with half of the values lying within the relatively narrower ranges of low to medium levels (i.e. on the left of the median) and half of the values within the much wider ranges of medium-high to extremely-high levels on the right of the median (Figure 3). Figure 3. Histograms of log-normal distributions of Hong Kong pollutant hourly concentrations in / / %$$$,$$ +$$ *$$ )$$ ($$ '$$ &$$ #$$ %$$ $ ($$ '($ '$$ &($ &$$ #($ #$$ %($ %$$ ($ $!"# '- #&- '%- )$- *,-,+- %%)- %&(- %('- %*&- Concentration (!g/m3) 67%$,- &+- ))-,(- %#'- %(#- %+%- #$,- #&+- #)*- Concentration (!g/m3)./ / %$$$,$$ +$$ *$$ )$$ ($$ '$$ &$$ #$$ %$$ ($$ '($ '$$ &($ &$$ #($ #$$ %($ %$$ ($ $ $ "& #- #'- '*- *$-,#- %%(- %&*- %)$- %+#- #$(- Concentration (!g/m3) 67#8( &- #%- '$- (+- *)-,(- %%&- %&%- %($- %)+- Concentration (!g/m3)./ ($$ '($ '$$ &($ &$$ #($ #$$ %($ %$$ ($ $ 9"# %%- &)- )#- +*- %%#- %&*- %)#- %+*- #%#- #&*- Concentration (!g/m3) As the distribution is highly skewed towards the high end with a wide range of levels above the median, the mean may therefore be strongly influenced by the frequent occurrence of high levels during air pollution episodes and reducing the occurrence of high levels would also reduce the mean (Figure 4). This concept can be seen in the WHO air quality guidelines which specified clearly the highest allowable levels of short-term averaging time for all criteria pollutants. While the short-term air quality guidelines could be more practically useful than the annual guidelines in pollution controls and measures for emissions abatement, the annual mean level is on the other hand a more useful yardstick to assess the overall health impacts on population health as demonstrated in analyses of costs and health benefits. 10

11 Figure 4. What is the effect on annual mean levels of setting the short-term (daily or hourly) AQOs at different levels? Skewed distribution of pollutant concentrations Result of tighter AQO: Lower annual mean Result of lax AQO: Higher annual mean Probability Tighter AQO: limiting the high-end values at a lower concentration level Lax AQO: limiting the high-end values at a higher concentration level $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ Pollutant concentration 11

12 2.5 Estimation of the annual mean for a specific pollutant When the short-term highest allowable level, or exceedance level, at a certain percentile (a value below which a specific proportion of observations can be found) is defined, the annual mean can be estimated based on log-normal probability density functions. For example, in the Arup AQO, the 24-hr PM 10 is 100!g m -3 with 9 days of exceedances to be allowed (whereas the WHO AQG only permits 3 to 4 days of exceedances). The annualised percentile for 9 days can be calculated as [1 (9/365)]*100%, which is equal to the 97.5 th percentile and three days of allowable exceedances as [1 (3/365)]*100%, which is equal to the 99.2 th percentile. Note that WHO has approximated and stated the 24-hr guideline as the 99 th percentile in the AQG Global Report (page 12 of Executive Summary and pages 278 and 279 of the full document). Based on the statistical distribution that best describes the central tendency and dispersion of pollutants, i.e. the geometric mean and geometric standard deviation, the annual means for different percentiles can be estimated by models based on a log-normal probability density function (Figure 5). Figure 5. Estimated annual (1-yr) means of PM 10 for different number of days of exceedances (Ex.) of 100!g m -3 (24-hr average) based on the dispersion of PM 10 in :;8-<-%+--=%>5/-?0@3-<-')A --:;8-<--,--=%>5/-?0@3-<-&,A --:;8-<--&--=%>5/-?0@3-<-&#A $ %$$ Figure 5 demonstrates the estimated 1-yr means of PM 10 for 18, 9, and 3 days of exceedances of 100!g m -3 (24-hr average), which are 46, 39, 32!g m -3 respectively. These distributions have remained stable for many years and 2007 is a typical year. Based on 2007 data, the percentage error for estimating the annual means of other recent years is quite small for all pollutants, therefore our model predictions of the annual means for a number of years in the future based on Arup s proposal should be satisfactorily reliable (Appendix 3). In the present appraisal, this method was applied to test whether each of the Arup s shortterm AQO were appropriately determined by Arup for the ultimate goal of reducing the average Hong Kong population exposures in long-term. 12

13 3.0 Appraisal of the Arup AQOs This section aims to appraise Arup AQOs using their interpretation of exceedances, which is based on the maximum levels among all stations. In this section, the estimated annual mean derived from the log-normal model therefore represents the ambient mean pollution levels based on the maximum levels. Although this is difficult to interpret and cannot be used to represent the average population exposure levels, comparisons with the 2007 levels (also based on maximum levels) would also allow us to assess whether the Arup AQOs would in fact set limits which would ensure improvements, but not deterioration, of air quality from the current levels towards the WHO AQG. Appraisal of the Arup AQOs based on the average number of exceedances (the EU EEA method of counting, which is compatible with the WHO guidelines) is shown in Appendix 4. In this document, we use the phrase, annual mean maximum, to represent the annual mean of the maximum levels among all stations and to distinguish it from the annual mean that represents the average concentration of all measured records of the monitoring stations. The reason for having two types of annual mean due to the difference in counting exceedances between Arup s method (maximum approach) and EU EEA method (average approach) is illustrated in Table 2. Table 2. Maximum approach versus average approach in counting exceedances K@5-%- %$$- '$- %$$- %- K@5-#- '$- %$- '$- $- K@5-&-,$- '$-,$- %- K@5-'- %#$- )$- %#$- %- BC?0-!D@DCE3-%- F0G0F-!D@DCE3-#- F0G0F- 7@;8- F0G0F- 9E8-EH-:;8-@D-($- =MG0/@N0-@II/E@4JA- 70@3L- )#8(- +*8(- - &- %- - - Table 2 shows that if we take 4 days in a year as an example, the annual mean maximum is 87.5 while the annual mean is 62.5; the number of exceedances is 3 based on the maximum approach while it is calculated as 2, i.e. (3+1)/2, when based on the average approach. The disadvantages of using the maximum approach as compared with the average approach are shown later in Section 5 (Table 7). 13

14 3.1 The Arup AQOs versus WHO s original guidelines Arup has made reference to WHO guidelines and selected a combination of interim targets level-1 (IT-1) and level-2 (IT-2) for SO 2, PM and O 3 and also selected the WHO AQG for NO 2. No matter which exceedance counting method is based, Arup does not in our view in fact adopt any WHO guidelines or interim targets because WHO only allows 3 days of exceedances for 24-hr PM 10 and PM 2.5 and no exceedances are allowed for the rest of the guidelines. On the other hand Arup has proposed to allow exceedances up to 9 days for all short-term AQOs of all the criteria pollutants included in their review. In Table 3, the WHO original interims or guidelines are stated together with the number of days of exceedances allowed (#). In the second tier of this table the Arup proposed AQOs are shown with days of exceedances. The potential impact of these exceedances of the Arup short-term AQO on the predicted annual mean maximum is examined in section 3.2. Table 3. WHO guidelines compared with Arup AQOs WHO's original guidelines Averaging IT-1 IT-2 IT-3 AQG Pollutants Time (!g/m 3 ) # (!g/m 3 ) # (!g/m 3 ) # (!g/m 3 ) # SO 2 PM 10 PM 2.5 NO 2 10-min 24-hour 24-hour 1-hour hour 1-year 1-year 1-year O 3 8-hour Arup's proposed AQOs (shaded area) Averaging IT-1 IT-2 IT-3 AQG Pollutants Time (!g/m 3 ) # (!g/m 3 ) # (!g/m 3 ) # (!g/m 3 ) # SO 2 PM 10 PM 2.5 NO 2 10-min hour hour 24-hour 1-hour year 1-year 1-year O 3 8-hour [#] The number of exceedances to be allowed. Discrepancies between the Arup AQOs and WHO s original guidelines are highlighted. 14

15 3.2 Impact of exceedances on annual mean maximum of pollutant levels The effects of allowing the proposed number of exceedances (linked to Arup s short-term AQOs) on the annual mean maximum, as applied to the 2007 air pollutant levels, are shown in Figure In the following scenarios, the estimated annual mean maximum derived from the model is used for comparisons with the annual mean maximum in 2007 to illustrate the application of the method Sulphur dioxide: The annual mean maximum for SO 2 in 2007 was 39!g m -3. If Arup IT-1 for AQO (24-hr SO 2 at 125!g m -3 with 3 days of exceedances allowed) is fully exploited by polluters, the estimated annual mean maximum will be 48!g m -3 based on the model using log-normal probability density functions. On the other hand, if the original WHO IT-1 ( 24-hr SO 2 at 125!g m -3 with no exceedances) is fully exploited by polluters, the estimated annual mean maximum will be 42!g m -3 based on the same model. Figure 6 clearly shows that the adoption of Arup IT-1 for SO 2 may allow increases of the annual mean maximum of the current SO 2 levels (as in 2007) by up to 23%, and even the adoption of the original WHO IT-1 also predicts increases in the annual mean maximum of the current SO 2 levels (as in 2007) by 8%. There is clear evidence, from a perspective based on the precautionary principle, that this proposed AQO must not be adopted as it legally permits the creation of more SO 2 pollution, which will substantially increase the health burden in Hong Kong. It is also clear that the existing SO 2 levels in Hong Kong are still unsatisfactory since the estimated annual mean maximum of WHO AQG (24-hr SO 2 at 20!g m -3 with no exceedance) is 7!g m -3, based on stations maximum levels, or the estimated annual mean is 4!g m -3, based on the average method in calculating exceedances (Appendix 4). Note that the WHO AQG is not unachievable because the annual mean in London is already quite close to this level following action to reduce the annual average in recent years (Appendix 1). If we were to design an effective regulatory framework to control ambient concentrations of SO 2 in Hong Kong and achieve compliance with the WHO AQG, as an absolute minimum intervention we should set the 24-hr SO 2 at no higher than 67!g m -3 (with no exceedance), which is the estimated 100 th percentile (an approximation of the th percentile) for an annual mean maximum at 23!g m -3 (a level between the current level at 39!g m -3 and the notional achievable 1-yr WHO AQG level at 7!g m -3 ). However 23 µg m -3 is above the WHO AQG and an unacceptable target. On the basis of the London experience we suggest it is possible to set a target which would improve air quality at least halfway towards the WHO AQG to be achieved in 4 years (Appendix 1). We suggest that as a precautionary approach, and to consolidate previous improvements in SO 2 pollution, the WHO IT-2 (50 µg m -3 ) should be adopted as a minimum intervention. The Arup AQO for SO 2 is too lax to provide any effective additional health protection and it allows further deterioration in SO 2 pollution. While Hong Kong has made progress in achieving an annual mean maximum of 39!g m -3, the current trend and pattern of exceedances indicates that more stringent measures are urgently needed. We would be interested to see the detailed rationale behind the Arup SO 2 AQO and the reasons why senior officers of the Environment Bureau believe the WHO AQG is an inappropriate decision rule. 15

16 Figure 6. Estimated change in annual mean maximum of SO 2 with adoption of Arup AQO plots of probability distribution of SO 2 concentrations (!g m -3 ) Arup IT-1: 24-hr SO2 (dotted line), if 3-day exceedances of 125!g/m3, est. 1-yr mean max = 48!g/m SO2 data (solid line) 1-yr mean max = 39!g/m3 $ #$ '$ )$ +$ %$$ %#$ %' $ WHO IT-1: 24-hr SO2 (dotted line) no exceedances of 125!g/m3, est. 1-yr mean max = 42!g/m SO2 data (solid line) 1-yr mean max = 39!g/m3 $ #$ '$ )$ +$ %$$ %#$ %' $ WHO AQG: 24-hr SO2 (dotted line) no exceedances of 20!g/m3, est. 1-yr mean max = 7!g/m SO2 data (solid line) 1-yr mean max = 39!g/m3 $ #$ '$ )$ +$ %$$ %#$ %' $ All figures presented above are based on maximum levels of all general stations (including Tap Mun) in hr averaging periods in year

17 3.2.2 Ozone: The annual mean maximum of the secondary pollutant O 3 in 2007 was 71!g m -3. If Arup IT-1 for AQO (daily maximum 8-hr O 3 at 160!g m -3 with 9 days of exceedances allowed) is fully exploited (indirectly) by polluters, the estimated annual mean maximum will be 56!g m -3 based on the model using log-normal probability density functions. On the other hand, if the original WHO IT-1 (daily maximum 8-hr O 3 at 160 with no exceedance) is rigorously applied, the estimated annual mean maximum will be 46!g m -3 based on the same model. Figure 7 clearly shows that the adoption of Arup IT-1 for O 3 will only allow decreases of the annual mean maximum of the current O 3 levels (as in 2007) by 21% unless other environmental controls reduce or eliminate the factors which drive the formation of the ozone. If we are going to control the formation of O 3 half way towards the WHO AQG (estimated annual mean maximum at 29!g m -3 ), we should adopt the original WHO IT-1 (daily maximum 8-hr O 3 at 160!g m -3 with no exceedance) so that we can achieve at least an annual mean maximum at 46!g m -3. The Arup AQO for O 3 is permissive for any additional health protection to be achieved in the prevailing environmental conditions in Hong Kong Nitrogen dioxide: The annual mean maximum of NO 2 in 2007 was 79!g m -3. If Arup AQO (1-hr NO 2 at 200!g m -3 with 18 hours of exceedances allowed) is fully exploited then the estimated annual mean maximum will be 64!g m -3 based on the model using log-normal probability density functions. On the other hand, if the original WHO AQG (1-hr NO 2 at 200!g m -3 with no exceedance) is fully complied with then the estimated annual mean maximum will be 50!g m -3 based on the same model. Figure 8 clearly shows that the adoption of Arup AQG for NO 2 will only decrease the annual mean maximum of the current NO 2 levels (as in 2007) by 19%, while the adoption of the WHO AQG could achieve a decrease by 37%. The difference between the two estimated means will be 14!g m -3, and neither are adequate to improve air quality in Hong Kong to a WHO AQG annual mean maximum level at 40!g m -3. The 1-hr WHO AQG for NO 2 is a high absolute value by any criteria. When the intense roadside levels of NO 2 pollution in Hong Kong are considered, at least in the context of this model, the pollution abatement strategy needs to focus on the high daily levels. We suggest that more stringent rather than more permissive regulation of short-term pollution levels is urgently required. Adopting the short-term WHO AQG of 200!g m -3 is not adequate for improving air quality in Hong Kong and as a result the annual AQG of 40!g m -3 is unlikely to be achieved. Our estimated 100 th percentile (a level at which no exceedance is allowed) to achieve a WHO AQG (1-yr NO 2 at 40!g m -3 ) is 159!g m -3 (as indicated by the black triangle in Figure 8). If we are going to improve our NO 2 quality towards the WHO AQG with annual mean maximum at 40!g m -3, we should aim at setting the 1-hr NO 2 not exceeding 159!g m -3 (with no exceedance), which is the estimated 100 th percentile for annual mean maximum at 40!g m -3. However we need to bear in mind that this must be regarded as an interim measure. Studies on childhood lung growth and function suggest that even WHO AQG, associated with high roadside exceedances, may be harmful to health. 17

18 Figure 7. Estimated change in annual mean maximum of O 3 with adoption of Arup AQO plots of probability distribution of O 3 concentrations (!g m -3 ) Arup IT-1: daily max 8-hr O3 (dotted line), if 9-day exceedances of 160!g/m3, est. 1-yr mean max = 56!g/m O3 data (solid line) 1-yr mean max = 71!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ #'$ #)$ WHO IT-1: daily max 8-hr O3 (dotted line), no exceedances of 160!g/m3, est. 1-yr mean max = 46!g/m O3 data (solid line) 1-yr mean max = 71!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ #'$ #)$ WHO AQG: daily max 8-hr O3 (dotted line), no exceedances of 100!g/m3, est. 1-yr mean max = 29!g/m O3 data (solid line) 1-yr mean max = 71!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ #'$ #)$ All figures presented above are based on maximum levels of daily maximum 8-hr mean among all general stations (including Tap Mun) in 365 days in year

19 Figure 8. Estimated change in annual mean maximum of NO 2 with adoption of Arup AQO plots of probability distribution of NO 2 concentrations (!g m -3 ) Arup AQG: 1-hr NO2 (dotted line), if 18-hr exceedances of 200!g/m3, est. 1-yr mean max = 64!g/m NO2 data (solid line) 1-yr mean max = 79!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ WHO AQG: 1-hr NO2 (dotted line), no exceedances of 200!g/m3, est. 1-yr mean max = 50!g/m3, 2007 NO2 data (solid line) 1-yr mean max = 79!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ WHO AQG: 1-yr NO2 (dotted line), no exceedances of 40!g/m3, max. level = 159!g/m3, (no exceedances) 2007 NO2 data (solid line) 1-yr mean max = 79!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ All figures presented above are based on maximum levels of all general stations (including Tap Mun) in hr averaging periods in year

20 3.2.4 Respirable suspended particulates (PM 10 ): The annual mean maximum of PM 10 in 2007 was 70!g m -3. If Arup IT-2 for AQO (24-hr PM 10 at 100!g m -3 with 9 days of exceedances allowed) is exploited by polluters, the estimated annual mean maximum will be 45!g m -3 based on the model using log-normal probability density functions. On the other hand, if the original WHO IT-2 (24-hr PM 10 at 100!g m -3 with 3 days of exceedances) is fully exploited, the estimated annual mean maximum will be 39!g m -3 based on the same model. Figure 9 clearly shows that the adoption of Arup IT-2 for PM 10 will decrease the annual mean maximum of the current PM 10 levels (as in 2007) by 36%, and the adoption of the original WHO IT-2 will decrease the current annual mean maximum by 44%. The difference of the two estimated means will be 6!g m -3, which is not trivial and would be predictably related to loss of potential health gains. It appears that the Arup AQO for PM 10 is nearly halfway towards the WHO AQG. If we adopt the original WHO IT-2 with only 3-day exceedances, this will facilitate improvement of particulate levels at least half-way towards the WHO AQG level provided that it is fully complied with. As with the other pollutants, a more permissive approach to exceedances will compromise any strategy intended to reduce particulate levels Fine particulates (PM 2.5 ): The annual mean maximum of PM 2.5 in 2007 was 46!g m -3 (346% above WHO AQG). If Arup IT-1 for AQO (24-hr PM 2.5 at 75!g m -3 with 9-day exceedances allowed) is fully utilised by polluters, the estimated annual mean maximum will be 30!g m -3 based on the model using log-normal probability density functions. On the other hand, if the original WHO IT-1 (24-hr PM 2.5 at 75!g m -3 with 3-day exceedances) is fully exploited by polluters, the estimated annual mean maximum will be 25!g m -3 based on the same model. Figure 10 clearly shows that the adoption of and compliance with Arup IT-1 for PM 2.5 will only decrease the annual mean maximum of the current PM 2.5 levels (as in 2007) by 35%, while the adoption of the original WHO IT-1 (3-day exceedances allowed) will decrease the current annual mean by 46%. The difference between the two estimated means (25 and 30!g m -3 ), will be 5!g m -3 ; it should be compared with the annual WHO AQG of only 10!g m -3 and the US EPA NAAQS of 15!g m -3. It is clearly an important difference in terms of potential health gains or losses. If we adopt the original WHO IT-1 with only 3-day exceedances and with rigorous compliance this would facilitate reduction of particulate levels at least halfway towards the WHO AQG level. 20

21 Figure 9. Estimated change in annual mean of PM 10 with adoption of Arup AQO plots of probability distribution of PM 10 concentrations (!g m -3 ) Arup IT-2: 24-hr PM10 (dotted line), if 9-day exceedances of 100!g/m3, est. 1-yr mean max = 45!g/m PM10 data (solid line) 1-yr mean max = 70!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ WHO IT-2: 24-hr PM10 (dotted line), 3-day exceedances of 100!g/m3, est. 1-yr mean max = 39!g/m PM10 data (solid line) 1-yr mean max = 70!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ WHO AQG: 24-hr PM10 (dotted line), 3-day exceedances of 50!g/m3, est. 1-yr mean max = 19!g/m PM10 data (solid line) 1-yr mean max = 70!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ %+$ #$$ ##$ All figures presented above are based on maximum levels of all general stations (including Tap Mun) in hr-averaging periods in year

22 Figure 10. Estimated change in annual mean maximum of PM 2.5 with adoption of Arup AQO plots of probability distribution of PM 2.5 concentrations (!g m -3 ) Arup IT-1: 24-hr PM2.5 (dotted line), if 9-day exceedances of 75!g/m3, est. 1-yr mean max = 30!g/m PM2.5 data (solid line) 1-yr mean max = 46!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ WHO IT-1: 24-hr PM2.5 (dotted line), 3-day exceedances of 75!g/m3, est. 1-yr mean max = 25!g/m PM2.5 data (solid line) 1-yr mean max = 46!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ WHO AQG: 24-hr PM2.5 (dotted line), 3-day exceedances of 25!g/m3, est. 1-yr mean max = 8!g/m PM2.5 data (solid line) 1-yr mean max = 46!g/m3 $ #$ '$ )$ +$ %$$ %#$ %'$ %)$ All figures presented above are based on maximum levels of all general stations (including Tap Mun) in hr-averaging periods in year

23 3.3 Summary! The proposed Arup AQOs were systematically appraised by using lognormal probability density function models.! Arup did not adopt WHO guidelines/interim targets because they have increased the number of allowed exceedances; this will then increase the annual mean maximum, which is the annual mean based on maximum levels among all general stations an approach adopted by Arup to count exceedances.! The Arup proposed AQO for SO 2 was incorrectly determined because the annual mean maximum will be higher than the current levels (as in 2007) if polluters fully utilize the number of allowable exceedances. Even using the original version of WHO IT-1 guidelines (no exceedance is allowed) will also allow polluters to increase the annual mean maximum of the current levels. Tighter AQOs must be adopted to sustain the environmental gains achieved through sulphur restriction in fuels and control of emissions.! Arup proposed AQOs for O 3 and NO 2 are permissive and inadequate to improve air quality in Hong Kong because the annual mean maximum will not be much different to the current levels (as in 2007) if polluters fully utilize the number of allowable exceedances.! Adopting the 1-hr WHO AQG for NO 2 as proposed by Arup is not sufficient to reduce the annual mean maximum towards the 1-yr WHO AQG level (at 40!g m -3 ).! The Arup proposed AQOs for PM 10 and PM 2.5 fall short of what is required to underpin any strategic intervention to control particulate pollution. Although these AQOs may reduce the annual mean maximum of particulate levels from the current levels (as in 2007), neither target can guarantee improvement to at least halfway towards the WHO AQG levels unless the numbers of exceedances are reduced to 3 days, as indicated by WHO.! Table 4 summarizes the alternative AQOs required under this appraisal. Table 4. Summary of Arup s and alternative AQOs under the appraisal Averaging Time Arup: Alternative 1: Alternative 2: Alternative 3: Short-term AQOs proposed by Arup WHO short-term guidelines or interim targets before Arup modifications Short-term AQOs for halfway achievement towards the WHO AQGs WHO AQGs Pollutants (!g/m 3 ) # (!g/m 3 ) # (!g/m 3 ) # (!g/m 3 ) # SO2 10-min hour * PM10 24-hour ** PM hour *** NO2 1-hour # 0 O3 8-hour To be achieved by Not specified - 31 Dec *Estimated from our model **WHO 24-hour IT2 ***WHO 24-hour IT1 #may still be inadequate to attain the WHO annual AQG at 40 (see Figure 8, page 19) 23

24 4.0 Appraisal of the health economic cost In this section we have analysed the predicted outcomes of the proposed AQOs, under certain assumptions about the resulting ambient concentrations of the four criteria pollutants PM, NO 2, SO 2 and O 3. These estimates of harm reduction or increase, dollar values of health care utilisation and lost productivity, and the intangible costs assessed as willingness to pay to avoid illness and the value of the lives lost due to deaths from pollution. 4.1 Methods Health burden attributable to exceedances of WHO AQG: When in any hour the moving average of the past 1 hour (1-hr), 24 hours (24-hr), 8760 hours (1-yr), or the maximum 8 hours over the past 24 hours (8-hr) was higher than the corresponding AQG, the per unit (µg m -3 ) pollutant exceedance was calculated and used to estimate the excess health burden attributable to air pollution. When the moving average of any hour was below the AQG, the health burdens were assumed to be non-observable, although we acknowledge the absence of any evidence for a threshold. Although there are no formally stated annual guideline values for SO 2 and O 3 (WHO 2006), health effects due to long-term exposure to these two air pollutants have been demonstrated (Elliott et al 2007; Jerrett et al 2009) and the WHO short-term AQGs are designed to protect population health from both short and long term impacts. Although the annual mean can be derived from the short-term guideline values, as a conservative approach we assume the 1-yr WHO AQG values of SO 2 and O 3 to be equal to their 24-hr and 8-hr guideline values respectively. Since all WHO interim target values are higher than the WHO AQG values, the difference between the interim and AQG values must be regarded as an exceedance of the AQG for the purpose of estimating excess health burdens attributable to any adopted regulatory level Excess risks for specific health outcomes: To illustrate the possible reduction in adverse health effects and monetary benefits from abatement of air pollution, differences between air quality levels defined by Arup, WHO and current Hong Kong means (and exceedances) were used to calculate the value of reductions or increases in air pollution on an annualized basis. From previously published local studies on air pollution and associated increased daily utilization of primary and secondary health care and mortality, the excess risks for each 10!g m -3 increase in air pollutants were obtained (Table 5). In the studies of mortality, hospital admissions and family doctor visits, Poisson regression adjusted for autocorrelation and overdispersion was employed to estimate the change in risks due to the daily variation of a single pollutant, taking into account season, temperature, humidity, holidays, and influenza periods (Wong et al 2001; Wong et al 2002a, 2002b; Wong et al 2002c, 2006; Ko et al 2007). The total number of primary care events was based on a survey of daily family doctor visits for respiratory complaints in year 2004, and the daily numbers of hospital admissions and deaths in the years 2000 to 2004 were obtained from the Hong Kong Hospital Authority and the Census and Statistics Department death registration (Hong Kong Hospital Authority 2002; Hong Kong Census and Statistics Department 2001). In addition, excess risks were also derived from the odds ratios obtained from prevalence studies for various respiratory ill-health outcomes in relation to SO 2 exposure, reported in a risk assessment intended to re-define Air Quality Objectives, conducted for the Environmental Protection Department (Hedley et al 1999). 24

25 Table 5. Excess risks (%) and 95% confidence intervals for mortality, hospital admissions, family doctor visits and respiratory ill-health symptoms per 10 µg m -3 change in pollutant PM10 NO2 SO2 O3 Mortality: All natural causes 0.24 (0.01, 0.46) 0.64 (0.36, 0.91) 1.36 (0.93, 1.78) -0.11(-0.37,0.16) Hospital admissions: Cardiovascular diseases 0.37 (0.18, 0.57) 0.73 (0.48, 0.98) 1.08 (0.72, 1.44) 0.24 (0.01, 0.47) Respiratory diseases 0.50 (0.28, 0.71) 0.54 (0.27, 0.80) 0.76 (0.34, 1.18) 0.55 (0.31, 0.79) Asthma (age 0-14) 1.02 (1.02, 1.03) 1.04 (1.03, 1.05) (1.03, 1.05) Asthma (age 15-65) 1.01 (1.01, 1.02) 1.02 (1.01, 1.03) 1.02 (1.00, 1.04) 1.04 (1.03, 1.05) Asthma (age >65) 1.02 (1.01, 1.02) 1.02 (1.01, 1.03) (1.01, 1.03) Family doctor visits: Respiratory diseases 3.28 (2.54, 4.05) 3.42 (-0.62, 7.63) 0.68 (-3.03, 4.54) 1.50 (-1.18, 4.26) Respiratory ill-health symptoms: Frequent evening cough (age 8-9) Frequent morning phlegm (age 8-9) Any cough frequently (age 8-12) Any phlegm frequently (age 8-12) Bronchial hyper-reactivity* (age 9-12) *PD20 < 3.2!mol Calculating the avoidable health events: The linear exposure-response relationship was employed between air pollution and adverse health outcomes to estimate the overall reduction or increase in risks that would be associated with the defined improvements or deterioration in air quality. This risk reduction or elevation was applied to population mortality and health care utilization data to obtain the annual number of avoidable deaths and health care events. For primary care these estimates were restricted to respiratory complaints; for hospital admissions, they were applied to cardiovascular and respiratory diseases; and for deaths they were applied to all non-accidental causes of death. For each pollutant (P) the impact (I p ) in avoidable health events (avoidable mortality, avoidable health care utilization, and avoidable cases with respiratory ill-health symptoms), for each type of health outcome resulting from air quality improvements, was estimated as I p = N I O ER p O L p where N I is the annual number of the event I in the population; ER p the excess risk for 10!g m -3 of pollutant P (assumed equivalent to the increase in risk with an increase of 10!g m -3 of pollutant); L p the change in the level of pollutant P for the reduction or increase from one defined level to the other; and P, each of the four pollutants (PM 10, NO 2, SO 2, and O 3 ). 25

26 4.1.5 Combining the effects of pollutants: Using 1 to represent the 100% contribution of PM 10, first the correlation was obtained between the concentrations of PM 10 and NO 2 (r), then the proportional variation of NO 2 explained by PM 10 (r 2 ) was calculated and subtracted from 1. This obtained value was then reduced by the correlation between NO 2 and SO 2 adjusted by PM 10 and between PM 10 and NO 2 adjusted by SO 2 (Figure 3). For our analyses, we assumed that only the contributions of PM 10 and O 3 were 100%, so the total number (T) of avoidable health events associated with pollution was estimated on the basis of: T = PM *NO *SO 2 + O 3 This rule of thumb approach has been subject to peer review; it assumes a significant contribution from each chemical species but does not assume equal proportional contributions. This is likely to be conservative given the collective evidence of the potency of the oxidant gases on harm to health from studies in Hong Kong and centres in mainland China. Figure 11. Method for combining pollutant effects based on correlation between PM 10, NO 2 and SO 2 at monitoring stations PM 10 NO 2 (41%) (1-[0.768] 2 ) = 0.41 NO 2 SO 2 (84%) (1-[0.067] 2 [0.39] 2 ) = 0.84 SO 2 Correlation between NO 2 and PM 10 Partial correlation between NO 2 and SO 2 adjusted by PM 10 Partial correlation between PM 10 and SO 2 adjusted by NO Monetary valuation: The direct costs of illness estimates in public and private hospital admissions, public out-patient consultations (general, specialist, accident and emergency), family doctor visits, average costs of a bed day, and the consultation fee were included (McGhee et al., 1998). All costs were based on the available health and economic data from year 2000 to Patient travel costs for hospital admissions and doctor visits (but not for accident and emergency) were also included. The productivity loss for working ages (15 to 64 years) includes the person-years of life lost, the time lost from work due to hospital admissions and family doctor visits. All losses were adjusted for by labour force, employment rates, and sex-specific median daily salaries (Hong Kong Census and Statistics Department, 2005) to the year 2004 values. The intangible loss was based on the average valuation of willingness-to-pay to avoid a life lost. 26