UK government not reducing pollution in line with legal limits

With all the concern over atmospheric pollution levels in China a story may have escaped notice. The UK government is facing a case in the UK Supreme Court over its failure to reduce air pollution in line with legal limits (http://www.bbc.co.uk/news/science-environment-21691784). The government admitted that limits would not be meet in 15 regions until 2020 (London will not comply until 2025). This comes on top of the government having to issue a severe pollution warning for London this week.

The response of the government has been to say that the laws are unrealistically strict and that the EU didn’t set proper limits on pollution from diesel exhaust in the first place. Why they view these limits are unrealistic is not clear. Do they mean given the current economic situation it is not realistic to expect pollution to be tackled? Do they mean the limits are to be meet in too short a timeframe? Does the comment imply that there is an expected time lag between introducing the limits and compliance – if so why? Does the comment relate to how the government expects such changes in polluting behaviour to be tackled within the particular political and economic context of the UK.

 

DEFRA stated that the government has acted to reduce emissions of nitrogen dioxide through trying to encourage behaviour changes in divers via tax breaks and subsidies for low emission vehicles. Likewise, there has been investment in green bus technologies  (£75million) along with £560m to encourage local sustainable transport. This is the government response to trying to improve the atmospheric levels of PM10s and nitrogen dioxide, key pollutants from road traffic. In other words responsible for implementing and resolving the issue has been delegated downwards to the local level, indeed even as far as down the individual driver. Action is also indirect via tax incentives to which individuals are meant to respond in the manner the government thinks they should.  Rather than direct action or legislation, the government has taken a ‘nudge’ approach to the problem, developing policies and the context or environment that they believe will provide the impetus to encourage change in the direction they want. Reduction in atmospheric pollution is a side-effect, an outcome of these nudges. The question could be asked will these nudges be effective? Likewise, how can you measure the impact of such nudges to assess if they have been effective?

 

The threat of court action also places the complaints over Chinese pollution in a different light. It could be argued that the atmospheric pollution levels in the UK are much lower than in China and so different criteria should be applied to the problems of the UK government. The UK is not dealing with dense smogs that clog lungs and increase death rates (although calculations do suggest that traffic pollution does cause excess deaths in the UK as noted in the above report). The pollution of concern in the UK seems to be focused on road traffic and so a linear pollution source whilst the Chinese are having to deal with point, linear and areal sources as they go through rapid urbanization and economic growth.  Indeed the Chinese are having to cope with multiple sources of differing magnitudes and with both private and official institutions involved. The magnitudes of the pollution maybe of different orders in the UK and China but both are struggling to balance the needs of economic development and the pollution it produces.  So is atmospheric pollution the unavoidable price for economic development?

 

 

 

Beijing Pollution: Continuing Highs

In January and February of this year the air quality in and north-eastern China has been reported to have deteriorated to the extent that the smog so thick that it was visible from space (http://www.nydailynews.com/news/world/china-pollution-bad-visible-space-article-1.1253838). The rise in pollution has reported caused increases in hospital admissions of respiratory problems and, according to the report above, even resulted in an official recognition of the problem, the article stating that the Chinese Ministry of Environmental Protection stating that the haze covering Chinese cities covered over 500,000 square miles. The problem has been officially identified as being caused by unregulated industries, vehicle emissions and cheap gasoline.

The identification of the ‘causes’ is interesting. The focus is upon the action of individuals with respect to vehicle emissions and the use of cheap gasoline. This implies that the cause is a matter of individual responsibility. Placing causation at the feet of individuals means that there is justification for taking action against individuals for not taking appropriate steps deemed vital to reduce pollution by authorities. The focus on unregulated industries implies that regulated industries are not contributing to he pollution level. Again responsible and fault is placed onto individuals who run firms that do not conform to state regulations. Politicians, according to the report, even closed these firms for 48 hours as well as urging individuals to stay off the road. The implication is that the pollution is an inevitable result of the outcome of ‘development’ or ‘progress’ with the individualistic bend of capitalism.  The pollution is as predictable a result of economic progress as were the dark satanic mills of nineteenth century Manchester were of progress in Britain. By implication, the more measured and responsible activities of the state have no role in producing this smog.  Despite the state setting the economic regulatory climate as well as enforcing regulations relevant to pollution production, the role of the state is regulated to a backseat in the internal pollution narrative that is emerging from these reports.

The pollution does, however, have a flip-side in the new China – the hazard is an economic opportunity for the few. Anti-pollution domes, with interiors of pollutant-free atmospheres have been jointly developed by a Shenzhen-based manufactuer of outdoor enclosures and a Calfornian-based company (UVDI) that specialises in air filtration and disinfection systems (http://wallstnews.blogspot.co.uk/p/asia-edge.html#!/p/asia-edge.html ). Combining these existing technologies it is possible to create a pollutant free environment within outdoor activities can continue. Additionally, face masks, ranging from high-tech neoprene masks to strips of cloth, have been increasingly sold to try to prevent inhalation of pollutants. Within homes air filtration units are being employed to ensure a clean supply of domestic air.  This, however, also means that there is increasingly a social, or even a class, aspect to this hazard. The emerging middle-class in China can afford to buy these new ‘must-have’ accessories to sustain urban life. The poor are left to cope using tatters of cloth across their mouths and noses to filter their domestic air.  How long before your income determines your ability to survive extreme pollution episodes?

One enterprising individual has even taken to selling cans of fresh air to hassled urbanites, for 80 cents a can. Although to be fair, Chen Guangbiao, although promoting himself says that the sale of the fresh air cans is a tactic to push ‘mayors, county chiefs and heads of big companies’ not to just pursue economic goals but also to consider the impact of their actions on the future.

 

Using St Paul’s Erosion Data to Predict Future Stone Decay in Central London

In a recent blog I mentioned a research project just completed on a 30-year remeasurement of stone decay on St Paul’s cathedral in central London. A second paper looks at how this data might be used to model decay into the future (http://www.sciencedirect.com/science/article/pii/S1352231012007145  - you need to have an account to get access to the full paper in Atmospheric Environment). Modelling erosion rates into the future tends to use relationships derived from erosion data of small (50x50x10mm) stone tablets exposed in different environmental conditions. Using such data and regression analysis a statistical relationship can be derived between stone loss and changing environmental conditions. These relationships are often referred to as dose-response functions.


Two equations stand out – the Lipfert and the Tidblad et al. does response functions. Using these two equations for the decades 1980-2010, they predict an erosion rate of 15 and 12 microns per year as opposed to the measured losses on St Paul’s of 49 and 35 microns per year. The ratio between the measured and the dose-response erosion rates varies from 3.33 in the decade 1980-1990 to 2.75 in the decade 2000-2010, so fairly consistent. The difference between the two measures of decay may result from differences in what they are actually measuring. The dose-response function uses small stone tablets, exposed vertically in polluted environments. The weight loss of these tablets is measured and then converted to a loss across the whole surface of the tablet. The micro-erosion meter sites measure the loss of height of a number of points across the same surface on a decadal time scale. Both measures are changes in height but derived in different ways. What is important is that both methods indicate the same patterns of change in relation to declining sulphur dioxide levels. Both measures of erosion show a decline and both show it in the same direction and, by and large, in proportion to each other. Interestingly, when the dose-response functions are used to work out erosion on the cathedral since it was built the long-term erosion rate (as measured by lead fin heights relative to the stone surface) is only 2.5 times greater than that predicted by the does-response functions. This is a similar ratio, more or less, to those indicated over the last three decades.

The St Paul’s data does not imply that dose-response functions do not work – if anything it confirms the patterns in decay they indicate – but the St Paul’s data does suggest that using these dose-response functions to model decay into the future may require a correct function, equivalent to the ratio of about 2.5-2.75 to convert the losses to those that will be found on St Paul’s Cathedral.

Atmospheric Pollution and Stone Decay: St Paul’s Cathedral

I have recently published a paper with colleagues from Oxford, Cambridge, Sussex and York on a 30-year measurement of erosion rates on St Paul’s Cathedral, London (http://www.sciencedirect.com/science/article/pii/S1352231012008400  - you need to have an account with the journal to access the paper). Pleasingly, the academic work did get some press (http://www.independent.co.uk/news/uk/home-news/pollution-erosion-at-st-pauls-cathedral-in-record-300year-low-8205562.html , http://www.stpauls.co.uk/News-Press/Latest-News/St-Pauls-safer-from-pollution-than-at-any-time-in-its-history , ) and I even did a very short radio interview on local radio (distracted during it because they just started their afternoon quiz to which I knew the answer!)


The paper outlines how the rates of erosion (and the rates of surface change) of five micro-erosion meter sites around the cathedral have changed over the decades since 1980 and how this has mirrored a dramatic fall in pollution levels in central London.

Figure 1 Micro-erosion meter site with protective caps being removed for remeasurement

Figure 2 Erosion rates, rates of surface change and environmetnal variables for central London 1980-2010

The erosion rates have dropped since the closure of Bankside power station in the early 1980s with atmospheric pollution, as indicated by sulphur dioxide levels dropping from 80ppb in 1980 to about 3ppb in 2010. Erosion rates fell from 49 microns per year in the decade 1980-1990 to 35 microns per year in the decade 2000-2010. Erosion rates in the 1980-1990 were statistically significantly higher than erosion rates in both the decades 1990-2000 and 2000-2010. Erosion rate in the decade 1990-2000 and 2000-2010 were statistically similar. Although the decline in erosion rates was not as steep as the fall in pollution levels, erosion rates are now at a level that could be explained by the action of the acidity of ‘normal’ or ‘natural’ rainfall alone. ‘Normal’ rainfall is a weak carbonic acid, produced by the reaction of carbon dioxide and water in the atmosphere, meaning that ‘normal’ rainfall has an acidity of about pH5.6.

Erosion rates represent the loss of material from a surface but not all points’ measured lost material, some gained height over the measurement periods – this is surface change. Points can gain height for a number of reasons; slat in the stone could distort and push the surface up, lichens and bacteria could form crusts that raise the surface and eroded material might be deposited in depressions in the surface causing an apparent raising of the surface. The rates of surface change were 44 microns per year in the decade 1980-1990 but fell to 26 microns per year by the decade 2000-2010 (and were only 25 microns per year in the decade 2000-2010). This suggests that rats of surface change fell in a similar manner to rates of erosion and match the drop in sulphur dioxide levels as well.

Back in the 1980s the long-term rates of erosion, since the early 1700s were also determined using lead find. These lead fins were produced when the holes used to raise the stone blocks into the balustrade were filled with lead. Over time the fins became proud of the surface as the stone around them eroded. By measuring the height difference between the fins and the stone (and then dividing by the time of exposure) the long-term rates of erosion can be calculated. The long-term rates from 1690/1700 to 1980 were about 78 microns per year. This suggests that the cathedral has experienced much higher erosion in the decades before 1980. This does suggest that the erosion rates we have managed to measure from 1980 onwards, and the associated pollution levels, were not as damaging to the cathedral as those experienced in the years up to 1980.

Urban Air Pollution Around the World

Two interesting blogs and a website for all issues cocnerning atmospheric pollution can be found at urbanemission.blogspot.co.uk/ , aipollutionalerts.blogspot.co.uk/ and at urbanemissions.info/ . All of these sties are run by Sarath Guttikunda from New Delhi. An important aspect of these sites are reports from all over the globe concern atmospheric pollution in urban areas. The reports highlight that atmospheric pollution is a global issue, a world-wide problem that needs action. Taking action, however, requires information that can inform decision-makers about the extent of the problem. These sties also provide this by linking through to monitoring information from urban areas from around the world. These sites also highlight that local populations, communities and neighbourhoods, are not just passively sitting there waiting for decision-makers to make decisions. The volume of reports and community awareness show the concern and impetus for changes driven by the local-level certainly exists. Enabling those changes is another issue that is dependent on local conditions and their context, political, economic and social. The information and data provided by these websites, however, does permit individuals and communities from all over the world to compare their conditions with others in similar circumstances and to exchange ideas and plans for pressuring decision-makers for change.

The Urban Emissions website is worth a look as well for the modelling tools that are available for download. An interesting one, given my last blog, is the Air Quality Indicator download. This simple calculator helps you work out the air quality for an urban area based on daily observations or modelled values. It does, of course, assume that the data will be available in the first place!

Understanding Daily Air Quality

Atmospheric pollution is a continuing environmental problem across the globe. Within the UK data on historic pollution levels as well as current pollution levels can be found at DEFRA Air Quality site. A great store of information and one that you can download data from.

Wonderful as this source is for research, atmospheric pollution is not a problem that has past or is under tight control on a global scale. The locations of UK data reflects the monitoring networks set up in the 1960s by Warren Springs Laboratory, largely in response to the Clean Air Act (1956) and the need to monitor levels of pollutants to ensure that standards were being meet. The early monitors tended to be instruments such as the sulphur dioxide bubbler (so old I couldn't fidn a photo of it on the Web!). Air was pumped into the machine at a known rate and the atmosphere reacted with the liquid as it bubbled through the machine. After day the flask with the liquid in was removed and replaced with another flask of liquid. The liquid from the previous day was analysed using titration techniques (reacting the sulphur dioxide with another chemical to get a colour change and a reaction product that could be accurately measured) to determine the levels of sulphur dioxide (once the various calibrations and calculations had been done). I know this because I used an old bubbler in my thesis to monitor sulphur dioxide levels on the roof of the Geography Department at UCL, London. It was educational, but was a pain to have to process daily, particularly as it was just self-taught me undertaking the titration much to the amusement of colleagues in the lab. Passive monitors such as nitration tubes (they just sit there and the pollutants react with them) were also used, but still needed chemical post-processing to obtain a result.

By the time I finished my thesis in 1989, real-time monitoring of pollutants, or at least hourly averaged and then 15-minute averaged values, were becoming more usual and replaced the daily averaged data. This is great for monitoring levels virtually continuously and for identifying specific pollution episodes but how much information is there and how can you interpret it? Air quality standards have varying monitoring levels for different pollutants and even the same pollutant can have different exceedence values. Sulphur dioxide levels in the UK, for example, should not exceed 266 mirocgrams/m3 more than 35 times per year if measured as averaged 15-minute concentrations. If measured as 1 hourly means then 350 micrograms/m3 should not be exceeded more than 24 times per year. If measured as a 24 hour average then 125 micrograms/m3 should not be exceeded more than 3 times a year. So the limits change with the monitoring period and the type of equipment being used to monitor pollution levels. This variation may begin to get confusing if you try to communicate it to too many different end-users.

A simplified version, the Daily Air Quality Index, recommended by the Committee on the Medical Effects of Air Pollutants (COMEAP) uses an index and banding system with bands numbered1-10 and colour coded for the level of severity of atmospheric pollution. The scale mirrors established ones for pollen and sunburn so draws on existing public understanding of colour and levels. Bands 1-3 are green, so represent low atmospheric pollution levels, 4-6 are shades of orange and represent moderate atmospheric pollution levels, 7-9 are darkening shades of red ending up at brown and represent high atmospheric pollution levels, whilst the oddly coloured purple band of 10 represents very high levels of atmospheric pollution. The index itself combines the highest concentrations for a site or region of five key pollutants: nitrogen dioxide, sulphur dioxide, ozone, PM2.5 and PM10.

The DAQI may be a useful tool for communicating information about the general level of pollution as it relates to human health but does the simplicity mask complexity that disaggregated data would not? The relative contribution of the five pollutants to the index can be gauged by the information on each at the DEFRA website. PM2.5 and PM10 uses 24-hour running mean concentrations and have specific threshold levels fro each band, whilst sulphur dioxide is measured as 15-minute averaged concentrations and, again, has threshold values for each band. The index itself, though, hides if all or just one or two of the pollutants push the DAQI into a band. The index misses other pollutants that could impact upon human health, even though these may be monitored such as benzene. The cocktail of pollutants used to create the index also reflects a specific context, the UK, would the cocktail of significant pollutants vary with other contexts? The cocktail and the monitoring intervals are not necessarily ‘natural’ ones – they have been developed from monitoring set up for other purposes such as regulatory requirements. The index is squeezed out of what exists.


The DAQI is a very, very useful tool, but it reflects an attempt to communicate complex and huge volumes of information in a simplified manner that, the makers believe, will be of use to specific end-users. Once data is compressed and simplified you are bound to loss some of the information contained in its variations and detail. The index you develop for targeted end-users will, of necessity, exclude a lot of the information you have collected and it is just useful, for the end-users in particular, to be aware of this.

Beijing Air Quality – Citizen-Science Approach to Mapping Levels?

A recent article in Environmental Technology Online reports on a community-based science project called ‘Float’ that is actually part-science and part-art project. The idea is that pollution-sensitive kites will be flown over Beijing. These kites contain Arduino pollution-sensing modules and LED lights and will indicate levels of volatile organic compounds, carbon monoxide and particulate matter by changing colour to green, yellow or red depending on the pollutant levels. The kites are attached to GPS device loggers and the real-time data website Cosm.

The project is designed by students Xiaowei Wang from Harvard’s Graduate School of Design and Deren Guler from Carneige Mellon and is designed to involve local residents in data collection. The project relies on public funding and is still raising funds. The project derives its funds from Kickstarter, a website devoted to creative projects and obtaining funding for such projects (The Float project on Kickstart). The project also has funding from the Black Rock Arts Foundation and the Awesome Foundation.

The project has generated a lot of interest on the Web:

Fighting China’s Pollution Propaganda, with Glowing Robot Kites For the People

Pollution-detecting kites to monitor Beijing's air quality
Glowing Pollution Sensor Equipped Kites Replace Beijing's Stars
Kickstarter Project Plans to Measure Beijing Pollution Using Kite Sensors

Only a couple of comments and an expression of interest in the results really.


The project is undoubtedly part of the growing and, in my view, superb trend towards more inclusive community or participatory science (choose whichever term you prefer, Guler uses citizen-science). The ideal of getting local communities involved in the data collection as well as involving them in all aspects of the research process is an excellent way to raise awareness of an issue as well as educate people about the scientific approach and its problems and potentials. The Float project has involved local communities, young and old, from the start with workshops in Beijing and as well as in the design of the kites. In terms of how to organise a community-based, participatory science project it is one that I will advice my students to look at. It is just a shame that the descriptions of the project veer from highlighting the science to highlighting the arts aspects as if the two are, or need to be, distinct. It should also be remembered that this project, as any project involved in monitoring pollution, is entering the political as well as the scientific arena. Involving local populations is a political act (as is their agreement to involvement) as much as the monitoring of pollution by the American Embassy or the siting of monitoring sites by the Chinese. Local is as political as the national or international, but the nature of the act does not necessarily mean the data is political bias only that data collection is for a purpose.

As with most community-based projects, however, there is the issue of belief, trust or confidence in the data collected. These projects do tend to illustrate quite nicely the continuing divide between the ‘specialist’ or ‘expert’ and the ‘public’ (I would say amateur, but much of British science in the nineteenth and early twentieth century only developed because of amateurs!) The expert has been trained and accepts certain methods as being appropriate for data collection. Control and standardization are essential in ensuring what is termed ‘intersubjectivity communication’ between researchers – basically it means  I know what you did because that is how I was trained to do it, so I trust your data as being real. Guler seems to downgrade the status of the data collected even before the project really begins by stating:

‘We’re trying to interact with people on the street and see what they’re tying to do with the information they see. I don’t plan to argue that this is the most accurate data because there are many potential reasons for differences in air quality reports. We want to just keep it up, upload the data, and focus on that more after we come back’.

My impression is this statement is a great get-out clause for ‘official’ monitoring be it by the Chinese or atop the American Embassy. I wouldn’t’ be so pessimistic. The aims of the project in terms of improving public understanding of air pollution, its impact on health and the visualization of pollution through the kites are all excellent and likely to be successful. The data collected is also of value. The ‘official’ pollution monitoring sites probably conform to national or international standards for static sites in terms of equipment and monitoring periods. The kite data does not necessarily provide comparable data to these sites. The kites are mobile and collect data on levels that can be spatially references (I assume in 4 dimensions). They provide a different perspective on atmospheric pollution rather as a spatially altering phenomenon, something the official monitoring sites can not provide.  It could even be argued that the kite data provides information on pollution as experienced by the population (although the population is unlikely to move across the sky at the height of the kites!) The important thing to remember is that there is not one, single correct measure of atmospheric pollution; there are merely different representations of atmospheric pollution. The official static sites have the advantage of having clearly defined protocols that ensure the data or information they collect is immediately comparable with data or information collected at similar monitoring sites globally. The Float project is generating a different and novel set of data or information. This may require a different approach to thinking about the information and its interpretation (Guler seems to suggest this with some hints at triangulation of trends) and in how confidence or belief in the information is assessed either qualitatively or quantitatively. I will be very interested to see what form the results and interpretation takes. Good luck with the project!

Road Traffic Pollution and Death: Interpreting the Data

A recent report suggests that road traffic pollution causes 5,000 premature deaths a year in the UK, whilst exhaust from planes adds another 2,000 (http://www.bbc.co.uk/news/science-environment-17704116 for summary, the actual report is a paper in Environmental Science and Technology which is a journal for which you need a subscription). The numbers are comparable with those produced by COMEAP (Committee On the Medical Effects of Air Pollution) "The Mortality Effects of Long-Term Exposure to Particulate Air Pollution in the United Kingdom" which estimates air pollution was responsible for 28,000 deaths in the UK in 2008 (the more recent study estimates 19,000 deaths in that year). One interesting statistics from the more recent report is that road traffic accidents caused only 1,850 deaths in 2010, meaning that traffic pollution is a more potent killer.

So what can we make of these figures. The exact number of deaths depends on how you calculate 'premature' deaths. This means you need to extract from the number of deaths those that would not have happened had it not been for the pollution. This means using life-table analysis to predict survival rates of different age groups. If air pollution improves, for example, you might expect everyone to have an improved survival change but that this would be greater for young children than for people in their 80s. The children who benefited from the reduction in pollution have to die sometime so the benefit is not sustained indefinitely. This means that you have a dynamic or continually changing death rate based on a reduction in pollution levels.  The COMEAP report suggests that any benefits from reductions in air pollution should be expressed in terms of improved life expectancy or number of life-years gained but accept that the 'number of attributable deaths' is a much catchy way of expressing the information.

An interesting read for interpreting the 'deaths' is the appendix Technical Aspects of Life Table Analysis by Miller and Hurley. This short report goes through the technical aspects and assumptions involved in this sort of analysis. Be aware through it does get into the mathematics fairly quickly. Importantly, starting with 2008 as a baseline you construct an age-specific all-cause mortality hazard rates, hi, that acts upon age-specific populations, ei.  Additionally, the number of viable births into the future is taken to be the same as the 2008 baseline. Changing policies alters the 'impact factors' which differ by age group and time. By altering this impact factor you change the the hazard impact and so alter the mortality rates.


Understanding how 'deaths' are calculated and the assumptions involved are vital to interpreting the information provided. This tends to be particularly important when, as in this report, the 'deaths' are the end result of mathematically modelling of a data set and a series of key assumptions about the impact of different scenarios.  I am not suggesting that the mathematics is wrong, the use of life-table analysis has a long and profitable history in the insurance industry so the modelling is on a very sound base. The COMEAP report recognises this problem of interpretation (starting page 13) and knows that there is a trade-off between between full accuracy and accessibility. It is also acutely aware that the numbers are open to misunderstanding if the basis of their calculation is not understood. On page 14 of the report, for example, they state for the term 'number of attributable deaths' that:

To emphasize that the number of deaths derived are not a number of deaths for which the sole cause is air pollution, we prefer an expression of the results as “an effect equivalent to a specific number of deaths at typical ages”. It is incomplete without reference also to associated loss of life. The Committee considered it inadvisable to use annual numbers of deaths for assessing the impacts of pollution reduction, because these vary year by year in response to population dynamics resulting from reduced death rates.

In interpreting this type of data it is important to know how it was derived, to know if it was modelled, and if so how, and, as importantly, the exact technical definitions used for terms. The alternative is relying on others to interpret the data for you with all the attendant agendas potentially coming into play as they draw their conclusions.

Beijing Atmospheric Pollution now online

On 23rd January the Beijing Municipal Environmental Monitoring Centre began to release atmospheric pollution data online (see this site but a knowledge of Chinese helps in navigating and understanding the data http://translate.google.co.uk/translate?hl=en&sl=zh-CN&u=http://zx.bjmemc.com.cn/&ei=EBVjT5LAIKXS0QWE-JT1AQ&sa=X&oi=translate&ct=result&resnum=5&ved=0CH4Q7gEwBA&prev=/search%3Fq%3DBeijing%2BMunicipal%2BEnvironmental%2BMonitoring%2BCenter%26hl%3Den%26biw%3D1707%26bih%3D1121%26prmd%3Dimvns ).





The hourly data had previously only been available for laboratory use (http://www.china.org.cn/environment/2012-01/06/content_24337033.htm) but the release of the data seems to be a response to public concern over air quality and the mismatch between government statistics and public perception of air quality. Some of this perception may have resulted from the release of atmospheric pollution data by the US Embassy from a rooftop monitoring station(http://ecocentric.blogs.time.com/2012/01/22/political-pollution-how-bad-air-equals-social-unrest-in-china/ for report and http://www.nytimes.com/2011/12/07/world/asia/beijing-journal-anger-grows-over-air-pollution-in-china.html?_r=1 for a discussion of the halting of the tweets in July 2009 and http://twitter.com/#!/beijingair for the tweet). The mismatch between official announcements about good quality air and the tweet caused some friction between officials and the embassy.



So what are we to make of the release of this data? Firstly, it is handy to know Chinese to interpret the site but then again the site is not aimed at an English speaking foreigner but at the Chinese inhabitants of Beijing so this is a fairly lame criticism. Secondly, the data release may be a political decision but at least the data is out there and can now be assessed by the public and by other scientists around the world working on air pollution – surely a good thing in its own right. Thirdly, should the data be questioned? The US embassy site seems to have taken on the role of arbitrator in assessing the data quality (at least in Western press releases). The US embassy is just one site with monitoring equipment at a specific height (not necessarily standardized to the height of the Chinese monitoring stations) so any spatial variation in air quality would not be picked up by data from one site. Even asking the question about data reliability is political. It suggests that the Chinese data will somehow be affected by the political powers that be (as if the US act of monitoring pollution isn’t political as well?!) Details of where the monitoring sites are located, the accuracy and standardization of the monitoring equipment, etc are reasonable scientific questions to ask both of Chinese pollution data and the pollution data of any monitoring network wherever it is. Such questioning ensures comparability of datasets. By releasing the data the Chinese scientists and authorities are putting themselves within this scientific debate. Criticising a dataset does not mean the data set is wrong; questioning and clarification and refinement to ensure compatibility is merely part of the scientific process.