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.
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.
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.
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