Pedestrian exposure to urban air pollution

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vehicular pollution: civilising urban traffic". ... both pedestrian and vehicular traffic flows of major urban projects. The 'space .... traffic than Tottenham Court Rd.
Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

Pedestrian exposure to urban air pollution: exploratory results B. Croxford, A. Penn The Bartlett School ofArchitecture and Planning, Philips House, University College London, Gower Street, London, WC1E 6BT, UK

Abstract This paper will present findings from the EPSRC funded research project (GR/J50613), "Effects of the street grid configuration on pedestrian exposure to vehicular pollution: civilising urban traffic". The project has developed a monitoring instrument the Street Box, which can be used to measure Carbon Monoxide (CO), wind speed, temperature, humidity, and light. This Street Box is being used to measure urban pollution at head height in several, closely situated streets. This paper includes a detailed examination of data gathered from several Street Boxes sited in a small area of central London near to Huston station. The effect of different variables on CO concentration is considered and a possible methodology for enabling more accurate estimates of pedestrian exposure to urban pollution is proposed. The variables examined are wind speed, wind direction, and monitoring site location. Introduction This work is extracted from a project that builds on previous work done at the Bartlett looking at spatial configuration of cities. A "space syntax" computer analysis method has been developed to predict pedestrian flows in the fine scale structure of city streets [1]. This method has also been adapted to predict vehicular flows[2],[3],[4] and is being used commercially to predict the effect on both pedestrian and vehicular traffic flows of major urban projects. The 'space syntax' method of city analysis can provide a map of pedestrian or vehicular flow on every street in a city, since both modes of traffic stem from the way a street fits into the pattern of the entire network, the methods can be used to predict the effect of physical design changes to the network on flows in all streets within an urban area. If this can be tied in with urban pollution

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

440

Air Pollution Engineering and Management

measurements, then, by making flow estimates for each street, it should be possible to generate pedestrian exposure maps for a city, to evaluate the effects of design changes[5]. However, there are some methodological problems, it is difficult to measure pedestrian exposure to urban pollution, there is no clear measure of "urban pollution" and there is no clear method of calculating pedestrian exposure to it. Also very little research has been conducted, looking at the distribution of pollution at the street segment scale [6],[7]. Increasing evidence of links between various components of urban pollution and health problems is being published [8],[9], and this is now being reported in such a way that "Urban pollution" is being perceived as a major problem by the public. (The term "Urban pollution" is used throughout this paper to refer to urban airbourne pollution.) This paper addresses only the problems of measuring urban pollution at the scale of the street segment, not the question of how to calculate pedestrian exposure. Carbon Monoxide (CO) is used as a tracer for "urban pollution" and the final phase of this project will be the monitoring of 60 street segments in a small area of North London. This paper presents results from five prototype monitors which measure CO along with wind speed, temperature, relative humidity and light. The monitors have been developed here at the Bartlett and are called "Street Boxes". The Street Box measuring instrument The major part of this project has been concerned with developing a method of measuring urban pollution based on the City Technology Carbon Monoxide (CO) fuel cells, in a cheap, reliable and accurate way. The fuel cells themselves are relatively cheap and extremely accurate, with quoted specifications of +1-5% from 0 to 4000 ppm. These cells are accurate right down to background levels and lower, and have a detection limit of less than 0.1 ppm. There is no apparent drift even over a period of 6 months or more, with the maximum error between any one sensor and the average of all six, is approximately 5%. These CO sensors have been combined with sensors measuring wind speed, light, humidity, and temperature and connected to a datalogger. All the components have been fitted into a small, (171 x 122 x 55 mm) weather proofed box powered by a battery and "topped up" via a photo-voltaic panel. The result is a totally self-contained pollution monitoring instrument, the "Street Box",

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

Air Pollution Engineering and Management 441 which can be fixed anywhere, and can be left unattended for up to 6 weeks between data downloads. Wind speed is measured using an experimental sensor, it has no moving parts, and has been tested against a conventional anemometer, giving an r% of 0.6. The good correlation gives confidence in the assigning of a qualitative category to each street measured at a particular time. The measuring of wind speed in the street itself is a problem due to turbulence caused by the shape of the street and its orientation relative to the wind and also traffic-induced turbulence. However by typing each street at a particular moment into calm, breezy or windy it is possible to achieve a data separation that is useful for analysis. Wind direction is not measured at the street level. The datalogging board has only integer mathematic functions and uses only 8 bit numbers, (0->255), the practical consequences of this are that time is scaled from 0 to 240, so the ten's figure is the hour and the last digit expresses fractions of an hour, so 175 is 5:30 pm, 178 is 5:48 pm. The Carbon monoxide value also has to be scaled to fit into one of 255 levels, I have arbitrarily set this to be from 0 to 25.5 ppm, so the measurement is CO concentration in parts per million times 10. More detailed explanation is given in Croxford [5]. Pollution survey of the area around

UCL

The turbulent effects of air movement mean that two measurements taken at the same junction can differ enormously from each other with only a small spatial difference in position. In addition, the stop-start nature of traffic at junctions adds confusion to the data. I have therefore tried to measure the pollution at a point in the middle of a street segment. So all the street boxes are mounted at the same height using the same criteria, that they should be at a height of 2.5m from the ground, near to the road, away from the possibility of stationary traffic, and as far from any junctions as possible. Berkowicz et al [10] has shown the effects of vortices produced in the street canyon can produce large differences in pollutant concentrations across a street. These vortices are set up by the prevailing wind crossing the street perpendicular to the direction of the street. The area used in this survey is immediately surrounding the UCL main campus. Huston Road is the busiest road in the area and is 6 lanes wide, 3 in each direction. Tottenham Court Rd is 3 lanes heading North only and Gower Street has three lanes heading South only. Gordon Square is a quiet road on one side

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

442

Air Pollution Engineering and Management

of a leafy square, and Gordon Street is a busy "rat run" providing access across and onto Huston Road. 140

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—,- 1- ,- -r-- r- ""~i- -"i 250 50 75 100 125 150 175 200 225 Time (19th February 1995} Figure 1: A bad day on Huston Road, Huston road reads much higher than the other streets for the whole day, this is perhaps due to a constant high level of slow moving traffic. In figure 1 results are shown for 5 streets over a period of one day, the levels on Huston Road are approaching World Health Organisation limits for CO, while -20 H

25

only a few streets away, the pollutant concentrations are only just above background levels. This graph was a Sunday and was a particularly bad day, but it clearly shows how great the differences can be from street to street. The question now arises of whether these results are a meaningful representation of how Huston Road as a whole has a higher concentration of CO than four other nearby roads, or are they just a comparison of 5 points in a city. A clearer picture emerges by looking at each street in greater detail, Street bv street analysis of the UCL pollution data This section considers the effect of wind on pollutant concentrations and distribution. By splitting the data into three wind type categories for each road, based on the wind speed measured in that road, further analysis can be made from the data. Full data for 3 of the streets was available for this period, 23rd to the 28th February, the wind data for Gordon Street and Gordon Square was not available during the period of study. By splitting the data into three categories,

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

Air Pollution Engineering and Management 443 windy, calm and an in-between state called breezy, allows the following analyses to be made. Considering all three graphs, figures 2,3 and 4, gives a detailed picture of how the wind can affect pollution levels, in all cases increased wind reduces pollutant concentrations, and all the pollution peaks occur on calm days. The peak seen on Huston Rd. on the 24th is seen less sharply on Gower St. but reaches the same level. Tottenham Court Rd has 1.5 ppm at the same time, which is close to the urban background level. The wind speeds at all three sites are mainly calm. The few windy occasions recorded on Gower St. may be due to passing lorry traffic. The conclusion is that for this day the readings mainly reflect traffic levels, with Gower St. and Huston Rd. more heavily loaded with traffic than Tottenham Court Rd. 80 —•—• ^—«070-

24th February peak of 8 ppm CO.

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27th February peak of 3 ppm CO.

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Figure 2 shows the results for Euston Road, which is a wide West-East road and is one of the busiest in London with traffic flows of 50-60 thousand vehicles per day (AADT). For most of this period the wind was blowing from the West. On the 25th February the highest peak occurs on Tottenham Court Rd. which also registers the lowest wind speeds. Euston road is windiest and has the lowest CO reading of 2 ppm while Gower St. is also windy but reaches 3 ppm. A possible analysis of this days' results is that the Tottenham Court Road site may be in a "dead" spot during a generally windy day. The peak of 5.5 ppm is "spiky" and may be due to only one parked vehicle.

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

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Air Pollution Engineering and Management 80

Peak 25th Feb. 5.5 ppm Oso -K

Peak 26th Feb. 3 ppm Peak 24th Feb. 1,5 ppr

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Observations Tot. Crt. Rd. (23rd - 28th February) calm Figure 3: Tottenham Court Road with wind effects, Gower St and Tottenham Court Road are aligned roughly North-South and are of similar width, whereas Euston Road is wider than both and is aligned roughly West-East. Peak 27th Feb 11 ppm Peak 24th Feb 8 ppm

windy

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Observations Gower St (23rd - 28th February) _____ Figure 4: Gower St with wind effects, shows the same pattern as before, with peaks at calm times and lower levels at windier times.

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

Air Pollution Engineering and Management 445 On the 26th February the profiles of all three road's readings are the same with a slowly rising CO concentration from the low of the very early morning to a late afternoon peak of 1.5 ppm for Huston Rd, 3 ppm for Tottenham Court Rd and 2 ppm for Gower St. All three sites register as mainly windy, and the CO concentrations are low due to the dispersal effect of higher wind speeds. The 27th February sees the highest peak of the period with 11 ppm CO registered on Gower St. in the late afternoon and a smaller morning peak of 6.5 ppm. Huston Road has a peak of only 3 ppm and Tottenham Court Rd reads only 1 ppm. Huston road is the windiest while Gower St. is quite calm for the whole day. Perhaps, heavy traffic on Gower St. was moving slowly and generating high levels of CO, the frequent wind speed category changes on Huston Rd suggest that the traffic may be generating enough turbulence to register on the wind sensor, while this was not the case for Gower St. or Tottenham Court Rd. This section has shown that this fine scale of data gathering can provide enough data to investigate the effects of wind speed, wind direction, monitoring position and traffic flows. Unfortunately it wasn't possible to get simultaneous traffic flows and speeds for this period for the roads in question to back up the hypotheses made in this section. Conclusion This paper is the result of reconsidering data gathered during the project, following the findings of Berkowicz et al [10]. For this reason several important factors were not taken into consideration at the time of the original study. The analysis would be improved by simultaneous traffic flow and traffic speed data. However the findings in this paper generally agree with the findings of Berkowicz et al., these being that the leeward side of the street experiences higher pollutant levels than the windward side and that increased wind speeds decrease pollutant levels. The method of data analysis outlined here shows up the weaknesses of most urban air pollution measurements, where the exact sites are often dictated by the size and value of the monitoring equipment rather than by good monitoring practice. The shape and orientation of the road, the traffic situation, the exact position of the monitoring site and the frequency of measurements that are taken all affect the concentration reading. By taking frequent readings of wind speed as well as pollutant concentrations, a more detailed analysis of urban pollution can

Transactions on Ecology and the Environment vol 6, © 1995 WIT Press, www.witpress.com, ISSN 1743-3541

446

Air Pollution Engineering and Management

be made. It is now possible to examine pollutant distribution under different wind conditions. This should lead to better calculations of urban pollution over a whole city which should in turn ensure better estimates of pedestrian exposure to urban pollution. Further work includes; investigating the use of CO and the other variables monitored as a proxy for other major urban pollutants, completing a total of 60 Street Boxes to be used for a survey of a Ikrn^ area of North London, and developing clear presentation methods for this fine scale data for use by councils and the public. References 1. Hillier B., Penn A., Hanson J., Grajewski T., Xu J., (1993), Natural Movement: or configuration and attraction in urban pedestrian movement, Planning and Design: Environment and Planning B, Pion, London. 2. Penn, A.,Banister D., Hillier B., et al, (1991), The relationship between vehicular and pedestrian movement in the smaller scale urban grid: a pilot study. SERC report GR/G 23609. 3. Penn A . Dalton N.. (1994). The architecture of society, stochastic simulation of urban movement.. Simulating Societies, University College London Press pp 85-126. 4.. Stonor T., Hillier B., Penn A., Karvoutzi K., (1993) The Manchester pedestrian and vehicular movement study. Internal Report. 5. Croxford B, Hillier B., Penn A., (1995) Spatial distribution of Urban Pollution. Fifth Symposium on Highway and Urban pollution , Copenhagen, May 1995. 6. Quality of Urban Air Review Group (QUARG) (Jan. 1993), Urban Air Quality in the United Kingdom 7. L.Y.Chan, W.Y. Wu, (1993) A Study of bus commuter and pedestrian exposure to traffic air pollution in Hong Kong', Environment International, Vol. 19, pp!21-132. 8. Vostal JJ., Physiologically based assessment of human exposure to urban air pollutants and its significance for public health risk evaluation. Environmental Health Perspectives, 1994, Vol. 102, No. S4, pp 101-106. 9. Sunyer J., et al, Air pollution and emergency room admissions for chronic obstructive pulmonary disease- A 5 year study, American Journal of Epidemiology, 1993, Vol. 137, No. 7, pp 701-705. 10. Berkowicz, R.,Palmgren, F., Hertel, O., Vignati, E., Using Measurements of Air Pollution in Streets for Evaluation of Urban Air Quality- Meteorological Analysis and Model Calculations, Fifth Symposium on Highway and Urban pollution , Copenhagen, May 1995. Please also see world wide web pages for colour versions of these figures and further explanations, Urban Pollution graphs http://doric.bart.ucl.ac.uk/web/ben/index.html