Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
The effect of rain on suspended participate
matter and other pollutants in an urban area
F. Polla Mattiot, E. Scafe EniTecnologie S.p.A, Via E. Ramarini 32
00016 Monterotondo, Italy E-Mail: fpolla@enitecnologie. eni. it
Abstract
A study on the effect of rain on atmospheric pollutants in the city of Rome from
1994 to 1996 has been conducted based on data collected by governmental monitoring stations located in different areas of the city. In the city of Rome, the average annual precipitation value is over 700 mm, referring to measurements collected from over a century. Almost every month
exhibits at least one rainy day. Days have been divided into two categories: rainy days, if it has rained at least 2 mm in the day, and days with no rain, in the other cases. Particulate matter concentration has been averaged every month in both categories. The
difference between the two monthly values has been divided by the days-with- no-rain average to calculate the monthly abatement. Abatement in the three years is around 10%, although there exist single events of heavily rainy days that reveal an up to 50 % decrease in hourly
concentration. Concentrations of paniculate matter, CO and NO% have been correlated with precipitation, using working days and low wind speed conditions. Results have been compared with both the day preceding and succeeding the actual rainy day.
1 Introduction
Atmospheric aerosols are produced by a variety of natural and anthropogenic sources and have a wide range of sizes and densities. Among anthropogenic sources, combustion originated paniculate matter (residential heating and mobile
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
944 Air Pollution
sources) accounts for one third of the total Polycyclic Aromatic Hydrocarbons (PAH) emissions*.
The major area of environmental concern with PAHs is their ability to produce cancer in exposed organisms. A large effort has been made to understand acid rain phenomena, which has stimulated many studies on the scavenging and solubility of gases during rainfall^ whereas, until now, fewer studies have been devoted to the removal of particulate matter by raindrops. Most of these papers are focused on the assessment of the physical-chemical process in simulated conditions. Nevertheless, positive effects from precipitation are generally experienced both in visibility analysis^ and in managing urban air quality; in fact many municipalities do not adopt programmed traffic restrictions in the event of rain. The aim of this paper is to analyze statistical effects of precipitation ~on particulate matter removal using real data, collected over three years by the Municipality of Rome. Our results allow a conservative estimate of the effect of rain, due to the dramatic reduction in the city of Rome of the circulating two- wheel/four-wheel ratio during rainy days.
2 Methods
2.1 Pollutants' concentration levels: site locations, sampling methods and data availability
The Municipality of Rome has organized a network of monitoring stations in order to assess the air quality, to record the number of occasions that exceed the specified limits and to evaluate trends since 1992. The urban Air Quality
Network is made up of nine measuring stations classified according to traffic density. Automated instruments are distributed among the stations depending on site characteristics.
A NDIR (Non Dispersive InfraRed) CO analyzer and a chemiluminescence NOx instrument are present in almost every station. UV photometers for ozone are generally installed in areas reserved for pedestrians, and fluorescence SOj analyzer are located in densely populated areas. Total Suspended Particulate matter analyzers are p gauge instruments, now converted into PM,o analyzers. Ambient measurements are taken at ground level (1.5 m). Calibration is generally performed nightly. Hourly data are available for all pollutants except for particulate matter which displays an average value every two hours. Particulate matter is measured in four stations but our attention will focus on one station located in a heavily trafficked area. Corso Francia is a six-lane street, oriented with the direction of predominant wind in the city of Rome during fall- winter seasons.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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2.2 Meteorological variables
Meteorological data are supplied by a governmental institute located in the historical center of the city at a height of 60 m. Temperature, pressure, solar radiation, relative humidity, rainfall (total precipitation in a day, beginning hour, maximum intensity) and wind speed and direction are recorded daily. Moreover, some of the monitoring network (at Via Arenula, for instance, but not at Corso Francia) are equipped for meteorological measurements at ground level. As reported in the annual bulletin*, the years from 1994 to 1996 appear similar on a macro scale through comparing monthly averages of meteorological variables. Winter 1994 was mild; wind speed presented anomalous data in fall 1994 and in winter 1995. Rainfall is spread all over the months although it is concentrated with a few days of stormy weather particularly during the fall. For instance, 1996 was a particularly rainy year (893 mm, 70% in the period August
- December) exceeding the mean values (745 mm, 99 rainy days) calculated from 1862 to 1990.
2.3 Processing participate matter data
As our aim is to examine how many days are effective for TSP removal, we studied the monthly behavior of TSP concentration with and without the presence of rain. A list of requirements were established and a detailed screening of the data was performed. First of all, codes given by the instrument were checked. Then, iterative procedures were run in order to find out concentration levels under urban background and if there is repetition of identical 10 digit values. Therefore we consider that 80% data reliability is the minimum required; that is to say, that when more than 20% of the data have been rejected in a month, it has to be excluded from the study. Anyway the number of months and rainy days are representative of every year and no insertion of calculated data - as suggested by Glen* - is necessary or convenient to our purposes. Moreover we realized that during a month in the city of Rome it can be observed that the mean of rainy days is less than six (< 20% in a month).
Days have been divided into two categories: rainy days, with at least 2 mm of total precipitation^, and days with no rain. Particulate matter concentration has been averaged every month in both categories. The difference between the two monthly values has been divided by the days- with-no-rain average to calculate the abatement which is expressed as a percentage. Mean values are considered with 95 % confidence interval of the mean to compare data.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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3 Results and discussion
3.1 Annual trends of mayor pollutants
The measurements from all the stations detecting the pollution level were averaged to obtain the mean urban values reported in Table 1. Averages from one station are also shown for comparison.
Table 1 Annual pollutant levels 1994 1995 1996 NOxWnf) 254 (158) 230 (149) 219 (136)
CO (mg/nf) 3.9 (3.6) 3.6 (3.4) 34 (3) TSP Wnf ) 73 (90) 80 (100) 72 (117)
Discrepancies of single station data from the mean value are attributed to differences in traffic density and positioning with respect to wind direction.
Decreasing trends are outlined for all the pollutants, except particulate matter. In particular Corso Francia TSP mean values show a noticeable increase from 1994 to 1996. Monthly behavior of particulate matter concentration is presented in
Fig. 1 where an increase in the summer is outlined. Herein no distinction between rainy day and days with no rain has been accomplished.
1995 - Corso Francia-
160 150 --
140 4* : 130
« 120 - §* 110 -~ , Q. [2 100 -
90 80 -
70 -- 60 1234567 9 10 11 12
months
Fig. 1 Monthly average concentration of Total Suspended Particulate Matter
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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3.2 Single events of heavily rainy days
In order to examine the removal efficiency of rain on pollutants we observed some working days characterized by the presence of rain at peak TSP levels without noticeable increases in wind speed (VV). Nevertheless, TSP concentration and VV maxima in the city of Rome are nearly simultaneous and a slight increase in wind speed has been often observed at midday. Due to the complexity of the wind effect on paniculate matter, it is useful to analyze other pollutants and to correct the experimental data^, according to the box model approach* (1/VV). A significant example (Tuesday 5* September 1995) regarding particulate matter (Fig. 2), NOxand CO (Fig. 4, 5) is reported.
In presence of rain, TSP concentration levels drop down from 50% of the initial value, as shown in Fig. 2, well below the average diurnal concentration levels?
5 Sep rain 12-14
6 Sep no rain
10 12 14 16 18 20 22 24 hour
Fig. 2 TSP concentration data on September 1995. Comparison with the day preceding and succeeding the actual rainy day.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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1 average concentration + 4 Sep no rain _O_5 Sep rain 12-14
_•• 6 Sep no rain
Fig. 3 NOx concentration data on September 1995. Comparison with the day preceding and succeeding the actual rainy day.
_ average concentration
_ 4 Sep no rain .5 Sep rain 12-14 o u _ 6 no rain
0 2 4 6 8 10 12 14 16 18 20 22 24
Fig. 4 CO concentration data on September 1995. Comparison with the day preceding and succeeding the actual rainy day.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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and CO concentration levels before rain are high, final levels are below the average concentration thus dramatically reduced by the rain. The decreasing trend outlined is fairly confirmed by the wind-corrected data (Fig. 5). We can therefore assert that main reduction has to be attributed to precipitation. This example agrees with the literature on acid rains and confirms the removal efficiency of precipitation; high scavenging efficiency for paniculate matter is observed as well*. But not all cases analyzed in this study present the same behavior and a statistical monthly approach to know how many days are effective is suggested.
_ average concentration
_ 4 Sep no rain _ 5 Sep rain 12-14 _ 6 Sep no rain
Fig. 5 CO concentration data on September 1995 with wind correction. Comparison with the day preceding and succeeding the actual rainy day.
3.3 Particulate matter and monthly abatement
The results of processing TSP monthly data are shown for each year in Table 2, which distinguishes the two categories of data. Data reliability, mean value, 95% confidence interval of the data and abatement are outlined. Information on total precipitation and number of rainy days is displayed alongside.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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Table 2 Monthly TSP data for 1994,1995 and 1996
fa II mean value 95' rain confid ence rJity 1994 I (ug/m3) No rain rainy j - ;abat6rrieiit| no rain rainy no rain rainy mm rainy days days days days
Jan 88% 59 32 24 65 6 April 93% 85 28 22 71 11 91%#^^^z| 96 June 99% 105 81 31 24 52 5 Dec 80% 98/o r\ < -';M;|3 ; /o^ -"-'%- 7 o 75 29 21 56 5 ^ \ . :'; «*\^ . {\\,""X,.J f ' A^ 1995 r No rain rain•y/ KSkfiifemeh'fcI * «.-» waklw; S :,\'& ^%'^S< n #o rain rainy no rain rain) mm rainy days JM|:|#k## days days days Feb 86% 93%i;##%@S3 92 89 3.7 68 62 8
March 90% 95%p%#^%##l 96 91 39 5 April 97% o 'jo/ //o >jr :< 5- >;;• ^" .i ""%"&$.,% o >/o,,;/ V^^' ^"* '. "' 97 75 4.2 84 91 5 May 98% 100%;<{#§%M^^^ 122 115 43 8
June 99% 127 126 62 6 99%W^9#^g Aug 99% 98%^9':i5%%% 100 85 64 10
Sep 99% 100%U%'23%:fI# 85 83 3.3 5 5 27 4 Nov 86% ioo%g;gg#g^ 92 92 4.3 85 23 4 O A O/ K* "^.' '^ AO/"^''' '% 111 4.0 85 128 10 Dec 92% o4% \t-*~ • -" ZUJ70;'|;; '"'-f 89 |i 1996 ||
No rain rainy abatement no rain rainy no rain rain)F mm rainy days r \\'' (''>/(' , '- days days days 5 6 63 11 Jan 109 95 April 121 119 4 8 49 6 May 92% 95% 3%; 133 129 7 6 62 10
Aug 83% 82%' . 3% % 134 130 4 7 56 5 Sep 96% 90%; 4% 126 121 4 7 94 9
Dec 93% 92% 17% 94 78 4 5 130 8
Fluctuations on abatement values are evident. For example, we obtained 3% and 23% (June and December 94) for two months which show the same precipitation amount and number of rainy days. Indeed no simple relationship has been established between abatement and precipitation amounts or number of rainy days.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
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In Fig.6 we report the removal efficiency versus the precipitation, both integrated over a month. Although there is some noise in the data, the presence of a threshold in the range 50-60 mm stands up. Some noise is expected because of the dependence of removal efficiency on the particulate matter^' and raindrop size distributions^, particle density (natural and anthropogenic sources), wind speed, and so on. It is reported in the literature^ an analogous threshold behavior, observed in laboratory experiments (monodispersed particles and water drops) as a function of an impaction parameter. That parameter takes into account particle size and density, and water droplet characteristics. In our case we dealt with actual complex distributions of both variables.
The threshold indicates that the probability to have useful events increases when the total precipitation is higher than 60 mm. We note that under the threshold value, the abatement stands at a small percentage. On the other side the precipitation events can be considered very efficient at collecting particle and delivering them to the ground.
Fortunately in Rome the number of months that overcome the threshold value is considerable and a mean value over 10 % can be calculated.
25%
20% -
g 15% - @/ A 1994
o> ^1995 w 10% _ jQ • 1996 CO 5% _
0% 0 50 100 150
monthly precipitation (mm)
Fig. 6 Scatter-plot of monthly abatement versus precipitation
4 Conclusions
The effect of precipitation on the immediate removal of pollutant have been verified in some precipitation events. As reported in the literature, the removal efficiency is controlled by the characteristics of raindrops and of the particulate matter; then not all the precipitation events are effective for TSP reduction.
Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541
952 Air Pollution
Over the three years analyzed no simple relationship between the
abatement and the total precipitation in a month has been found. Nevertheless a step behavior has been observed, as a result of the dependence on the rain and particulate matter features.
According to this picture the city of Rome could rely on an effective TSP average abatement over 10%, on a monthly basis, with a maximum value that
does not reach 25% in the three years examined. Our results indicate that chemical and meteorological measurements should be improved for in depth investigations, by in situ data collection of rain and pollutants' characteristics. In fact, the lack of complete and detailed data sets does not permit the assessment of relationships between physical properties and abatement.
Acknowledgements
The authors thank Dr G. Pallotti and E. Campagna of Presidio Multizonale di Prevenzione (Settore Ambiente - Roma), and Dr. F. Mangianti of Ufficio Centrale di Ecologia Agraria for supplying data. Moreover they thank Dr P.
Buttini for her helpful advice.
References
' Connell, D.W., Basic concepts of Environmental Chemistry, Lewis Publisher, New York, 1997 ^ Baechmann K., et al., The chemical content of raindrops as a function of drop radius - I. Field measurements at the cloud base and below the cloud, Atmospheric Environment, 30, pp. 1019-1025, 1996, and references therein * Trier A., Firinguetti L., A time series investigation of visibility in an urban atmosphere - I, Atmospheric Environment, 28, pp. 991-996 , 1994 * Mangianti F., Perino L., Osservazioni meteorologiche dell'anno 1996, Ufficio Centrale di Ecologia Agraria, Roma * Glen W.G., Zelenka M. P., Graham R. C., Relating meteorological variables
and trends in motor vehicle emissions to monthly urban carbon monoxide concentrations, Atmospheric Environment, 30, pp.-4225-4232, 1996 G Monn Ch. Et al. Small-scale spatial variability of particulate matter <10 pm (PM,o) and nitrogen dioxide, Atmospheric Environment, 31, pp. 2243-2247,
1997. ^ Polla Mattiot F., Buttini P., Fusco R., Prastaro M., Empirical relationships between fuel consumption and atmospheric concentration levels in an urban area, Applied Sciences and the Environment, Computational Mechanics
Publications, Southampton and Boston, pp. 241-250, 1998 s Lettau H. H., Physical and meteorological basis for mathematical models of urban diffusion processes, Proc. Symposium on Multiple-Source Urban j, U. S. EPA Publication No. AP-86, 1970
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* Ambe Y., Nishikawa M., Variations in different sized water insoluble particulate matter in rain water, Atmospheric Environment, 21, pp. 1469-1471, 1987 ™ Jindal M., Heinold D., A climatological algoritm for wet deposition of p articulate matter, Proc. of the 85^ Air& WasteManagement Annual Meeting, June 21-26, 92-69.15, 1992 " Zankel K. et al., Difficulties in estimating wet deposition of atmosphric particuate material, Proc. of the 83™ Air-&WasteManagement Annual Meeting,
June 24-29, 90-74.1, 1990 ^ Haddad Z. S., Durden S. L., Im E., Parameterizing the raindrop size distribution, Journal of Applied Meteorology, 35, pp 3-13, 1996 ^ Chate D.M., Kamra K., Collection efficiencies of large water drops collecting
aerosol particles of various densities, Atmospheric Environment, 31, pp. 163 K 1635,1997