Atmospheric particulate matter concentration and annual ... - CiteSeerX

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES Volume 1, No 6, 2011 © Copyright 2010 All rights reserved Integrated Publishing Association Research article

ISSN 0976 – 4402

Atmospheric particulate matter concentration and annual variability in an urban area of NW Spain Jorge SanjurjoSánchez University Institute of Geology “Isidro Parga Pondal”, Campus de Elviña. University of A Coruña. A Coruña, 15071, Spain [email protected] ABSTRACT Atmospheric particulate matter (PM) refers fine solid and liquid particles suspended in air, strongly dependent of anthropogenic air emissions in urban areas. High PM levels have been measured in several cities around the world. Several important industrial facilities exist in the urban area of A Coruña, NW of Spain. They emit important PM to the air. A network of air quality monitoring stations exists and it allowed knowing the hourly PM10 concentration in the air. PM10 is used to denote particles of diameter under 10 µm. Such data is used to know the seasonal and yearly content on PM10 in the air between 2005 and 2008 in the urban area. The data provided shows small variability in the air PM10 concentration among stations and seasonal periods. Slightly higher PM10 concentrations and variability can be observed during spring and summer due to climatic factors, above all in rural and industrial settings located in the outskirts of the city. Keywords: PM10, atmospheric particles, air pollution, seasonal periods, NW Spain. 1. Introduction Both the gaseous and particulate components of atmospheric aerosols, and particularly atmospheric pollutants contribute to the deterioration of air quality. This has encouraged diverse studies on the chemistry, distribution and effects of gaseous and particulate pollutants. However, few research works on deposition of particles have been performed in comparison to gaseous compounds (Judeikis and Stewart 1976; Ruijgrok et al. 1995). The term “atmospheric particulate matter” is used to refer fine solid or liquid particles suspended in air. Particulate matter (PM) have strong influence in many atmospheric processes, with important environmental effects, including changes in visibility, solar radiation transfer (related with global warming), cloud formation, and play a major role in the acidification of clouds, rain and fog (Pueschel et al., 1986). Also, they are important for human health and other animals, ecosystems and also on the built environment and processes related with environmental pollution and atmospheric chemistry. Thus, the economic impact of high PM concentrations in air is evident. 1.1 Particulate pollutants PM can be classified considering their size. The smallest particles have very short lifetimes in air because their attachment to larger particles. The largest particles are shortlived and remain airborne near to their source due to their high rate of sedimentation (Amoroso and Fassina 1983). PM may be originated by some natural and anthropogenic sources. Natural sources exceed anthropogenic emissions, but the latter are frequently concentrated in urban environments. Natural sources of atmospheric particles are volcanic outgassing, forest fires,

Received on March, 2011 Published on March 2011

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Atmospheric particulate matter concentration and annual variability in an urban area of NW Spain

sea salt (directly emitted), and gasphase conversion of other atmospheric compounds. Anthropogenic sources are mainly burning of fossil fuels (industrial, transport and domestic burning), diverse industrial processes, mining and agriculture. Industrial and transport emissions are a significant source of particles mainly due to combustion of fossil fuels. They can be responsible of high concentration of particles in the air in great urban settings. However, the distribution of atmospheric particles in urban settings will depend on the characteristics of the urban planning. In canyon streets higher PM emitted by car engines have been found closer to the ground (Janhäll et al. 2009). Other emissions caused by car traffic are not usually considered in pollution studies (Hildemann et al. 1991). There exist four main causes of particulate pollution episodes in European cities (Vardoulakis and Kassomenos, 2008): strong trafficrelated emission sources, local atmospheric dispersion conditions (e.g. calm winds), synoptic weather conditions that favour longrange transport of particles, and natural sources of PM not easily controllable (e.g. windblown dust). The dilution and transport of pollutants, including PM, are controlled by atmospheric transport, dispersión and renoval mechanisms, depending on the air and climatic conditions of an area. Due to climatic factors, the cyclic human activity and the diurnal cycles, the concentration of suspended particulate matter in the air oscillates diary, weakly and yearly (Amoroso and Fassina 1983; Fellenberg 2000). PM is important for human health. Evidence of public health impact of PM has been shown in urban settings. The effect of PM on health has been often studied in relationship to hospital admissions due to cardiovascular and respiratory diseases, but also with some types of cancer (Dockery and Pope, 1996; Englert, 2004; Curtis et al., 2006). Thus, PM has been classified as PM10 (spring>summer. It can be observed decreasing trend from winter to summer and high variability of PM10 concentrations in autumn. Figure 4b shows the mean PM10 concentrations measured at Castrillón station, revealing the order: spring>autunm>winter>summer. Strong variations are measured in spring and summer, being the station with more variable mean PM10 concentrations. A Grela station (figure 4c) shows

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similar variability to Sta Margarita and slight autumn>summer>winter>spring (from 2005 to 2008).

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Figure 5: Box plots of PM10 concentrations measured at the stations located at suburban and rural settings during 20052008 The five suburban air quality stations (Arteixo, Lañas, Sorrizo, Paiosaco, Bemantes) show different trends. Figure 4d shows that the seasonal variability mean PM10 concentrations measured at the Arteixo station occurs in the follow order: spring>summer>winter>autumn. Autumn shows slight lower dispersion of PM10 concentrations than the other seasons. The Lañas station (figure 4e) shows variations of the mean concentration in the following order: summer>spring>winter>autumn. PM10 concentration in air is highly variable in summer, compared to the other seasonal periods in this station (20062008). The Sorrizo station (figure 4f) shows that the seasonal variability mean PM10 occurs in the order winter>spring>summer>autumn. The mean values measured between spring and summer are not different and the seasonal dispersion of the measured values is similar, but slightly higher in these seasons. Figure 5a shows the PM10 concentration trend in air at the Paiosaco station. This station shows very low variability among stations following the order: spring>summer>winter>autumn. The deviation is low in every season, although little higher in summer. The station of Bemantes (figure 5b) shows the lower deviation in each station and


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lower variability of the mean PM10 concentration among stations. The order of such variations is spring>summer>winter>autumn. The rural stations can be divided in two groups: those situated into or near industrial settings (Cerceda and Mesón, respectively), and those situated in rural settings far from industrial facilities (Xalo and Paraxón). The Cerceda station (figure 5c) shows seasonal oscillations of the mean PM10 concentration in the following order: summer>spring>winter>autumn. The PM10 concentration is more variable in summer than in the other seasonal periods. The Mesón station (figure 5d) shows that the seasonal variability mean PM10 occurs in the same order summer>spring>winter>autumn. However, the seasonal dispersion of the measured values is higher in this station and similar in the different seasons, except autumn with lower deviation. The air quality stations situated in rural settings (Xalo and Paraxón) far from industrial facilities are considered as representative of clean air in the area. This clean air must not be considered in a strict meaning. They represent air measured on areas far from important industrial and traffic sources of PM10. The Xalo station (figure 5e) shows that the seasonal variability mean PM10 occurs in the order summer>spring>winter>autumn. The seasonal dispersion of the measured values is similar in summer and autumn, higher in winter and lower in spring. Figure 5f shows the PM10 concentration trend in air at the Paranxón station. This station shows variability among stations following the order: summer>spring>winter>autumn. The deviation is lower in spring and summer than deviation in winter (the higher) and autumn. In general, the information system of air quality stations of A Coruña shows light seasonal variability in the mean PM10 concentration in air in and near the urban area. Although, the direct anthropogenic emission of PM10 have been related to mean values PM10 of concentrations near the emission sources (Amoroso and Fassina, 1983; Queron et al., 2001; Weckwerth, 2010), the data taken from the stations reveal important mixing of atmospheric air and little effect of the nearby emission sources on the PM10 concentration. Regarding seasonal mean PM10 concentrations increased concentrations are measured in summer and spring between 2005 and 2008 in the area of A Coruña. This effect is more visible in rural areas near or far from industrial emission focus. It can be related with the variability of climatic conditions during the year. Autumn and winter are more humid and rainy than summer and spring in the area. Also, urban and suburban stations show more variable mean PM10 concentrations. This can be related with the effect of emissions due to diary and weekly cycles. Such emissions have an strong urban component, as can be directly related to emissions from traffic and exhaust of car engines (Gaffney and Marley, 2009). 3.4 Compared concentrations with other urban areas The measurements and mean PM10 concentrations can be compared with data obtained in other urban areas around the world (table 10). In most cases, such studies have been carried out in great cities with millions of habitants. In general, as it can be expected mean concentrations in such cities are higher due to the high concentration of emissions. Residential urban areas usually show values two or three times higher than those measured in A Coruña. Also, coastal areas do not always show lower values due to mild climatic conditions. Thus, the PM10 emissions, concentrations and distributions in an urban area must be studied in detail in each case, due to the decisive influence of local climatic conditions. The existence of information systems of networks of air quality stations is probably one of the most powerful techniques to understand the behaviour PM10 emissions. Jorge SanjurjoSánchez International Journal of Environmental Sciences Volume 1 No.6, 2011

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Table 10: Mean PM10 concentrations (µg/m3) measured in different cities of the world and references City (country) Area type PM10 Reference (µg/m 3 ) Taiwan Island Airborne 53 Fang and Chang 2010 Taiwan Island Urban 181 Chen et al. 2003 Residential Taiwan Island Industrial 175 Chen et al. 2003 Kolkata (India) Inland near Urban 68 Gupta et al. 2007 coast Residential Kolkata (India) Inland near Industrial 110 Gupta et al. 2007 coast Hong Kong Coastal Traffic corridor 73 Ho et al. 2002 Hong Kong Coastal Urban 80 Ho et al. 2002 Residential Macao (China Coastal Urban 172 Wu et al. 2002 Residential Seoul (Korea) Coastal Urban 50 Kim et al. 2003 Residential Taejon (Korea) Inland near Industrial 92 Kim et al. 2003 coast Mar del Plata Coastal Urban 34 Arkoulli et al 2010 (Argentina) Residential Athens (Greece) Coastal Urban 48 Vardoulakis and Residential Kassomenos 2008 Birminghan (UK) Inland near Urban 17 Vardoulakis and coast Residential Kassomenos 2008 Bor (Serbia) Inland Urban 10 Nikolic et al 2010 Residential Bor (Serbia) Inland Rural 6 Nikolic et al 2010 Residential Cologne Inland Urban 68 Weckwerth 2010 (Germany) Residential Cologne Inland Traffic corridor 27 Weckwerth 2010 (Germany) 4. Conclusion High PM levels have been measured in several cities of Europe in the last years despite improvements in vehicle and fuel technology. A network of air quality stations exist at the city of A Coruña (NW of Spain) that provides hourly and daily data of the PM10 concentration in air, to monitor industrial and trafficrelated emissions in the urban area and outskirts. Small variability in the air PM10 concentration has been observed in space and time (considering the different stations and seasonal periods) between 2005 and 2008. The mean PM10 particle concentrations are significantly higher at the monitored suburban industrial settings. If we compare rural stations corresponding to clean air and urban stations representative of urban air, differences in the seasonally mean PM10 concentration are not observed, although higher deviation of the mean is observed in urban air. Such variability and Jorge SanjurjoSánchez International Journal of Environmental Sciences Volume 1 No.6, 2011

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differences could be related to the different effect of traffic car emissions, with a local effect in the air PM10 concentration in the urban area. This can be related with the effect of diary and weekly cycles of economic activity, higher in the urban area. Also, the variability of climatic conditions during the year can be considered as responsible of lower PM10 concentrations in autumn and winter are more humid and rainy than summer and spring in the area. This seasonal variability is more evident in rural and industrial settings located in the outskirts of the city. Such variability seems to be a general issue in this kind of studies and thus, the information systems of air quality stations is a powerful technique to understand the behaviour PM10 emissions. Acknowledgements This study has been supported by the University of A Coruña (Project: “Utilización de isotopos estables en morteros de edificios del Patrimonio Histórico como trazadores de la polución amosférica”, 2010). I would like to thank to the Dirección Xeral de Calidade e Avaliación Ambiental da Xunta de Galicia, Consellería de Medio Ambiente Territorio e Infraestructuras for supplying the data from the monitoring stations. 5. References 1. Amoroso, G.G., and Fassina, V., 1983, Stone decay and conservation: Atmospheric Pollution, Cleaning, Consolidation and Protection, Amsterdam Elsevier. 2. Arkouli, M., Ulke, A.G., Endlicher, W., Baumbach, G., Schultz, E., Vogt, U., Muller, M., Dawidowski, L., Faggi, A., Wolf‐Benning, U., and Scheffknecht, G., 2010, Distribution and temporal behavior of particulate matter over the urban area of Buenos Aires, Atmospheric Pollution Research, 1, pp 1‐8. 3. Carballeira, A., Devesa, C., Retuerto, R., Santillán, E., and Ucieda, F., 1983, Bioclimatología de Galicia. A Coruña, Spain, Fundación Pedro Barrié de la Maza Conde de Fenosa. 4. Chan, Y.C., Simpson, R.W., Mctainsh, G.H., Vowles, P.D., Cohen, D.D., Bailey, G. M. (1997) Characterisation of chemical species in PM2.5 and PM10 aerosols in Brisbane, Australia, Atmospheric Environment, 31, pp 3773–3785. 5. Chan, Y.C., Simpson, R.W., Mctainsh, G.H., Vowles, P.D., Cohen, D.D., and Bailey, G. M., 1999, Source apportionment of PM2.5 and PM10 aerosols in Brisbane (Australia) by receptor modelling, Atmospheric Environment, 33, pp 32513268. 6. Chen, J.S., Hsieh, L.T., Tsai, C.C., and Fang, G.C., 2003, Characterization of atmospheric PM10 and related chemical species in southern Taiwan during the episode days, Chemosphere, 53, pp 2941. 7. Chow, J.C., 1995, Measurement methods to determine compliance with ambient air quality standards for suspended particles, Air and Waste Management Association, 45, pp 320382. 8. Chow, J.C., Watson, J.G., Green, M.C., Lowenthal, D.H., Bates, B., Oslund, W., and Torres, G., 2000, Grossborder transport and spatial variability of suspended particles


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