Francesca Costabile

Spatial Distribution of Urban Air Pollution in Lanzhou, China~!2009-07-23~!2010-01-27~!2010-04-02~!

Urban air quality, and its variability in space and time, is a critical issue for human exposure and health related studies. In this work, we investigated the intra-urban distribution of SO2, NOx, NO2, Benzene, Toluene, and Xylenes in ambient air in one of the worlds most polluted cities, Lanzhou, China. Measurements were contemporarily carried out at forty locations in four seasonal campaigns during the period 2005-2006. Diffusive samplers allowing a sampling period of one month were used. As a general finding, the selected air pollutant concentrations often exceeded the EU limit values, and varied significantly with space, time, and proximity to relevant point emission sources. A statistical analysis revealed that monthly air pollutant concentrations were normally distributed in space. This suggests that the spatial distribution of urban air pollution was governed by the spatial diffusion of emission sources, at least for its apparent average behaviour. This result might be relevant to link urban air quality measurements and human exposure assessment. To gain insights into the properties of the urban air pollution distribution in space, makes the assessment of homogeneous areas of air pol- lution in the urban area less critical - and, consequently, allows a proper selection of the sites where to monitor air quality for health-effects studies.

Monitoring Air Quality in Urban Areas

Air quality improvement in rapidly developing countries like China requires to generate valuable data with high-level of representativeness to be transformed into useful information about air pollution. However, the problem of monitoring representativeness has been overlooked. In this respect, a comprehensive methodology to monitor air quality has been developed by this Institute, engaged since 2001 in several projects in China dealing with air quality. The new approach requires rearranging the existing monitoring strategies. In short, saturation monitoring is employed to preliminary assess air pollution and provide spatial resolution over the study area. Automatic monitoring is reduced to a minimum to make time-related data available. The information so-measured with high degree of both spatial and temporal resolution, are completed by statistical and mathematical modelling to generate data interpretation schemes. This methodology extensively tested in China during these years has been found to be very useful for macro/micro-designing emission and air quality monitoring networks, apportioning emission sources, assessing spatial representativeness of measurements, and evaluating spatial frequency distributions of air pollutants. Case-studies of Suzhou, Lanzhou and Beijing are presented to discuss these findings.