Urban Air Quality Monitoring Network Research Articles

Analysis of an anomalous case of high air pollution concentration in Turin after a foehn event

A case of unusually high concentrations of some urban air pollutants (CO, NO, SO2) in Turin (Northwestern Italy) is presented. This episode occurred during the late afternoon of 7 November 1995. This day was characterised by a strong northern foehn event in the morning, which followed the passage of a cold front. The analysis has been carried out by means of data derived from the urban and suburban air quality monitoring networks, of meteorological data (wind velocity, temperature and relative humidity) from the same network and from other networks in the region, and of the output of the numerical model LAMBO (operatively used by the Regional Meteorological Service of Emilia Romagna). The analysis of meteorological data appears to be in good correlation with the distribution of the air pollutant concentrations; in particular, the high concentrations observed in the late afternoon are due to a strong thin inversion layer near the ground, developing immediately after the sudden end of the foehn episode.

Optimal estimators for ambient air quality levels

Abstract Procedures to estimate missing data, determine extrema, and derive uncertainties for data collected in ambient air monitoring networks are presented. The optimal linear estimators used obtain unbiased, minimum variance results based on the temporal and spatial correlation of the data and estimates of sample uncertainty. The first estimator interpolates missing data. The second estimator derives extrema, e.g. minimum and maximum concentrations, from the completed data set. Together the estimators can be used to check the validity of monitored observations, identify outliers, and estimate regional and local components of pollutant levels. The estimators are evaluated using data collected in urban air quality monitoring networks in Houston, Philadelphia and St Louis.

Interactive design of urban level air quality monitoring network

An interactive optimization method for designing an air quality monitoring network in an urban area is proposed. The main purpose is to determine representative areas of monitoring stations rather than their precise locations. Two topologies are introduced to define similarities among pre-divided uniform meshes. The first is derived from the differences of long-term averages of pollutant concentrations between every two meshes and used in the Ward method clustering. The second is obtained by the cross-impacts between pairs of meshes and used as a constraint in the clustering process. Participation of specialists in the optimization process is allowed in such a way that they can modify the second topology by taking account of economic and physical conditions as well as inaccuracy of simulation models. This technique is applied to the NO x monitoring network of Kyoto, Japan.