Bias adjustment of spatially-distributed wireless pollution sensors for environmental studies in India

A pollution data collection exercise was conducted in Hyderabad, India in February, 2012. Fifteen bespoke Carbon Monoxide (CO) monitors were deployed across a small section of a busy highway to collect data for an urban environmental engineering study targeting traffic-generated pollution. The monitors were used to record CO concentrations and temperature; however, in spite of the fact that the monitors were calibrated in advance of deployment, interpretation of the data collected has proved to be challenging. This paper reports the findings of the experiment and proposes a bias-adjustment separation technique that provides a consensual baseline for all the monitors. The result is that spatial variation in the distribution of CO can be studied at snapshots of time. Moreover, the cross-correlations between sensors can be reliability extracted after the bias adjustment.