The Berkeley Environmental Air-quality and CO.sub.2 Network: field calibrations of sensor temperature dependence and assessment of network scale CO.sub.2 accuracy

The majority of global anthropogenic CO.sub.2 emissions originate in cities. We have proposed that dense networks are a strategy for tracking changes to the processes contributing to urban CO.sub.2 emissions and suggested that a network with â¼ 2 km measurement spacing and â¼ 1 ppm node-to-node precision would be effective at constraining point, line, and area sources within cities. Here, we report on an assessment of the accuracy of the Berkeley Environmental Air-quality and CO.sub.2 Network (BEACO.sub.2 N) CO.sub.2 measurements over several years of deployment. We describe a new procedure for improving network accuracy that accounts for and corrects the temperature-dependent zero offset of the Vaisala CarboCap GMP343 CO.sub.2 sensors used. With this correction we show that a total error of 1.6 ppm or less can be achieved for networks that have a calibrated reference location and 3.6 ppm for networks without a calibrated reference.