Analysis and fit of surface CO2 concentrations at a rural site

• Published in: Environmental science and pollution research international 2012-08, Vol.19 (7), p.3015-3027
• Main Authors: Pérez, Isidro A., Sánchez, M. Luisa, García, M. Ángeles, Pardo, Nuria
• Format: Article
• Language: English
• Subjects: Air Pollutants - chemistry; Airborne particulates; Altitude; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Carbon cycle; Carbon dioxide; Carbon Dioxide - chemistry; Circadian Rhythm; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental Monitoring - methods; Models, Statistical; Research Article; Rural areas; Rural Population; Sensitivity analysis; Spain; Statistical analysis; Statistics; Studies; Symmetry; Time Factors; Urban areas; Waste Water Technology; Water Management; Water Pollution Control; Wind
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-012-0813-4

Purpose The impact of CO 2 urban plume in a rural area was investigated by concentrations recorded near surface. Methods CO 2 dry concentrations at three levels near surface were recorded for about 8 months at a rural site. Daily cycles were obtained and directional analysis was made with percentiles. Several functions were used to fit background and plume concentrations and the goodness of fit was evaluated with different statistics, which were also compared. Results Daily cycle showed a difference of around 2 ppm during the night between the lowest (1.8 m) and the highest (8.3 m) levels. Weighting functions of the directional analysis revealed the influence of the Valladolid urban plume. Two regions were established, with local factors prevailing below 3 m s −1 and transport dominating above 6 m s −1 . The best fit was achieved with a quadratic function for the background and a cubic function for the plume due to the lack of symmetry observed. Gamma and Weibull distributions were also successfully used. Some statistics, such as the root mean square error (RMSE), stood out when evaluating the goodness of fit, whilst others were discarded due to their extremely low values and the lack of sensitivity against the functions used. Finally, a comprehensive metric merging several statistics was also tested with slight differences against RMSE.