| Autor: |
Zamora ML; University of Connecticut Health Center, Department of Public Health Sciences UConn School of Medicine, 263 Farmington Avenue, Farmington, CT, USA 06032-1941.; Johns Hopkins University Bloomberg School of Public Health, Environmental Health and Engineering 615 N Wolfe St, Baltimore, MD, USA 21205-2103.; SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University, New Haven, CT, USA 06520., Buehler C; SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University, New Haven, CT, USA 06520.; Yale University, Chemical and Environmental Engineering, PO Box 208286, New Haven, CT, USA 06520., Datta A; Johns Hopkins University Bloomberg School of Public Health, Department of Biostatistics 615 N. Wolfe Street, Baltimore, MD, USA 21205-2103., Gentner DR; SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University, New Haven, CT, USA 06520.; Yale University, Chemical and Environmental Engineering, PO Box 208286, New Haven, CT, USA 06520., Koehler K; Johns Hopkins University Bloomberg School of Public Health, Environmental Health and Engineering 615 N Wolfe St, Baltimore, MD, USA 21205-2103.; SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University, New Haven, CT, USA 06520. |
| Abstrakt: |
Low-cost sensors are often co-located with reference instruments to assess their performance and establish calibration equations, but limited discussion has focused on whether the duration of this calibration period can be optimized. We placed a multipollutant monitor that contained sensors that measure particulate matter smaller than 2.5 μm (PM 2.5 ), carbon monoxide (CO), nitrogen dioxide (NO 2 ), ozone (O 3 ), and nitric oxide (NO) at a reference field site for one year. We developed calibration equations using randomly selected co-location subsets spanning 1 to 180 consecutive days out of the 1-year period and compared the potential root mean square errors (RMSE) and Pearson correlation coefficients (r). The co-located calibration period required to obtain consistent results varied by sensor type, and several factors increased the co-location duration required for accurate calibration, including the response of a sensor to environmental factors, such as temperature or relative humidity (RH), or cross-sensitivities to other pollutants. Using measurements from Baltimore, MD, where a broad range of environmental conditions may be observed over a given year, we found diminishing improvements in the median RMSE for calibration periods longer than about six weeks for all the sensors. The best performing calibration periods were the ones that contained a range of environmental conditions similar to those encountered during the evaluation period (i.e., all other days of the year not used in the calibration). With optimal, varying conditions it was possible to obtain an accurate calibration in as little as one week for all sensors, suggesting that co-location can be minimized if the period is strategically selected and monitored so that the calibration period is representative of the desired measurement setting. |
