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Estimates of past emission inventories suggest that toxic heavy metal pollution in Europe was highest in the mid‐1970s for lead and in the mid‐1960s for cadmium, but these previous estimates have not been compared to observations. Here, alpine ice‐cores were used to document cadmium and lead pollution in western Europe between 1890 and 2000. The ice‐core trends show that while lead pollution largely from leaded gasoline reached a maximum in ~1975 as expected, cadmium pollution primarily from zinc smelters peaked in the early‐1980s rather than in ~1965 and was up to fourfold higher than estimated after 1975. Comparisons between ice‐core trends, estimated past emissions, and state‐of‐the‐art atmospheric aerosol transport and deposition modeling suggest that the estimated decreases in cadmium emissions after 1970 were based on overly optimistic emissions reductions from the introduction of pollution control devices and other technological improvements.
American Geophysical Union (AGU)
2020
2006
Calculation of person-weighted average concentrations of NO2, PM10 and PM 2,5 in Oslo for 1992-2002. NILU PP
2005
Calculation of person-weighted average concentrations of NO2, PM10 and PM2,5 in Oslo for 1992-2002. NILU F
2005
2005
Calculation of pseudo PM2.5 annual mean concentrations in Europe based on annual mean PM10 concentrations and other supplementary data. ETC/ACC Technical Paper, 2010/9
2011
Calculations of personal exposure to particulate matter in urban areas. Developments in environmental science, 6
2007
Calculations of Radiative Forcing from Ozone Change. NATO Science Series, vol. 557
2000
Calibration and application of a passive air sampler (XAD-PAS) for volatile methyl siloxanes. NILU PP
2013
2013
Calibration and assessment of electrochemical low-cost sensors in remote alpine harsh environments
This work presents results from an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. Our study was conducted at the Col Margherita Observatory (2543 m above sea level), in the Italian Eastern Alps. The sensor system mounts three commercial low-cost O3/NO2 sensors that have been calibrated before field deployment against a laboratory standard (Thermo Scientific; 49i-PS), calibrated against the standard reference photometer no. 15 calibration scale of the World Meteorological Organization (WMO). Intra- and intercomparison between the sensors and a reference instrument (Thermo Scientific; 49c) have been conducted for 7 months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. We showed that it is possible to reduce the bias of one LCS by using the average coefficient values of another LCS working in tandem, suggesting a way forward for the development of remote field calibration techniques. We showed that it is possible reconstruct the environmental ozone concentration during the loss of reference instrument data in situations caused by power outages. The evaluation of the analytical performances of this sensing system provides a limit of detection (LOD) <5 ppb (parts per billion), limit of quantification (LOQ) <17 ppb, linear dynamic range (LDR) up to 250 ppb, intra-Pearson correlation coefficient (PCC) up to 0.96, inter-PCC >0.8, bias >3.5 ppb and ±8.5 at 95 % confidence. This first implementation of a LCS system in an alpine remote location demonstrated how to obtain valuable data from a low-cost instrument in a remote environment, opening new perspectives for the adoption of low-cost sensor networks in atmospheric sciences.
2021
Calibration of CO, NO2, and O3 Using Airify: A Low-Cost Sensor Cluster for Air Quality Monitoring
During the last decade, extensive research has been carried out on the subject of low-cost sensor platforms for air quality monitoring. A key aspect when deploying such systems is the quality of the measured data. Calibration is especially important to improve the data quality of low-cost air monitoring devices. The measured data quality must comply with regulations issued by national or international authorities in order to be used for regulatory purposes. This work discusses the challenges and methods suitable for calibrating a low-cost sensor platform developed by our group, Airify, that has a unit cost five times less expensive than the state-of-the-art solutions (approximately €1000). The evaluated platform can integrate a wide variety of sensors capable of measuring up to 12 parameters, including the regulatory pollutants defined in the European Directive. In this work, we developed new calibration models (multivariate linear regression and random forest) and evaluated their effectiveness in meeting the data quality objective (DQO) for the following parameters: carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). The experimental results show that the proposed calibration managed an improvement of 12% for the CO and O3 gases and a similar accuracy for the NO2 gas compared to similar state-of-the-art studies. The evaluated parameters had different calibration accuracies due to the non-identical levels of gas concentration at which the sensors were exposed during the model’s training phase. After the calibration algorithms were applied to the evaluated platform, its performance met the DQO criteria despite the overall low price level of the platform.
MDPI
2021
2023
2009
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2012
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2011