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2005
In this report, we investigate the relative expanded uncertainty (REU) formula for comparing low-cost sensors (microsensors) and reference measurements. The purpose of the REU formula is to check if microsensor measurements follow the data quality objective (DQO) of the European Air Quality Directive 2008/50/EC to be considered equivalent to a reference instrument. The project aimed to obtain a good understanding of the REU formula for its proper use in current and future projects involving microsensors.
NILU
2020
Air pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited accuracy of the PM detector, the measurement data are refined using a two-stage procedure that involves elimination of the non-physical signal spikes followed by a non-linear correction of the responses using a multiplicative surrogate model. The correction layer is derived from the sparse and non-uniform calibration data, i.e., a combination of the measurements from the PM monitoring station and the sensor obtained in the same location over a specified (relatively short) interval. The device and the method have been both demonstrated based on the data obtained during three measurement campaigns. The proposed correction scheme improves the fidelity of PM measurements by around two orders of magnitude w.r.t. the responses for which the post-processing has not been considered. Performance of the proposed surrogate-assisted technique has been favorably compared against the benchmark approaches from the literature.
Elsevier
2022
2015
Dichloromethane (CH2Cl2) and perchloroethylene (C2Cl4) are chlorinated very short lived substances (Cl‐VSLS) with anthropogenic sources. Recent studies highlight the increasing influence of such compounds, particularly CH2Cl2, on the stratospheric chlorine budget and therefore on ozone depletion. Here, a multiyear global‐scale synthesis inversion was performed to optimize CH2Cl2 (2006–2017) and C2Cl4 (2007–2017) emissions. The approach combines long‐term surface observations from global monitoring networks, output from a three‐dimensional chemical transport model (TOMCAT), and novel bottom‐up information on prior industry emissions. Our posterior results show an increase in global CH2Cl2 emissions from 637 ± 36 Gg yr−1 in 2006 to 1,171 ± 45 Gg yr−1 in 2017, with Asian emissions accounting for 68% and 89% of these totals, respectively. In absolute terms, Asian CH2Cl2 emissions increased annually by 51 Gg yr−1 over the study period, while European and North American emissions declined, indicating a continental‐scale shift in emission distribution since the mid‐2000s. For C2Cl4, we estimate a decrease in global emissions from 141 ± 14 Gg yr−1 in 2007 to 106 ± 12 Gg yr−1 in 2017. The time‐varying posterior emissions offer significant improvements over the prior. Utilizing the posterior emissions leads to modeled tropospheric CH2Cl2 and C2Cl4 abundances and trends in good agreement to those observed (including independent observations to the inversion). A shorter C2Cl4 lifetime, from including an uncertain Cl sink, leads to larger global C2Cl4 emissions by a factor of ~1.5, which in some places improves model‐measurement agreement. The sensitivity of our findings to assumptions in the inversion procedure, including CH2Cl2 oceanic emissions, is discussed.
American Geophysical Union (AGU)
2020
2008
A systematic Approach to Air Quality Management in Asian Cities: Examples from the Urbair Cities. NILU F
2000
1999
2022
2024
2011
2005
2006
Top-down approaches, such as atmospheric inversions, are a promising tool for evaluating emission estimates based on activity-data. In particular, there is a need to examine carbon budgets at subnational scales (e.g. state/province), since this is where the climate mitigation policies occur. In this study, the subnational scale anthropogenic CO2 emissions are estimated using a high-resolution global CO2 inverse model. The approach is distinctive with the use of continuous atmospheric measurements from regional/urban networks along with background monitoring data for the period 2015–2019 in global inversion. The measurements from several urban areas of the U.S., Europe and Japan, together with recent high-resolution emission inventories and data-driven flux datasets were utilized to estimate the fossil emissions across the urban areas of the world. By jointly optimizing fossil fuel and natural fluxes, the model is able to contribute additional information to the evaluation of province–scale emissions, provided that sufficient regional network observations are available. The fossil CO2 emission estimates over the U.S. states such as Indiana, Massachusetts, Connecticut, New York, Virginia and Maryland were found to have a reasonable agreement with the Environmental Protection Agency (EPA) inventory, and the model corrects the emissions substantially towards the EPA estimates for California and Indiana. The emission estimates over the United Kingdom, France and Germany are comparable with the regional inventory TNO–CAMS. We evaluated model estimates using independent aircraft observations, while comparison with the CarbonTracker model fluxes confirms ability to represent the biospheric fluxes. This study highlights the potential of the newly developed inverse modeling system to utilize the atmospheric data collected from the regional networks and other observation platforms for further enhancing the ability to perform top-down carbon budget assessment at subnational scales and support the monitoring and mitigation of greenhouse gas emissions.
2023
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