AS3.18

The emission of greenhouse gases and the resulting global warming is one of the most important and challenging issues of the 21^st century. Carbon dioxide is one of the major contributors to the greenhouse effect and its atmospheric abundance has growing constantly since the beginning of the industrialization. The isotope ratios n(¹³C)/n(¹²C) and n(¹⁸O)/n(¹⁶O) are important tools for studying the impact of anthropogenic CO₂. Usually, isotopic compositions of CO₂ are reported as δ-values, that express isotope ratios relative to an artifact based on a fossil calcite called VPDB. This relative VPDB scale was necessary, since absolute and SI-traceable isotope ratios of CO₂ are currently not available, neither by isotope ratio mass spectrometry (IRMS) nor by optical isotope ratio spectroscopy (OIRS). In this study we present a potential way of deriving absolute carbon and oxygen isotope ratios of carbon dioxide via IRMS based on the gravimetric mixture approach. Besides practical improvements like an air buoyancy correction scheme for masses of gases, we show first results applying our method which demonstrate its feasibility, limitations, and achievable uncertainties. Also, we show the mathematics behind our approach and discuss further improvements and applications. Furthermore, we show how these absolute ratios can be used in field applications by OIRS methods including a new approach on OIRS uncertainty assessments according to the GUM. For this contribution we report on our recent results within in the European metrology research projects SIRS (16ENV06). and STELLAR (19ENV05).

How to cite: Flierl, L., Braden-Behrens, J., Nwaboh, J., Rienitz, O., Werhahn, O., and Ebert, V.: Towards SI-traceable Isotope Ratios of Greenhouse Gases, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16568, https://doi.org/10.5194/egusphere-egu21-16568, 2021.

Deploying a dense network of sensors around emitting industrial facilities allows to detect and quantify possible CH₄ leaks and monitor the emissions continuously. Designing such a monitoring network with highly precise instruments is limited by the elevated cost of instruments, requirements of power consumption and maintenance. Low cost and low power metal oxide sensor could come handy to be an alternative to deploy this kind of network at a fraction of the cost with satisfactory quality of measurements for such applications.

Recent studies have tested Metal Oxide Sensors (MO_x) on natural and controlled conditions to measure atmospheric methane concentrations and showed a fair agreement with high precision instruments, such as those from Cavity Ring Down Spectrometers (CRDS). Such results open perspectives regarding the potential of MOx to be employed as an alternative to measure and quantify CH₄ emissions on industrial facilities. However, such sensors are known to drift with time, to be highly sensitive to water vapor mole fraction, have a poor selectivity with several known cross-sensitivities to other species and present significant sensitivity environmental factors like temperature and pressure. Different approaches for the derivation of CH₄ mole fractions from the MO_x signal and ancillary parameter measurements have been employed to overcome these problems, from traditional approaches like linear or multilinear regressions to machine learning (ANN, SVM or Random Forest).

Most studies were focused on the derivation of ambient CH₄ concentrations under different conditions, but few tests assessed the performance of these sensors to capture CH₄ variations at high frequency, with peaks of elevated concentrations, which corresponds well with the signal observed from point sources in industrial sites presenting leakage and isolated methane emission. We conducted a continuous controlled experiment over four months (from November 2019 to February 2020) in which three types of MOx Sensors from Figaro® measured high frequency CH₄ peaks with concentrations varying between atmospheric background levels up to 24 ppm at LSCE, Saclay, France. We develop a calibration strategy including a two-step baseline correction and compared different approaches to reconstruct CH₄ spikes such as linear, multilinear and polynomial regression, and ANN and random forest algorithms. We found that baseline correction in the pre-processing stage improved the reconstruction of CH₄ concentrations in the spikes. The random forest models performed better than other methods achieving a mean RMSE = 0.25 ppm when reconstructing peaks amplitude over windows of 4 days. In addition, we conducted tests to determine the minimum amount of data required to train successful models for predicting CH₄ spikes, and the needed frequency of re-calibration / re-training under these controlled circumstances. We concluded that for a target RMSE <= 0.3 ppm at a measurement frequency of 5s, 4 days of training are required, and a recalibration / re-training is recommended every 30 days.

Our study presents a new approach to process and reconstruct observations from low cost CH₄ sensors and highlights its potential to quantify high concentration releases in industrial facilities.

How to cite: Rivera Martinez, R., Santaren, D., Laurent, O., Cropley, F., Mallet, C., Broquet, G., Ramonet, M., Caldow, C., Kumar, P., Fontanier, B., Shah, A., Lienhardt, L., Lozano, M., Lauvaux, T., Rivier, L., Bouchet, C., Juery, C., and Ciais, P.: Reconstruction of high frequency methane peaks from measurements of metal oxide low-cost sensors using machine learning, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16027, https://doi.org/10.5194/egusphere-egu21-16027, 2021.

Commercially available laser-based spectrometers permit continuous field measurements of water vapour (H₂O) stable isotope compositions, yet continuous observations in the Amazon, a region that significantly influences atmospheric hydrological cycles on regional to global scales, are largely missing. In order to achieve accurate on-site observations in such conditions, these instruments will require regular on-site calibration, including for H₂O concentration dependence ([H₂O]-dependence) of isotopic accuracy.

With the aim of conducting accurate continuous δ¹⁸O and δ²H on-site observation in the Amazon rainforest, we conducted a laboratory experiment to investigate the performance and determine the optimal [H₂O]-dependence calibration strategy for two commercial cavity-ring down (CRDS) analysers (L1102i and L2130i models, Picarro, Inc., USA), coupled to our custom-built automated calibration unit. We particularly focused on the rarely investigated performance of the instruments at atmospheric H₂O contents above 35,000 ppm, a value regularly reached at our site.

The later analyser model (L2130i) had better precision and accuracy of δ¹⁸O and δ²H measurements with a less pronounced [H₂O]-dependence compared to the older L1102i. The [H₂O]-dependence calibration uncertainties did not significantly change with calibration intervals from 28 h up to 196 h, suggesting that one [H₂O]-dependence calibration per week for the L2130i and L1102i analysers is enough. This study shows that with both CRDS analysers, correctly calibrated, we should be able to discriminate natural diel, seasonal and interannual signals of stable water vapour isotopes in a tropical rainforest environment.

How to cite: Komiya, S., Kondo, F., Moossen, H., Seifert, T., Schultz, U., Geilmann, H., Walter, D., and Lavric, J.: Laboratory evaluation of water vapour concentration dependence of commercial water vapour isotope cavity ring-down spectrometers for continuous onsite atmospheric measurements in the Amazon rainforest, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15424, https://doi.org/10.5194/egusphere-egu21-15424, 2021.

The long-term monitoring of reactive gases, such as NO₂, provides significant challenges for the development of gas standards that can demonstrate fit-for-purpose stability and accuracy.  Over the last fifteen years the BIPM’s primary gas facility for the dynamic production of mixtures of nitrogen dioxide in nitrogen, operating over the range (1 μmol/mol to 15 μmol/mol) has been shown to operate with a relative standards uncertainty of 0.4%. The system is based on continuous weighing of a permeation tube and on the accurate impurity quantification and correction of the gas mixtures using FT-IR.

The operation of the system has been demonstrated in two international comparisons organized by the CCQM Working Group on Gas Analysis (CCQM-GAWG), in 2009 and 2018, with the former demonstrating the requirement to correct for HNO₃ impurities in gas standards produced in cylinders, and the more recent, the potential for non-linear decay in NO₂ concentration in gas cylinder standards in the first 100 to 150 days following their production.

The CCQM-K74 (2009/2010) was organized, with all cylinders prepared by the one NMI (VSL) with the same surface treatment and characterized for stability and with reference values provided by the BIPM dynamic reference facility. The initial comparison identified small decay rates in the circulated standards, accounted for by the addition of an uncertainty to the reference value, and calculated to have been no more than 0.1 nmol/mol per day loss of NO₂. However, the 2009 comparison did not examine standards maintained by individual participating institutes directly. The protocol of the CCQM-K74.2018 comparison, was modified so that the standards prepared by participating institutes (two per participant), were all directly measured at the BIPM against its dynamic reference facility. The modified protocol, although technically more challenging, has allowed the different decay rates in different cylinder preparations from different institutes to be identified, as well as the time dependence of these days rates.

The work has highlighted the challenges in NO₂ standard development, and that fit-for-purpose standards can be obtained following appropriate protocols. Further development of these protocols is the focus of a number of research programmes, for example  METNO2 and MetroPEMS projects within the EMPIR programmes. Further activities at the BIPM facility are focused on validating the performance of NO₂ dynamic reference systems below 1 μmol/mol and into the nmol/mol range, with the comparison of different dynamic reference systems, in support of future international comparisons and knowledge transfer activities.

How to cite: Flores, E., Idrees, F., Moussay, P., and Wielgosz, R. I.: Long term stability of dynamic reference systems for NO2 atmospheric monitoring, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7233, https://doi.org/10.5194/egusphere-egu21-7233, 2021.

Inland waterway shipping is an important mode of freight transport in Europe with an extended network especially in Germany, e.g. the Rhine and Danube Rivers, and a variety of artificial channels. Nitrogen oxides (NO_x = NO + NO₂), which are also emitted by ships, play an important role in tropospheric chemistry. NO_x contributes to the formation of tropospheric ozone and thus photochemical smog. Moreover, NO_x affects human health and increases the acidification of ecosystems.  Monitoring of NO_x emissions from inland waterway vessels could provide cities that are located along the rivers with valuable information about ship contribution to the pollution.

In this study, ground-based MAX-DOAS (Multi AXis-Differential Optical Absorption Spectroscopy) measurements were performed along the Rhine River. The aim is to derive NO₂ emissions from individual ships. First sensitivity measurements showed that our Tube MAX-DOAS instrument is sensitive enough to detect a NO₂ signal that can be attributed to passing ships. However, finding the optimal measurement mode to determine the emissions proves to be a challenging endeavour.

How to cite: Lukosiunaite, S., Dörner, S., Donner, S., Lauster, B., Beirle, S., Remmers, J., and Wagner, T.: Deriving Nitrogen Oxide emissions from inland waterway vessels using MAX-DOAS measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2808, https://doi.org/10.5194/egusphere-egu21-2808, 2021.

There is a severe lack of air pollution data around the world. This includes large portions of low- and middle-income countries (LMICs), as well as rural areas of wealthier nations as monitors tend to be located in large metropolises. Low cost sensors (LCS) for measuring air pollution and identifying sources offer a possible path forward to remedy the lack of data, though significant knowledge gaps and caveats remain regarding the accurate application and interpretation of such devices.

The Clean Air Monitoring and Solutions Network (CAMS-Net) establishes an international network of networks that unites scientists, decision-makers, city administrators, citizen groups, the private sector, and other local stakeholders in co-developing new methods and best practices for real-time air quality data collection, data sharing, and solutions for air quality improvements. CAMS-Net brings together at least 32 multidisciplinary member networks from North America, Europe, Africa, and India. The project establishes a mechanism for international collaboration, builds technical capacity, shares knowledge, and trains the next generation of air quality practitioners and advocates, including domestic and international graduate students and postdoctoral researchers. 

Here we present some preliminary research accelerated through the CAMS-Net project. Specifically, we present LCS calibration methodology for several co-locations in LMICs (Accra, Ghana; Kampala, Uganda; Nairobi, Kenya; Addis Ababa, Ethiopia; and Kolkata, India), in which reference BAM-1020 PM2.5 monitors were placed side-by-side with LCS. We demonstrate that both simple multiple linear regression calibration methods for bias-correcting LCS and more complex machine learning methods can reduce bias in LCS to close to zero, while increasing correlation. For example, in Kampala, Raw PurpleAir PM2.5 data are strongly correlated with the BAM-1020 PM2.5 (r² = 0.88), but have a mean bias of approximately 12 μg m^-3. Two calibration models, multiple linear regression and a random forest approach, decrease mean bias from 12 μg m^-3 to -1.84 µg m^-3 or less and improve the the r² from 0.88 to 0.96. We find similar performance in several other regions of the world. Location-specific calibration of low-cost sensors is necessary in order to obtain useful data, since sensor performance is closely tied to environmental conditions such as relative humidity. This work is a first step towards developing a database of region-specific correction factors for low cost sensors, which are exploding in popularity globally and have the potential to close the air pollution data gap especially in resource-limited countries. 

How to cite: Westervelt, D., McFarlane, C., McNeill, F., Subramanian, R. (., Giordano, M., and Presto, A.: CAMS-Net: The Clean Air Monitoring and Solutions Network, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13912, https://doi.org/10.5194/egusphere-egu21-13912, 2021.

How to cite: Roy, A., Takahama, S., Nenes, A., Sharma, S., and Goel, A.: The representativeness of ground-based air quality monitoring stations: observation and recommendation from Indian cities, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13197, https://doi.org/10.5194/egusphere-egu21-13197, 2021.

The high level of surface ozone (O₃) concentration is produced from the various complex chemical reaction of oxides of nitrogen (NO_x) and volatile organic compounds (VOCs) under varied meteorological conditions. It has severe effects on human health, vegetation, and as well on infrastructure. The guidelines value for surface ozone level was set 50 ppb for an 8-hours daily average by Indian National Ambient Air Quality Standard (INAAQS, 2009) and World Health Organization (WHO, 2005) for India and worldwide respectively. Identifying the primary source of high ozone events based on observation is challenging. The relationship of the surface measured O3 with carbon monoxide (CO) and water vapor content are useful to identify the possible source of origin for the increased O3 in the stratosphere, regional or local influence.

The continuous observation of O₃, NO_x, CO at 1 minute temporal resolution along with the meteorological parameter (1-hour temporal resolution) were taken during August 2014 to April 2017. All parameters were averaged to 8-hourly for further analysis. The high ozone events were identified based on exceeding the surface ozone concentration limit as discussed above (50 ppb). The relationship of the surface measured O₃ and CO (∆O₃/∆CO) and water vapor were used to explain the source of high ozone such as stratospheric origin and anthropogenic activity. The HYSPLIT’s backward air mass trajectories of the height of 1000 meters for 120 hours were calculated for the site to understand the dispersion of the pollutants. During the high ozone event, the average concentration of O₃, NO_x, and CO was found to be 55.46 ppb, 5.19 ppb, and 0.180 ppb respectively which were lower than the normal conditions. The positive correlation of O₃ with CO (∆O₃/∆CO) and low water vapor mixing ratio (10.0 g/kg) indicate regional or local influence on observed high ozone events.

The high ozone events were explained based on the distribution of the ozone precursors such as NO_x, CO, and meteorological parameters such as relative humidity solar radiation, wind speed, and wind direction at local. The local high ozone concentration was supported by local chemistry such as the low concentration of CO and NO_x. The relationship between O₃ and CO was used to explain the source of high ozone events.

How to cite: K. Sagar, V., Asuri, L. K., P. Kanawade, V., and K. Nayak, R.: Ozone chemistry during high ozone event at semi-urban region, Shadnagar, in Southern India, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12787, https://doi.org/10.5194/egusphere-egu21-12787, 2021.

Volatile Organic Compounds (VOCs) play a key role in the atmospheric pollution, especially as they are precursors of secondary pollutants (ozone, secondary organic aerosols, etc.), and they are key tracers of many sources.. Previous studies in the Mediterranean region, which is a hotspot of air pollution and climate change, have shown a high organic pollution due to VOCs. Moreover, in the Western part of the Mediterranean, few studies have been conducted regarding VOCs despite frequent ozone pollution episodes still occurring especially in Marseille-France. Long-term high quality VOC datasets are therefore crucial for the evaluation of emission inventories used as inputs of the chemical-transport models. The objective of our work is to improve our knowledge regarding VOC source apportionment in Marseille with a focus on emissions related to shipping raising the need of high quality monitoring datasets. For the first time, a one year and half (March 2019 - August 2020) measurement campaign has been conducted in Marseille at an urban area representative site receiving air masses from the harbor. In addition to a large set of instruments, two on-line thermal-desorption gas chromatography flame ionization detector have been used for the continuous hourly measurement of 70 Non-Methane HydroCarbons (NMHCs) from 2 to 16 carbon atoms covering alkanes including IVOCs, alkenes, alkynes, aromatics. Here, we will focus on the metrological aspects of the analytical instruments (traceability, repeatability, etc.), intercomparison of common species measured with both instruments, as well as an intercomparison of several calibration methods developed for IVOC (C10 to C16) measurement. A special attention has been given to the uncertainty estimation following ACTRIS and WMO guidelines.  Finally, we will show an overview of the Positive Matrix Factorization (PMF) model results, applied to a necessarily large robust dataset of observations with the associated uncertainties.

How to cite: Dufresne, M., Salameh, T., Léonardis, T., Gille, G., Lanzi, L., Armengaud, A., and Sauvage, S.: High quality monitoring dataset needed for improving VOC emission knowledge in a Mediterranean port city, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15080, https://doi.org/10.5194/egusphere-egu21-15080, 2021.

In urban areas, a large number of people use public transport systems on a daily basis, and depending on the length of their commute, they spend a considerable amount of time in it. Part of the public transport system runs underground. Even though underground trains are powered by electric traction motors, the accumulation of airborne particles may be of concern due to limited air exchange in underground transport systems.

Initial measurements carried out in previous studies worldwide have shown that the air in a subway train station can be considerably more polluted with particulate matter than the air at a busy road junction. PM10 mass concentrations as high as 120 µg/m³ have been measured at a subway train station in Stuttgart. This is more than double the daily average PM10 limit value of 50 µg/m³ for outside air in Europe.

In order to study particulate matter concentrations in the underground transport system of Berlin (Germany) and potential particle sources, first semester students carried out preliminary measurements in a student project in January 2021. The students were equipped with handheld optical particle counters to study particulate matter levels at various locations of the underground transport system and at roadside station at street level for comparison. In additions, airborne particles were collected by using a single staged impactor, and subsequently analysed for their metal content using Total Reflection X-ray Fluorescence (TXRF) analysis.

The results indicate significantly elevated PM10 levels in underground train stations compared to street levels. Up to 35 times as much iron was found in the air of an underground train station compared to a busy street intersection at Potsdamer Platz. These high levels of iron suggest that a reason for the elevated concentrations of particulate matter in the underground system could be abrasion from wheels and rails.

This preliminary study sets the basis for a more comprehensive investigation of PM sources in public underground transport systems required to evaluate its effect on urban air quality.

How to cite: Crazzolara, C., Lüchtrath, S., Stosnach, H., and Held, A.: Measurements of airborne particles and chemical identification of metal content in a public underground transport system, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13599, https://doi.org/10.5194/egusphere-egu21-13599, 2021.