In this work, aerosol absorption and scattering properties were investigated to gather additional information on aerosol types and sources. During a one-year campaign in Milan (Italy), a multi-wavelength aethalometer and a nephelometer were operated in parallel. Scattering coefficients are in general scarcely available at urban sites and this was the very first dataset for Milan and, more generally, for an urban site in the Po valley which is a wellknown pollution hot-spot in Europe. Time patterns of the absorption and scattering coefficients throughout the year were investigated and Absorption/Scattering & Aring;ngstrom Exponents (AAE and SAE, respectively) were also computed to relate the optical properties to fossil vs. wood fuel combustion emission sources and to small vs. large particle size. The average daily trends for the absorption coefficients reflected the behaviour of the sources, with peaks in the morning due to traffic emissions observed in all seasons, and high values during the night as a consequence of lower mixing heights and, in winter, of domestic heating emissions, too. To gain knowledge about aerosol types and origin an innovative cluster analysis approach using AAE and SAE led to the identification of different aerosol types; this is an easy-to-implement approach which could be applied in monitoring networks for near-real time aerosol types identification. Moreover, episodes affected by specific aerosol types (i.e., fire event, desert dust air mass transport...) were singled out applying a more refined approach combining five intensive optical parameters.

Airborne particulate matter is increasingly recognized as a hazard for developmental health. While epidemiological studies associate PM₁₀ prenatal exposure and adverse outcomes (including low birth weight and preterm birth), experimental evidence clarifying biological plausibility remains limited, especially for complex PM mixtures collected in non-urban settings. Air-quality-related developmental risks in rural areas interested by PM pollutions are underestimated. In this context, our study aimed to assess the developmental toxicity of PM₁₀ extracts collected at a rural Po Valley site, using a sensitive vertebrate embryo model. We exposed Xenopus laevis embryos to extracts of daytime and nighttime PM₁₀ collected over two weeks (March 2022) and evaluated lethality, teratogenicity and developmental progression with the Refined Frog Embryo Teratogenesis Assay-Xenopus (R-FETAX). In parallel, PM₁₀ filters were chemically characterized (mass, major ions, carbon fractions, and multiple elements), allowing us to model links between developmental outcomes and specific PM components. To provide a conventional toxicological benchmark, extracts were also tested in A549 human lung epithelial cells for cytotoxicity and genotoxicity. Our results show that, despite the absence of lethality or gross malformations, some PM₁₀ extracts induced statistically significant developmental delays. Modelling revealed correlations between delays and PM₁₀ mass as well as several measured analytes, with Zn and Cu displaying the clearest dose-dependent associations. Embryonic development detected subtle effects of low-level PM₁₀ exposure that were not captured by standard cytotoxicity/genotoxicity endpoints in A549 cells under the tested conditions. Collectively, these findings support the utility of a developmental model for mixture-based particulate toxicology evaluation.

Mineral desert dust is a major contributor to total atmospheric particulate matter1. Desert dust outbreaks degrade air quality and can pose adverse health effects2, including asthma exacerbation3 and increased mortality4. At some European locations, there has been a rise in the intensity and frequency of transported dust outbreaks from deserts in recent decades5-9. However, it remains unclear whether this increase is consistent across Europe and whether desertification and aridity or shifts in atmospheric circulation are the main drivers behind this rise. Here we compile a database of daily dust metal concentrations from European sites, establishing robust elemental ratios for transported dust. Using this database, we develop a machine learning model to estimate daily PM10 (particulate matter smaller than 10 μm) dust concentrations from 2012 to 2021, ranging from 2.09 ± 1.05 μg m-3 across northern and central Europe to 5.28 ± 2.65 μg m-3 across the south. In southern Europe, residents are exposed to transported dust events averaging 9.68 ± 4.85 μg m-3, linked to a 0.67 ± 0.02% rise in daily mortality. Intensified dust intrusions over the past decade are linked to shifts in atmospheric circulation. Data from an Alpine ice core record shows a 110% increase in dust concentrations since pre-industrial times, mostly associated with North African desertification. As climate change accelerates land degradation and affects weather patterns, worsening dust pollution may pose increasing risks to public health and air quality goals.

New particle formation (NPF) is a crucial process that significantly affects the number of atmospheric particles, forming a substantial portion of the total aerosol population. Therefore, it has important implications for both human health and climate. While extensive research has been conducted in rural areas of the Po Valley, Italy, there is a substantial lack of continuous measurements with state-of-the-art instruments in Milan, one of the most industrialized and densely populated cities in the region. This study aims to address this gap by analysing one year of detailed particle number size distribution measurements between 1.2 and 480 nm at an urban background site in Milan. These data were used to examine the occurrence and characteristics of NPF and to identify how the meteorological and air pollution conditions affect it. We show that a cleaner atmosphere, meaning lower concentrations of air pollutants and lower condensation sink, and a higher ventilation promote NPF. Detailed modelling of the air masses history further revealed that a longer residence time in the Po Valley and a greater exposure to anthropogenic emissions inhibit NPF. Furthermore, we show that strong winds, particularly from the northwest sector (e.g., Foehn winds), facilitate NPF, likely by reducing the condensation sink for precursor vapours. This locates Milan among the urban sites where atmospheric cleaning enhances NPF, providing insights for urban air quality management.

In today's rapidly evolving society, the sources of atmospheric particulate matter (PM) emissions are shifting significantly. Stringent regulations on vehicle tailpipe emissions, in combination with a lack of control of non-exhaust vehicular emissions, have led to an increase in the relative contribution of non-exhaust PM in Europe. This study analyzes the spatial distribution, temporal trends, and impacts of brake wear PM pollution across Europe by modeling copper (Cu) concentrations at a high spatial resolution of ∼250 m which is a key tracer of brake-wear emissions. We integrated coarse-resolution brake-wear Cu from CAMx chemical transport model and high-resolution land use data into a random forest (RF) model to predict Cu concentrations at ∼250 m over whole of continental Europe. The RF model was trained using an unprecedented dataset of over 50,000 daily Cu measurements from 152 sites. It corrected CAMx underestimation and downscaled Cu to a higher spatial resolution. In validation, the model showed robust spatial and temporal prediction with good Pearson's correlation coefficients of 0.6 and 0.7, respectively. We generated 10 years (2010-2019) of daily Cu concentrations over Europe, revealing spatial patterns aligned with urbanization and road networks, with peaks in cities and lower values in rural areas. Temporal trends reveal that Cu concentrations generally peak on weekdays and in winter. Despite a decline in PM across Europe over decades, Cu concentrations showed no decrease in many cities from 2010 to 2019. Cu levels are strongly correlated with population density with more than 12 million Europeans exposed to levels exceeding 40 ng/m3, equivalent to around 1 μg/m3 of total PM10 from brake wear. Our findings highlight the need for expanded metal measurement for non-exhaust tracers for a better understanding of the health relevance of PM composition including Cu, and more effective regulations of non-exhaust PM emissions as included in EURO 7 vehicles.

C-14 measurements on the carbonaceous fractions of atmospheric aerosol are an important tool for source apportionment. In this paper, a C-14-based source apportionment study was carried out on samples collected during winter 2021 at an urban background site in the Po Valley, one of the main pollution hot-spot areas in Europe. The samples were prepared using MISSMARPLE (MIlan Small-SaMple Automated Radiocarbon Preparation LinE for atmospheric aerosol), a recently developed sample preparation line for C-14 measurements on atmospheric aerosol carbon fractions, specifically targeting small samples (about 50 mu gC). C-14-based source apportionment was performed separately for elemental carbon (EC) and organic carbon (OC), after suitable optimization of model parameters. As this is the first source apportionment study using MISSMARPLE-prepared samples, our results were compared with other tracers and source apportionment outcomes obtained through parallel methodologies, demonstrating strong correlations in all tests (R > 0.87). The source apportionment results showed that fossil fuel combustion remains the main source of EC in the investigated area (60%), while modern contributions generally dominate the OC fraction (66%). However, some episodes were identified where fossil fuel combustion was the dominant contributor also to the OC fraction (up to 66%). During these episodes, the importance of secondary OC formation from fossil fuel combustion was highlighted through the EC-tracer approach. Thus, fossil fuel combustion is still a significant source of carbonaceous aerosol in the Po Valley during the winter. Both primary emissions and gaseous precursors must be targeted by future abatement policies to effectively reduce pollution in the area.

Soot aerosol generated from the incomplete combustion of biomass and fossil fuels is a major light-absorber; however its spectral optical properties for varying black carbon (BC) and brown carbon (BrC) content remain uncertain. In this study, soot aerosols with varying maturity and composition, i.e. elemental-to-total-carbon ratio (EC/TC), have been studied systematically in a large simulation chamber to determine their mass absorption, scattering, and extinction cross sections (MAC, MSC, MEC); single-scattering albedo (SSA); and absorption and scattering & Aring;ngstr & ouml;m exponents (AAE, SAE). The MAC, MEC, SSA, and AAE show a variability between the different types of soot with varying EC/TC ratios. The MAC (MEC) at 550 nm increases for increasing EC/TC, with values of 1.0 (1.4) m2 g-1 for EC/TC = 0.0 (BrC-dominated soot) and 4.6 (5.1) m2 g-1 for EC/TC = 0.79 (BC-dominated soot). The AAE and SSA (550 nm) decrease from 3.79 and 0.29 (EC/TC = 0.0) to 1.27 and 0.10 (EC/TC = 0.79). Combining present results for soot from propane combustion with literature data for flame soot from diverse fuels supports a generalised exponential relationship between particle EC/TC and its MAC and AAE values (MAC550=(1.3 +/- 0.05) e(1.8 +/- 0.1)ECTC; AAE=(0.73 +/- 0.12)+(3.29 +/- 0.12) e-(2.32 +/- 0.30)ECTC), which represents the optical continuum of spectral absorption for soot with varying maturity. From this, it is possible to extrapolate a MAC of 7.9 and 1.3 m2 g-1 (550 nm) and an AAE (375-870 nm) of 1.05 and 4.02 for pure EC (BC-like) and pure OC (BrC-like) soot. The established relationship can provide a useful parameterisation for models to estimate the absorption from combustion aerosols and their BC and BrC contributions.

We introduce a new instrument to measure spectral light absorption by aerosol particles. BLAnCA (Broadband Light Analyzer of Complex Aerosol) is an automatic laboratory instrument for offline measurement of aerosol collected on suitable media. BLAnCA is equipped with a white light source and a high-resolution spec-trometer, and measures in the range between 375 and 1000 nm with a spectral resolution of 5 nm. This allows for the determination of fine structure of the ab-sorption properties of a sampled aerosol, which can lead to improvement in the robustness and scope of source apportionment and the evaluation of climate-relevant properties such as the aerosol mass absorption cross-section. The new instrument has been validated against a multi-wavelength absorbance analyzer, obtaining an agreement of up to 99 % between absorption coefficient measurements. The absorption coefficient limit of detection for BLAnCA has been estimated at 1.20 Mm-1 (2.70 Mm-1 ) for standard EU (EPA) sampling conditions, corresponding to an elemental carbon detection limit of about 1.3 mu g cm-2 , if a mass absorption cross-section of 4.7 m 2 g-1 at 1000 nm is considered. The instrument has been used to characterize several types of aerosol samples, each with its own distinct absorp-tion features, which show the potential for BLAnCA to identify different kinds of particulate matter based on their optical properties.

The joint use of hourly resolution sampling and analyses with accelerated ion beams such as with the particle-induced X-ray emission (PIXE) technique has allowed the measurement of hourly temporal patterns of particulate matter (PM) composition at many sites in different parts of the world. The demand within the scientific community for this type of analysis has been continuously increasing in recent years, but hourly resolution samplers suitable for PIXE analysis have been discontinued and/or suffer from some technical limitations. In this framework, a new hourly sampler, STRAS (Size- and Time-Resolved Aerosol Sampler), was developed for the collection of PM10, PM2.5 or PM1. It allows automatic sequential sampling of up to 168 hourly samples (1 week), and it is mechanically robust, compact and easily transportable. To increase PIXE sensitivity, each sample is concentrated on a small surface area on a polycarbonate membrane. Comparison between the elemental concentrations retrieved by STRAS samples and samples collected using a standard sequential sampler operated in parallel shows very good agreement; indeed, if both the samplers use the same kind of membrane, the concentrations of all detected elements are in agreement within 10 %.

Tire and road wear particles (TRWP) have emerged as air quality hazardous matters and significant sources of airborne microplastic pollution, contributing to environmental and human health concerns. Regulatory initiatives, such as the Euro 7 standards, emphasize the urgent need for standardized methodologies to quantify TRWP emissions accurately. Despite advancements in measuring tire abrasion rates, critical gaps persist in the characterization of airborne TRWP, particularly regarding the influence of collection system design and influencing parameters on measurement accuracy and repeatability. This study addresses these challenges by designing a controlled methodological framework that aims to minimize the influencing effects and ensure comparability in TRWP emission quantification results. At the German Aerospace Center (DLR) dynamometer testbench in Stuttgart, Germany, a methodical framework was established to ensure the repeatability and comparability of TRWP measurements, incorporating standardized tire testing conditions and particulate matter sampling methodologies. The results indicated that the DLR® housing-based system with an encapsulated tire exhibited higher particle concentrations in fine and ultrafine fractions compared to the nozzle-based system. Statistical analyses following ISO standards confirmed that the DLR® housing system demonstrated higher measurement consistency, with lower deviations in repeated tests. In contrast, the nozzle system showed higher deviations, particularly in the PM10 fraction (i.e., particles with aerodynamic diameter less than 10 μm), suggesting potential particle losses and lower collection efficiency. These findings emphasize the importance of designing measurement methodologies that minimize the influence of external factors and improve the repeatability of TRWP characterization. By establishing a standardized and comparable framework that isolates tire-road interaction effects from environmental and surface variability, this study enhances the accuracy of TRWP emission measurements. The proposed methodology aims to serve as a robust foundation for regulatory frameworks, offering valuable insights into the optimization of current TRWP measurement techniques.

Measuring the elemental composition of atmospheric particulate matter (PM) can provide useful information on the adverse effects of PM and facilitate the identification of emission sources. Carrying out these measurements at a high temporal resolution (1 h or less) allows describing the fast processes to which aerosol particles are subjected in the atmosphere, leading to a better characterization of the emissions. Energy dispersive X-ray fluorescence (ED-XRF) spectrometry is one of the most widespread techniques used to determine the elemental composition of PM. In recent years, new systems known as online XRF spectrometers have been developed to provide real-time measurements of the PM elemental concentration at a high temporal resolution. Among these advanced instruments, the Xact® 625i Ambient Metals Monitor by Cooper Environmental (USA) performs in situ automated measurements with a user-selected temporal resolution ranging from 15 to 240 min. In this study, an Xact® 625i monitor equipped with a PM10 inlet was deployed for nearly 6 months (July–December 2023) in Milan (Po Valley, Italy) at a monitoring station of the Lombardy Regional Agency for Environmental Protection (ARPA Lombardia). The instrument was configured to quantify 36 elements, ranging from Al to Bi, with 1 h temporal resolution in the PM10 fraction. The objective of the study was to verify the correct functioning of the instrument and to evaluate the quality and robustness of the data produced. Xact® 625i data were aggregated to 24 h daily means and then compared to 24 h PM10 filter data retrieved by ARPA Lombardia in the same station and analyzed offline for the elemental concentration with a benchtop ED-XRF spectrometer. The intercomparison focused on 16 elements (Al, Si, S, Cl, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Br, Sr, and Pb) whose concentrations were consistently above their minimum detection limits (MDLs) for both online and offline techniques. The results of the intercomparison were satisfying, showing that the Xact® 625i elemental concentrations were highly correlated to the offline ED-XRF analyses (R2 ranging from 0.67 to 0.99 and slopes ranging from 0.79 to 1.3, with only a few elements showing slopes up to 1.70).

Abstract. The joint use of hourly resolution sampling and analyses with accelerated ion beams such as Particle Induced X-ray Emission (PIXE) technique has allowed the measurement of hourly temporal patterns of particulate matter (PM) composition at many sites in different parts of the world. The demand within the scientific community for this type of analysis has been continuously increasing in recent years, but hourly resolution samplers suitable for PIXE analysis are now discontinued and/or suffer from some technical limitations. In this framework, a new hourly sampler, STRAS (Size and Time Resolved Aerosol Sampler), was developed for the collection of PM10, PM2.5 or PM1. It allows automatic sequential sampling of up to 168 hourly samples (1 week), it is mechanically robust, compact, and easily transportable. To increase PIXE sensitivity, each sample is concentrated on a small surface area on a polycarbonate membrane. The comparison between the elemental concentrations retrieved by STRAS samples and samples collected using a standard sequential sampler operated in parallel shows a very good agreement; indeed, if both the samplers use the same kind of membrane, the concentrations of all detected elements are in agreement within 10 %.

In this paper, we applied the Dispersion Normalised Positive Matrix Factorisation (DN-PMF) approach recently proposed in the literature to provide a more realistic picture of the relative importance of emission strength vs. atmospheric dispersion conditions. The disentanglement of such effects is of great concern in pollution hot spots like the Po Valley (Italy), where particulate matter limit values are exceeded despite the existing abatement measures. To explore the potentiality of the DN-PMF approach - still scarcely applied in the literature - a well -chemically characterised PM1 (atmospheric particles with aerodynamic diameter <1 mu m) dataset comprising samples collected at different time resolutions at an urban background site (Bologna) in the southern Po Valley was used. Indeed, it is well known that shallow mixing layers promote pollutant accumulation but this obser-vation is not enough to exclude an enhancement of emission strength which could be tackled by appropriate abatement strategies.The source apportionment of sub-micron sized aerosols having a quite long atmospheric residence time in a complex environment like the Po Valley -which is also strongly impacted by secondary aerosol formation on a basin-scale -is generally quite challenging when using receptor models. Due to the availability of a huge dataset with variables having multiple time resolutions, in this work the DN-PMF was implemented in a multi-time resolution approach (MT) to achieve a better source identification and to gain knowledge about the relative importance of atmospheric dilution vs. emissions. A comparison between results obtained by the application of the regular multi time resolution (REG-MT) vs. the DN-MT approach is presented here for the five factors identified (nitrate-dominated, sulphate-dominated, biomass burning, mineral dust, and urban aerosol). The first interesting outcome is that REG-MT and DN-MT results do not point at significant differences in temporal pat-terns for aerosol components and sources impacting at the basin-scale (i.e. sulphate-and nitrate-dominated aerosol, biomass burning) thus suggesting that the diel modulation of these PM1 emissions is somehow masked by the stronger variability of the mixing layer. Conversely, contributions from local sources with more pronounced diel variation like traffic are quite well reproduced by DN-MT and the ambient concentrations are enhanced compared to REG-MT. This is an important piece of information highlighting that PM1 concentrations from local sources have been likely underestimated by REG-MT assessments.To our knowledge, this is one of the very few applications of DN-MT and the first one at a European site where the huge effort made to implement air pollution containment measures is still not very much effective in reducing PM levels; moreover, in this paper a detailed discussion about the possible interpretation of the output of DN-MT in terms of temporal patterns is reported.

In the recent decades, advanced instrumentation has been developed to measure the atmospheric aerosol's physical-chemical properties with increased temporal detail and size resolution. The characterization of the atmospheric aerosol is now provided at a more detailed level. Nevertheless, it is still challenging to maximize the exploitation of such detailed information in receptor models to perform more reliable source apportionment studies. Indeed, detailed time- and size-resolved sampling can, in principle, provide additional information to better identify specific emission sources and/or atmospheric processes, but an associated complete chemical characterization is often lacking, or is provided at low time resolution by PMX samples. To this aim, a completely novel, multi-time, multi-size resolution positive matrix factorization (MTMS-PMF) is presented. This cutting-edge receptor model is an expansion of the widely used PMF and allows the analysis of data measured at different time resolutions in multiple size classes. As output, it provides size-segregated chemical profiles and factor temporal contributions retrieved at the highest temporal resolution available in the dataset. The MTMS-PMF was implemented in a script for the Multilinear Engine ME-2 program and successfully tested on a large dataset collected in the Po Valley (Ferrara, Italy) during years 2008–2018. The dataset included aerosol chemical species measured on multistage impactor samples (8 size classes) at a low time resolution of about 1–3 weeks and daily PM10 samples covering almost the same sampling periods. The outputs retrieved at the higher time and size resolutions greatly strengthened the source-to-factor assignment. Moreover, the possibility to acquire information about the size distributions of atmospheric aerosol emitted by a variety of sources is highly valuable for impact assessment and for developing focused mitigation strategies aimed at addressing specific negative aerosol effects.

To mitigate climate change, CO2 sequestration from the atmosphere is being considered as a method to reduce its greenhouse effect and subsequently lower the Earth's surface temperature. A promising approach is the storage of CO2 in minerals, of which Olivine is a promising candidate due to its Earth abundance and high CO2 absorption capacity, which is of the order of 50 wt.%. A bottleneck for Olivine carbonation is the slow reaction rate at ambient conditions, which previously resulted in supplying CO2 at extreme pressures and temperatures to force carbonation. In this study, nanoscale Olivine particles are fabricated, which due to their high surface‐to‐volume ratio, reach a very high carbonation conversion at a time scale of minutes at ambient conditions. The carbonation is measured by X‐ray photoelectron spectroscopy (XPS), which yielded both the presence of carbonates as well as information on the Olivine oxidation state, in agreement with electron diffraction analysis. This work forms the basis for employing Olivine nanoparticles, as fabricated by the relatively simple method of magnetron sputtering, to capture CO2 from the atmosphere at economic conditions.

Particulate Matter (PM) is a complex and heterogeneous mixture of atmospheric particles recognized as a threat to human health. Oxidative Potential (OP) measurement is a promising and integrative method for estimating PM -induced health impacts since it is recognized as more closely associated with adverse health effects than ordinarily used PM mass concentrations. OP measurements could be introduced in the air quality monitoring, along with the parameters currently evaluated. PM deposition in the lungs induces oxidative stress, inflammation, and DNA damage. The study aimed to compare the OP measurements with toxicological effects on BEAS-2B and THP-1 cells of winter and summer PM( 1 )collected in the Po Valley (Italy) during 2021. PM (1 )was extracted in deionized water by mechanical agitation and tested for OP and, in parallel, used to treat cells. Cytotoxicity, genotoxicity, oxidative stress, and inflammatory responses were assessed by MTT test, DCFH-DA assay, micronucleus, gamma -H2AX, comet assay modified with endonucleases, ELISA, and Real -Time PCR. The evaluation of OP was performed by applying three different assays: dithiothreitol (OP (DTT) ), ascorbic acid (OP (AA) ), and 2 ' ,7 ' -dichlorofluorescein (OP (DCFH) ), in addition, the reducing potential was also analysed (RP (DPPH) ). Seasonal differences were detected in all the parameters investigated. The amount of DNA damage detected with the Comet assay and ROS formation highlights the presence of oxidative damage both in winter and in summer samples, while DNA damage (micronucleus) and genes regulation were mainly detected in winter samples. A positive correlation with OP DCFH (Spearman's analysis, p < 0.05) was detected for IL -8 secretion and gamma -H2AX. These results provide a biological support to the implementation in air quality monitoring of OP measurements as a useful proxy to estimate PM -induced cellular toxicological responses. In addition, these results provide new insights for the assessment of the ability of secondary aerosol in the background atmosphere to induce oxidative stress and health effects.

Radiocarbon measurements on the carbonaceous aerosol fractions are an effective tool for aerosol source apportionment. For these measurements, a new sample preparation line (MISSMARPLE: MIlan Small-SaMple Automated Radiocarbon Preparation LinE for atmospheric aerosol) was built in Milan (Italy). MISSMARPLE can separate different carbon fractions (i.e. total carbon (TC), elemental carbon (EC)), automates the sample combustion processes and the CO2 isolation in the "combustion line", and was designed to handle small samples, of about 50 mu g carbon. The CO2 obtained in the combustion line is then reduced to graphite in the graphitization line for subsequent accelerator mass spectrometry (AMS) analysis at the INFN-LABEC in Sesto Fiorentino (Italy). MISSMARPLE was tested for reproducibility of 14C/12C ratio in primary standard samples, for background contamination by the analysis of blank samples (graphite with zero percent Modern Carbon (pMC)), and for accuracy by the analysis of IAEA-C7 for pMC(TC) and NIST RM8785 for pMC(EC) used as secondary standards. Measurements were carried out in different AMS runs. Reproducibility of 14C/12C was within 1.2%; blank values were down to 2.2 +/- 0.2 pMC in the latest AMS run, and both IAEA-C7 and NIST RM8785 measurements were within 1 sigma with the reference value (but for one IAEA-C7 sample within 2.3 sigma). These results point to MISSMARPLE as a new, valuable tool for aerosol sample preparation for radiocarbon measurements to be exploited not only on traditional 24-h samples but also when small carbon quantities are available (e.g. collected at remote sites or with high temporal resolution).