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Global occurrence, chemical properties, and ecological impacts of e-wastes (IUPAC Technical Report)
The waste stream of obsolete electronic equipment grows exponentially, creating a worldwide pollution and resource problem. Electrical and electronic waste (e-waste) comprises a heterogeneous mix of glass, plastics (including flame retardants and other additives), metals (including rare Earth elements), and metalloids. The e-waste issue is complex and multi-faceted. In examining the different aspects of e-waste, informal recycling in developing countries has been identified as a primary concern, due to widespread illegal shipments; weak environmental, as well as health and safety, regulations; lack of technology; and inadequate waste treatment structure. For example, Nigeria, Ghana, India, Pakistan, and China have all been identified as hotspots for the disposal of e-waste. This article presents a critical examination on the chemical nature of e-waste and the resulting environmental impacts on, for example, microbial biodiversity, flora, and fauna in e-waste recycling sites around the world. It highlights the different types of risk assessment approaches required when evaluating the ecological impact of e-waste. Additionally, it presents examples of chemistry playing a role in potential solutions. The information presented here will be informative to relevant stakeholders seeking to devise integrated management strategies to tackle this global environmental concern.
2020
2021
Global greenhouse gas reconciliation 2022
n this study, we provide an update on the methodology and data used by Deng et al. (2022) to compare the national greenhouse gas inventories (NGHGIs) and atmospheric inversion model ensembles contributed by international research teams coordinated by the Global Carbon Project. The comparison framework uses transparent processing of the net ecosystem exchange fluxes of carbon dioxide (CO2) from inversions to provide estimates of terrestrial carbon stock changes over managed land that can be used to evaluate NGHGIs. For methane (CH4), and nitrous oxide (N2O), we separate anthropogenic emissions from natural sources based directly on the inversion results to make them compatible with NGHGIs. Our global harmonized NGHGI database was updated with inventory data until February 2023 by compiling data from periodical United Nations Framework Convention on Climate Change (UNFCCC) inventories by Annex I countries and sporadic and less detailed emissions reports by non-Annex I countries given by national communications and biennial update reports. For the inversion data, we used an ensemble of 22 global inversions produced for the most recent assessments of the global budgets of CO2, CH4, and N2O coordinated by the Global Carbon Project with ancillary data. The CO2 inversion ensemble in this study goes through 2021, building on our previous report from 1990 to 2019, and includes three new satellite inversions compared to the previous study and an improved managed-land mask. As a result, although significant differences exist between the CO2 inversion estimates, both satellite and in situ inversions over managed lands indicate that Russia and Canada had a larger land carbon sink in recent years than reported in their NGHGIs, while the NGHGIs reported a significant upward trend of carbon sink in Russia but a downward trend in Canada. For CH4 and N2O, the results of the new inversion ensembles are extended to 2020. Rapid increases in anthropogenic CH4 emissions were observed in developing countries, with varying levels of agreement between NGHGIs and inversion results, while developed countries showed a slowly declining or stable trend in emissions. Much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites, coordinated into a global constellation, is expected in the coming years. The methodology proposed here to compare inversion results with NGHGIs can be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objectives of their pledges. The dataset constructed for this study is publicly available at https://doi.org/10.5281/zenodo.13887128 (Deng et al., 2024).
2025
Road traffic externalities are an important consequence of land-use and transport interactions and may be especially induced by their inefficient combinations. In this study, we integrate land-use, transport and emission modelling tools (the LUTEm framework) to assess how suburban expansion vs. inward densification scenarios influence journey parameters, road network performance and traffic emissions. Case-study simulations for Warsaw (Poland) underscore the negative consequences of suburban sprawl development, which are hardly mitigated by additional land-use or transport interventions, such as rebalancing of population-workplace distribution or road capacity reductions. On the other side, compact city development lowers global traffic congestion and emissions, but can also raise the risks of traffic externalities in central city area unless complemented with further interventions such as improved public transport attractiveness. This study aims to enrich the understanding of how integrating the land-use development and transport interventions can ultimately influence travel parameters and reduce urban road traffic externalities.
2025
Poor Indoor Environmental Quality (IEQ) in schools significantly impacts students’ well-being, learning capabilities, and health. Perceived dissatisfaction rates (PD%) among students often remain high, even when indoor environmental variables appear well-controlled. This study aims to predict perceived dissatisfaction rates (PD%) across multi-domain environmental factors—thermal, acoustic, visual, and indoor air quality (IAQ)—using machine learning (ML) models. The research integrates sensor-based environmental measurements, outdoor weather data, building parameters, and 1437 student survey responses collected from three classrooms in a Norwegian school across multiple seasons. Statistical tests were used to pre-select relevant input variables, followed by the development and evaluation of multiple ML algorithms. Among the tested ML models, Random Forest (RF) demonstrated the highest predictive accuracy for PD%, outperforming multi-linear regression (MLR) and decision trees (DT), with R² values up to 0.91 for overall IEQ dissatisfaction (PDIEQ%). SHAP analysis revealed key predictors: CO₂ levels, VOCs, humidity, temperature, solar radiation, and room window orientation. IAQ, thermal comfort, and acoustic environment were the most influential factors affecting students' perceived well-being. Despite limitations as implementation in building level scale, the study demonstrates the feasibility of deploying predictive ML models under real-world constraints for improving IEQ monitoring system. The findings support practical strategies for adaptive indoor environmental management, particularly in educational settings, and provide a replicable framework for future research. Future research can expand to other climates, buildings, measurements, occupant levels, and ML training optimization.
2025
Long-term monitoring of regulated organic chemicals, such as legacy persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAHs), in ambient air provides valuable information about the compounds' environmental fate as well as temporal and spatial trends. This is the foundation to evaluate the effectiveness of national and international regulations for priority pollutants. Extracts of high-volume air samples, collected on glass fibre filters (GFF for particle phase) and polyurethane foam plugs (PUF for gaseous phase), for targeted analyses of legacy POPs are commonly cleaned by treatment with concentrated sulfuric acid, resulting in extracts clean from most interfering compounds and matrices that are suitable for multi-quantitative trace analysis. Such standardised methods, however, severely restrict the number of analytes for quantification and are not applicable when targeting new and emerging compounds as some may be less stable under acid treatment. Recently developed suspect and non-target screening analytical strategies (SUS and NTS, respectively) are shown to be effective evaluation tools aimed at identifying a high number of compounds of emerging concern. These strategies, combining highly sophisticated analytical technology with extensive data interpretation and statistics, are already widely accepted in environmental sciences for investigations of various environmental matrices, but their application to air samples is still very limited. In order to apply SUS and NTS for the identification of organic contaminants in air samples, an adapted and more wide-scope sample clean-up method is needed compared to the traditional method, which uses concentrated sulfuric acid. Analysis of raw air sample extracts without clean-up would generate extensive contamination of the analytical system, especially with PUF matrix-based compounds, and thus highly interfered mass spectra and detection limits which are unacceptable high for trace analysis in air samples.
In this study, a novel wide-scope sample clean-up method for high-volume air samples has been developed and applied to real high-volume air samples, which facilitates simultaneous target, suspect and non-target analyses. The scope and efficiency of the method were quantitatively evaluated with organic compounds covering a wide range of polarities (logP 2–11), including legacy POPs, brominated flame retardants (BFRs), chlorinated pesticides and currently used pesticides (CUPs). In addition, data reduction and selection strategies for SUS and NTS were developed for comprehensive two-dimensional gas chromatography separation with low-resolution time-of-flight mass spectrometric detection (GC × GC-LRMS) data and applied to real high-volume air samples. Combination of the newly developed clean-up procedure and data treatment strategy enabled the prioritisation of over 600 compounds of interest in the particle phase (on GFF) and over 850 compounds in the gas phase (on PUF) out of over 25 000 chemical features detected in the raw dataset. Of these, 50 individual compounds were identified and confirmed with reference standards, 80 compounds were identified with a probable structure, and 774 compounds were assigned to various compound classes. In the dataset available here, 11 hitherto unknown halogenated compounds were detected. These unknown compounds were not yet listed in the available mass spectral libraries.
2021
2018
Technical note: Reanalysis of Aura MLS chemical observations
This paper presents a reanalysis of the atmospheric chemical composition from the upper troposphere to the lower mesosphere from August 2004 to December 2017. This reanalysis is produced by the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by the chemical observations from the Microwave Limb Sounder (MLS) on board the Aura satellite. BASCOE is based on the ensemble Kalman filter (EnKF) method and includes a chemical transport model driven by the winds and temperature from the ERA-Interim meteorological reanalysis. The model resolution is 3.75∘ in longitude, 2.5∘ in latitude and 37 vertical levels from the surface to 0.1 hPa with 25 levels above 100 hPa. The outputs are provided every 6 h. This reanalysis is called BRAM2 for BASCOE Reanalysis of Aura MLS, version 2.
Vertical profiles of eight species from MLS version 4 are assimilated and are evaluated in this paper: ozone (O3), water vapour (H2O), nitrous oxide (N2O), nitric acid (HNO3), hydrogen chloride (HCl), chlorine oxide (ClO), methyl chloride (CH3Cl) and carbon monoxide (CO). They are evaluated using independent observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and N2O observations from a different MLS radiometer than the one used to deliver the standard product and ozonesondes. The evaluation is carried out in four regions of interest where only selected species are evaluated. These regions are (1) the lower-stratospheric polar vortex where O3, H2O, N2O, HNO3, HCl and ClO are evaluated; (2) the upper-stratospheric–lower-mesospheric polar vortex where H2O, N2O, HNO3 and CO are evaluated; (3) the upper troposphere–lower stratosphere (UTLS) where O3, H2O, CO and CH3Cl are evaluated; and (4) the middle stratosphere where O3, H2O, N2O, HNO3, HCl, ClO and CH3Cl are evaluated.
In general BRAM2 reproduces MLS observations within their uncertainties and agrees well with independent observations, with several limitations discussed in this paper (see the summary in Sect. 5.5). In particular, ozone is not assimilated at altitudes above (i.e. pressures lower than) 4 hPa due to a model bias that cannot be corrected by the assimilation. MLS ozone profiles display unphysical oscillations in the tropical UTLS, which are corrected by the assimilation, allowing a good agreement with ozonesondes. Moreover, in the upper troposphere, comparison of BRAM2 with MLS and independent observations suggests a positive bias in MLS O3 and a negative bias in MLS H2O. The reanalysis also reveals a drift in MLS N2O against independent observations, which highlights the potential use of BRAM2 to estimate biases between instruments. BRAM2 is publicly available and will be extended to assimilate MLS observations after 2017.
2019
Unexpected nascent atmospheric emissions of three ozone-depleting hydrochlorofluorocarbons
Global and regional atmospheric measurements and modeling can play key roles in discovering and quantifying unexpected nascent emissions of environmentally important substances. We focus here on three hydrochlorofluorocarbons (HCFCs) that are restricted by the Montreal Protocol because of their roles in stratospheric ozone depletion. Based on measurements of archived air samples and on in situ measurements at stations of the Advanced Global Atmospheric Gases Experiment (AGAGE) network, we report global abundances, trends, and regional enhancements for HCFC-132b (CH2ClCClF2), which is newly discovered in the atmosphere, and updated results for HCFC-133a (CH2ClCF3) and HCFC-31 (CH2ClF). No purposeful end-use is known for any of these compounds. We find that HCFC-132b appeared in the atmosphere 20 y ago and that its global emissions increased to 1.1 Gg⋅y−1 by 2019. Regional top-down emission estimates for East Asia, based on high-frequency measurements for 2016–2019, account for ∼95% of the global HCFC-132b emissions and for ∼80% of the global HCFC-133a emissions of 2.3 Gg⋅y−1 during this period. Global emissions of HCFC-31 for the same period are 0.71 Gg⋅y−1. Small European emissions of HCFC-132b and HCFC-133a, found in southeastern France, ceased in early 2017 when a fluorocarbon production facility in that area closed. Although unreported emissive end-uses cannot be ruled out, all three compounds are most likely emitted as intermediate by-products in chemical production pathways. Identification of harmful emissions to the atmosphere at an early stage can guide the effective development of global and regional environmental policy.
2021
2018
There are large knowledge gaps concerning environmental levels and fate of many organic pollutants, particularly for chemicals of emerging concern in tropical regions of the Global South. In this study, we investigated the levels of chlorinated paraffins (CPs) and dechloranes in air and soil in rural, suburban, and urban regions in and around Dar es Salaam, Tanzania. Samples were also collected near the city's main municipal waste dumpsite and an electronic waste (e-waste) handling facility. In passive air samples, short chain CPs (SCCPs) dominated, with an average estimated concentration of 22 ng/m3, while medium chain CPs (MCCPs) had an average estimated concentration of 9 ng/m3. The average estimated air concentration of ∑dechloranes (Dechlorane Plus (DP) + Dechlorane 602 + Dechlorane 603) was three to four orders of magnitudes lower, 2 pg/m3. In soil samples, MCCPs dominated with an average concentration of 640 ng/g dw, followed by SCCPs with an average concentration of 330 ng/g dw, and ∑dechloranes with an average concentration of 0.9 ng/g dw. In both air and soil, DP was the dominating dechlorane compound. Urban pulses were observed for CPs and dechloranes in air and soil. CPs were in addition found in elevated levels at the municipal waste dumpsite and the e-waste handling facility, while DPs were found in elevated levels at the e-waste handling facility. This suggests that waste handling sites represent important emission sources for these pollutants. Investigations into seasonal trends and environmental fate of CPs and dechloranes showed that monsoonal rain patterns play a major role in governing air concentrations and mobility, particularly for the less volatile MCCPs and dechloranes. This study is the first to report levels of CPs in air from sub-Saharan Africa, and DP, Dechlorane 602, and Dechlorane 603 in soil from sub-Saharan Africa.
2021
The blood enzyme glutamate-oxaloacetate transaminase (GOT) has been postulated as an effective therapeutic to protect the brain during stroke. To demonstrate its potential clinical utility, a new human recombinant form of GOT (rGOT) was produced for medical use.
We tested the pharmacokinetics and evaluated the protective efficacy of rGOT in rodent and non-human primate models that reflected clinical stroke conditions.
We found that continuous intravenous administration of rGOT within the first 8 h after ischemic onset significantly reduced the infarct size in both severe (30%) and mild lesions (48%). Cerebrospinal fluid and proteomics analysis, in combination with positron emission tomography imaging, indicated that rGOT can reach the brain and induce cytoprotective autophagy and induce local protection by alleviating neuronal apoptosis.
Our results suggest that rGOT can be safely used immediately in patients suspected of having a stroke. This study requires further validation in clinical stroke populations.
2024
In the framework of the EURODELTA-Trends (EDT) modeling experiment, several chemical transport models (CTMs) were applied for the 1990–2010 period to investigate air quality changes in Europe as well as the capability of the models to reproduce observed long-term air quality trends. Five CTMs have provided modeled air quality data for 21 continuous years in Europe using emission scenarios prepared by the International Institute for Applied Systems Analysis/Greenhouse Gas – Air Pollution Interactions and Synergies (IIASA/GAINS) and corresponding year-by-year meteorology derived from ERA-Interim global reanalysis. For this study, long-term observations of particle sulfate (SO2−4
), total nitrate (TNO3), total ammonium (TNHx) as well as sulfur dioxide (SO2) and nitrogen dioxide (NO2) for multiple sites in Europe were used to evaluate the model results. The trend analysis was performed for the full 21 years (referred to as PT) but also for two 11-year subperiods: 1990–2000 (referred to as P1) and 2000–2010 (referred to as P2).
The experiment revealed that the models were able to reproduce the faster decline in observed SO2 concentrations during the first decade, i.e., 1990–2000, with a 64 %–76 % mean relative reduction in SO2 concentrations indicated by the EDT experiment (range of all the models) versus an 82 % mean relative reduction in observed concentrations. During the second decade (P2), the models estimated a mean relative reduction in SO2 concentrations of about 34 %–54 %, which was also in line with that observed (47 %). Comparisons of observed and modeled NO2 trends revealed a mean relative decrease of 25 % and between 19 % and 23 % (range of all the models) during the P1 period, and 12 % and between 22 % and 26 % (range of all the models) during the P2 period, respectively.
Comparisons of observed and modeled trends in SO2−4
concentrations during the P1 period indicated that the models were able to reproduce the observed trends at most of the sites, with a 42 %–54 % mean relative reduction indicated by the EDT experiment (range of all models) versus a 57 % mean relative reduction in observed concentrations and with good performance also during the P2 and PT periods, even though all the models overpredicted the number of statistically significant decreasing trends during the P2 period. Moreover, especially during the P1 period, both modeled and observational data indicated smaller reductions in SO2−4
concentrations compared with their gas-phase precursor (i.e., SO2), which could be mainly attributed to increased oxidant levels and pH-dependent cloud chemistry.
An analysis of the trends in TNO3 concentrations indicated a 28 %–39 % and 29 % mean relative reduction in TNO3 concentrations for the full period for model data (range of all the models) and observations, respectively. Further analysis of the trends in modeled HNO3 and particle nitrate (NO−3
) concentrations revealed that the relative reduction in HNO3 was larger than that for NO−3 during the P1 period, which was mainly attributed to an increased availability of “free ammonia”. By contrast, trends in modeled HNO3 and NO−3 concentrations were more comparable during the P2 period. Also, trends of TNHx concentrations were, in general, underpredicted by all models, with worse performance for the P1 period than for P2. Trends in modeled anthropogenic and biogenic secondary organic aerosol (ASOA and BSOA) concentrations together with the trends in available emissions of biogenic volatile organic compounds (BVOCs) were also investigated. A strong decrease in ASOA was indicated by all the models, following the reduction in anthropogenic non-methane VOC (NMVOC) precursors. Biogenic emission data...
2019
2019
Regionally sourced bioaerosols drive high-temperature ice nucleating particles in the Arctic
Primary biological aerosol particles (PBAP) play an important role in the climate system, facilitating the formation of ice within clouds, consequently PBAP may be important in understanding the rapidly changing Arctic. Within this work, we use single-particle fluorescence spectroscopy to identify and quantify PBAP at an Arctic mountain site, with transmission electronic microscopy analysis supporting the presence of PBAP. We find that PBAP concentrations range between 10−3–10−1 L−1 and peak in summer. Evidences suggest that the terrestrial Arctic biosphere is an important regional source of PBAP, given the high correlation to air temperature, surface albedo, surface vegetation and PBAP tracers. PBAP clearly correlate with high-temperature ice nucleating particles (INP) (>-15 °C), of which a high a fraction (>90%) are proteinaceous in summer, implying biological origin. These findings will contribute to an improved understanding of sources and characteristics of Arctic PBAP and their links to INP.
2023
A flexible algorithm for network design based on information theory
A novel method for atmospheric network design is presented, which is based on information theory. The method does not require calculation of the posterior uncertainty (or uncertainty reduction) and is therefore computationally more efficient than methods that require this. The algorithm is demonstrated in two examples: the first looks at designing a network for monitoring CH4 sources using observations of the stable carbon isotope ratio in CH4 (δ13C), and the second looks at designing a network for monitoring fossil fuel emissions of CO2 using observations of the radiocarbon isotope ratio in CO2 (Δ14CO2).
2023
Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present-day greenhouse gas (GHG) budgets. We compare bottom-up (data-driven upscaling and process-based models) and top-down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom-up approaches estimate higher land-to-atmosphere fluxes for all GHGs. Both bottom-up and top-down approaches show a sink of CO2 in natural ecosystems (bottom-up: −29 (−709, 455), top-down: −587 (−862, −312) Tg CO2-C yr−1) and sources of CH4 (bottom-up: 38 (22, 53), top-down: 15 (11, 18) Tg CH4-C yr−1) and N2O (bottom-up: 0.7 (0.1, 1.3), top-down: 0.09 (−0.19, 0.37) Tg N2O-N yr−1). The combined global warming potential of all three gases (GWP-100) cannot be distinguished from neutral. Over shorter timescales (GWP-20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process-based models and the compilation of process-model ensembles for CH4 and N2O. Discrepancies between bottom-up and top-down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well-distributed in situ GHG measurements and improved resolution in upscaling techniques.
2024
The aim of this work was to assess how improvements to the indoor environment could affect the future condition, frequency and costs of major conservation-cleaning campaigns on the monumental paintings (1909–1916) by Edvard Munch, centrally located in the Aula assembly hall of the University of Oslo. A lower soiling rate is expected to reduce the need for frequent and major cleaning campaigns. Estimations were performed using the freely available NILU-EnvCul web-model. The conservation of these large, mostly unvarnished, oil paintings is challenging, and it is important to understand the potential benefits of preventive conservation measures. The results from the model suggested benefits from preventive conservation in protecting the paintings, and as a cost-efficient strategy to reduce the soiling and cleaning frequency. The model results indicated that an improvement in the indoor air quality in the Aula, of 50–80% as compared to the 1916–2009 average, would increase the time until the next similar major conservation cleaning campaign from approximately 45 years to between about 85 and 165 years. This should give a 45–70% reduction in the respective conservation costs. This saving was probably initiated by improvements in the recent past, before the last Aula campaign in 2009–11.
2019
Solar irradiance has been universally acknowledged to be dominant by quasi-decadal variability, which has been adopted frequently to investigate its effect on climate decadal variability. As one major terrestrial energy source, solar-wind energy flux into Earth's magnetosphere (Ein) exhibits dramatic interannual variation, the effect of which on Earth's climate, however, has not drawn much attention. Based on the Ein estimated by 3D magnetohydrodynamic simulations, we demonstrate a novelty that the annual mean Ein can explain up to 25% total interannual variance of the northern-hemispheric temperature in the subsequent boreal winter. The concurrent anomalous atmospheric circulation resembles the positive phase of Arctic Oscillation/North Atlantic Oscillation. The warm anomalies in the tropic stratopause and tropopause induced by increased solar-wind–magnetosphere energy persist into the subsequent winter. Due to the dominant change in the polar vortex and mid-latitude westerly in boreal winter, a ‘top-down’ propagation of the stationary planetary wave emerges in the Northern Hemisphere and further influences the atmospheric circulation and climate.
2020
Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines
Wind turbines are one of the primary sources of renewable energy, which leads to a sustainable and efficient energy solution. It does not release any carbon emissions to pollute our planet. The wind farms monitoring and power generation prediction is a complex problem due to the unpredictability of wind speed. Consequently, it limits the decision power of the management team to plan the energy consumption in an effective way. Our proposed model solves this challenge by utilizing a 5G-Next Generation-Radio Access Network (5G-NG-RAN) assisted cloud-based digital twins’ framework to virtually monitor wind turbines and form a predictive model to forecast wind speed and predict the generated power. The developed model is based on Microsoft Azure digital twins infrastructure as a 5-dimensional digital twins platform. The predictive modeling is based on a deep learning approach, temporal convolution network (TCN) followed by a non-parametric k-nearest neighbor (kNN) regression. Predictive modeling has two components. First, it processes the univariate time series data of wind to predict its speed. Secondly, it estimates the power generation for each quarter of the year ranges from one week to a whole month (i.e., medium-term prediction) To evaluate the framework the experiments are performed on onshore wind turbines publicly available datasets. The obtained results confirm the applicability of the proposed framework. Furthermore, the comparative analysis with the existing classical prediction models shows that our designed approach obtained better results. The model can assist the management team to monitor the wind farms remotely as well as estimate the power generation in advance.
2022
BACKGROUND. Methodology for estimation of cerebrospinal fluid (CSF) tracer clearance could have wide clinical application in predicting excretion of intrathecal drugs and metabolic solutes from brain metabolism and for diagnostic workup of CSF disturbances. METHODS. The MRI contrast agent gadobutrol (Gadovist) was used as a CSF tracer and injected into the lumbar CSF. Gadobutrol is contained outside blood vessels of the CNS and is eliminated along extravascular pathways, analogous to many CNS metabolites and intrathecal drugs. Tracer enrichment was verified and assessed in CSF by MRI at the level of the cisterna magna in parallel with obtaining blood samples through 48 hours. RESULTS. In a reference patient cohort (n = 29), both enrichment within CSF and blood coincided in time. Blood concentration profiles of gadobutrol through 48 hours varied between patients diagnosed with CSF leakage (n = 4), idiopathic normal pressure hydrocephalus dementia (n = 7), pineal cysts (n = 8), and idiopathic intracranial hypertension (n = 4). CONCLUSION. Assessment of CSF tracer clearance is clinically feasible and may provide a way to predict extravascular clearance of intrathecal drugs and endogenous metabolites from the CNS. The peak concentration in blood (at about 10 hours) was preceded by far peak tracer enhancement at MRI in extracranial lymphatic structures (at about 24 hours), as shown in previous studies, indicating a major role of the spinal canal in CSF clearance capacity. FUNDING. The work was supported by the Department of Neurosurgery, Oslo University Hospital; the Norwegian Institute for Air Research; and the University of Oslo.
2021