Found 2678 publications. Showing page 74 of 268:
Physical controls of dynamics of methane venting from a shallow seep area west of Svalbard
We investigate methane seepage on the shallow shelf west of Svalbard during three consecutive years, using discrete sampling of the water column, echosounder-based gas flux estimates, water mass properties, and numerical dispersion modelling. The results reveal three distinct hydrographic conditions in spring and summer, showing that the methane content in the water column is controlled by a combination of free gas seepage intensity and lateral water mass movements, which disperse and displace dissolved methane horizontally away from the seeps. Horizontal dispersion and displacement of dissolved methane are promoted by eddies originating from the West Spitsbergen Current and passing over the shallow shelf, a process that is more intense in winter and spring than in the summer season. Most of the methane injected from seafloor seeps resides in the bottom layer even when the water column is well mixed, implying that the controlling effect of water column stratification on vertical methane transport is small. Only small concentrations of methane are found in surface waters, and thus the escape of methane into the atmosphere above the site of seepage is also small. The magnitude of the sea to air methane flux is controlled by wind speed, rather than by the concentration of dissolved methane in the surface ocean.
2019
2019
BACKGROUND: In order to use in situ measurements to constrain urban anthropogenic emissions of carbon dioxide (CO2), we use a Lagrangian methodology based on diffusive backward trajectory tracer reconstructions and Bayesian inversion. The observations of atmospheric CO2 were collected within the Tokyo Bay Area during the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) flights, from the Tsukuba tall tower of the Meteorological Research Institute (MRI) of the Japan Meteorological Agency and at two surface sites (Dodaira and Kisai) from the World Data Center for Greenhouse Gases (WDCGG).
RESULTS: We produce gridded estimates of the CO2 emissions and calculate the averages for different areas within the Kanto plain where Tokyo is located. Using these inversions as reference we investigate the impact of perturbing different elements in the inversion system. We modified the observations amount and location (surface only sparse vs. including aircraft CO2 observations), the background representation, the wind data used to drive the transport model, the prior emissions magnitude and time resolution and error parameters of the inverse model.
CONCLUSIONS: Optimized fluxes were consistent with other estimates for the unperturbed simulations. Inclusion of CONTRAIL measurements resulted in significant differences in the magnitude of the retrieved fluxes, 13% on average for the whole domain and of up to 21% for the spatiotemporal cells with the highest fluxes. Changes in the background yielded differences in the retrieved fluxes of up to 50% and more. Simulated biases in the modelled transport cause differences in the retrieved fluxes of up to 30% similar to those obtained using different meteorological winds to advect the Lagrangian trajectories. Perturbations to the prior inventory can impact the fluxes by ~ 10% or more depending on the assumptions on the error covariances. All of these factors can cause significant differences in the estimated flux, and highlight the challenges in estimating regional CO2 fluxes from atmospheric observations.
2019
The wet deposition of nitrogen and sulfur in Europe for the period 1990–2010 was estimated by six atmospheric chemistry transport models (CHIMERE, CMAQ, EMEP MSC-W, LOTOS-EUROS, MATCH and MINNI) within the framework of the EURODELTA-Trends model intercomparison. The simulated wet deposition and its trends for two 11-year periods (1990–2000 and 2000–2010) were evaluated using data from observations from the EMEP European monitoring network. For annual wet deposition of oxidised nitrogen (WNOx), model bias was within 30 % of the average of the observations for most models. There was a tendency for most models to underestimate annual wet deposition of reduced nitrogen (WNHx), although the model bias was within 40 % of the average of the observations. Model bias for WNHx was inversely correlated with model bias for atmospheric concentrations of NH3+NH+4
, suggesting that an underestimation of wet deposition partially contributed to an overestimation of atmospheric concentrations. Model bias was also within about 40 % of the average of the observations for the annual wet deposition of sulfur (WSOx) for most models.
Decreasing trends in WNOx were observed at most sites for both 11-year periods, with larger trends, on average, for the second period. The models also estimated predominantly decreasing trends at the monitoring sites and all but one of the models estimated larger trends, on average, for the second period. Decreasing trends were also observed at most sites for WNHx, although larger trends, on average, were observed for the first period. This pattern was not reproduced by the models, which estimated smaller decreasing trends, on average, than those observed or even small increasing trends. The largest observed trends were for WSOx, with decreasing trends at more than 80 % of the sites. On average, the observed trends were larger for the first period. All models were able to reproduce this pattern, although some models underestimated the trends (by up to a factor of 4) and others overestimated them (by up to 40 %), on average. These biases in modelled trends were directly related to the tendency of the models to under- or overestimate annual wet deposition and were smaller for the relative trends (expressed as % yr−1 relative to the deposition at the start of the period).
The fact that model biases were fairly constant throughout the time series makes it possible to improve the predictions of wet deposition for future scenarios by adjusting the model estimates using a bias correction calculated from past observations. An analysis of the contributions of various factors to the modelled trends suggests that the predominantly decreasing trends in wet deposition are mostly due to reductions in emissions of the precursors NOx, NH3 and SOx. However, changes in meteorology (e.g. precipitation) and other (non-linear) interactions partially offset the decreasing trends due to emission reductions during the first period but not the second. This suggests that the emission reduction measures had a relatively larger effect on wet deposition during the second period, at least for the sites with observations.
2019
2019
There is little information to decision support in air traffic management in case of nuclear releases into the atmosphere. In this paper, the dose estimation due to both, external exposure (i.e. cloud immersion, deposition inside and outside the aircraft), and due to internal exposure (i.e, inhalation of radionuclides inside the aircraft) to passengers and crew is calculated for a worst-case emergency scenario. The doses are calculated for different radionuclides and activities. Calculations are mainly considered according to International Commission on Radiological Protection (ICRP) recommendations and Monte Carlo simulations. In addition, a discussion on potential detectors installed inside the aircraft for monitoring the aerosol concentration and the ambient dose equivalent rate, H*(10), for during-flight monitoring and early warning is provided together with the evaluation of a response of a generic detector. The results show that the probability that a catastrophic nuclear accident would produce significant radiological doses to the passengers and crew of an aircraft is very low. In the worst-case scenarios studied, the maximum estimated effective dose was about 1 mSv during take-off or landing operations, which is the recommended yearly threshold for the public. However, in order to follow the ALARA (As Low As Reasonably Achievable) criteria and to avoid aircraft contamination, the installation of radiological detectors is considered. This would, on one hand help the pilot or corresponding decision maker to decide about the potential change of the route and, on the other, allow for gathering of 4D data for future studies.
2019
Using life cycle assessment to inform municipal climate mitigation planning
Local governments can play a key role in reducing emissions associated with local energy use. 17 Polish municipalities provided data on energy use and CO2 emissions for 2015. Life Cycle Assessment (LCA) was used to calculate lifecycle impact indicators for greenhouse gases, particulate matter, acidification and eutrophication associated with the annual energy demand in each municipality. Results showed that impacts from energy use increase almost proportionally with total energy used in the participating municipalities due to the heavy reliance on fossil fuels. Analysis of two municipalities of similar size showed that impacts can be attributed to different usage sectors. For one municipality, energy plans should focus on reducing emissions from private transport and associated fuel use. For the other, energy plans should focus on reducing energy demand from residential buildings. This means that a ‘one-size-fits-all’ energy plan, which may be developed at a national level, would not fit all municipalities. The application of LCA allows for identifying and informing energy planning with impact reduction potential for multiple environmental pressures. Analysis of the provided energy use and CO2 data showed large uncertainties in CO2 emission intensities and allowing for sufficient time and guidance in the energy and emissions accounting is recommended.
2019
2019
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
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