| 1. |
- Björkman, Mats P., et al.
(författare)
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Nitrate dry deposition in svalbard
- 2013
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Ingår i: Tellus. Series B, Chemical and physical meteorology. - : Stockholm University Press. - 0280-6509 .- 1600-0889. ; 65, s. 19071-
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Tidskriftsartikel (refereegranskat)abstract
- Arctic regions are generally nutrient limited, receiving an extensive part of their bio-available nitrogen from the deposition of atmospheric reactive nitrogen. Reactive nitrogen oxides, as nitric acid (HNO3) and nitrate aerosols (p-NO3), can either be washed out from the atmosphere by precipitation or dry deposited, dissolving to nitrate (NO3-). During winter, NO3- is accumulated in the snowpack and released as a pulse during spring melt. Quantification of NO3- deposition is essential to assess impacts on Arctic terrestrial ecology and for ice core interpretations. However, the individual importance of wet and dry deposition is poorly quantified in the high Arctic regions where in-situ measurements are demanding. In this study, three different methods are employed to quantify NO3- dry deposition around the atmospheric and ecosystem monitoring site, Ny-Alesund, Svalbard, for the winter season (September 2009 to May 2010): (1) A snow tray sampling approach indicates a dry deposition of -10.27 +/- 3.84 mg m(-2) (+/- S.E.); (2) A glacial sampling approach yielded somewhat higher values -30.68 +/- 12.00 mg m(-2); and (3) Dry deposition was also modelled for HNO3 and p-NO3 using atmospheric concentrations and stability observations, resulting in a total combined nitrate dry deposition of -10.76 +/- 1.26 mg m(-2). The model indicates that deposition primarily occurs via HNO3 with only a minor contribution by p-NO3. Modelled median deposition velocities largely explain this difference: 0.63 cm s(-1) for HNO3 while p-NO3 was 0.0025 and 0.16 cm s(-1) for particle sizes 0.7 and 7 mm, respectively. Overall, the three methods are within two standard errors agreement, attributing an average 14% (total range of 2-44%) of the total nitrate deposition to dry deposition. Dry deposition events were identified in association with elevated atmospheric concentrations, corroborating recent studies that identified episodes of rapid pollution transport and deposition to the Arctic.
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| 2. |
- Partridge, Daniel G., 1984-, et al.
(författare)
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Inverse modeling of cloud-aerosol interactions : Part 2: Sensitivity tests on liquid phase clouds using a Markov Chain Monte carlo based simulation approach
- 2012
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 12:6, s. 2823-2847
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel approach to investigate cloud-aerosol interactions by coupling a Markov Chain Monte Carlo (MCMC) algorithm to a pseudo-adiabatic cloud parcel model. Despite the number of numerical cloud-aerosol sensitivity studies previously conducted few have used statistical analysis tools to investigate the sensitivity of a cloud model to input aerosol physiochemical parameters. Using synthetic data as observed values of cloud droplet number concentration (CDNC) distribution, this inverse modelling framework is shown to successfully converge to the correct calibration parameters. The employed analysis method provides a new, integrative framework to evaluate the sensitivity of the derived CDNC distribution to the input parameters describing the lognormal properties of the accumulation mode and the particle chemistry. To a large extent, results from prior studies are confirmed, but the present study also provides some additional insightful findings. There is a clear transition from very clean marine Arctic conditions where the aerosol parameters representing the mean radius and geometric standard deviation of the accumulation mode are found to be most important for determining the CDNC distribution to very polluted continental environments (aerosol concentration in the accumulation mode >1000 cm−3) where particle chemistry is more important than both number concentration and size of the accumulation mode. The competition and compensation between the cloud model input parameters illustrate that if the soluble mass fraction is reduced, both the number of particles and geometric standard deviation must increase and the mean radius of the accumulation mode must increase in order to achieve the same CDNC distribution. For more polluted aerosol conditions, with a reduction in soluble mass fraction the parameter correlation becomes weaker and more non-linear over the range of possible solutions (indicative of the sensitivity). This indicates that for the cloud parcel model used herein, the relative importance of the soluble mass fraction appears to decrease if the number or geometric standard deviation of the accumulation mode is increased. This study demonstrates that inverse modelling provides a flexible, transparent and integrative method for efficiently exploring cloud-aerosol interactions efficiently with respect to parameter sensitivity and correlation.
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| 3. |
- Partridge, Daniel G., 1984-, et al.
(författare)
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Inverse modeling of cloud-aerosol interactions : Part 1: Detailed response surface analysis
- 2011
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 11:14, s. 7269-7287
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Tidskriftsartikel (refereegranskat)abstract
- New methodologies are required to probe the sensitivity of parameters describing cloud droplet activation. This paper presents an inverse modeling-based method for exploring cloud-aerosol interactions via response surfaces. The objective function, containing the difference between the measured and model predicted cloud droplet size distribution is studied in a two-dimensional framework, and presented for pseudo-adiabatic cloud parcel model parameters that are pair-wise selected. From this response surface analysis it is shown that the susceptibility of cloud droplet size distribution to variations in different aerosol physiochemical parameters is highly dependent on the aerosol environment and meteorological conditions. In general the cloud droplet size distribution is most susceptible to changes in the updraft velocity. A shift towards an increase in the importance of chemistry for the cloud nucleating ability of particles is shown to exist somewhere between marine average and rural continental aerosol regimes. We also use these response surfaces to explore the feasibility of inverse modeling to determine cloud-aerosol interactions. It is shown that the "cloud-aerosol" inverse problem is particularly difficult to solve due to significant parameter interaction, presence of multiple regions of attraction, numerous local optima, and considerable parameter insensitivity. The identifiability of the model parameters will be dependent on the choice of the objective function. Sensitivity analysis is performed to investigate the location of the information content within the calibration data to confirm that our choice of objective function maximizes information retrieval from the cloud droplet size distribution. Cloud parcel models that employ a moving-centre based calculation of the cloud droplet size distribution pose additional difficulties when applying automatic search algorithms for studying cloud-aerosol interactions. To aid future studies, an increased resolution of the region of the size spectrum associated with droplet activation within cloud parcel models, or further development of fixed-sectional cloud models would be beneficial. Despite these improvements, it is demonstrated that powerful search algorithms remain necessary to efficiently explore the parameter space and successfully solve the cloud-aerosol inverse problem.
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| 4. |
- Partridge, Daniel, 1984-
(författare)
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Inverse Modeling of Cloud – Aerosol Interactions
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The role of aerosols and clouds is one of the largest sources of uncertainty in understanding climate change. The primary scientific goal of this thesis is to improve the understanding of cloud-aerosol interactions by applying inverse modeling using Markov Chain Monte Carlo (MCMC) simulation. Through a set of synthetic tests using a pseudo-adiabatic cloud parcel model, it is shown that a self adaptive MCMC algorithm can efficiently find the correct optimal values of meteorological and aerosol physiochemical parameters for a specified droplet size distribution and determine the global sensitivity of these parameters. For an updraft velocity of 0.3 m s-1, a shift towards an increase in the relative importance of chemistry compared to the accumulation mode number concentration is shown to exist somewhere between marine (~75 cm-3) and rural continental (~450 cm-3) aerosol regimes. Examination of in-situ measurements from the Marine Stratus/Stratocumulus Experiment (MASE II) shows that for air masses with higher number concentrations of accumulation mode (Dp = 60-120 nm) particles (~450 cm-3), an accurate simulation of the measured droplet size distribution requires an accurate representation of the particle chemistry. The chemistry is relatively more important than the accumulation mode particle number concentration, and similar in importance to the particle mean radius. This result is somewhat at odds with current theory that suggests chemistry can be ignored in all except for the most polluted environments. Under anthropogenic influence, we must consider particle chemistry also in marine environments that may be deemed relatively clean. The MCMC algorithm can successfully reproduce the observed marine stratocumulus droplet size distributions. However, optimising towards the broadness of the measured droplet size distribution resulted in a discrepancy between the updraft velocity, and mean radius/geometric standard deviation of the accumulation mode. This suggests that we are missing a dynamical process in the pseudo-adiabatic cloud parcel model.
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| 5. |
- Sá, Jacinto, et al.
(författare)
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SpaciMS : spatial and temporal operando resolution of reactions within catalytic monoliths.
- 2010
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Ingår i: The Analyst. - : Royal Society of Chemistry (RSC). - 0003-2654 .- 1364-5528. ; 135:9, s. 2260-72
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Tidskriftsartikel (refereegranskat)abstract
- Monolithic catalysts are widely used as structured catalysts, especially in the abatement of pollutants. Probing what happens inside these monoliths during operation is, therefore, vital for modelling and prediction of the catalyst behavior. SpaciMS is a spatially resolved capillary-inlet mass spectroscopy system allowing for the generation of spatially resolved maps of the reactions within monoliths. In this study SpaciMS results combined with 3D CFD modelling demonstrate that SpaciMS is a highly sensitive and minimally invasive technique that can provide reaction maps as well as catalytic temporal behavior. Herein we illustrate this by examining kinetic oscillations during a CO oxidation reaction over a Pt/Rh on alumina catalyst supported on a cordierite monolith. These oscillations were only observed within the monolith by SpaciMS between 30 and 90% CO conversion. Equivalent experiments performed in a plug-flow reactor using this catalyst in a crushed form over a similar range of reaction conditions did not display any oscillations demonstrating the importance of intra monolith analysis. This work demonstrates that the SpaciMS offers an accurate and comprehensive picture of structured catalysts under operation.
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