scholarly journals Estimating bacteria emissions from inversion of atmospheric transport: sensitivity to modelled particle characteristics

2013 ◽  
Vol 13 (11) ◽  
pp. 5473-5488 ◽  
Author(s):  
S. M. Burrows ◽  
P. J. Rayner ◽  
T. Butler ◽  
M. G. Lawrence

Abstract. Model-simulated transport of atmospheric trace components can be combined with observed concentrations to obtain estimates of ground-based sources using various inversion techniques. These approaches have been applied in the past primarily to obtain source estimates for long-lived trace gases such as CO2. We consider the application of similar techniques to source estimation for atmospheric aerosols, using as a case study the estimation of bacteria emissions from different ecosystem regions in the global atmospheric chemistry and climate model ECHAM5/MESSy-Atmospheric Chemistry (EMAC). Source estimation via Markov Chain Monte Carlo is applied to a suite of sensitivity simulations, and the global mean emissions are estimated for the example problem of bacteria-containing aerosol particles. We present an analysis of the uncertainties in the global mean emissions, and a partitioning of the uncertainties that are attributable to particle size, activity as cloud condensation nuclei (CCN), the ice nucleation scavenging ratios for mixed-phase and cold clouds, and measurement error. For this example, uncertainty due to CCN activity or to a 1 μm error in particle size is typically between 10% and 40% of the uncertainty due to observation uncertainty, as measured by the 5–95th percentile range of the Monte Carlo ensemble. Uncertainty attributable to the ice nucleation scavenging ratio in mixed-phase clouds is as high as 10–20% of that attributable to observation uncertainty. Taken together, the four model parameters examined contribute about half as much to the uncertainty in the estimated emissions as do the observations. This was a surprisingly large contribution from model uncertainty in light of the substantial observation uncertainty, which ranges from 81–870% of the mean for each of ten ecosystems for this case study. The effects of these and other model parameters in contributing to the uncertainties in the transport of atmospheric aerosol particles should be treated explicitly and systematically in both forward and inverse modelling studies.

2013 ◽  
Vol 13 (2) ◽  
pp. 4391-4432 ◽  
Author(s):  
S. M. Burrows ◽  
P. J. Rayner ◽  
T. Butler ◽  
M. G. Lawrence

Abstract. Model-simulated transport of atmospheric trace components can be combined with observed concentrations to obtain estimates of ground-based sources using various inversion techniques. These approaches have been applied in the past primarily to obtain source estimates for long-lived trace gases such as CO2. We consider the application of similar techniques to source estimation for atmospheric aerosols, using as a case study the estimation of bacteria emissions from different ecosystem regions in the global atmospheric chemistry and climate model ECHAM5/MESSy-Atmospheric Chemistry (EMAC). Source estimation via Monte Carlo Markov Chain is applied to a suite of sensitivity simulations and the global mean emissions are estimated. We present an analysis of the uncertainties in the global mean emissions, and a partitioning of the uncertainties that are attributable to particle size, activity as cloud condensation nuclei (CCN), the ice nucleation scavenging ratios for mixed-phase and cold clouds, and measurement error. Uncertainty due to CCN activity or to a 1 μm error in particle size is typically between 10% and 40% of the uncertainty due to observation uncertainty, as measured by the 5%-ile to 95%-ile range of the Monte Carlo ensemble. Uncertainty attributable to the ice nucleation scavenging ratio in mixed-phase clouds is as high as 10% to 20% of that attributable to observation uncertainty. Taken together, the four model parameters examined contribute about half as much to the uncertainty in the estimated emissions as do the observations. This was a surprisingly large contribution from model uncertainty in light of the substantial observation uncertainty, which ranges from 81% to 870% of the mean for each of ten ecosystems for this case study. The effects of these and other model parameters in contributing to the uncertainties in the transport of atmospheric aerosol particles should be treated explicitly and systematically in both forward and inverse modelling studies.


2018 ◽  
Author(s):  
Paul J. DeMott ◽  
Ottmar Möhler ◽  
Daniel J. Cziczo ◽  
Naruki Hiranuma ◽  
Markus D. Petters ◽  
...  

Abstract. The second phase of the Fifth International Ice Nucleation Workshop (FIN-02) involved the gathering of a large number of researchers at the Karlsruhe Institute of Technology's Aerosol Interactions and Dynamics of the Atmosphere (AIDA) facility to promote characterization and understanding of ice nucleation measurements made by the variety of methods used worldwide. Compared to the previous workshop in 2007, participation was doubled, reflecting a vibrant research area. Experimental methods involved sampling of aerosol particles by online ice nucleation measuring systems from the same volume of air in separate experiments using different ice nucleating particle (INP) types, and collections of aerosol particle samples onto filters or into liquid for sharing amongst offline measurement techniques. In this manner, any errors introduced by differences in generation methods when samples are shared across laboratories were mitigated. Furthermore, as much as possible, aerosol particle size distribution was controlled so that the size limitations of different methods were minimized. The results presented here use data from the workshop to assess the comparability of offline immersion freezing measurement methods activating INPs in bulk suspensions, offline methods that activate INPs in condensation and/or immersion freezing modes as single particles on a substrate, online continuous flow diffusion chambers (CFDCs) operating well above water saturation to maximize immersion and subsequent freezing of aerosol particles, and expansion cloud chamber simulations in which liquid cloud droplets were first activated on aerosol particles prior to freezing. The AIDA expansion chamber measurements are expected to be the closest representation to INP activation in atmospheric cloud parcels in these comparisons, due to exposing particles freely to adiabatic cooling. The different particle types used as INPs included the minerals illite NX and K-feldspar, two natural soil dusts representative of arable sandy loam (Argentina) and highly erodible sandy dryland (Tunisia) soils, respectively, and a bacterial INP (Snomax®). Considered together, the agreement among offline immersion freezing measurements of the numbers and fractions of particles active at different temperatures following bulk collection of particles into liquid was excellent, with possible temperature uncertainties inferred to be a key factor in determining INP uncertainties. Collection onto filters versus directly into liquid in impingers made little difference. For offline methods that activated single particles on a substrate at a controlled humidity at or above water saturation, agreement with immersion freezing methods was good in most cases, but was biased low in a few others for reasons that have not been resolved, but could relate to water vapor competition effects. Amongst CFDC-style instruments, various factors requiring (variable) higher supersaturations to achieve equivalent immersion freezing activation dominate the uncertainty between these measurements, and for comparison with bulk immersion freezing methods. When operated above water saturation to include assessment of immersion freezing, CFDC measurements often measured at or above the upper bound of immersion freezing device measurements, but often underestimated INP concentration in comparison to an immersion freezing method that first activates all particles into liquid droplets prior to cooling (the PIMCA-PINC device), and typically slightly underestimated INP number concentrations in comparison to cloud parcel expansions in the AIDA chamber; this can be largely mitigated when it is possible to raise the relative humidity to sufficiently high values in the CFDCs, although this is not always possible operationally. Correspondence of measurements of INPs among online and offline systems varied depending on the INP type. Agreement was best for Snomax® particles in the temperature regime colder than −10 °C, where their ice nucleation activity is nearly maximized and changes very little with temperature. At warmer than −10 °C, Snomax® INP measurements (all via freezing of suspensions) demonstrated discrepancies consistent with previous reports of the instability of its protein aggregates that appear to make it less suitable as a calibration INP at these temperatures. For Argentinian soil dust particles, there was excellent agreement across online and offline methods; measures ranged within one order of magnitude for INP number concentrations, active fractions and calculated active site densities over a 25 to 30 °C range and 5 to 8 orders of corresponding magnitude change in number concentrations. This was also the case for all temperatures warmer than −25 °C in Tunisian dust experiments. In contrast, discrepancies in measurements of INP concentrations or active site densities exceeded two orders of magnitude across a broad temperature range for illite NX, and divergent activation spectra between online and offline measurements found at warmer than −25 °C in a previous study were replicated. Discrepancies also exceeded two orders of magnitude at temperatures of −20 to −25 °C for K-feldspar, but these coincided with the range of temperatures where INP concentrations increase rapidly at approximately an order of magnitude per 2 °C cooling for K-feldspar. These few discrepancies did not outweigh the overall positive outcomes of the workshop activity, nor the future utility of this data set or future similar efforts for resolving remaining measurement issues. Measurements of the same materials were repeatable over the time of the workshop and demonstrated strong consistency with prior studies, as reflected by agreement of data broadly with parameterizations of different specific or general (e.g., soil dust) aerosol types. The divergent measurements of the INP activity of illite NX by online and offline methods was not repeated for other particle types, and the Snomax® data demonstrated that, at least for a biological INP type, there is no expected measurement bias between bulk offline versus online freezing methods to as warm as −10 °C. Since particle size ranges were limited for this workshop, it can be expected that for atmospheric populations of INPs, measurement discrepancies will appear due to the different capabilities of methods for sampling the full aerosol size distribution, or due to limitations on achieving sufficient water supersaturations to fully capture immersion freezing in online instruments. Overall, this workshop presents an improved picture of present capabilities for measuring INPs than in past workshops, and provides direction toward addressing remaining measurement issues.


2014 ◽  
Vol 14 (22) ◽  
pp. 12513-12531 ◽  
Author(s):  
T. Berkemeier ◽  
M. Shiraiwa ◽  
U. Pöschl ◽  
T. Koop

Abstract. Organic aerosol particles play a key role in climate by serving as nuclei for clouds and precipitation. Their sources and composition are highly variable, and their phase state ranges from liquid to solid under atmospheric conditions, affecting the pathway of activation to cloud droplets and ice crystals. Due to slow diffusion of water in the particle phase, organic particles may deviate in phase and morphology from their thermodynamic equilibrium state, hampering the prediction of their influence on cloud formation. We overcome this problem by combining a novel semi-empirical method for estimation of water diffusivity with a kinetic flux model that explicitly treats water diffusion. We estimate timescales for particle deliquescence as well as various ice nucleation pathways for a wide variety of organic substances, including secondary organic aerosol (SOA) from the oxidation of isoprene, α-pinene, naphthalene, and dodecane. The simulations show that, in typical atmospheric updrafts, glassy states and solid/liquid core-shell morphologies can persist for long enough that heterogeneous ice nucleation in the deposition and immersion mode can dominate over homogeneous ice nucleation. Such competition depends strongly on ambient temperature and relative humidity as well as humidification rate and particle size. Due to differences in glass transition temperature, hygroscopicity and atomic O / C ratio of the different SOA, naphthalene SOA particles have the highest potential to act as heterogeneous ice nuclei. Our findings demonstrate that kinetic limitations of water diffusion into organic aerosol particles are likely to be encountered under atmospheric conditions and can strongly affect ice nucleation pathways. For the incorporation of ice nucleation by organic aerosol particles into atmospheric models, our results demonstrate a demand for model formalisms that account for the effects of molecular diffusion and not only describe ice nucleation onsets as a function of temperature and relative humidity but also include updraft velocity, particle size and composition.


2018 ◽  
Vol 14 (1) ◽  
pp. 31-60 ◽  
Author(s):  
M. Y. Guida ◽  
F. E. Laghchioua ◽  
A. Hannioui

This article deals with fast pyrolysis of brown algae, such as Bifurcaria Bifurcata at the range of temperature 300–800 °C in a stainless steel tubular reactor. After a literature review on algae and its importance in renewable sector, a case study was done on pyrolysis of brown algae especially, Bifurcaria Bifurcata. The aim was to experimentally investigate how the temperature, the particle size, the nitrogen flow rate (N2) and the heating rate affect bio-oil, bio-char and gaseous products. These parameters were varied in the ranges of 5–50 °C/min, below 0.2–1 mm and 20–200 mL. min–1, respectively. The maximum bio-oil yield of 41.3wt% was obtained at a pyrolysis temperature of 600 °C, particle size between 0.2–0.5 mm, nitrogen flow rate (N2) of 100 mL. min–1 and heating rate of 5 °C/min. Liquid product obtained under the most suitable and optimal condition was characterized by elemental analysis, 1H-NMR, FT-IR and GC-MS. The analysis of bio-oil showed that bio-oil from Bifurcaria Bifurcata could be a potential source of renewable fuel production and value added chemicals.


2008 ◽  
Vol 10 (2) ◽  
pp. 153-162 ◽  
Author(s):  
B. G. Ruessink

When a numerical model is to be used as a practical tool, its parameters should preferably be stable and consistent, that is, possess a small uncertainty and be time-invariant. Using data and predictions of alongshore mean currents flowing on a beach as a case study, this paper illustrates how parameter stability and consistency can be assessed using Markov chain Monte Carlo. Within a single calibration run, Markov chain Monte Carlo estimates the parameter posterior probability density function, its mode being the best-fit parameter set. Parameter stability is investigated by stepwise adding new data to a calibration run, while consistency is examined by calibrating the model on different datasets of equal length. The results for the present case study indicate that various tidal cycles with strong (say, >0.5 m/s) currents are required to obtain stable parameter estimates, and that the best-fit model parameters and the underlying posterior distribution are strongly time-varying. This inconsistent parameter behavior may reflect unresolved variability of the processes represented by the parameters, or may represent compensational behavior for temporal violations in specific model assumptions.


2007 ◽  
Vol 20 (5) ◽  
pp. 843-855 ◽  
Author(s):  
J. A. Kettleborough ◽  
B. B. B. Booth ◽  
P. A. Stott ◽  
M. R. Allen

Abstract A method for estimating uncertainty in future climate change is discussed in detail and applied to predictions of global mean temperature change. The method uses optimal fingerprinting to make estimates of uncertainty in model simulations of twentieth-century warming. These estimates are then projected forward in time using a linear, compact relationship between twentieth-century warming and twenty-first-century warming. This relationship is established from a large ensemble of energy balance models. By varying the energy balance model parameters an estimate is made of the error associated with using the linear relationship in forecasts of twentieth-century global mean temperature. Including this error has very little impact on the forecasts. There is a 50% chance that the global mean temperature change between 1995 and 2035 will be greater than 1.5 K for the Special Report on Emissions Scenarios (SRES) A1FI scenario. Under SRES B2 the same threshold is not exceeded until 2055. These results should be relatively robust to model developments for a given radiative forcing history.


2021 ◽  
Author(s):  
Najin Kim ◽  
Yafang Cheng ◽  
Nan Ma ◽  
Mira Pöhlker ◽  
Thomas Klimach ◽  
...  

<p>For understanding and assessing aerosol-cloud interactions and their impact on climate, reliable measurement data of aerosol particle hygroscopicity and cloud condensation nuclei (CCN) activity are required. Furthermore, aerosol liquid water, mainly controlled by hygroscopicity, affects heterogeneous and multiphase reactions of aerosol particles. The CCN activity of aerosol particles can be determined by scanning particle size and supersaturation (S) in the CCN measurement. Compared to the existing CCN activity measurement, a broad supersaturation scanning CCN (BS2-CCN) system, in which particles are exposed to a range of S simultaneously, can measure particle hygroscopicity and CCN activity with a high-time resolution. Based on a monotonic relation between the activation supersaturation of aerosol particles (S<sub>aerosol</sub>)  and the activation fraction (F<sub>act</sub>) of the BS2-CCN measurement, we can derive κ, a single hygroscopicity parameter, directly.</p><p>Here, we describe how the BS2-CCN system can be effectively calibrated and which factors can affect the calibration curve (F<sub>act</sub> - S<sub>aerosol</sub>). For calibration, size-resolved CCN measurements with ammonium sulfate (AS) and sodium chloride particles are performed under the three different thermal gradient (dT) conditions (dT=6, 8, and 10). First, the shape of the calibration curve is primarily influenced by S<sub>max</sub>, maximum S in the activation tube. We need to determine appropriate S<sub>max</sub> depending on particle size and κ to be investigated. To minimize the effect of double/multiple charged particles, small  D<sub>g </sub>and σ<sub>g</sub>  in number size distribution are recommended when generating the calibration aerosols. Sheath-to-aerosol-flow ratio (SAR) is the third factor to be considered. BS2-CCNC system uses a low SAR with a wider inlet compared to the typical CCN measurement, which can make a monotonic relation between F<sub>act</sub> and S<sub>aerosol</sub>. Lastly, F<sub>act </sub>is affected by particle number concentration and has a decreasing rate of 0.02/100 cm<sup>-3</sup> (within N<sub>CN</sub> ~ 300 cm<sup>-3</sup> for AS) due to the water consumption in the chamber. For evaluating the BS2-CCN system, inter-comparison experiments between typical DMA-CCN and BS2-CCN measurement were performed with the laboratory-generated aerosol mixture and ambient aerosols. Statistically good agreements of κ values between DMA-CCN and BS2-CCN measurements for both inter-comparison experiments imply that the BS2-CCN system can measure particle hygroscopicity and CCN activity well compared to the existing measurement. We expect that this new system can be applied to aircraft and ship measurements that require a high-time resolution as well as ground measurement for a broad range of hygroscopicity distribution. Because hygroscopicity is closely related to the fraction of organics/inorganics in aerosol particles, our method can also serve as a complementary approach for fast detection/estimation of aerosol chemical compositions. </p>


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