Variability in modelled airborne dust mineralogy derived from global soil composition uncertainties

2021 ◽  
Author(s):  
María Gonçalves Ageitos ◽  
Matt Dawson ◽  
Vincenzo Obiso ◽  
Martina Klose ◽  
Ron Miller ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Biogeochemical Cycles ◽  
Wave Radiation ◽  
Climate Modelling ◽  
Soil Composition ◽  
Soil Mineralogy ◽  
Airborne Dust ◽  
Global Soil ◽  
Dust Composition ◽  
The Impact

<p>Dust aerosols consist on a variety of minerals with different physic and chemical properties. As such, they interact with short and long wave radiation, potentially form clouds, act as nutrients modulating biogeochemical cycles, or influence atmospheric chemistry, differently. Most current state-of-the-art Earth System Models (ESMs) neglect the complexity in dust composition, mainly due to computational constraints, but also to the existing uncertainties in the size resolved composition of parent soils, the resulting distribution of minerals in airborne dust, and the scarcity of observations to constrain them.</p><p>Within this work, we assess the variability of global dust composition due to uncertainties in the characterization of the parent soil mineralogy. To that end, we consider two available global soil mineralogy atlases, developed by Claquin et al. (1999) –C1999- and Journet et al. (2014) –J2014-, which represent respectively 8 and 12 relevant minerals for climate (namely: illite, smectite/montmorillonite, kaolinite, calcite, gypsum, hematite, quartz, and feldspars in C1999, and those plus chlorite, vermiculite, goethite, and mica in J2014). Thanks to a recently developed feature of the MONARCH atmospheric-chemistry model, we are able to explicitly resolve the minerals’ atmospheric cycle. Therefore, we define two global experiments to assess changes on airborne dust composition attributed to the soil mineralogy assumptions and provide a measure of their variability. We also perform a preliminary evaluation of the global mineralogy results against available observations of mineral fractions in surface dust concentration.</p><p>Our results will inform the climate modelling community about the potential variability in dust composition, an aspect that will gain relevance as ESMs continue growing in complexity and new processes to better characterize aerosols’ forcing or biogeochemical cycles are added. Further observational constraints, such as those that will derive from the EMIT NASA mission on soil composition or the FRAGMENT experimental campaigns on airborne dust characterization, will be key in the near future to improve our understanding of the impact of dust mineralogy on fundamental climate features.</p>

scholarly journals A new data set of soil mineralogy for dust-cycle modeling

2014 ◽  
Vol 14 (8) ◽  
pp. 3801-3816 ◽  
Author(s):  
E. Journet ◽  
Y. Balkanski ◽  
S. P. Harrison
Keyword(s):  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Single Scattering ◽  
Dust Particles ◽  
Data Set ◽  
Airborne Dust ◽  
Global Soil ◽  
Climate Interactions ◽  
Soil Units ◽  
The Impact

Abstract. The mineralogy of airborne dust affects the impact of dust particles on direct and indirect radiative forcing, on atmospheric chemistry and on biogeochemical cycling. It is determined partly by the mineralogy of the dust-source regions and partly by size-dependent fractionation during erosion and transport. Here we present a data set that characterizes the clay and silt-sized fractions of global soil units in terms of the abundance of 12 minerals that are important for dust–climate interactions: quartz, feldspars, illite, smectite, kaolinite, chlorite, vermiculite, mica, calcite, gypsum, hematite and goethite. The basic mineralogical information is derived from the literature, and is then expanded following explicit rules, in order to characterize as many soil units as possible. We present three alternative realizations of the mineralogical maps, taking the uncertainties in the mineralogical data into account. We examine the implications of the new database for calculations of the single scattering albedo of airborne dust and thus for dust radiative forcing.

scholarly journals A new data set of soil mineralogy for dust-cycle modeling

2013 ◽  
Vol 13 (9) ◽  
pp. 23943-23993 ◽  
Author(s):  
E. Journet ◽  
Y. Balkanski ◽  
S. P. Harrison
Keyword(s):  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Single Scattering ◽  
Dust Particles ◽  
Data Set ◽  
Airborne Dust ◽  
Global Soil ◽  
Climate Interactions ◽  
Soil Units ◽  
The Impact

Abstract. The mineralogy of airborne dust affects the impact of dust particles on direct and indirect radiative forcing, on atmospheric chemistry and on biogeochemical cycling. It is determined partly by the mineralogy of the dust-source regions and partly by size-dependent fractionation during erosion and transport. Here we present a data set that characterizes the clay and silt sized fractions of global soil units in terms of the abundance of 12 minerals that are important for dust-climate interactions: quartz, feldspars, illite, smectite, kaolinite, chlorite, vermiculite, mica, calcite, gypsum, hematite and goethite. The basic mineralogical information is derived from the literature, and is then expanded following explicit rules, in order to characterize as many soil units as possible. We present three alternative realisations of the mineralogical maps that account for the uncertainties in the mineralogical data. We examine the implications of the new database for calculations of the single scattering albedo of airborne dust and thus for dust radiative forcing.

scholarly journals Projected global tropospheric ozone impacts on vegetation under different emission and climate scenarios

2017 ◽  
Author(s):  
Pierre Sicard ◽  
Alessandro Anav ◽  
Alessandra De Marco ◽  
Elena Paoletti
Keyword(s):  
Atmospheric Chemistry ◽  
High Surface ◽  
Central Africa ◽  
Ground Level ◽  
Global Scale ◽  
Climate Modelling ◽  
North Asia ◽  
Vegetation Models ◽  
The Impact ◽  
Surface O3

Abstract. The impact of ground-level ozone (O3) on vegetation is largely under-investigated at global scale despite worldwide large areas are exposed to high surface O3 levels and concentrations are expected to increase in the next future. To explore future potential impacts of O3 on vegetation, we compared historical and projected O3 concentrations simulated by six global atmospheric chemistry transport models on the basis of three representative concentration pathways emission scenarios (i.e. RCP2.6, 4.5, 8.5). To assess changes in the potential O3 threat to vegetation, we used the AOT40 metric. Results point out a significant overrun of AOT40 in comparison with the recommendations of UNECE for the protection of vegetation. In fact, many areas of the northern hemisphere show that AOT40-based critical levels will be exceeded by a factor of at least 10 under RCP8.5. Changes in surface O3 by 2100 range from about +4–5 ppb worldwide in RCP8.5 scenario to reductions of about 2–10 ppb in the RCP2.6 scenario. The risk of O3 injury for vegetation decreased by 61 % and 47 % under RCP2.6 and RCP4.5, respectively and increased by 70 % under RCP8.5. Key biodiversity areas in South and North Asia, central Africa and Northern America were identified as being at risk from high O3 concentrations. To better evaluate the regional exposure of ecosystems to O3 pollution, we recommend the use of improved chemistry-climate modelling system, fully coupled with dynamic vegetation models.

scholarly journals Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10

2019 ◽  
Vol 12 (3) ◽  
pp. 1209-1225 ◽  
Author(s):  
Christoph A. Keller ◽  
Mat J. Evans
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Random Forest Regression ◽  
Data Set ◽  
Gas Phase Chemistry ◽  
Chemical Conditions ◽  
Phase Chemistry ◽  
The Impact

Abstract. Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models are numerically intense, and previous attempts to reduce the numerical cost of chemistry solvers have not delivered transformative change. We show here the potential of a machine learning (in this case random forest regression) replacement for the gas-phase chemistry in atmospheric chemistry transport models. Our training data consist of 1 month (July 2013) of output of chemical conditions together with the model physical state, produced from the GEOS-Chem chemistry model v10. From this data set we train random forest regression models to predict the concentration of each transported species after the integrator, based on the physical and chemical conditions before the integrator. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for long-lived species and the absolute concentration for short-lived species. We also find improvements from a simple implementation of chemical families (NOx = NO + NO2). We then implement the trained random forest predictors back into GEOS-Chem to replace the numerical integrator. The machine-learning-driven GEOS-Chem model compares well to the standard simulation. For ozone (O3), errors from using the random forests (compared to the reference simulation) grow slowly and after 5 days the normalized mean bias (NMB), root mean square error (RMSE) and R2 are 4.2 %, 35 % and 0.9, respectively; after 30 days the errors increase to 13 %, 67 % and 0.75, respectively. The biases become largest in remote areas such as the tropical Pacific where errors in the chemistry can accumulate with little balancing influence from emissions or deposition. Over polluted regions the model error is less than 10 % and has significant fidelity in following the time series of the full model. Modelled NOx shows similar features, with the most significant errors occurring in remote locations far from recent emissions. For other species such as inorganic bromine species and short-lived nitrogen species, errors become large, with NMB, RMSE and R2 reaching >2100 % >400 % and <0.1, respectively. This proof-of-concept implementation takes 1.8 times more time than the direct integration of the differential equations, but optimization and software engineering should allow substantial increases in speed. We discuss potential improvements in the implementation, some of its advantages from both a software and hardware perspective, its limitations, and its applicability to operational air quality activities.

scholarly journals Analysis of actinic flux profiles measured from an ozonesonde balloon

2015 ◽  
Vol 15 (8) ◽  
pp. 4131-4144 ◽  
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

Evaluating the role of soil physical properties on simulated land-atmosphere interactions over South Africa using coupled atmosphere-hydrological modeling

2021 ◽  
Author(s):  
Zhenyu Zhang ◽  
Patrick Laux ◽  
Joël Arnault ◽  
Jianhui Wei ◽  
Jussi Baade ◽  
...  
Keyword(s):  
South Africa ◽  
Physical Properties ◽  
Land Degradation ◽  
Land Surface ◽  
Soil Physical Properties ◽  
Near Surface ◽  
Soil Database ◽  
Global Soil ◽  
The Impact

&lt;p&gt;Land degradation with its direct impact on vegetation, surface soil layers and land surface albedo, has great relevance with the climate system. Assessing the climatic and ecological effects induced by land degradation requires a precise understanding of the interaction between the land surface and atmosphere. In coupled land-atmosphere modeling, the low boundary conditions impact the thermal and hydraulic exchanges at the land surface, therefore regulates the overlying atmosphere by land-atmosphere feedback processes. However, those land-atmosphere interactions are not convincingly represented in coupled land-atmosphere modeling applications. It is partly due to an approximate representation of hydrological processes in land surface modeling. Another source of uncertainties relates to the generalization of soil physical properties in the modeling system. This study focuses on the role of the prescribed physical properties of soil in high-resolution land surface-atmosphere simulations over South Africa. The model used here is the hydrologically-enhanced Weather Research and Forecasting (WRF-Hydro) model. Four commonly used global soil datasets obtained from UN Food and Agriculture Organization (FAO) soil database, Harmonized World Soil Database (HWSD), Global Soil Dataset for Earth System Model (GSDE), and SoilGrids dataset, are incorporated within the WRF-Hydro experiments for investigating the impact of soil information on land-atmosphere interactions. The simulation results of near-surface temperature, skin temperature, and surface energy fluxes are presented and compared to observational-based reference dataset. It is found that simulated soil moisture is largely influenced by soil texture features, which affects its feedback to the atmosphere.&lt;/p&gt;

scholarly journals Accelerating simulations using REDCHEM_v0.0 for atmospheric chemistry mechanism reduction

2018 ◽  
Vol 11 (8) ◽  
pp. 3391-3407 ◽  
Author(s):  
Zacharias Marinou Nikolaou ◽  
Jyh-Yuan Chen ◽  
Yiannis Proestos ◽  
Jos Lelieveld ◽  
Rolf Sander
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
A Priori ◽  
Chemical Mechanism ◽  
Climate Modelling ◽  
Mechanism Reduction ◽  
Computational Speed ◽  
Speed Up ◽  
Spatio Temporal ◽  
Skeletal Mechanism

Abstract. Chemical mechanism reduction is common practice in combustion research for accelerating numerical simulations; however, there have been limited applications of this practice in atmospheric chemistry. In this study, we employ a powerful reduction method in order to produce a skeletal mechanism of an atmospheric chemistry code that is commonly used in air quality and climate modelling. The skeletal mechanism is developed using input data from a model scenario. Its performance is then evaluated both a priori against the model scenario results and a posteriori by implementing the skeletal mechanism in a chemistry transport model, namely the Weather Research and Forecasting code with Chemistry. Preliminary results, indicate a substantial increase in computational speed-up for both cases, with a minimal loss of accuracy with regards to the simulated spatio-temporal mixing ratio of the target species, which was selected to be ozone.

scholarly journals Geospatial technology perspectives for mining vis-a-vis sustainable forest ecosystems

2017 ◽  
Vol 11 (1) ◽  
pp. 219-238 ◽  
Author(s):  
Laxmi Goparaju ◽  
P. Rama Chandra Prasad ◽  
Firoz Ahmad
Keyword(s):  
Forest Ecosystems ◽  
Anthropogenic Activities ◽  
Biogeochemical Cycles ◽  
Mining Activities ◽  
Forest Environment ◽  
Mining Operations ◽  
Geospatial Technology ◽  
The Status ◽  
The Impact

Abstract Forests, the backbone of biogeochemical cycles and life supporting systems, are under severe pressure due to varied anthropogenic activities. Mining activities are one among the major reasons for forest destruction questioning the survivability and sustainability of flora and fauna existing in that area. Thus, monitoring and managing the impact of mining activities on natural resources at regular intervals is necessary to check the status of their depleted conditions, and to take up restoration and conservative measurements. Geospatial technology provides means to identify the impact of different mining operations on forest ecosystems and helps in proposing initiatives for safeguarding the forest environment. In this context, the present study highlights the problems related to mining in forest ecosystems and elucidates how geospatial technology can be employed at various stages of mining activities to achieve a sustainable forest ecosystem. The study collates information from various sources and highlights the role of geospatial technology in mining industries and reclamation process.

scholarly journals Multi-model study of mercury dispersion in the atmosphere: Vertical distribution of mercury species

2016 ◽  
Author(s):  
Johannes Bieser ◽  
Franz Slemr ◽  
Jesse Ambrose ◽  
Carl Brenninkmeijer ◽  
Steve Brooks ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Atmospheric Chemistry ◽  
Lower Troposphere ◽  
Elemental Mercury ◽  
Mercury Species ◽  
Substantial Impact ◽  
Model Studies ◽  
Model Study ◽  
The Impact ◽  
The Vertical Distribution

Abstract. Atmospheric chemistry and transport of mercury play a key role in the global mercury cycle. However, there are still considerable knowledge gaps concerning the fate of mercury in the atmosphere. This is the second part of a model inter-comparison study investigating the impact of atmospheric chemistry and emissions on mercury in the atmosphere. While the first study focused on ground based observations of mercury concentration and deposition, here we investigate the vertical distribution and speciation of mercury from the planetary boundary layer to the lower stratosphere. So far, there have been few model studies investigating the vertical distribution of mercury, mostly focusing on single aircraft campaigns. Here, we present a first comprehensive analysis based on various aircraft observations in Europe, North America, and on inter-continental flights. The investigated models proved to be able to reproduce the distribution of total and elemental mercury concentrations in the troposphere including inter-hemispheric trends. One key aspect of the study is the investigation of mercury oxidation in the troposphere. We found that different chemistry schemes were better at reproducing observed oxidized mercury (RM) patterns depending on altitude. High RM concentrations in the upper troposphere could be reproduced with oxidation by bromine while elevated concentrations in the lower troposphere were better reproduced by OH and ozone chemistry. However, the results were not always conclusive as the physical and chemical parametrizations in the chemistry transport models also proved to have a substantial impact on model results.

scholarly journals Impact of uncertainties in inorganic chemical rate constants on tropospheric composition and ozone radiative forcing

2017 ◽  
Author(s):  
Ben Newsome ◽  
Mat Evans
Keyword(s):  
Rate Constant ◽  
Atmospheric Chemistry ◽  
Rate Constants ◽  
Tropospheric Ozone ◽  
Radiative Forcing ◽  
Transport Model ◽  
Surface Ozone ◽  
Photolysis Rates ◽  
The Impact ◽  
Chemical Rate

Abstract. Chemical rate constants determine the composition of the atmosphere and how this composition has changed over time. They are central to our understanding of climate change and air quality degradation. Atmospheric chemistry models, whether online or offline, box, regional or global use these rate constants. Expert panels synthesise laboratory measurements, making recommendations for the rate constants that should be used. This results in very similar or identical rate constants being used by all models. The inherent uncertainties in these recommendations are, in general, therefore ignored. We explore the impact of these uncertainties on the composition of the troposphere using the GEOS-Chem chemistry transport model. Based on the JPL and IUPAC evaluations we assess 50 mainly inorganic rate constants and 10 photolysis rates, through simulations where we increase the rate of the reactions to the 1σ upper value recommended by the expert panels. We assess the impact on 4 standard metrics: annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime. Uncertainty in the rate constants for NO2 + OH    M →  HNO3, OH + CH4 → CH3O2 + H2O and O3 + NO → NO2 + O2 are the three largest source of uncertainty in these metrics. We investigate two methods of assessing these uncertainties, addition in quadrature and a Monte Carlo approach, and conclude they give similar outcomes. Combining the uncertainties across the 60 reactions, gives overall uncertainties on the annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime of 11, 12, 17 and 17 % respectively. These are larger than the spread between models in recent model inter-comparisons. Remote regions such as the tropics, poles, and upper troposphere are most uncertain. This chemical uncertainty is sufficiently large to suggest that rate constant uncertainty should be considered when model results disagree with measurement. Calculations for the pre-industrial allow a tropospheric ozone radiative forcing to be calculated of 0.412 ± 0.062 Wm−2. This uncertainty (15 %) is comparable to the inter-model spread in ozone radiative forcing found in previous model-model inter-comparison studies where the rate constants used in the models are all identical or very similar. Thus the uncertainty of tropospheric ozone radiative forcing should expanded to include this additional source of uncertainty. These rate constant uncertainties are significant and suggest that refinement of supposedly well known chemical rate constants should be considered alongside other improvements to enhance our understanding of atmospheric processes.

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