scholarly journals Non-stomatal exchange in ammonia dry deposition models: Comparison of two state-of-the-art approaches

2016 ◽  
Author(s):  
Frederik Schrader ◽  
Christian Brümmer ◽  
Chris R. Flechard ◽  
Roy J. Wichink Kruit ◽  
Margreet C. van Zanten ◽  
...  
Keyword(s):  
Air Quality ◽  
Large Scale ◽  
Leaf Surface ◽  
State Of The Art ◽  
Temperature Response ◽  
Stomatal Resistance ◽  
Quality Models ◽  
Response Parameter ◽  
Leaf Surface Chemistry ◽  
Models Comparison

Abstract. The accurate representation of bidirectional ammonia (NH3) biosphere-atmosphere exchange is an important part of modern air quality models. However, the cuticular (or external leaf surface) pathway, as well as other non-stomatal ecosystem surfaces, still pose a major challenge of translating our knowledge into models. Dynamic mechanistic models including complex leaf surface chemistry have been able to accurately reproduce measured bidirectional fluxes in the past, but their computational expense and challenging implementation into existing air quality models call for steady-state simplifications. We here qualitatively compare two semi-empirical state-of-the-art parameterizations of a unidirectional non-stomatal resistance (Rw) model after Massad et al. (2010), and a quasi-bidirectional non-stomatal compensation point (χw) model after Wichink Kruit et al. (2010), with NH3 flux measurements from five European sites. In addition, we tested the feasibility of using backward-looking moving averages of air NH3 concentrations as a proxy for prior NH3 uptake and driver of an alternative parameterization of non-stomatal emission potentials (Γw) for bidirectional non-stomatal exchange models. Results indicate that the Rw-only model has a tendency to underestimate fluxes, while the χw model mainly overestimates fluxes, although systematic underestimations can occur under certain conditions, depending on temperature and ambient NH3 concentrations at the site. The proposed Γw parameterization appears to have potential for improvement, but cannot be recommended for use in large scale simulations in its present state due to large uncertainties. As an interim solution for improving flux predictions, we recommend to reduce the minimum allowed Rw and the temperature response parameter in the unidirectional model and to revisit the temperature dependent Γw parameterization of the bidirectional model.

scholarly journals Non-stomatal exchange in ammonia dry deposition models: comparison of two state-of-the-art approaches

2016 ◽  
Vol 16 (21) ◽  
pp. 13417-13430 ◽  
Author(s):  
Frederik Schrader ◽  
Christian Brümmer ◽  
Chris R. Flechard ◽  
Roy J. Wichink Kruit ◽  
Margreet C. van Zanten ◽  
...  
Keyword(s):  
Air Quality ◽  
Leaf Surface ◽  
State Of The Art ◽  
Temperature Response ◽  
Stomatal Resistance ◽  
Moving Averages ◽  
Quality Models ◽  
Response Parameter ◽  
Leaf Surface Chemistry ◽  
Models Comparison

Abstract. The accurate representation of bidirectional ammonia (NH3) biosphere–atmosphere exchange is an important part of modern air quality models. However, the cuticular (or external leaf surface) pathway, as well as other non-stomatal ecosystem surfaces, still pose a major challenge to translating our knowledge into models. Dynamic mechanistic models including complex leaf surface chemistry have been able to accurately reproduce measured bidirectional fluxes in the past, but their computational expense and challenging implementation into existing air quality models call for steady-state simplifications. Here we qualitatively compare two semi-empirical state-of-the-art parameterizations of a unidirectional non-stomatal resistance (Rw) model after Massad et al. (2010), and a quasi-bidirectional non-stomatal compensation-point (χw) model after Wichink Kruit et al. (2010), with NH3 flux measurements from five European sites. In addition, we tested the feasibility of using backward-looking moving averages of air NH3 concentrations as a proxy for prior NH3 uptake and as a driver of an alternative parameterization of non-stomatal emission potentials (Γw) for bidirectional non-stomatal exchange models. Results indicate that the Rw-only model has a tendency to underestimate fluxes, while the χw model mainly overestimates fluxes, although systematic underestimations can occur under certain conditions, depending on temperature and ambient NH3 concentrations at the site. The proposed Γw parameterization revealed a clear functional relationship between backward-looking moving averages of air NH3 concentrations and non-stomatal emission potentials, but further reduction of uncertainty is needed for it to be useful across different sites. As an interim solution for improving flux predictions, we recommend reducing the minimum allowed Rw and the temperature response parameter in the unidirectional model and revisiting the temperature-dependent Γw parameterization of the bidirectional model.

scholarly journals A revised parameterization for gaseous dry deposition in air-quality models

2003 ◽  
Vol 3 (6) ◽  
pp. 2067-2082 ◽  
Author(s):  
L. Zhang ◽  
J. R. Brook ◽  
R. Vet
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Stomatal Resistance ◽  
Model Output ◽  
Gaseous Species ◽  
Area Index ◽  
Quality Models ◽  
Deposition Velocities ◽  
Study Results ◽  
Land Types

Abstract. A parameterization scheme for calculating gaseous dry deposition velocities in air-quality models is revised based on recent study results on non-stomatal uptake of O3 and SO2 over 5 different vegetation types. Non-stomatal resistance, which includes in-canopy aerodynamic, soil and cuticle resistances, for SO2 and O3 is parameterized as a function of friction velocity, relative humidity, leaf area index, and canopy wetness. Non-stomatal resistance for other chemical species is scaled to those of SO2 and O3 based on their chemical and physical characteristics. Stomatal resistance is calculated using a two-big-leaf stomatal resistance sub-model for all gaseous species of interest. The improvements in the present model compared to its earlier version include a newly developed non-stomatal resistance formulation, a realistic treatment of cuticle and ground resistance in winter, and the handling of seasonally-dependent input parameters. Model evaluation shows that the revised parameterization can provide more realistic deposition velocities for both O3 and SO2, especially for wet canopies. Example model output shows that the parameterization provides reasonable estimates of dry deposition velocities for different gaseous species, land types and diurnal and seasonal variations. Maximum deposition velocities from model output are close to reported measurement values for different land types. The current parameterization can be easily adopted into different air-quality models that require inclusion of dry deposition processes.

scholarly journals A revised parameterization for gaseous dry deposition in air-quality models

2003 ◽  
Vol 3 (2) ◽  
pp. 1777-1804 ◽  
Author(s):  
L. Zhang ◽  
J. R. Brook ◽  
R. Vet
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Stomatal Resistance ◽  
Model Output ◽  
Gaseous Species ◽  
Area Index ◽  
Quality Models ◽  
Deposition Velocities ◽  
Study Results ◽  
Land Types

Abstract. A parameterization scheme for calculating gaseous dry deposition velocities in air-quality models is revised based on recent study results on non-stomatal uptake of O3 and SO2 over 5 different vegetation types. Non-stomatal resistance, which includes in-canopy aerodynamic resistance, soil resistance and cuticle resistance, for SO2 and  O3 is parameterized as a function of friction velocity, relative humidity, leaf area index, and canopy wetness. Non-stomatal resistance for all other species is scaled to those of SO2 and  O3 based on their chemical and physical characteristics. Stomatal resistance is calculated using a leaf-stomatal-resistance model for all gaseous species of interest. The improvements in the present model compared to its earlier version include a newly developed non-stomatal resistance formulation, a realistic treatment of cuticle and ground resistance in winter and the handling of seasonally-dependent input parameters. Model evaluation shows that the revised parameterization can provide more realistic deposition velocities for both  O3 and SO2, especially for wet canopies. Example model output shows that the parameterization provides reasonable estimates of dry deposition velocities for different gaseous species, land types and diurnal and seasonal variations. Maximum deposition velocities from model output are close to reported measurement values for different land types. The current parameterization can be easily adopted into different air-quality models that require inclusion of dry deposition processes.

Automatic generation from MCM of reduced mechanisms to study the formation and evolution of SOA in 3D air quality models 

2021 ◽  
Author(s):  
Zhizhao Wang ◽  
Florian Couvidat ◽  
Karine Sartelet
Keyword(s):  
Molecular Structure ◽  
Air Quality ◽  
Large Scale ◽  
Automatic Generation ◽  
Oxidation Products ◽  
Chemical Mechanism ◽  
Aerosol Formation ◽  
Quality Models ◽  
Chemical Mechanisms ◽  
Formation And Evolution

<p>As secondary organic aerosols (SOA) largely contribute to the mass of particles and may strongly affect health, it is essential to represent them as accurately as possible in air quality models (AQM). Their formation and aging involve multi-generation oxidations of numerous volatile organic compounds (VOC) combined with gas-particle partitioning processes.<br> <br>Tracking the non-linear relationship between VOC emissions and aerosol formation demands comprehensive chemical mechanisms, which take into account the whole complexity of the SOA precursor oxidation to simulate aerosols under various conditions.<br>However, the use of explicit gas-phase chemical mechanism (e.g., MCM, GECKO-A) or molecular structure-limited parameterization (e.g., VBS, SOM, FGOM) could be problematical in large-scale SOA modeling, as the former is overwhelmingly computational expensive while the latter loses tracks of VOC oxidation products after few generations and specific properties relying on aerosol formation.<br> <br>Consequently, we have developed semi-explicit SOA chemical mechanisms designed to model the SOA formation and evolution in 3D AQM. These mechanisms are reduced based on simulations of the near-explicit master chemical mechanism (MCM) performed under various conditions representative of ambient conditions and different lumping strategies. The new mechanisms integrate the crucial SOA species/reactions with different mechanism complexities. The mechanisms, therefore, preserve the complexity of the oxidation chemistry (dependence on NOx of the SOA formation, the influence of radical concentrations, humidity, photolysis, etc..) as well as the molecular composition of the organic aerosol. The mechanisms are implemented in a novel 0D aerosol model SSH-aerosol, which can use the molecular structure of lumped compounds to estimate the influence of non-ideality on SOA formation.</p><p>The current application has been conducted on the MCM degradation scheme of beta-caryophyllene (C<sub>15</sub>H<sub>24</sub>), the most representative sesquiterpene. A reduction of the average 90% CPU time and up to 92% number of S/IVOCs species has been achieved compared to the original MCM mechanism.</p>

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals VIPPrint: Validating Synthetic Image Detection and Source Linking Methods on a Large Scale Dataset of Printed Documents

2021 ◽  
Vol 7 (3) ◽  
pp. 50
Author(s):  
Anselmo Ferreira ◽  
Ehsan Nowroozi ◽  
Mauro Barni
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Child Pornography ◽  
Forensic Analysis ◽  
Synthetic Image ◽  
Image Detection ◽  
Face Images ◽  
Large Scale Dataset ◽  
Scanned Images ◽  
Analysis Of The Images

The possibility of carrying out a meaningful forensic analysis on printed and scanned images plays a major role in many applications. First of all, printed documents are often associated with criminal activities, such as terrorist plans, child pornography, and even fake packages. Additionally, printing and scanning can be used to hide the traces of image manipulation or the synthetic nature of images, since the artifacts commonly found in manipulated and synthetic images are gone after the images are printed and scanned. A problem hindering research in this area is the lack of large scale reference datasets to be used for algorithm development and benchmarking. Motivated by this issue, we present a new dataset composed of a large number of synthetic and natural printed face images. To highlight the difficulties associated with the analysis of the images of the dataset, we carried out an extensive set of experiments comparing several printer attribution methods. We also verified that state-of-the-art methods to distinguish natural and synthetic face images fail when applied to print and scanned images. We envision that the availability of the new dataset and the preliminary experiments we carried out will motivate and facilitate further research in this area.

scholarly journals SketchGNN: Semantic Sketch Segmentation with Graph Neural Networks

2021 ◽  
Vol 40 (3) ◽  
pp. 1-13
Author(s):  
Lumin Yang ◽  
Jiajie Zhuang ◽  
Hongbo Fu ◽  
Xiangzhi Wei ◽  
Kun Zhou ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Large Scale ◽  
State Of The Art ◽  
Semantic Segmentation ◽  
Structure Information ◽  
Graph Neural Networks ◽  
Node Labels ◽  
Point Level

We introduce SketchGNN , a convolutional graph neural network for semantic segmentation and labeling of freehand vector sketches. We treat an input stroke-based sketch as a graph with nodes representing the sampled points along input strokes and edges encoding the stroke structure information. To predict the per-node labels, our SketchGNN uses graph convolution and a static-dynamic branching network architecture to extract the features at three levels, i.e., point-level, stroke-level, and sketch-level. SketchGNN significantly improves the accuracy of the state-of-the-art methods for semantic sketch segmentation (by 11.2% in the pixel-based metric and 18.2% in the component-based metric over a large-scale challenging SPG dataset) and has magnitudes fewer parameters than both image-based and sequence-based methods.

scholarly journals Spatial and Temporal Characteristics of Environmental Air Quality and Its Relationship with Seasonal Climatic Conditions in Eastern China during 2015–2018

2021 ◽  
Vol 18 (9) ◽  
pp. 4524
Author(s):  
Zhiyuan Wang ◽  
Xiaoyi Shi ◽  
Chunhua Pan ◽  
Sisi Wang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Large Scale ◽  
Asian Summer Monsoon ◽  
Eastern China ◽  
Climatic Conditions ◽  
Uniform Structure ◽  
Concentration Limit ◽  
Environmental Air

Exploring the relationship between environmental air quality (EAQ) and climatic conditions on a large scale can help better understand the main distribution characteristics and the mechanisms of EAQ in China, which is significant for the implementation of policies of joint prevention and control of regional air pollution. In this study, we used the concentrations of six conventional air pollutants, i.e., carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5), coarse particulate matter (PM10), and ozone (O3), derived from about 1300 monitoring sites in eastern China (EC) from January 2015 to December 2018. Exploiting the grading concentration limit (GB3095-2012) of various pollutants in China, we also calculated the monthly average air quality index (AQI) in EC. The results show that, generally, the EAQ has improved in all seasons in EC from 2015 to 2018. In particular, the concentrations of conventional air pollutants, such as CO, SO2, and NO2, have been decreasing year by year. However, the concentrations of particulate matter, such as PM2.5 and PM10, have changed little, and the O3 concentration increased from 2015 to 2018. Empirical mode decomposition (EOF) was used to analyze the major patterns of AQI in EC. The first mode (EOF1) was characterized by a uniform structure in AQI over EC. These phenomena are due to the precipitation variability associated with the East Asian summer monsoon (EASM), referred to as the “summer–winter” pattern. The second EOF mode (EOF2) showed that the AQI over EC is a north–south dipole pattern, which is bound by the Qinling Mountains and Huaihe River (about 35° N). The EOF2 is mainly caused by seasonal variations of the mixed concentration of PM2.5 and O3. Associated with EOF2, the Mongolia–Siberian High influences the AQI variation over northern EC by dominating the low-level winds (10 m and 850 hPa) in autumn and winter, and precipitation affects the AQI variation over southern EC in spring and summer.

scholarly journals ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition

2021 ◽  
Author(s):  
Anil S. Baslamisli ◽  
Partha Das ◽  
Hoang-An Le ◽  
Sezer Karaoglu ◽  
Theo Gevers
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
State Of The Art ◽  
Image Decomposition ◽  
Natural Environments ◽  
Decomposition Algorithms ◽  
Ambient Light ◽  
Fine Grained ◽  
Large Scale Dataset ◽  
Direct Illumination

AbstractIn general, intrinsic image decomposition algorithms interpret shading as one unified component including all photometric effects. As shading transitions are generally smoother than reflectance (albedo) changes, these methods may fail in distinguishing strong photometric effects from reflectance variations. Therefore, in this paper, we propose to decompose the shading component into direct (illumination) and indirect shading (ambient light and shadows) subcomponents. The aim is to distinguish strong photometric effects from reflectance variations. An end-to-end deep convolutional neural network (ShadingNet) is proposed that operates in a fine-to-coarse manner with a specialized fusion and refinement unit exploiting the fine-grained shading model. It is designed to learn specific reflectance cues separated from specific photometric effects to analyze the disentanglement capability. A large-scale dataset of scene-level synthetic images of outdoor natural environments is provided with fine-grained intrinsic image ground-truths. Large scale experiments show that our approach using fine-grained shading decompositions outperforms state-of-the-art algorithms utilizing unified shading on NED, MPI Sintel, GTA V, IIW, MIT Intrinsic Images, 3DRMS and SRD datasets.

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